United States
Environmental
Protection Agency
EPA Region 3
Philadelphia, PA
EPA 9-03-R-00013F
June 2003
Draft Programmatic
Environmental Imoact Statement
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APPENDIX I
CUMULATIVE IMPACT STUDY
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Mountaintop Mining/'Valley Fill EIS 1~1 Draft - December 2002
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Landscape Scale Cumulative Impact Study
of Mountaintop Mining Operations
December 2002
Prepared By:
USEPA Region 3
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With assistance from:
D Gannett Fleming
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FIGURES
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APPENDIX A
DETAILED LAND COVER RESULTS
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APPENDIX B
DETAILED PERMIT INFORMATION
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TABLE OF CONTENTS
EXECUTIVE SUMMARY i
I. INTRODUCTION 1
A. STUDY AREA 2
B. AQUATIC HABITATS 5
1. Representative Streams 5
a. Physical Characteristics 5
b. Stream Classification 5
c. Habitats in Streams 6
2. Energy Sources and Plant Communities 7
a. Primary Producers and Primary Production 8
b. Allochthonous Energy Sources and Processing 8
3. Animal Communities 10
a. Invertebrates 10
b. Vertebrates 11
4. Ecosystem Function 12
C. TERRESTRIAL HABITATS 13
1. Defining Factors Associated with the Terrestrial Habitat 14
a. Forest Fragmentation 14
b. Edge Habitat 15
c. Patches 16
d. Biological Integrity and Potential Ecological Condition 17
e. Interior Forest Habitat 17
2. Relating the Terrestrial Factors to Biodiversity 18
a. Forest Fragmentation 18
b. Edge Habitat 20
c. Patches 20
d. Biological Integrity and Potential Ecological Condition 21
e. Interior Forest Habitat 21
D. RIPARIAN AND WETLAND HABITAT 22
II. METHODOLOGY 22
A. LANDSCAPE ECOLOGY 22
B. DESCRIPTION OF GEOGRAPHIC DATA 24
1. Stream Network 24
2. Land Cover Data 24
3. Riparian Habitat 26
4. Mine Data 26
C. METRIC CALCULATION 39
1. Metric List 39
2. Mine and Valley Fill Area 41
3. Mine Data Ratios 41
4. Direct Impact to Streams 41
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5. Direct Impact to Forests 42
6. Percent Forest Cover 42
7. Grassland as Indicator of Past Mining Impact 42
8. Non-forest Land Cover Class Area Change & Percent Change 43
9. Impacts to Riparian Habitat 44
10. Potential Ecological Condition 44
11. Forest Edge 46
12. FRAGSTATS Metrics 47
III. RESULTS 49
A. MINING SURFACE AREA METRIC RESULTS 49
1. Permit Area 49
2. Mine Data Ratios 49
B. AQUATIC METRIC RESULTS 50
1. Calculated Stream Length 50
2. Aquatic Direct Impacts 52
C. TERRESTRIAL METRIC RESULTS 54
1. Study Area and State Results 54
a. Forest Loss 54
b. Non-forest Land Cover Class Change 55
c. Grasslands as Indicators of Past Mining Impacts 59
2. West Virginia Specific Results 59
a. Forest Loss 59
b. Impacts to Riparian Habitats 60
c. Potential Ecological Condition 61
d. Forest Edge 61
e. Number of Patches 62
f Mean Patch Size 62
g. Percent of the Landscape 62
IV. UNCERTAINTY SECTION 65
A. AQUATIC IMPACTS 65
1. Direct Stream Loss 65
a. Permit Boundaries 65
b. Stream Network 65
B. TERRESTRIAL IMPACTS 66
1. Forest Loss 66
a. Permit Boundaries 66
b. Kentucky Permit Data 68
c. Timber Harvesting 68
d. Temporal Misrepresentations 69
2. Non-forest Land Cover Class Change 69
a. Underestimations Due to Scale 69
b. Temporal Misrepresentations 70
c. Other Land Use Changes 70
3. Grasslands as Indicators of Past Mining Impacts 70
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4. Impacts to Riparian Habitats 72
a. Uncertainty in the Data 72
b. Problems in Defining Riparian Habitat 72
5. Potential Ecological Condition 73
a. Factors Associated with Calculation and Application 73
b. Lack of Pre-Impact Value 73
6. Forest Edge 74
7. Number of Patches, Mean Patch Size, and Percent
of the Landscape 74
V. DISCUSSION 74
A. ECOLOGICAL SIGNIFICANCE OF METRICES ASSOCIATED
WITH THE AQUATIC ENVIRONMENT 74
1. Summary and Discussion of Results of Aquatic Metrices 74
2. Consequences of Altering Ecological Processes in
Aquatic Systems 75
a. Considerations in the Cumulative Impact Assessment
of Ecological Process Effects 75
b. Ecological Process Effects in Aquatic Systems 76
B. ECOLOGICAL SIGNIFICANCE OF METRICS ASSOCIATED
WITH THE TERRESTRIAL ENVIRONMENT 88
1. Ecological Significance of Forest Loss 88
a. Uniqueness of Habitats Within the Study Area 91
b. Discussion of Wildlife Dependent on Forested Habitats 94
c. Important Wildlife That May Serve as Models or Ecological
Indicators of Disturbance 97
2. Discussion of Habitat Changes and Interpretation
of Significance 102
3. Potentially Adverse Impact on Biodiversity 103
4. Carbon sequestration and the Forest Carbon Cycle 104
V. REFERENCES 106
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Tables
Table I.A-1 Ecological Subregion Section in the Study Area 3
Table I. A-2 Ecological Subregion Section Characteristics 4
Table II.C-1 Metric List 37
Table III.B-1 Miles of Stream in the Synthetic Stream Network 46
Table III.B-2 Percent of Streams within Different Stream Orders 47
Table III.B-3 Miles of Direct Stream Impact 48
Table III.B-4 Miles of Direct Stream Impact Per Mineral Extraction and Valley Fill Areas . . 49
Table III.C-1 Non-Forest Land Cover Class Impacts (acres) 51
Table III.C-2 Land Class Patch Type Percent of Landscape, WV 58
Table V.B-1 Predicted Terrestrial Impacts 82
Table V.B-2 Summary of West Virginia Gap Terrestrial Land Use Data and
the Number of Wildlife Species Associated with Each Land Use Class 87
Table V.B-3 Summary of the Avian Richness of the West Virginia Portion
of the Study Area 89
Table V.B-4 Forest Area Requirements for 19 Neotropical Migrant Bird Species
of the Study Area 91
Figures
Figure II. A-1
Figure III.A-1
Figure IE. A-2
Figure III.B-1
Figure III.C-1
Figure V. A-1
Figure V.A-2
Figure V.B-1
Figure V.B-2
Figure V.B-3
Figure V.B-4
Figure V.B-5
Study Area
Location of Permits in Study Area
Typical MTM/VF Mine Site Layout
Percent of Streams within Different Stream Orders
Relationship Between Forest Cover and Potential Ecological Condition
Most Impacted Watersheds Based on Miles of Direct Stream Impact or Percent of
Direct Stream Impact
Miles of Stream Length Directly Impacted (by Watershed)
Most Impacted Watersheds Based on Percent Forest Loss
Watersheds with Less Than 87% Total Forest Cover
Breeding Range Distribution of Forest Interior Bird Species Known to Occupy
the Study Area
Breeding Range Distribution of Grassland Bird Species Known to Occupy the
Study Area
Percent Change in Cover Types
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ACRONYM LIST
Acronym Explanation
ac or Ac Acre(s)
CEQ Council on Environmental Quality
CPOM Coarse Paniculate Organic Matter
DEM Digital Elevation Model
DOM Dissolved Organic Matter
DOC Dissolved Organic Carbon
FPOM Fine Particulate Organic Matter
GIS Geographic Information System
Mi Miles
MMU Minimum Mapping Unit
MTM/VF Mountaintop Mining/Valley Fill
NEPA National Environmental Policy Act
NLCD National Land Cover Datasets
NDVI Normalized Difference Vegetation Index
NRAC Natural Resource Analysis Center
NRAV Natural Resource Analysis Center (of WVU)
PEC Potential Ecological Condition
WVGAP West Virginia Gap Analysis Project
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EXECUTIVE SUMMARY
This Landscape Scale Cumulative Impact Study evaluates the potentially adverse impacts of future
mountaintop mining in a four-state study area in the Mid-Atlantic Region of the United States. The
study area encompasses 12,200,888 acres within the Appalachian Coalfield Region in portions of
West Virginia, Virginia, Tennessee, and Kentucky. The study area is characterized by steep
mountainous slopes, confined river valleys, and narrow ridge tops. Forests dominate the land cover
of the study area coveringl 1,231,622 acres (92.1%). Ecological communities of the study area are
unique in that they combine characteristically northern species with their southern counterparts, and
thus boast great richness and diversity.
The potential adverse impacts of mountaintop mining in the study area are evaluated here at both
a state-by-state level and the four-state study area level. Potential adverse impacts to aquatic,
terrestrial, and riparian habitats are assessed. In addition, the West Virginia portion of the study area
is evaluated in further detail as described below.
The study uses a Geographic Information System (GIS) approach to project future potentially
adverse impacts on the natural environment within the study area by measuring specific landscape
indicators. Aquatic, terrestrial, and riparian habitat data were acquired and entered into the GIS to
determine pre-impact conditions of the study area. Then surface mine and valley fill spatial
coverages from issued mine permits were imported into the GIS to calculate projected potentially
adverse impacts. Within the West Virginia portion of the study area the GIS was used to calculate
more detailed landscape indicators, some at the watershed level. The study methods build upon a
Landscape Assessment Approach developed by Canaan Valley Institute and "landscape indicators"
used to assess watershed conditions as described in the publication An Ecological Assessment of
the United States Mid-Atlantic Region: A Landscape Atlas USEPA Office of Research and
Development, Washington DC, November 1997.
Future ecological conditions in the study area are represented by the results of the landscape
indicators. Landscape indicators are specific metrics (calculations) that provide an index to the
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health of an ecological region. Landscape indicators are direct or indirect measures of environmental
parameters or combinations of parameters. By evaluating several indicators for a specific landscape
unit (study area) it is possible to assess a level of ecological integrity or vulnerability to degradation.
Landscape indicator metrics calculated for each state and the four-state study area include:
• Mine permit surface area (ac)
Direct impact to streams (mi and %)
Direct impact to forests (ac and %)
• Grassland as indicator of past mining impact (ac and %)
Non-forest land cover class area change (ac and %)
Landscape indicator metrics calculated in further detail for the West Virginia portion of the study
area include:
• Mine data ratios (ac) - Valley fill area to mineral extraction area, Valley fill area to permit
area, Mineral extraction area to permit area
• Direct impact to streams from valley fill area (mi and %)
• Direct impact to streams from mineral extraction area (mi and %)
Direct impact to streams from permit area (mi and %)
• Forest loss from permit area (ac and %)
Forest loss from valley fill area (ac and %)
Forest loss from mineral extraction area (ac and %)
• Forest loss from auxiliary areas (ac and %)
Impacts to riparian habitats (ac)
• Potential Ecological Condition (unit)
• Forest edge (%)
Number of land cover patches (count)
• Percent landscape of patch type (%)
Mean patch size (ac)
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All metrics and the input data utilized are described in detail within the methodology section of the
report. Individual metrics may not describe the complete ecological condition of a watershed.
However, when considered collectively some conclusions regarding the ecological health of the
watershed may be reached.
Mountaintop Mining Surface Area Metric Results
In the last ten years 403,810 acres were permitted for surface mining in the study area. Disturbance
from surface mining has ecological implications in that the conversion of land use leads to a change
in available habitat.
Aquatic Metric Results
The stream network used in the study is a synthetic network generated from a Digital Elevation
Model (DEM). A DEM is a digital representation of the earth's surface based on a regular series of
sample elevation points. The detail of a synthetic stream network generated in this fashion exceeds
that of a USGS 1:24000 scale stream network. There are 58,998 miles of stream in the study area,
as calculated by the synthetic network. The Kentucky portion of the study area contains more than
one-half of the total stream lengths with 34,468 miles. Studies conducted in the West Virginia
portion of the study area, which has over 12,000 miles of streams, indicate that first and second
order streams comprise more than one-half of the total stream length in the study area.
Mountaintop mining has the potential to adversely impact 1,208 miles of stream in the study area
(2.05%). The potential adverse impact to streams within the Kentucky portion of the study area is
730 miles, or 2.12%. While the greatest potential adverse impact in terms of percent of streams loss
is in the West Virginia portion of the study area at 2.55%, or 307 miles.
Direct impacts to streams in the study area were calculated by mineral extraction area (0.42%) and
valley fill (1.31%) that would result in actual destruction of existing streams. Indirect impacts to
streams such as those that would occur downstream from filled or mined out stream areas were not
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evaluated in this analysis. As such, results of the direct impacts of stream metrics likely
underestimates total impacts to streams.
Terrestrial Metric Results
Forests dominate the terrestrial habitats of the study area. Dominant among these forest types is the
diverse mesophytic hardwood forest. This forest type is characterized by a diverse understory of
trees that never attain canopy status and wildflowers are common. The cove hardwoods are a type
of mixed mesophytic hardwood forest. Cove hardwoods are found in ravines, coves and along
north-facing slopes. Due to the abundance and variety of fruits, seeds, and nuts the diverse
mesophytic forest type provides excellent habitat for wildlife and game species alike. Grasslands
and open habitats are naturally rare in the study area, therefore, species that require these types of
habitats are also, generally rare in the study area.
Forest loss has the potential to impact the biodiversity of the study area in the form a floral and
faunal shift with grassland species becoming more common. Likewise increases in edge habitat and
forest fragmentation may lead to an increase in the number and abundance of edge dwelling species
while inflicting a cost on forest interior species. Forest interior species, such as neotropical migrant
birds, and terrestrial salamanders may be significantly impacted by such land use changes due
largely to direct loss of critical habitat. The study area contains critical habitat for many forest
interior bird species, likewise, forests in the eastern United States are among the most diverse in
salamander richness and abundance in the world.
A decrease in forest cover, subsequently followed by conversion to grasslands, within the study area
has the potential of shifting the fauna of the region from that which is dependent upon undisturbed
intact forest to one dominated by grassland and edge dwelling species. This shift may take a
considerably long amount of time to be recognized; however, some changes may be recognized
immediately. This is a potentially adverse change in that many of the species that may be replaced
have ranges that are restricted to the study area and nearby similar habitats. Thus, a change in these
habitats could put a number of species in peril. The shift in terrestrial habitat would provide new
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refuge for some species that are considered rare in the study area, however, most of these species
are well established in other parts of their range and are most likely rare in West Virginia because
their habitat does not naturally occur there.
Results of this study support the thesis that fundamental changes to the terrestrial environment of
the study area may occur from mountaintop mining. For example, it is estimated that the study area
may have lost approximately 3.4% forest cover in the last ten years from surface mining. This
equates to 380,547 acres. When adding past, present and future terrestrial disturbance, the study
area estimated forest impact is 1,408,372 acres which equates to 11.5 % of the study area. This
number is derived by adding grassland as an indicator of past mining, barren land classification,
forest lost from the last ten years of surface mine permits and a projection of future forest loss that
equates to the last ten years.
Much of this forest is the predominant diverse mesophytic hardwood forest, however, impacts to
cove hardwood, oak, and other forest types are also expected. The predicted condition from the
permit data suggests more than a 3X increase in the surface mining/quarries/gravel pits land class
to 334,791 acres, and this is an underestimation because only fours years of permit data were used
for the Kentucky evaluation of this metric . Not projected by the data but intuitively expected is a
similar increase in the grassland cover types in the study area as mine sites move into reclamation.
Furthermore, the permit data predict that edge habitat will increase by as much as 2.7% from the
present condition in the West Virginia portion of the study area. Fragmentation of the terrestrial
environment, predicted in the West Virginia portion of the study area, will be recognized by an
increase in the number of land use patches from the present 100,392 to 139,689 and a decrease in
average patch size under the permit condition.
All of these changes suggest that the biological integrity of the study area may be jeopardized. The
potential ecological condition (PEC) is a measure of the biological integrity specific for eastern
forests that takes into account forest cover, interior forest, and surrounding land use. PEC was
calculated at the watershed level for the West Virginia portion of the study area and graphically
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extrapolated to predict PEC of the four-state study area. Results suggest that the predicted
pre-impact PEC of study area is higher than that of the issued permits condition.
Riparian Habitat Metric Results
Riparian habitats are generally ecologically diverse and they often provide habitat for unique, or
ecologically important species. For example, many neotropical migrant birds utilize this habitat type
for breeding and the moist environment provides excellent habitat for salamanders. Furthermore,
riparian habitats are the interface between the terrestrial and aquatic environment thus they
contribute to the flow of energy between these environments. Due to the rugged topography of the
study area, a large majority of the riparian habitats are associated with small, first and second order,
streams.
Riparian habitats occupy 236,843 acres of the West Virginia portion of the study area. The
projected potential adverse impacts in the West Virginia portion of the study area is 7,591 acres, or
3.2%. Approximately 55% of the projected riparian habitat impacts occur in first and second order
streams which are important habitats to many species of salamanders and other wildlife.
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I. INTRODUCTION
This Landscape Scale Cumulative Impact Study evaluates the cumulative impacts of past, present,
and proposed mountaintop mining in a four-state study area of the Mid-Atlantic Region of the
United States. The term mountaintop mining as used in this study refers to all surface mining in
steep slope Appalachia. This study evaluates all surface mining operations in the study area that
were permitted in or after 1992. Excluded from the study are permits that represent underground
mining, preparation facilities, coal waste disposal areas, etc. so that only past, present, and proj ected
surface mining activities are included. It is assumed that disturbances for permits approved before
1992 that were still operating after 1992 will be offset by digitized permits approved in recent years
(2000-2002) that have not commenced.
A detailed description of the study methods is included in Section II - Methodology. In short the
study evaluated impacts to both the aquatic and terrestrial environment in the four-state study area
using digitized permit polygons and land cover data imported into a geographic information system
(GIS).
In an attempt to relate the proj ect impacts to cumulative impacts in the natural environment the study
further evaluated a portion of the study area (West Virginia) in greater detail using methods built
upon a Landscape Assessment Approach developed by Canaan Valley Institute and "landscape
indicators" used to assess watershed conditions as described in the publication An Ecological
Assessment of the United State sMid-A tlantic Region: A Landscape Atlas USEP A Office of Research
and Development, Washington DC, November 1997. The detailed West Virginia-based study
evaluated the future impacts based on permit data that was 60% complete.
Future ecological conditions in the study area are represented by the results of the landscape
indicators. Landscape indicators are specific metrics that provide an index to the health of an
ecological region. Landscape indicators are direct or indirect measures of environmental parameters
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or combinations of parameters. By evaluating several indicators it is possible to assess a level of
ecological integrity or vulnerability to degradation relative to other watersheds.
All metrics and the input data utilized are described in detail within the methodology section of the
report. Individual metrics may not describe the complete ecological condition of a watershed;
however, when considered collectively some conclusions regarding the ecological health of the
watershed may be reached.
The report begins with a brief description of aquatic and terrestrial habitats. Factors such as forest
fragmentation are discussed as they relate to the study area habitats. Section II of the report details
the study methodology including a description of the metrics and the geographic data sets. Section
III presents the landscape indicator metric results including tables, figures and graphs. Section IV
presents a discussion of the ecological significance of the landscape indicator metric results.
A. STUDY AREA
The study area includes eastern Kentucky, northwest Virginia, southwestern West Virginia and a
small portion of Tennessee (Figure I.A-1). It covers an area of 12,200,888 acres. The study area
is located within portions of nine ecological subregion sections (refer to Figure I.A-1).
Analysis at the ecological subregion level is of considerable value when the purpose is for strategic,
multi-forest, statewide, and multi-agency assessment because several variables are considered when
defining the boundaries of each ecological subregion (U.S. Forest Service, USD A, 2002). The
ecological units of an ecological subregion analysis are termed sections. Within an ecological
subregion section geomorphology, lithology, soils, vegetation, fauna, climate, surface water
characteristics, disturbance regimes, land use, and cultural ecology are generally similar.
The percent of each ecological subregion section in the study area is outlined in Table I.A-1. Nearly
90% of the North Cumberland Mountains Ecological Subregion lies within the study area.
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Characteristics of each ecological subregion section of the study area are summarized in Table I. A-2.
Table I.A-1
Ecological Subregion Section in the Study Area
Ecological Subregion
Allegheny Mountains
Central Ridge and Valley
Interior Low Plateau, Bluegrass
Interior Low Plateau, Highland Rim
Northern Cumberland Mountains
Northern Cumberland Plateau
Northern Ridge and Valley
Southern Cumberland Mountains
Southern Unglaciated Allegheny Plateau
Percent in Study Area
(%)
6.5
0.4
0.4
0.7
89.7
57.9
0.9
49.2
11.0
Source: U.S. Forest Service, USDA, 2002
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Table I.A-2
Ecological Subregion Section Characteristics
Ecological Subregion
Allegheny Mountains
Central Ridge and
Valley
Interior Low Plateau,
Bluegrass
Interior Low Plateau,
Highland Rim
Northern Cumberland
Mountains
Northern Cumberland
Plateau
Northern Ridge and
Valley
Southern Cumberland
Mountains
Southern Unglaciated
Allegheny Plateau
Geomorphology
(Province)
Appalachian
Plateaus
Ridge and Valley
Interior Low
Plateaus
Interior Low
Plateaus
Appalachian
Plateaus
Appalachian
Plateaus
Ridge and Valley
Appalachian
Plateaus
Appalachian
Plateaus
Natural Vegetation
(Forest Type)
Northeastern Spruce-Fir
Northern Hardwoods
Mixed Mesophytic
Oak-Hickory-Pine
Appalachian Oak
Oak-Hickory
Oak-Hickory
Mixed Mesophytic
Appalachian Oak
Northern Hardwoods
Mixed Mesophytic
Appalachian Oak
Appalachian Oak
Oak-Hickory-Pine
Northern Hardwoods
Appalachian Oak
Mixed Mesophytic
Mixed Mesophytic
Appalachian Oak
Climate
(mean annual)
Free: 46-60"
Temp: 39-54T
Free: 36-55"
Temp: 55-61 T
Free: 44"
Temp: 55 T
Free: 44-54"
Temp: 55-61 T
Free: 40-47"
Temp: 45-50 T
Free: 46"
Temp: 55 T
Free: 30-45"
Temp: 39-57 T
Free: 46"
Temp: 55 T
Free: 35-45"
Temp: 5
Source: U.S. Forest Service, USDA, 2002
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The study area is located within the Appalachian Coalfield Region of the Appalachian Plateau
physiographic province and Bituminous Coal Basin. The rugged terrain of this region is generally
characterized by steep mountain slopes, confined river valleys, and narrow ridge tops. The geologic
processes and climatic conditions responsible for the formation of these land forms, have as a result,
helped to determine the past and present land use and land cover of the region. The ecological
communities of the study area are unique because they combine characteristically northern species
with their southern counterparts, and thus boast enormous richness and diversity.
B. AQUATIC HABITATS
Lotic or flowing aquatic systems are important landscape features in the study area. Lotic systems
may be considered to include rivers, streams, and creeks and springs. This section will discuss the
types, features and functions of lotic systems in the study area.
1. Representative Streams
a. Physical Characteristics
Numerous physical parameters such as flow volume, substrate (i.e., the stream bottom made up of
cobbles, gravel, sand, etc.), water chemistry, and bank cover influence the biota of the aquatic
systems in the study area. These parameters are determined by the climate, lithology, relief and land
use in the area of a particular stretch of stream.
b. Stream Classification
Streams are generally classified through a system called stream ordering (Strahler, 1957). This
system classifies streams based on size and position within the drainage network. A first-order
stream is defined as not having tributaries. The confluence of two streams of the same order
produces the next highest order. For example, the joining of two first-order streams results in a
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second-order stream. The joining of two second-order streams produces a third-order stream, etc.
Headwaters are usually classified as first- through third-order streams, mid-sized streams as fourth-
through sixth-order streams, and larger rivers as seventh- through twelfth-order streams (Ward,
1992).
c. Habitats in Streams
Generally, headwater streams originate at high elevations in the study area. Substrate patterns in
headwater streams channels are typically comprised of coarser material such as boulders, cobble
rubble and bedrock. Large, woody debris often contribute to the substrate complexity in headwater
streams. Small pools with finer sediments may also be found along headwater streams. Typical
substrate patterns in larger rivers are comprised of finer material such as silt and sand. Mid-sized
rivers typically contain a blend of cobble and gravel with some finer sediment interspersed in areas
of slower flow.
The combination of substrate characteristics and varying flow rates and other flow characteristics
(hydrologic cycles, flow patterns, load transport and storage) produce channel features such as
riffles, runs, and pools. Riffles are erosional habitats where surface water flows over coarser
substrate, creating turbulence, which causes disturbances in the surface of the water. This turbulence
increases levels of dissolved oxygen by encouraging the mixing of oxygen in the air with the water.
Pools are deposit!onal areas where flow is slow or stagnant, allowing finer particulate matter to settle
onto the stream bottom. Runs are moderately fast sections of streams where the water surface is not
as disturbed. Headwater streams, typically consist of alternating riffles and runs though small
depositional pools, may be present and represent an important microhabitat. Mid-sized rivers
typically contain all three features because increased width and depth allow more variation in flow.
Stream features that are important in determining habitat for aquatic organisms include, overhanging
vegetation, the presence and characteristics of leaf packs, in-stream vegetation, large woody debris,
undercut banks, and exposed tree roots. Overhanging vegetation consists of riparian shrub and
herbaceous vegetation on banks that grows over and sometimes into the surface water. In-stream
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vegetation occurs where proper substrate and flow conditions allow growth. Snags are pieces of
wood that have accumulated in a stream area. Undercut banks and exposed tree roots are caused by
a combination of unstable banks and fast streamflow. All of these features provide unique habitat
for cover, habitat, and food for macroinvertebrates and fish.
Other in-stream features that provide additional habitat include littoral areas such as shorelines,
sandbars, and islands. Typically these features exist most prominently in deposit!onal systems such
as larger rivers. These littoral areas are shallow habitats, which provide habitat for smaller fish and
macroinvertebrates that are unable to live in the deeper sections of the river.
2. Energy Sources and Plant Communities
Aquatic ecosystem energy sources consist of allochthonous (material produced outside the stream
such as leaves, wood, etc.) and autochthonous (instream primary production by plants, algae)
sources. Allochthonous organic material includes leaves and woody material. These materials reach
the stream either through directly falling into the stream or through indirectly being transported into
the stream, commonly though wind movement or runoff. Allochthonous organic material has been
found to be the predominant energy source in high-gradient streams of the southern Appalachians
(e.g., Hornick et al., 1981, Webster et al., 1983, Wallace et al., 1992). Headwater energy sources
are utilized, not only by invertebrates and vertebrates in upper reaches of the watershed, but, excess
organic carbon is subsequently utilized by life forms in all stream orders down gradient. Since
streams have a unidirectional flow, downstream areas are also dependent on upstream areas for
portions of their energy (Vannote et al. 1980).
Plant communities of high-gradient streams live in what may be considered to be a physically
challenging environment. Frequently these habitats are densely shaded and subject to high current
velocities. As a result, the plant communities in high-gradient streams are reduced relative to lentic
habitats and low-gradient streams (Wallace et al., 1992). However, the plant communities occurring
in high-gradient streams contain flora uniquely adapted to survive in this type of environment. This
habitat also supports an abundance of flora considered to be endemic (i.e., not found in other
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locations) to the region (Patrick, 1948). Possibly, the historic lack of direct anthropogenic (human-
induced) disturbance to watersheds of high-gradient streams may have contributed to the survival
of the unique and endemic flora of this region (Wilcove et al., 1998).
a. Primary Producers and Primary Production
Primary production is the input of energy into a system by the growth of flora living in the system.
In streams, primary production is generally measured as mass of carbon or ash free dry mass, which
is largely carbon, per unit area, per year. Primary production rates in Appalachian streams have
been shown to vary with stream order, season, degree of shading, nutrients, and water hardness
(Wallace et al., 1992). Although under some circumstances, gross primary production can be high
(see Hill and Webster 1982b [in Wallace et al., 1992]), typical primary production inputs appear to
range from approximately 9 to 446 pounds of carbon per acre of stream per year (Keithan and Lowe
1985,Rodgersetal., 1983, Wallace etal., 1992). Primary producers in Appalachian streams include
vascular plants, bryophytes and algae.
b. Allochthonous Energy Sources and Processing
Allochthonous energy sources consist primarily of leaves and woody material. However, dissolved
organic carbon (DOC) from a variety of sources is an additional allochthonous energy source.
Sources of DOC external to the stream include groundwater or runoff. Sources internal to the stream
relate largely to leaching of organic matter from detritus or other organic matter. Fisher and Likens,
in Science Applications International Corporation (1998), explain that over 90 percent of the annual
energy inputs to small forested streams can be attributed to leaf detritus and dissolved organic
carbon from the terrestrial environment. Webster et al. (1995) further discusses sources for organic
inputs to streams.
The estimate of almost 3600 pounds of carbon per acre of stream per year developed by Bray and
Gorham (1964) as a measure of leaf and wood litterfall into a stream per year, is considered to be
a good estimate for input into high-gradient Appalachian streams. The mass of material input as leaf
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fall is generally greater than that input as woody material. However, in some circumstances the
mass of input as woody material may equal that of leaf input (Webster et al., 1990).
The headwater stream (first- through third-order) is the origin for energy processing within the river
ecosystem. Headwater streams in the study area are located in forested areas and are characterized
by a heavy leaf canopy and low photosynthetic production. Sources of energy for headwater streams
are allochthonous in origin or derived from the terrestrial environment. The vast majority of this
allochthonous material arrives in the streams in the form of Coarse Particulate Organic Matter or
CPOM (> 1 mm in size). Smaller amounts of other allochthonous material that is transported to the
stream includes Fine Particulate Organic Matter (FPOM, 50 um - 1 um in size) and Dissolved
Organic Matter (DOM) traveling from surface and groundwater flow. Microbes and specialized
macroinvertebrates living in headwater streams, called shredders, feed on the DOM and CPOM,
converting it into FPOM and DOM. The FPOM and DOM are carried downstream to mid-sized
streams.
Because mid-sized streams (fourth- through sixth-order) are wider than headwater streams, the
canopy is usually more open and more light is able to penetrate to the stream bottom. As a result,
a greater abundance of algae and aquatic plants are able to grow along the stream bottom. In
general, the contribution of allochthonous material derived from terrestrial vegetation in midsized
streams is less than in the headwater streams. Autochthonous material, meaning material that is
derived from within the stream, becomes an important component of the energy budget in midsized
streams.
3. Animal Communities
a. Invertebrates
Stream order typically dictates the community structure of the resident aquatic life. Headwater
streams harbor primarily benthic macroinvertebrate communities who are specialized to feed on the
CPOM deposited in the system. Examples of benthic macroinvertebrates include crayfish, worms,
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snails and flies. The majority of benthic macroinvertebrates in headwater streams are classified as
shredders and collectors, who feed on the CPOM and FPOM, and predators who feed on the other
macroinvertebrates. Typical benthic macroinvertebrates found in headwater streams in the study area
include insects such as mayflies (Ephemeroptera), stoneflies (Plecoptera), caddisflies (Trichoptera),
dragonflies and damselflies (Odonata), beetles (Coleoptera), dobsonflies and alderflies
(Megaloptera), true bugs (Hemiptera), springtails (Collembola), and true flies (Diptera). Other
macroinvertebrates that have been collected include crayfish (Decapoda), isopods (Isopoda), worms
(Oligochaeta and Annelida) and snails (Gastropoda) (FWS, 1998; Science Applications International
Corporation, 1998).
In the southern Appalachian Mountains, macroinvertebrates of several orders including
Ephemeroptera, Plecopter and Trichoptera have been found to be rich in species, including many
endemic species and species considered to be rare. This diversity and unique assemblage of species
has been attributed to the unique geological, climatological and hydrological features of this region
(Morse et al., 1993, Morse et al., 1997). Many biologists agree that the presence of a biotic
community with such unique and rare populations should be considered a critical resource.
b. Vertebrates
Two groups of vertebrates, fish and salamanders are the major stream-dwelling vertebrates in the
study area. Typically, salamanders occupy small, high-gradient headwater streams while fish occur
farther downstream. Predation by fish is believed to restricts salamanders to the smaller streams or
the banks of large streams (Wallace et al., 1992).
Fish species present in headwater streams tend to be representative of cold water species, and
primarily sustained by a diet of invertebrates (Vannote et al, 1980). As found with invertebrates and
amphibians, the fish assemblages of the Appalachians tend to contain a relatively large number of
endemic and unique species. Some fish species collected in the pristine headwaters of West Virginia
include blacknose dace (Rhinichthys atmtiilus), creek chub (Semotilus atromaculatus), and slimy
sculpin (Cottus cognatus) (FWS, 1998).
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Many different kinds of amphibians and reptiles live in or near streams and wetlands. Many types
of amphibians in particular are unique to the Appalachian regions. The West Virginia Division of
Natural Resources has published a pamphlet, "Amphibians and Reptiles of West Virginia: A Field
Checklist." This list mentions 46 amphibious species and 41 reptilian species, the vast majority of
which are most likely located throughout the study area within suitable habitat of Kentucky,
Tennessee, and Virginia. Many of these amphibious and reptilian species may be primarily
terrestrial, but live in proximity to aquatic areas such as streams and wetlands. In addition, several
species strictly rely on the presence of streams or wetlands for at least part of their life cycle (Conant
and Collins, 1991).
It is difficult to predict what fish species will be found in a stream with a particular stream order
designation. For example, one would expect a much higher diversity of fishes in a first-order stream
that empties directly into a fourth-order stream than would be found in a first-order stream that joins
with another first-order stream to form a second-order stream. It would be wrong to interpret the
higher diversity in the first case as being indicative of a healthier or cleaner stream. In general, fish
diversity is greater in higher-order streams, but certainly so-called "big river" fishes will enter first-
order streams, when these streams drain directly into higher order lotic systems (Stauffer, 2000).
4. Ecosystem Function
The value of headwater streams in the study area was the subj ect of a symposium held in April 1999.
The proceedings of this symposium are summarized below.
Small streams play a pivotal role in lotic ecosystems. Small streams:
• Have maximum interface with the terrestrial environment with large inputs of organic matter
from the surrounding landscape
• Serve as storage and retention sites for nutrients, organic matter and sediments
Are sites for transformation of nutrients and organic matter to fine parti culate and dissolved
organic matter
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Are the main conduit for export of water, nutrients, and organic matter to downstream areas
(Wallace in Symposium on Aquatic Ecosystem Enhancement at Mountain Top Mining Sites,
January 2000)
The major functions of headwater streams can be summarized into two categories, physical and
biological (Wallace in Symposium on Aquatic Ecosystem Enhancement at Mountain Top Mining
Sites, January 2000):
Physical
• Headwater streams tend to moderate the hydrograph, or flow rate, downstream
They serve as a major area of nutrient transformation and retention
• They provide a moderate thermal regime compared to downstream waters- cooler in summer
and warmer in winter
• They provide for physical retention of organic material as observed by the short "spiraling
length"
Biological
Biota in headwater streams influence the storage, transportation and export of organic matter
• Biota convert organic matter to fine particulate and dissolved organic matter
They enhance downstream transport of organic matter
• They promote less accumulation of large and woody organic matter in headwater streams
• They enhance sediment transport downstream by breaking down the leaf material
They also enhance nutrient uptake and transformation
In summary, light and the input of allochthonous material are the two limiting factors in the
contribution of energy to a river ecosystem as a whole. When an energy source is altered or
removed in the upstream reaches, downstream biological communities are also affected. The value
of headwater streams to the river ecosystem is emphasized by Doppelt et al. (1993): "Even where
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inaccessible to fish, these small streams provide high levels of water quality and quantity, sediment
control, nutrients and wood debris for downstream reaches of the watershed. Intermittent and
ephemeral headwater streams are, therefore, often largely responsible for maintaining the quality
of downstream riverine processes and habitat for considerable distances."
C. TERRESTRIAL HABITATS
Forests dominate the terrestrial habitats of the study area. Data provided by the West Virginia Gap
Program indicates that at least nine forest types are located within the WV portion of study area.
Dominant among these forest types is the diverse mesophytic hardwood forest. The diverse
mesophytic forest is among the most diverse forest type in the southeastern United States (Hinkle
et al.,1993). Yellow poplar (Liriodendron tulipiferd) is the predominant species in the diverse
mesophytic forest type in the Central Appalachians (Hicks, 1998); however, dominance is shared
by a large number of species including various oaks (Quercus spp.), maples (Acer spp.), beech
(Fagusgrandifolia), hickories (Carya spp.), cherry (Prunus spp.), and black walnut (Juglansnigra),
to name but a few (Strausbaugh and Core, 1997). This forest type is characterized by a diverse
understory of trees that never attain canopy status and wildflowers are common.
The cove hardwoods are a type of mixed mesophytic hardwood forest. They are included here
because species common to the cove hardwoods are likely common to the mixed mesophytic
hardwood forest type as well due to their spatial relationship. Cove hardwoods are found in ravines,
coves and along north-facing slopes. Often, pure stands of yellow poplar are the hallmark of the
cove hardwood forests (Hicks, 1998). Species composition can be very diverse with red oak
(Quercus rubra), pin cherry (P. pennsylvanica), black cherry (P. serotina), paper birch (Betula
papyrifera), yellow birch (B. alleghaniensis), aspen (Populus spp.), sugar maple (A. sacchaum), red
maple (A. rubra), and Eastern hemlock (Tsuga canadensis) dominating (Strausbaugh and Core,
1997). Local species dominance patterns are often small scale with significant species changes over
relatively short distances.
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Due to the abundance and variety of fruits, seeds, and nuts the diverse mesophytic forest type
provides excellent habitat for wildlife and game species alike. Wildlife species richness of the
mixed mesophytic forests of the study area are considered one of the most diverse in the United
States (Hinkle et al., 1993). Factors associated with the terrestrial habitats of the study area are
described in detail below.
1. Defining Factors Associated with the Terrestrial Habitat
a. Forest Fragmentation
The phrase forest fragmentation describes a formerly continuous forest that has been broken into
smaller pieces. Forest fragmentation occurs when an activity removes some forest and leaves
remaining stands in smaller isolated blocks. The pattern of forest loss is as important as the amount
of loss. A checkerboard pattern of remaining forest represents more forest fragmentation than
clumps of forest of the same total acreage.
The degree of forest connectivity can affect the sustainability of forest species within and among
a landscape. However, connectivity can sometimes be misleading. For example, a series of small
woodlots may be connected and creating substantial area yet they make lack the interior forest
needed to support certain species. Areas with large blocks of continuous forests support a variety
of interior forest species, e.g., neotropical migrants, pileated woodpecker, etc., whereas areas with
small fragmented forests tend to support fewer interior forest species with more edge dwelling
species.
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b. Edge Habitat
Edge habitat occurs at boundaries between different types of land cover. Many wildlife species
require resources in two or more vegetation types and thus require edge habitat. Some species of
birds forage in grasslands and nest in forests. Nest parasitic bird species such as brown-headed
cowbirds (Molothrus ater) have their greatest impact on other native species in areas where edge
habitat is common (Robinson et al., 1995 and citations within). For instance, the brown-headed
cowbird is a native species of open prairies of the American mid-west but has spread to all of eastern
North American due to the conversion of forests to agricultural lands. This species is essentially
absent from interior forests but common along edge habitat ecotones. As forests are fragmented and
edge habitat increases, interior species such as the ovenbird, hooded warbler, and wood thrush, are
subject to nest parasitism by cowbirds, and thus decreased rates of reproductive success (Buckelew
and Hall 1994, Robinson et al., 1995).
The outer boundary of a forest is not a line, but rather a zone that varies in width. Meffe and Carroll
(1994) report of edge zones in Wisconsin that are as small as ten meters to those in Queensland that
are as great as 500 m. The breadth of edge zones may well have to do with microclimatic
differences associated with the edge. Edge zones are usually drier and receive more sunlight than
interior forests and thus have a different floral composition, favoring shade-intolerant species.
Microclimatic edge effects such as this may have a negative effect on interior species of the patch
through altering of the physical environment and competition for resources. On the other hand, due
to the different microclimate associated with the edge ecotone, these habitats are often more diverse
than the interior habitat.
Edge effect is usually used to describe two phenomenon associated with edge habitats. Often, the
phrase edge effect is used to describe the negative influence that edges have on the interior of a
habitat and on the species that use the interior habitat, like the microclimatic differences described
above. Furthermore, edge effect can be used to describe the increase in species richness often
observed at the ecotone of forest edges.
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Patches
Patch size refers to the area of a particular habitat or reserve within a landscape. The basic
species-area relationship (MacArthur and Wilson, 1963) implies that larger patches sustain a greater
number of species of a region than do smaller patches. This is due, in part, because large patches
have an increased chance for immigration. Another reason that this relationship is due to an increase
in habitat heterogeneity as patch size gets larger. Larger patches are also more likely to be able to
accommodate disturbances than smaller patches. As patch size decreases forest perimeter-to-volume
ratios increase, thereby increasing edge effects and reducing the amount of interior habitat.
Another aspect of patch size is isolation. Small, isolated patches are more prone to species
extinctions than large patches and small groups of closely spaced patches because they are less
likely to be colonized (MacArthur and Wilson, 1963). Isolation leads to a loss in genetic diversity
and often to an increase in deleterious gene frequencies within the isolated populations. Isolation
is a major cause of vicariant speciation but at the same time it is a major cause in species extinction
(Brown and Lomolino, 1998). Vicariant event speciation describes the presence of two closely
related yet disjunct species that are assumed to have been created when the range of their ancestor
was split.
d. Biological Integrity and Potential Ecological Condition
Biological integrity refers to the ability of an environment to support and maintain a balanced and
integrated adaptive assemblage of organisms having species composition, diversity, and functional
organization comparable to that of an undisturbed habitat within the same region (Karr et al., 1986).
Generally, the term biological integrity is limited to use of aquatic habitats where it has received
much recent attention because of the terms use in the Clean Water Act (section 101(a)). However,
the principal of biological integrity applies to all ecosystems. One measure of the biological
integrity of the terrestrial environment is the potential ecological condition (PEC), also known as
the bird community index (O'Connell et al., 1998). PEC and how it is calculated will be discussed
in detail in Chapter II. Methodology, later in this report. Bird guilds are used as models in the PEC
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calculation, however, the results are applicable for all taxa that depend on interior forests (O' Connell
etal. 1998; O'Connell etal., 2000). PEC is an effective measure of biologic integrity in that it takes
into account measures of forest cover, interior forest habitat, and human use conditions to generate
a value for a location (watershed or study area) that can be compared with values modeled from
other locations or under different disturbance regimes. These modeled changes in PEC are
equivalent to a change in biological condition, thus the link between biological integrity and PEC.
e. Interior Forest Habitat
A variety of wildlife species require large tracts of continuous forest cover for their survival. For
example, the cerulean warbler, Dendroica cerulea, is a common bird of mixed mesophytic and
Appalachian oak forests in West Virginia. This migratory species commonly occupies the heavily
leafed canopy of mature forests during summer months and is rarely seen. Studies suggest that a
minimum area of 700 hectares is required for sustaining a viable population of this species
(Bucketew and Hall 1994). Robbins et al. (1989a) addressed habitat area requirements for a large
number of forest-dwelling birds in the central Appalachians. Of the 75 forest and forest-edge
species included in the study, none was restricted to small forests and many had minimum breeding
habitat requirements greater than 3,000 hectares (Robbins et al., 1989b).
There are several reasons why interior forest habitat is required for the breeding success of many
forest birds. One factor is the increased diversity of microclimates within larger forest patches. A
second reason is the significantly higher rates of nest predation in small forest patches (Brittingham
and Temple, 1983; Small and Hunter, 1988). Finally, Robbins et al. (1989) suggests that the short
breeding period associated with neotropical migrants when compared to year-round residents leads
to increased susceptibility to negative environmental influences like nest predation and brood
parasitism. In short, many neotropical migrant species are forced to breed in large tracts of interior
forest because they only have time for one breeding event per year.
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2. Relating the Terrestrial Factors to Biodiversity
The term biodiversity is used to describe the variety of living organisms and can be applied to
various levels of biological organization. For example, biodiversity may be implied at the genetic,
species/population, or ecosystem levels. Often, biodiversity is used to describe the variety of a
higher taxonomic order, birds for instance, in a region or study area. The terrestrial factors
described above all have the potential to exert a considerable affect on biodiversity at one or
numerous of the levels biological organization and scale. Below is some discussion that attempts
to relate the terrestrial factors discussed above with biodiversity at both the watershed (local) and
study area (regional) spatial levels.
a. Forest Fragmentation
Some of the effects of habitat fragmentation occur almost immediately while others develop over
decades (Meffe and Carroll, 1994). The most notable effect of fragmentation is the loss of a
particular species from the fragmented landscape. Data suggests that habitat destruction is
responsible for more than one-half of the species lost. Endemic species, those with a very narrow
distribution range limited to a specific habitat, may exhibit immediate loss or local extinction of
populations. Meanwhile, species that are not rare or endemic may be affected at a much slower rate.
Take for example the reduced nesting/reproductive success of midwestern (United States) migratory
birds in response to forest fragmentation (Robinson et al., 1995). Robinson et al. (1995) suggests
that forest fragmentation leads to increase nest predation and ultimately to establishment of
migratory bird populations that are unable to sustain themselves without immigration from non-
fragmented habitats. Populations that exist this way are referred to as "sinks" depending solely on
immigration from the "source" population for survival (Pulliam, 1988). By definition, a source
habitat has reproductive success greater than local mortality, whereas, a sink habitat has mortality
rates higher than reproductive rates. Thus, individuals living in sink habitats are on the brink of
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local extinction. However, so long as the source population is unaffected and immigration routes
remain open, recolonization will likely take place following local extinction.
The reason that sink populations are unable to achieve reproductive success greater than mortality
is generally a condition of the local environment. This condition may be associated with isolation,
introduced species, loss of critical habitat, or any of a number of possible conditions. In any case,
the effect likely exhibited on the species is the loss of a genetically effective population size.
Genetic diversity is a key for the long-term survival of populations. Genetic variation is important
to both fitness of the individual and adaptive change. Small populations generally are less
genetically diverse than large populations and this decrease in genetic diversity tends to result in a
reduced evolutionary adaptive fitness (ability to change with a changing environment) and
ultimately to local extinction.
Thus, we can conclude that forest fragmentation exerts its effect on biodiversity at various levels of
biological organization and spatial scales. A decrease in genetic diversity may lead to local
extinction of a population while the local extinctions of many populations in a region may lead to
a decrease in biodiversity at a broader landscape level.
b. Edge Habitat
Ecological processes that structure biological communities may change as a result of edge effects
(Meffe and Carroll, 1995). These changes may be the result of an increase in those species that are
attracted to edges and the decrease in those species that have characteristics that make them
unsuitable for edge habitat. For example, Klein (1989) describes the decline of beetles from edge
habitat compared to interior forest because beetle larvae were desiccating in the drier soils along the
edge. It is unlikely that edge habitat itself would have considerable impact on genetic biodiversity.
Obviously, habitat fragmentation associated with edge habitat does have a major impact on genetic
variation as described above. The affect that edge habitat has on biodiversity is likely more at the
species/community and ecosystem levels. Edge habitats tend to attract certain species of animals
(Gates and Gysel, 1978) and this would lead to a shift in the composition of ecological communities.
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At the broader landscape level, increased edge habitat would lead to an increase in edge favoring
species and a decrease in numbers of those species associated with interior forests.
Patches
Patches and habitat fragmentation go hand-in-hand. Therefore, the affects that fragmentation has
on genetic, species/population, and ecosystem diversity described above also apply to this topic.
As fragmentation increases so do the number of patches in the landscape. Furthermore, an increase
in fragmentation is generally associated with a decrease in the average size of patch types. One
aspect of patches is associated with rare and endemic species. Some species have life history
characteristics that limit their distribution to a small, defined patch or set of patch types. Thus, loss
of a critical habitat across the region may lead to the complete extirpation of a species or group of
species from the landscape.
d. Biological Integrity and Potential Ecological Condition
The measure of PEC is basically a measure of the biological condition of the terrestrial habitat. It
is a tool that assigns a value to an area that can be interpreted as a measure of biodiversity. Since
PEC takes into account ecosystems, not individuals, it is a tool that approximates the ecosystem
biodiversity. Quite simply, PEC is a measure of the terrestrial ecosystem biodiversity at either the
local (watershed) or regional (study area) level.
e. Interior Forest Habitat
Interior forest habitat is important to many species, in particular birds. Birds exhibit many traits that
make them excellent indicators of ecological conditions at both a local and regional level (USEPA
2000). Ecological indicators describe the condition of an ecosystem or one of its critical components.
Different bird species require different habitats for foraging, shelter, and breeding. Thus, bird
populations are linked to an ecological condition and both are linked to a habitat or land cover type.
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Many of the birds of the study area have minimum forest area requirements. These birds are
considered forest interior species and their presence in the landscape is a good indication that
excellent ecological conditions exist. Robbins et al. (1989) defined habitat area requirements for 75
species of birds in the Middle Atlantic States. Among the 75 birds included in the study, 19 were
neotropical migrants. Declines in populations of neotropical migrants from eastern states have been
well documented (Hutto, 1988; Robbins et at., 1989b; Penhollow and Stauffer, 2000). Causes for
neotropical migrant population declines have been attributed to agriculture, urban and suburban
sprawl, and deforestation (Askins et al., 1990). These declines are likely due to factors associated
with forest fragmentation, as described above. Once habitats of contiguous interior forest become
fragmented the factors described above (see Forest Fragmentation discussion) that effect biodiversity
come into play.
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D. RIPARIAN AND WETLAND HABITAT
Wetlands and riparian zones may occur along streams. Wetlands and riparian zones may influence
the physical characteristics of streams, thereby affecting stream habitats. In addition, wetlands and
riparian zones may be used by stream biota directly during periods of elevated flow. Wetlands are
crucial transition zones between terrestrial and aquatic habitats. They are defined as areas "that are
inundated or saturated by surface or groundwater at a frequency and duration sufficient to support,
and that under normal circumstances do support, a prevalence of vegetation typically adapted for life
in saturated soil conditions" (COE, 1987). Wetlands can be found on floodplains along rivers and
streams (riparian wetlands). Typical steep geomorphology of headwater streams usually prohibits
the formation of a floodplain, so wetlands are usually restricted to small depressional areas. As the
gradient of the land becomes more gradual, more wetlands are found on the floodplain of the stream.
Wetlands associated with rivers can take the form of forested wetlands, emergent marshes, wet
meadows or small ponds. The unique characteristics and vegetative composition of wetlands provide
important habitat for many species of aquatic macroinvertebrates, amphibians, and reptiles.
II. METHODOLOGY
A. LANDSCAPE ECOLOGY
Landscapes are comprised of aggregations of various vegetation or land cover types (referred to as
patches) that combine to create patterns or mosaics on the earth's surface. Such patterns have
developed as the result of climatic influences, site quality, natural disturbances, plant succession, and
human activity. Landscape ecology is a discipline that focuses on understanding the causes and
consequences of changes in landscape patterns. A fundamental tenet of landscape ecology is that
humans and their activities are recognized as an integral part of the environment (USEPA, 1997).
Numerous metrics have been developed to quantify changes in landscape patterns over time and
space. Changes in patch diversity, size, proximity, edge, contagion, and connectivity have
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implications to floral and faunal communities as well as other natural features such as water ways.
Mountaintop mining and valley fill activities significantly affect the landscape mosaic. Landcover
changes occur as forests are removed, the topography and hydrology is altered, and vegetation is
eventually re-established. The result is an area drastically different from its pre-mining condition.
Soil qualities are different, the vegetative community has a different structure and composition, and
habitats are altered. Over time, if left unmanaged, forest succession will transform vegetative
communities but the rate of this change is heavily dependent on the reclamation intent (i.e. post
mining land use) and practice.
Scale plays an important role in landscape ecology. With changes in scale different patterns emerge
or recede. The scale of analysis should be appropriate to the phenomenon under study. Furthermore,
organisms perceive scale differently. The range of a salamander may be a single acre or less while
a black bear may range over many square miles therefore they will be affected differently by the same
landscape modification event. One species' entire range may be eliminated whereas another can shift
its activities to another location. The study discussed here summarizes data on a watershed scale and
is not intended to assess conditions for areas less than 5,000 to 10,000 acres in extent. Because of
the limitations inherent to the input data, it is not appropriate to assess impacts at a finer scale.
Indeed, any attempt to make a site specific evaluation would be a misuse of the data and any
conclusions from such an evaluation would be highly suspect.
Landscape indicators are direct or indirect measures of environmental parameters or combinations
of parameters. They have been likened to economic indicators such as housing starts, factory orders,
and unemployment percentages. These indicators are used by economists to gauge national economic
condition. No single indicator tells the entire story but by evaluating several one may perceive trends
and make predictions. Likewise, by evaluating several indicators for a specific watershed or group
of watersheds it is possible to assess a level of ecological integrity or vulnerability to degradation
relative to other watersheds. Indicators also serve as monitoring tools to assess ecosystem condition
as landcover modifications occur. To assess cumulative impact it is necessary to look a variety of
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indicators and make comprehensive analyses on the collective. It is also important to realize that
some indicators are strongly correlated with one another.
B. DESCRIPTION OF GEOGRAPHIC DATA
1. Stream Network
The GIS stream network was generated from DEM data using standard ARC Info commands. The
streams are "synthetic" in that they were not generated by conversion of existing maps, such as
orthophotographs or USGS 7.5' quad sheets, into digital format. Rather, they were generated using
a digital elevation model (DEM). A DEM is a digital representation of the earth's surface based on
a regular series of sample elevation points organized in a 30x30 meter grid. OEM's can be used to
model the direction of water flow and accumulation of flow.
For the data used in the cumulative impact study a contributing area of 30 acres was selected to
generate a stream. There is some uncertainty is this selection given that permits in Kentucky have
indicated perennial streams in watersheds smaller than 10 acres. Therefore; the synthetic stream
network may underestimate stream length. This 30 acre threshold is supported by studies by the
United States Geological Survey (USGS), West Virginia Water Resources Division District Office
to field determine the ephemeral-intermittent and intermittent-perennial stream boundaries. The
mean drainage area for 33 sampled ephemeral reaches in the West Virginia coal region was 30 acres
(USGS unpublished data 2000); therefore, the synthetic streams are considered to represent
ephermeral, intermittent, and perennial streams. The detail of these data exceeds that of USGS
1:24,000 scale stream networks (Figure II.C-1) which generally capture perennial and inconsistently
ephemeral streams. The synthetic stream network was not ground truthed.
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2. Land Cover Data
The forest loss was calculated using the National Land Cover Dataset (NLCD). The NLCD was
produced as a cooperative effort among six programs within four U. S. Government agencies: the U.S.
Environmental Protection Agency's (EPA) Environmental Monitoring and Assessment Program
(EMAP); the U.S. Geological Survey's (USGS) National Water Quality Assessment Program
(NAWQA); the Department of Interior National Biological Service's (NBS) Gap Analysis Program
(GAP); the USGS's Earth Resources Observation Systems (EROS) Data Center; the National Oceanic
and Atmospheric Administration's (NOAA) Coastal Change Analysis Program (C-CAP); and the
EPA's North American Landscape Characterization (NALC) project. It provides a consistent, land
cover data layer for the conterminous U.S. using early 1990s Landsat 5 thematic mapper (TM) data.
The goal was to select TM scenes acquired in 1992, plus or minus one year, to allow for basic
temporal consistency across the United States. Scenes were constrained to have a cloud coverage of
no greater than 10 percent and to be of high digital quality.
These data can be used for landscape scale analysis in various disciplines such as wildlife ecology,
forestry, or land use planning. The data scale is 1:50,000. The NLCD classification contains 21
different land cover categories. The National Land Cover Dataset has a spatial resolution of 30
meters and supplemented by various ancillary data. Map projection of original NLCD data set
converted from Albers Conical Equal Area to the Universal Transverse Mercator, Zone 17 coordinate
system.
The additional forest metrics that were calculated only for the West Virginia portion of the study area
(ie. PEC, forest fragmentation and forest edge) were calculated using WV GAP Land Cover. This
land Cover data set is a raster representation of vegetation/land cover for the state of West Virginia.
This data can be used for landscape scale analysis in various disciplines such as wildlife ecology,
forestry, or land use planning. The data have been developed for inclusion in the Gap Analysis
Program. Data scale is 1:50,000. There are 26 land cover codes. Land cover data were collected as
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part of the West Virginia Gap Analysis Project, a collaborative effort between West Virginia
University's Natural Resource Analysis Center, the West Virginia Cooperative Fish and Wildlife
Research Unit, the West Virginia Division of Natural Resources, and the Biological Resources
Division of the US Geological Survey. The source data were acquired from multiple 30-meter
Landsat imagery obtained between 1992-1994 and field checked with videography. Preliminary
results published 2000.
3. Riparian Habitat
While most habitats are mapped using land cover obtained from remotely sensed imagery, certain
reptiles and amphibians rely on wetland or riparian habitat features that cannot be readily mapped
from imagery therefore a separate model of riparian habitats is necessary to assess the relative sustain
ability of these species within each future mountaintop mining scenario. The West Virginia Gap
Analysis project (www.nrac.wvu.edu/gap/) created a model of these habitats using raster modeling
techniques (with the aide of Geographic Information Systems) based on stream hydrology, elevation,
slope and ancillary data including the USFWS National Wetlands Inventory (Strager et al., 2000.)
This modeled habitat shows mapped stream, wetland, open water, and riparian habitats throughout
the state at a much more detailed level than the WV-GAP land cover and allows for prediction of
amphibian and reptile distribution. These data are used to estimate loss of these habitats. These data
are intended to be used at a scale of 1:100,000 or smaller for the purpose of assessing the
conservation status of vertebrate species and vegetation types over large geographic regions.
The model of potential wetland and riparian habitats is created from the combination of the riparian
areas surrounding streams, existing wetlands data, and forested land cover data. This model is used
as an input for species distribution modeling. Stream hydrology, percent slope, and digital elevation
data were combined to produce relative cost path distance grids for headwater, small, and large
streams. Path distance grids were derived from the "cost" incurred by movement from source cells
(streams) to non-source cells. The cost of movement between cells is weighted by an impendent
factor (slope) applied over surface distances (derived from digital elevation data). The resulting grids
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can be used to approximate riparian areas surrounding streams. Forested land cover and existing
wetlands data were also input to the model of potential wetland and riparian habitats.
4. Mine Data
Mine permit GIS layers were obtained from the United States Office of Surface Mining (OSM). The
goal was to compile GIS layers representing approved surface mining permits from the ten year time
period of 1992-2002 within the four state EIS study area. Mine permit polygons are based on maps
submitted to the SMCRA authority by mine operators seeking to obtain a permit. The mine data set
was compiled in such a fashion as to be as consistent as practicable among the states in the study
area; however, there were differences in the available digital data sets. Data for the prior ten years
were available for Virginia, West Virginia, and Tennessee. Only four years of permit data were
available for Kentucky.
OSM filtered the GIS data to exclude operations permitted prior to 1992, as well as permits which
represent underground mining, preparation facilities, coal waste disposal areas, etc. The data were
filtered so that only surface mining permits are included. The permit coverage was "clipped" to
include permits located only within the EIS study area. The following are detailed descriptions of the
mine data specific to each state within the study area. The list of permits included in the permit data
set are presented in Appendix B.
Kentucky
Original Source Description
The Department for Surface Mining Reclamation and Enforcement (DSMRE) currently makes
available scanned and georeferenced mining and reclamation plan maps and annual underground
maps for permits issued by the Department. Mining and reclamation plan (MRP) maps are required
to be submitted with an application for a permit to conduct surface coal mining and reclamation
operations in the Commonwealth of Kentucky. MRP maps are generally drawn on an enlarged USGS
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seven and one-half (7 1/2) minute topographic map at a scale of between 400 and 600 feet to the inch.
Permitted surface and underground mine boundaries and facilities associated with coal mining
operations are shown along with names and locations of streams and other bodies of water, roads,
buildings, cemeteries, oil and gas wells, public parks, public property, and utility lines.
The source of the GIS mine polygons for Kentucky used in this cumulative impact study are the
surface mining overlay maps maintained by the Kentucky Department of Surface Mining
Reclamation and Enforcement (DSMRE). These maps consist of frosted mylar sheets that overlay
7 V2 minute USGS topographic maps. DSMRE staff draw permitted surface and underground mine
boundaries and selected other features in ink onto the mylar. DSMRE GIS specialist scanned and
georeferenced these mylar overlays, which are now available to the pubic for downloading. Here is
the site link where the scanned may be downloaded: http://kydsmre.nr.state.ky.us/gis/data.htm. MRP
maps georeferenced beginning in July 2002, and all georeferenced underground maps are projected
in the NAD83 Kentucky Single Zone Coordinate System. MRP maps processed prior to July 2002
were georeferenced in NAD83 Kentucky State Plane North or South zone coordinates.
Currently six series of overlays are available both in hardcopy and digitally. Each series represents
a time period in the permitting of surface coal mining in Kentucky.
Series I: Areas permitted from 1977 to March 1, 1981, and which were active as of January 1, 1981.
Series II: Areas permitted from 1961 to 1977, and which were inactive as of January 1, 1981.
Series III: Areas permitted from March 1, 1981 through January 18, 1983.
Series IV: Areas permitted under the permanent program after January 18, 1983 and through April
1, 1986.
Series V: Areas permitted under the new permanent program after April 1,1986 and through August
1, 1995.
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Series VI: Areas permitted after August 1, 1995 and through August 31, 1999.
Series VII Areas permitted after September 1,1999 and through April 30,2000. (Series VII has been
converted to GIS polygons by DSMRE.)
For the purposes of the cumulative impact analysis only the information from Series VI and VII were
used. Series VI consists of three primary overlay sheets: (1) Polygon Layer - closed polygons -
permit boundaries, etc... (2) Line Data Layer - lineal lines - roads, conveyors, utilities, etc... and (3)
Point Data Layer - small ponds, sampling sites, mine adits, etc. Overlaying permits will be drawn
on separate sheets of Mylar, thus there may be more than one polygon layer sheet (Sheet 1, Sheet 2,
etc...). Hatched lines denote underground shadow areas. Areas of less than full recovery have a
greater opening between hatch marks and recovery percentage is indicated.
Description of Map Symbols and Codes for KY data
The mining overlay maps are identified by the 7 /^ minute quadrangle name. Alpha characters are
assigned to each permit number and appear as the first portion of the attribute code assigned to each
map feature. The alpha codes are generally listed in alphabetic order and expand to multi-lettered
codes (AA, BB etc.) to include all permits pertaining to a given quadrangle. Alpha codes and the
specific permit number to which they correspond are listed at the bottom of the overlay. Adjacent
maps that share the same permit boundary have, in most cases, the same alpha code on both maps.
The number which follows the alpha code is a one-, two- or three-digit number defining the major
category in which a mining feature falls (i.e. mining, fill areas, haul roads, etc.). Often a sub-category
is used to describe a mining feature in greater detail. An example of a feature attribute code is
'A-610'. The code refers to a sediment structure (6), embankment type (10), within the permit number
assigned 'A. Areas common to more than one permit number are labeled with the alpha character and
feature attribute codes of both permit numbers with a comma placed between them.
The permit features are drawn as dashed lines, solid lines, dash-dot-dot lines, or single dots. Haul
roads and railroads are drawn as dashed lines unless they correspond to the permit boundary, in which
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case the permit boundary takes precedence. Features that appear as solid lines or polygons include
mining areas, fill/storage areas, permit boundary areas, face-ups, and reference areas. Points are used
to represent features of small acreage such as sediment structures, monitoring points and underground
mine openings. Hatched lines indicate underground areas.
Due to the influx of new mining permits and the absence of some permits at the time of drafting,
these overlays are not 100% comprehensive. The updating procedure (acreage additions and
deletions) was initialized to keep the mining operations overlays as up-to-date as possible.
Description of Digital Data Base Queried for the Cumulative Impact Study for KY data
Staff from OSM's Pittsburgh Office downloaded the Series VII and VI digital information from KY
DSMRE FTP server on October 7, 2002, and October XXX, respectively.
The Series VIIGIS data was filtered to retain only those mining disturbances associated with surface
mining activities. All polygons associated with the activities coded as "face up", "load out", "prep
plant", "surface auger", "slide", "stockpile", or "underground" were deleted from consideration for
the purpose of the cumulative impact analysis. Further, using the boundaries of the EIS study area
in Kentucky, a GIS specialist at OSM Pittsburgh Office used readily available querying tools in ESRI
ARCVEW software to select only those surface mining permits that were located wholly or partly
within the EIS study area. This filtered digital data for Series VII, which consisted of multiple
polygons for surface mines, were forwarded to EPA's Wheeling Office.
The Series VI scanned and georeferenced mylars posed a more challenging task. Staff from OSM
Pittsburgh Office used specialized software (Able Software R2 V for Windows) to convert the digital
picture images (rasters) to vectorized features (polygons, lines, and points). Once converted to GIS
polygons, features representing surface mining disturbances were retained and other disturbances
(such as underground mining, preparation plants, augering areas, face-up areas, stockpiles, ect) were
eliminated. Further, using the boundaries of the EIS study area in Kentucky, a GIS specialist at OSM
Pittsburgh Office used readily available querying tools in ESRI ARCVIEW software to select only
those surface mining permits that were located wholly or partly within the EIS study area. This
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filtered digital data for Series VII, which consisted of multiple polygons for surface mines, were
forwarded to EPA's Wheeling Office. Appendix B contains a list of digital mining polygons from
Kentucky forwarded for inclusion in the cumulative impact study.
Tennessee
Original Source Description
The source of the GIS mine polygons for Tennessee used in this cumulative impact study is the a
digital geographic database of coal mining permit boundaries in Tennessee produced by the U.S.
Department of Interior, Office of Surface Mining Reclamation and Enforcement (OSM) inKnoxville,
Tennessee. It consists of georeferenced digital map data and descriptive attribute data. OSM
Knoxville Field Office Geographic Information System (KFO GIS) Team developed this information
from public records. The source for most of these records is the permit application submitted by coal
mining operators for review and approval by OSM to conduct surface coal mining operations at
specific locations in the State of Tennessee. These materials are a working resource of OSM and are
contained in its file rooms and archives in paper format. Data contained in these materials were
converted to digital format generally through digitizing paper maps onto a planimetrically correct
base.
Selected features from the last approved Mining Operation Plan maps and Environmental Resources
maps contained within a permit application submitted by a coal mining operator to the Office of
Surface Mining (OSM) were manually digitized into an individual coverage using the ArcEdit
subsystem of Arclnfo Workstation. Each map was georeferenced using geographic features found
in common on both the paper manuscript (map) and on Digital Raster Graphic (DRG) images of
standard 7.5-minute series USGS topographic quadrangle maps as displayed on a computer monitor.
These DRG's were acquired from the U.S. Tennessee Valley Authority and were transformed to
Tennessee State Plane, NAD 27 coordinate system by OSM. After initial digitizing on a standard
digitizing table, the digital data set was inspected on a computer monitor and visually compared
against the paper manuscript. Coverage feature classes were edited to correct digitizing errors.
Attribute data was added to describe features contained in the coverage. Individual coverages were
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then posted to the Knoxville Field Office Geographic Information System (KFO GIS). Each
individual coverage was then incorporated into a master coverage of similar features. All compilation,
digitizing, and quality control were performed by GIS specialists at the OSM in Knoxville, TN.
The accuracy of these digital data is based on features represented on source maps supplied by
various coal mining operators. In general, these features were drawn by hand on paper reproductions
of standard 7.5-minute series USGS topographic quadrangle maps enlarged to a scale of 1 "=400' and
were submitted as Mining Operation Plan maps or Environmental Resource maps in a permit
application for approval by OSM to conduct surface coal mining operations at a specific location. It
is not known whether these paper reproductions of the standard USGS topographic maps meet
National Map Accuracy Standards. OSM digitized selected features from each paper source map
using a minimum of four georeferenced control point locations (tics). Approximately 95 percent of
the maps resulted in a Root Mean Square (RMS) error of less than 10 feet as reported by the software
during calibration. None exceeded 25 feet. The difference in positional accuracy between the actual
feature location on the ground and their digitized coordinates as shown in this data set are unknown
This data set is a work-in-progress and represents the current amount of digital data available for this
theme at the time of its production. During production, selected paper maps from individual permit
applications are digitized in reverse chronological order based on the permit and/or revision approval
date. This method is used to ensure that data resulting from the most recently approved permitting
action for any given mining operation is always available to KFO GIS users. As the general digitizing
effort continues, maps are retrieved from successively older permit applications for digitizing and
data entry. Current estimates of temporal coverage for this theme extend backto approximately 1984.
As new information is made available to OSM, and as resources are available to capture this
information into a digital format, this data set will be amended with updated features from newly
approved mining operations and also be revised to include features from older mining operations.
Although these data have been processed successfully on a computer system at OSM, no warranty
expressed or implied is made by OSM regarding the utility of the data on any other system, nor shall
the act of distribution constitute any such warranty. For further information about the coal mining
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data sets held by OSM, contact Bill Card, Geographer, Office of Surface Mining, Knoxville Field
Office, 530 Gay Street SW, Suite 500, Knoxville, TN 37902, telephone 865.545.4103, x. 134, fax
865.545.4111, e-mail bcard@osmre.gov.
Description of Digital Data Base Queried for the Cumulative Impact Study for TN data
Staff from OSM's Pittsburgh Office downloaded the most current digital database from Tennessee
mining permits from OSM Knoxville Field Office FTP server on September 23, 2002. This database
consisted of 816 mining polygons. Staff from the Knoxville Field Office telefaxed a list of new
mining permits issued by OSM from January 1992 to date that were approved to use surface mining
methods or a combination of surface and underground methods to extract coal. The permits on this
list met the criteria established by the EIS Steering Committee for the cumulative impact study and
was used to select a subset of mine permit digital data polygons from the source database. Further,
using the boundaries of the EIS study area in Tennessee, a GIS specialist at OSM Pittsburgh Office
used readily available querying tools in ESRI ARC VIEW software to select only those surface
mining permits that were located wholly or partly within the EIS study area. This filtered digital
data, which consisted of 39 new surface mines, were forwarded to EPA's Wheeling Office. Appendix
B contains a list of digital mining polygons forwarded for inclusion in the cumulative impact study.
Virginia
Original Source Description
The source of the GIS mine polygons for Virginia used in this cumulative impact study is the a digital
geographic database of coal mining permit boundaries in Virginia produced by the Virginia
Department of Mines, Lands, and Minerals - Division of Mined Land Reclamation (DMLR) in Big
Stone Gap, Virginia.
It consists of geo-referenced digital map data and descriptive attribute data. This data set is a
work-in-progress and represents the current amount of digital data available for this theme at the time
of its production.
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Description of Digital Data Base Queried for the Cumulative Impact Study for VA data
Staff from OSM's Pittsburgh Office downloaded the most current digital database from Virginia
DMLRFTP server on September 16, 2002. This database consisted of 2358 mining polygons. Staff
from OSM Big Stone Gap Field Office identified the prefix in the permit identification number (GIS
Data Field "PERMIT") representing mines approved to use surface mining methods or a combination
of surface and underground methods to extract coal: "11", "15", "16", and "17".
Mining permits approved by Virginia DMLR beginning from January 1992 to the most current date
were selected using information provided in the GIS database (GIS Data Field "PEISSUEDT"). The
permits on this list met the criteria established by the EIS Steering Committee for the cumulative
impact study and was used to select a subset of mine permit digital data polygons from the source
database. Further, using the boundaries of the EIS study area in Virginia, a GIS specialist at OSM
Pittsburgh Office used readily available querying tools in ESRIARCVIEW software to select only
those surface mining permits that were located wholly or partly within the EIS study area. This
filtered digital data, which consisted of multiple polygons for 98 surface mines, were forwarded to
EPA's Wheeling Office. Appendix B contains a list of digital mining polygons forwarded for
inclusion in the cumulative impact study.
West Virginia
Original Source Description
The source of the GIS mine polygons for West Virginia used in this cumulative impact study is the
a digital geographic database of coal mining permit boundaries, coal extraction polygons, and fill
polygons produced by the West Virginia Division of Mining and Reclamation - Information
Technology Office. These datasets are derived from hardcopy permit maps submitted to DMR.
Hardcopy maps were scanned and georeferenced prior to extraction of features via on-screen
digitizing by West Virginia University - Natural Resource Analysis Center. All datasets have been
projected to UTM zone 17, NAD27.
Description of Digital Data Base Queried for the Cumulative Impact Study for WV data
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Staff from OSM's Pittsburgh Office downloaded the most current digital database from West Virginia
mining permits from West Virginia Department of Environmental Protection website:
http://129.71.240.42/data/omr.html. Three GIS data layers — permit boundaries, surface mine
extraction areas, and valley fill areas - met the criteria established by the EIS Steering Committee for
the cumulative impact study. This data set was filtered by using the last two digits of the permit
identification number (the year the permit identification number was assigned) to include only those
activities associated with new surface mining permitted after January 1, 1992. Further, using the
boundaries of the EIS study area in West Virginia, a GIS specialist at OSM Pittsburgh Office used
readily available querying tools in ESRI ARCVIEW software to select only those surface mining
permits that were located wholly or partly within the EIS study area. Appendix B includes a list of
142 West Virginia mining permits forwarded for inclusion in the cumulative impact study.
60% complete WV mine data set
Due to project schedules the terrestrial forest metrics, except forest loss and percent forest, were
calculated using a mine permit data set for WV that was only 60% complete at the time. The mine
data set was provided by WVDEP. Mine permit polygons are based on maps submitted to the
WVDEP by mine operators seeking to obtain a permit. The maps were digitized by WVU Natural
Resource Analysis Center (NRAC.). These WV permit maps were queried by WVDEP to extract
active and pending surface mines. Specifically, surface mine permits with an inspection status of:
Al (possibly moving coal), A4 (active but no coal removed), AM (active, moving coal), IA
(approved inactive), and NS (not started) were used to approximate the present and near future active
surface mining regions. These selections were made under the direction of the WVDEP. The scale
of the mine permit data is reported as 1:24000 by the West Virginia GIS Technical Center. The mine
permit data however was incomplete because it was still in the process of conversion from hard copy
to digital format at the time of this investigation (60% complete as of August 2001). To further
supplement identification of present/near future mountaintop mining "foot prints", a third source of
geographically referenced surface mining data was obtained from the Tennessee Valley Authority
(TVA.) TVA compared satellite imagery obtained from the early 1990's to imagery collected in 1999
from Landsat 7. Using a technique called Normalized Difference Vegetation Index (NDVI) they
identified areas that experienced a dramatic drop in vegetative cover and compared these areas to the
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WV DEP permit data and aerial photographs to derive and updated spatial dataset of mining regions
in the Appalachian coal region. This effort was incomplete at the time of this study. These three
sources were combined in a GIS and used as an approximation of present and near future mine
disturbance area. These data are suitable for use at the HUC 11 watershed scale however it is not
intended for localized studies (generally below 1:100,000.)
C. METRIC CALCULATION
1. Metric List
Landscape indicators are specific metrics. The word "metric" refers to a particular GIS calculation.
Metrics calculated in this study are presented in Table II.C-1.
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Table II.C-1
Metric List
Habitat
Evaluated
Mine
Aquatic
Terrestrial
Metric (unit)
Permit area per state and for entire study area (ac)
Mine data ratios for West Virginia (ac) - Valley fill area to mineral extraction
area, Valley fill area to permit area, Mineral extraction area to permit area
Direct impact to streams per state and for entire study area (mi and %)
Direct impact to streams from valley fill area in West Virginia (mi and %)
Direct impact to streams from mineral extraction area in West Virginia (mi and
%)
Direct impact to streams from permit area in West Virginia (mi and %)
Direct impact to forests per state and for entire study area (ac and %)
Forest loss from permit area in West Virginia (ac and %)
Forest loss from valley fill area in West Virginia (ac and %)
Forest loss from mineral extraction area in West Virginia (ac and %)
Forest loss from auxiliary areas in West Virginia (ac and %)
Grassland as indicator of past mining impact per state for entire study area (ac
and %)
Non-forest land cover class area change per state for entire study area (ac and
%)
*Impacts to riparian habitats in West Virginia (ac)
*Potential Ecological Condition in West Virginia (unit)
*Forest edge in West Virginia (%)
*Number of land cover patches in West Virginia (count)
*Percent landscape of patch type in West Virginia (%)
*Mean patch size in West Virginia (ac)
* denotes results generated previously from 60% complete permit data.
ac = acres
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2. Mine and Valley Fill Area
Mine areas were calculated based on permit boundaries obtained for each state. For West Virginia
identification of valley fills and mineral extraction areas within the permit boundaries was possible
however this was not the case for the other states where only permit boundaries were delineated. The
permit boundaries represented the mine "footprint" that was used to determine areas of impact. The
mine areas were represented digitally as a series of polygons. These were converted to raster (i.e.
grid cells) format with a cell resolution of 30x30 meters to facilitate merging with the landcover data.
The mine permit areas were "burned" into the landcover data to generate a post-impact scenario that
could be compared to the original landcover data (i.e. pre-impact) for quantification of landcover
changes.
This procedure involved reclassifying any area on the original landcover grid that intersected the
permit boundaries to the Surface Mine category. Calculation of mine areas was done by totaling the
number of pixels of each mine class (i.e. permit area, valley fills, and mineral extraction areas) and
multiplying by the pixel area (900 square meters). The result was then divided by 4047 to convert
to acres.
3. Mine Data Ratios
For West Virginia, three ratios were calculated: Valley Fill: Mineral Extraction Area, Valley Fill :
Permit Area, and Mineral Extraction Area : Permit Area. This was done by dividing areas which
were computed as described above.
4. Direct Impact to Streams
Direct impact of mine/fill areas to streams was calculated by converting all mine regions to polygons
and overlaying them with the stream line data in a GIS. This operation essentially "clips out" the
portion of the stream coverage that falls within the mine/fill polygons. Length of impacted streams
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was calculated and percent of streams directly impacted was determined by dividing the impacted
length by the total length of streams. Total stream impact was calculated by using the permit area
as the disturbance area. Impact from mineral extraction area and impact from valley fill were
calculated for West Virginia permits.
5. Direct Impact to Forests
Forest loss was calculated by first converting both the pre- and post-impact landcover grid to a simple
forest/non-forest layer. Grid cells with the following classification were lumped into the forest class:
Q Deciduous Forest Q Mixed Forest
Q Evergreen Forest Q Woody Wetlands
All other categories were non-forest. Next, forested pixels were totaled and divided by the total
number of pixels in the study area to determine percent forest cover. This procedure was also done
for each watershed in the study area. To determine forest area, the forested pixels were totaled and
multiplied by 900 square meters. The result in square meters was then converted to acres by dividing
by 4047. Changes in forest cover due to mining activity was determined by comparing the results
of this procedure for the pre- and post-impact landcover scenarios.
6. Percent Forest Cover
Using the forest/non-forest layer described in the previous metric the percent forest cover with each
study watershed was calculated by dividing the number of forested pixels by the total number of
pixels in the watershed. Possible values range from 0 to 1, with 1 indicating 100% forest cover.
7. Grassland as Indicator of Past Mining Impact
Grassland as Indicator of Past Mining Impact was calculated by summing the transitional and
pasture/hay land cover class acreage. This metric was developed in an attempt to quantify terrestrial
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impacts from mining before 1992. Because grasslands are not common natural habitats in the West
Virginia portion of the study area (Straughsbaugh and Core, 1997), it can be assumed that natural
grasslands are uncommon habitat throughout the four-state study area. Therefore, the transitional and
pasture/hay land cover classes can generally be attributed to reclaimed mine areas. This metric gives
a general indication of past mining terrestrial impact.
8. Non-forest Land Cover Class Area Change & Percent Change
Losses to non-forest landcover classes were computed by taking the difference in the number of
pixels of each landcover category between the pre- and post-impact landcover grids. This difference
was then divided by the original number of pixels of each landcover type to obtain percent change.
Computation of areas was done by simply multiplying the pixel totals for a category by the pixel area
(900 square meters) and converting to acres. Differences in landcover arose solely from the
reclassification of the original (circa 1992 NLCD) landcover to surface mines (surface
mining/quarries/gravel pits) in areas that intersected mine permit boundaries as described above.
9. Impacts to Riparian Habitat
This metric calculated using prior permit data set. Having obtained the wetland/riparian habitat
(described above), determining the amount of loss due to mine/fill areas was accomplished through
an overlay operation. Much like the method used in the Streams Through Mines metric a clipping
operation was performed to identify and quantify wetland/riparian habitats that were spatially
coincident with mine/fill polygons. Once these impacted regions were identified the area of each
habitat type was totaled for each watershed.
10. Potential Ecological Condition
Potential Ecological Condition (PEC) is an index intended to assess the ecological integrity of each
watershed based primarily on the extent of large scale human disturbance and "local" tabulations of
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forest cover. This is a raster based metric. Calculation of the PEC is a multi-step process.
First, the land use/cover map for each scenario is reclassified to produce a forest/non-forest map and
a human use map. The human use map is simply all the land use area associated with human activity
including shrubland (which captures transitional areas such as recent clearcuts and mine sites in early
reclamation stages), major highways, powerlines, populated areas, agricultural landcover, and
mine/fill regions. The human use map was queried to identify areas of human use that were greater
than or equal to five (5) acres in extent. These areas were then buffered by three (3) pixels (each
pixel is 30x30 meters) to approximate an "edge effect." Human use areas smaller than five (5) acres
did not receive a buffer and were assumed to not affect the integrity of the surrounding forest.
The next step was to calculate a local forest cover percentage for every pixel in the watershed. This
is termed a "floating window" procedure and involves centering a 200 acre circle on every pixel in
the watershed and determining the percent forest cover within the circle. 200 acres was determined
by O'Connell et al. (1998) to be the landscape unit size within which bird communities respond to
alterations in land-cover and was part of a more detailed index of biotic integrity developed for the
Mid-Atlantic Highlands.
The local forest cover map was then combined with the buffered human disturbance map to arrive
at a PEC value for each pixel. The possible PEC values were zero, one, and two, with zero
representing the lowest ecological condition and 2 the highest. Table II.D-2 shows how the final PEC
number for a pixel was determined. As shown, the highest PEC rating could be attained only when
the pixel in question had a local forest cover greater than or equal to 87% and it was forested and not
within the buffer around a large human use area. Furthermore, a pixel received the lowest PEC rating
when it was either classified as a human use or was less than 28% forested within the 200 acre local
evaluation window. Interpretations of this data should not be made for areas less than 5000 acres
(CVI unpublished.)
The PEC metric is modeled on the Bird Community Index (BCI) through collaboration between the
Canaan Valley Institute and developers of the BCI (O'Connell etal. 1998.) The BCI is a type of IB I
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(Index of Biotic Integrity) developed to assess ecological condition on a landscape scale. The index,
developed by Penn State University researchers, is based on data for breeding songbird communities
under the premise that songbird community composition reflects ecosystem properties of concern
such as structural complexity, interspecific dynamics, and landscape configuration (O'Connell et al.
1998.) The BCI was tested on 126 sites in the Mid-Atlantic Highlands, an area which extends in a
northeast to southwest direction through Pennsylvania, southeastern Ohio, West Virginia, Maryland,
and Virginia. This is a mountainous area comprising the Blue Ridge, Ridge and Valley, Allegheny
Plateau, and Ohio Hills physiographic provinces (O'Connell et al. 1998). Study sites were selected
to represent the entire region. BCI was found to be highly correlated with a human disturbance
gradient used to rank sites and defined thresholds of land-cover change where significant shifts in
BCI categories were observed. The BCI may serve as a substitute for more numerous and intensive
measurements of condition and disturbance (O'Connell et al., 1998).
The PEC metric is a simplified version of the BCI based primarily on factors such as forest cover
with a 200 acre vicinity of a location and a buffer around large areas of human disturbance.
Locations with high PEC values are considered to have high ecological integrity. Such areas closely
resemble native conditions, largely unmodified by recent human activity. They have extensive,
unfragmented forests with mature vegetation, and a closed canopy. Although most of the forests in
this region have been cutover, enough time has passed to allow re-establishment of mature forests
on previously logged areas or abandoned agricultural land. Mid-range PEC values represent medium
integrity sites. Attributes of these sites include higher landscape diversity (i.e. a greater variety of
cover types), greater contagion (i.e. interspersion of different cover types), more edge, more
agricultural and mine land, less forest cover, and lower canopy height and closure when compared
to high integrity areas
Low-range PEC values indicate a landscape dominated by mountaintop mining, agricultural or other
human related activities. Forest cover is less than 28% at the 200 acre scale and trees are generally
smaller with a more open canopy and interior conditions are non-existent.
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11. Forest Edge
The forest edge metric was calculated for each scenario using the forest/non-forest map. Every
forested pixel in a watershed was evaluated in the four cardinal directions to determine the presence
of an adjacent non-forest pixel. If a non-forest pixel was found bordering a forested pixel that pixel
was considered to be a forest edge. The number of forest edge pixels were totaled for each watershed
and divided by the total number of forested pixels to obtain the forest edge metric. Values fall within
the zero to one range where zero represents no forest edge and one represents the maximum possible
if every forest cell were adjacent to a non-forest cell.
The significance of this metric is as follows. Fragmented forests have more edge habitat (areas along
the boundaries between different types of land cover) than non-fragmented forests. Irregularly
shaped forest patches have more edge habitat than simple shaped forest patches due to the amount
of perimeter per unit area. Small amounts of forest edge positioned naturally within the landscape can
be beneficial to both the forest itself and some wildlife. The edges provide ecotones where food
sources, habitat, and energy sources are enhanced. The creation of more forest edge habitat often
corresponds to an increase in local species diversity as "edge" species are attracted to the region.
However, the creation of edge habitat can also lead to the elimination of forest interior species and
the encroachment of diseases and invasive exotic species (Jones, 1997). In addition, trees along the
forest edge are subjected to greater variations in microclimate and greater storm damages. What
determines "too much" edge cannot be answered without ascertaining impact on a particular species
since species differ in their edge requirements and/or tolerance.
12. FRAGSTATS Metrics
Three metrics were calculated using FRAGSTATS, a program developed to quantify landscape
pattern based on land cover data where regions of the same cover type are considered patches and
groups of patches of a land cover type comprise classes.
43
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The Number of Landcover Patches is the number of different land cover class areas. Land cover class
area is the area of a land cover type.
The Percent Landscape of Patch Type is the percentage the landscape comprised of the corresponding
patch type. It is the class area (describe above) divided by the total landscape area (i.e. watershed.)
The Mean Patch Size was calculated by dividing the class area for each land cover type by the
number of patches of that cover type. This metric provides information on the average size of cover
type patches within the watersheds. If larger patches are being fragmented into smaller patches this
will be manifest in a general decrease in mean patch size.
The FRAGSTATS output generated patch specific data for each land use type in a watershed over
the 36 long-term scenarios. Thus, a watershed with 20 land use classes (from WV Gap data) would
have 720 results for each scenario (36 X 20 = 720). Patch analysis using FRAGSTATS was time
consuming and generated 14 patch specific metrics for each watershed. Therefore, patch analysis
was only run on those watersheds that exhibited major changes in the other metrics and the metric
output was truncated to the three metrics that appeared to yield the most important data. Eight of the
63 watersheds were included in the FRAGSTATS analysis of land use patches. Three metric results,
the number of patches, percent of the landscape, and mean patch size were used.
The number of patches within a watershed was calculated for each of the 36 long-term scenarios by
summing the total number of patches of all of the land class types within the watershed under each
scenario. FRAGSTATS calculates the total number of patches of each particular land class in each
watershed. Percent of the landscape is also calculated by FRAGSTATS for each land class type in
the watershed. This analysis was merely the graphing of the FRAGSTATS results. Mean patch size
was calculated by dividing the land class area in a watershed by the number of patches of that class
in the watershed.
44
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III. RESULTS
A. MINING SURFACE AREA METRIC RESULTS
1. Permit Area
The permit area from mountaintop mining in the study area from the last ten years is 403,810 acres.
If mining trends are consistent, an additional permit area of 403,810 acres will occur in the next ten
years. Of the four states in the study area, Kentucky has the greatest permit area with 271,972 acres
of mining projected for a ten year period. This permit area is derived by multiplying the acreage
based on four years of permit data by a multiplier to generate a ten year number comparable with the
other states (108,789 x 2.5). West Virginia, Virginia, and Tennessee permit areas are 90,104 acres,
32,325 acres, and 9,409 acres, respectively. Figure III. A-l presents the locations of the permits in the
study area.
2. Mine Data Ratios
A typical mountaintop mine site is divided into development areas, production areas, support areas,
reclamation areas, and valley fills. The mineral extraction area consists of the development and
production areas. In West Virginia, the potentially adverse impact of mountaintop mining is 90,104
acres. Of this, the total mineral extraction area equals 51,382 acres while the total valley fill area
equals 19,486 acres. The remaining 19,236 acres constitutes auxiliary areas such as office buildings,
infrastructure, etc. Figure III.A-2 presents a typical mountaintop mine layout depicting the permit
area, production areas and valley fills. The mine data ratios indicate that the permit area is twice as
large as the mine extraction area and the mine extraction area is almost twice the acreage of the valley
fills.
Mine data ratios from the West Virginia portion of the study area are:
45
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Valley fill : Mine extraction area = 0.4
Valley fill : Mine permit area = 0.2
Mine extraction area : Mine permit area = 0.5
B. AQUATIC METRIC RESULTS
1. Calculated Stream Length
The stream lengths for the Kentucky, Virginia, Tennessee and West Virginia portion of the study area
based on the synthetic stream network described in section II. B are as follows. These stream lengths
characterize the study area prior to overlaying the mine permits.
Table III.B-1 Miles of Stream in the Synthetic Stream Network
State
Kentucky
Tennessee
Virginia
West Virginia
Entire Study Area
Miles of Stream
within Study Area Portion of State
34,468
5,505
7,015
12,010
58,998
Total stream length for the approximate 12 million acre study area is 58,998 miles. The order of
streams found in the study area include first to sixth order streams. Identification and calculation of
stream length by order was not performed in this study. However; a previous analysis (Gannett
Fleming 2002) calculated the percent of first through sixth order streams in the West Virginia portion
of the study area. This prior identification and calculation of stream orders provides an indication that
46
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over half of the stream length in the study area is comprised of first and second order streams. The
percent of streams classified by order for the West Virginia portion of the study area are summarized
below.
Table III.B-2 Percent of Streams within Different Stream Orders
Stream Order
First
Second
Third
Fourth
Fifth
Sixth
Percent of Total Stream
Length
In the WV portion of study area
47%
25%
13%
7%
5%
4%
Figure III.B-1 Percent of Streams within Different Stream Orders
47
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2. Aquatic Direct Impacts
Based on permits issued in the last ten years and an assumption of similar permits in the next ten
years, aquatic direct impacts to 1, 208 miles of study area stream is estimated. The aquatic metrics
include the miles of direct stream impact per state portion of the study area and for the entire study
area. Because the calculation of miles of direct stream impact is based on the stream network used,
percent of direct stream impact is also a metric. The percent of direct stream impact per state portion
of the study area and for the entire study area is calculated. Additional metrices were calculated for
the West Virginia portion of the study area because the digital permit data included consistent
attribution of the mineral extraction and valley fill areas within the permit area.
Potential impacts to aquatic habitats were evaluated using the metric for direct impacts to stream
length and percent of stream directly impacted. Direct impacts are defined as the areas where the
permit polygons overlapped the synthetic stream network. The direct impacts reflect surface mining
impacts including valley filling, backfilling, and other surface mining impacts that would directly
destroy the stream.
Table III.B-3 Miles of Direct Stream Impact
State
Kentucky
Tennessee
Virginia
West Virginia
Entire Study
Miles of Direct Stream Impact
within Study Area Portion of State
Based on Permit Area
730
20
151
307
1,208
Percent Impact
2.12%
0.36 %
2.10%
2.55 %
2.05 % of study area streams
48
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Additional results are available for the West Virginia portion of the study area. The digital permit
data for West Virginia allowed calculation of the direct stream impacts from mineral extraction area
and from valley fill area. These results are as follows.
Table III.B-4 Miles of Direct Stream Impact Per Mineral Extraction and
Valley Fill Areas
Mineral Extraction
Area
Valley Fill
Permit Area
Miles of Direct Stream Impact
within West Virginia Portion of Study
Area
50.43
156.82
307
Percent Impact
0.42 %
1.31%
2.55 %
As can be seen from the table above, an additional 100 miles of direct stream impact is calculated
when the entire permit boundary is used as the disturbance area, as opposed to discrete valley fill and
mineral extraction polygons. Although direct stream impact could occur from road crossing and
ancillary operations outside of the mineral extraction and valley fill areas, calculation of direct stream
impacts using the permit area may be an overestimate.
C. TERRESTRIAL METRIC RESULTS
1. Study Area and State Results
a.
Forest Loss
The potentially adverse impact of forest loss from mountaintop mining in the study area from the last
ten years of permitting is 380,547 acres. The study area contains 11,231,622 acres of forest. This
49
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terrestrial impact equates to a 3.4% forest loss in the study area. Of the four states included in the
study area, Kentucky is projected to have the greatest potentially adverse impact of forest loss from
mountaintop mining with 255,582 acres (4.0%) of forest loss; however, Kentucky also has the
greatest acreage within the study area. The Kentucky forest loss is based on four years of permit data
multiplied by 2.5 to yield a ten year estimate( 102,233 acres x 2.5). Projected forest loss from the
other three states in order of potential adverse impact are: West Virginia, 86,587 acres (3.2%);
Virginia, 29,224 acres (2.5%); and Tennessee, 9,154 acres (1.0%).
When adding past, present and future terrestrial disturbance, the study area estimated forest impact
is 1,408,372 acres which equates to 11.5 % of the study area. This number is derived by adding
grassland as an indicator of past mining, barren land classification, forest lost from the last ten years
of surface mine permits and a projection of future forest loss that equates to the last ten years.
b. Non-forest Land Cover Class Change
Forests occupy 92.1% of the study area. Therefore, the greatest potential adverse impact from
mountaintop mining is to the forest cover classes. Table III.C-1 summarizes the impacts to all non-
forest land cover classes for each state and for the entire study area. In general, the potential adverse
impacts for non-forest land cover classes are consistent among each state.
High intensity residential is the only land cover class with no projected impact in the four-state study
area. Urban/recreational grasses and emergent herbaceous wetlands are projected to have negligible
potential adverse impacts in the study area. Transitional lands and the pasture/hay cover class exhibit
the greatest potential adverse impact of the non-forest land cover classes with projected losses of
1,986 acres and 999 acres, respectively. The greatest net change is an increase of 231,177 acres in
the surface mining/quarries/gravel pits cover class. This net change takes into account the acres of
remining (surface mining/quarries/gravel pits landcover acres in permit polygons). The acres of
remining are 4,922 in Kentucky; 16 in Tennessee; 1,849 in Virginia; and 2,664 in West Virginia.
50
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Grasslands (pasture/hay and transitional) are expected to increase as mine sites move to the
reclamation phase. This trend is not depicted in the table.
Table III.C-1
Non-Forest Land Cover Class Im
Kentucky Portion of the Study
Area
Open Water (ac)
Low Intensity Residential (ac)
High Intensity Residential (ac)
Commercial/Industrial/Transportation
(ac)
Surface Mining/Quarries/Gravel Pits (ac)
Transitional (ac)
Pasture / Hay (ac)
Row Crops (ac)
Urban/Recreational Grasses (ac)
Emergent Herbaceous Wetlands (ac)
Pre-Impact
(NLCD)
43,914
23,674
5,459
24,673
37,710
17,133
251,470
65,866
9,410
1,210
pacts (acres)
Condition from
4 yrs of Issued
Permits
43,731
23,628
5,459
24,526
141,577
16,363
251,051
65,798
9,408
1,210
Difference
-182
-46
0
-147
103,867
-770
-419
-68
-2
0
51
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Table III.C-1 continued
Tennessee Portion of the Study
Area
Open Water (ac)
Low Intensity Residential (ac)
High Intensity Residential (ac)
Commercial/Industrial/Transportation
(ac)
Surface Mining/Quarries/Gravel Pits (ac)
Transitional (ac)
Pasture / Hay (ac)
Row Crops (ac)
Urban/Recreational Grasses (ac)
Emergent Herbaceous Wetlands (ac)
Virginia Portion of the Study
Area
Open Water (ac)
Low Intensity Residential (ac)
High Intensity Residential (ac)
Commercial/Industrial/Transportation
(ac)
Surface Mining/Quarries/Gravel Pits (ac)
Transitional (ac)
Pasture / Hay (ac)
Row Crops (ac)
Urban/Recreational Grasses (ac)
Emergent Herbaceous Wetlands (ac)
Pre-Impact
(NLCD)
12,472
10,771
1,471
6,185
1,208
3,059
56,114
15,358
6,297
146
Pre-Impact
(NLCD)
4,790
10,484
133
4,749
18,981
11,592
117,519
13,738
182
316
Condition from
10 yrs of
Issued Permits
12,454
10,769
1,471
6,166
10,601
2,897
56,083
15,350
6,297
146
Condition from
10 yrs of
Issued Permits
4,672
10,473
133
4,729
49,458
10,896
117,224
13,629
182
311
Difference
-18
-2
0
-19
9,393
-162
-31
-8
0
0
Difference
-118
-11
0
-20
30,477
-696
-295
-109
0
5
52
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Table III.C-1 continued
West Virginia Portion of the
Study Area
Open Water (ac)
Low Intensity Residential (ac)
High Intensity Residential (ac)
Commercial/Industrial/Transportation
(ac)
Surface Mining/Quarries/Gravel Pits (ac)
Transitional (ac)
Pasture / Hay (ac)
Row Crops (ac)
Urban/Recreational Grasses (ac)
Emergent Herbaceous Wetlands (ac)
Entire Study Area
Open Water (ac)
Low Intensity Residential (ac)
High Intensity Residential (ac)
Commercial/Industrial/Transportation
(ac)
Surface Mining/Quarries/Gravel Pits (ac)
Transitional (ac)
Pasture / Hay (ac)
Row Crops (ac)
Urban/Recreational Grasses (ac)
Emergent Herbaceous Wetlands (ac)
Pre-Impact
(NLCD)
16,622
16,110
86
9,310
45,715
19,441
67,335
17,048
128
1,383
Pre-Impact
(NLCD)
77,798
61,039
7,149
44,917
103,614
51,225
492,438
112,010
16,017
3,055
Condition from
10 yrs of
Issued Permits
16,607
16,079
86
9,275
133,155
19,083
67,081
16,914
128
1,383
Condition from
Issued Permits
77,464
60,949
7,149
44,696
334,791
49,239
491,439
111,691
16,015
3,050
Difference
-15
-31
0
-35
87,440
-358
-254
-134
0
0
Difference
-334
-90
0
-221
231,177
-1,986
-999
-319
-2
-5
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c. Grasslands as Indicators of Past Mining Impacts
Grasslands are not common natural habitats in the West Virginia portion of the study area
(Straughsbaugh and Core, 1997). It can be assumed that natural grasslands are uncommon habitat
throughout the four-state study area, in particular in the steep mountainous portions of the study area
like West Virginia and Kentucky. The NLCD indicates that there are 543,663 acres of grasslands
(transitional and pasture/hay land cover classes) in the four-state study area. Much of the present
grasslands in the study area could be attributed to past mining impacts.
The NLCD indicate that Kentucky has historically undergone the greatest potential adverse impact
from mining with 268,603 acres of grasslands. Grasslands equal 129,110 acres in Virginia, 86,777
acres West Virginia, and 59,173 acres in Tennessee. There is a low likelihood that all of the
grasslands of the study area can be attributed to mining. However, this acreage for West Virginia is
supported by a separate study which estimated 244,000 acres of West Virginia has been disturbed
by past or current mining (Yuill, 2002). For further extrapolation on this subject please refer to IV.
Uncertainty Section of this report.
2. West Virginia Specific Results
a. Forest Loss
Total forest area of the West Virginia portion of the study area is 2,703,677 acres. The potentially
adverse impact of mountaintop mining in West Virginia is summarized below based on specific
mining disturbance activities:
Forest loss from mine permit areas = 86,587 ac (3.2%)
Forest loss from mineral extraction areas = 45,544 ac (1.7%)
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Forest loss from valley fill areas = 18,338 ac (0.7%)
Forest loss from auxiliary areas = 22,705 ac (0.8%)
b. Impacts to Riparian Habitats
The projected riparian habitat potential adverse impact in the West Virginia portion of the study area
total 7,591 acres of an existing 23 6,843 acres (WV GAP Dataset). This equates to a 3.2% loss in this
habitat type in the West Virginia portion of the study area. Approximately 55% of the potentially
adverse impacts occur in forested headwater (1st and 2nd order Strahler streams) riparian areas (3,233
ac) and forested small stream (3rd and 4th order Strahler streams) riparian areas (913 ac). There is a
high likelihood that these impacts will occur because they are inherently associated with valley fill
activities due to this type habitat's position on the landscape. This analysis used the 60% complete
permit dataset, therefore, potentially adverse impacts may be underestimations.
c. Potential Ecological Condition
Potential ecological condition (PEC) is a metric designed to determine the ecological condition of
a particular landscape unit. Generally, PEC is evaluated at the watershed level. Figure III.C-l shows
the positive relationship between PEC and forest cover using data from the 63 watersheds in the West
Virginia portion of the study area.
Using the relationship represented in Figure III.C-l the PEC of the study area can be calculated for
the existing condition (pre-impact), the issued permit condition, and the future projected condition.
These conditions are represented on the figure with dashed lines. PEC of the study area under the
pre-impact condition is near 1.7 units. Under the permit issued condition PEC scores have the
potential adverse impact of dropping to near 1.65 units. The projected future condition could yield
a potential adverse impact of a drop in PEC score for the study area to about 1.59 units.
55
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It should be noted that although forest cover is a large determinant in the calculation of PEC, other
land use variables also go into the variable (refer to II. Methodology for description of PEC
calculation). The values represented in Figure III.C-1 are approximations; however, due to the strong
relationship between forest cover and PEC there is a high likelihood that these approximations are
accurate.
d. Forest Edge
Forest loss from mountaintop mining in the West Virginia portion of the study area has the potential
of creating 2.7% more edge habitat. A total of 17,477 more edge pixels are in the West Virginia
portion of the study area after the 60% complete permit dataset is applied to the pre-impact WV GAP
dataset. This potentially adverse impact has a high likelihood of occurrence. This increase in edge
habitat is an underestimation since the value was calculated using the 60% complete permit dataset.
e. Number of Patches
There area 100,392 pre-impact land class patches in the West Virginia portion of the study area (WV
GAP Dataset). When the 60% complete permit data is applied to the WV GAP land cover dataset
the number of land class patches increases to 139,689. This is equates to an approximately 40%
increase in the number of land class patches which implies an increase in fragmentation of the natural
environment. This potentially adverse impact has a high likelihood of occurrence and is an
underestimation especially since the result was generated from 60% of the permit data set.
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f. Mean Patch Size
Mean patch size in the West Virginia portion of the study area is 24.64 acres (WV GAP Dataset)
before the mine permit dataset is applied. Application of the 60% complete permit dataset to the WV
GAP land cover dataset yields a mean patch size of 14.33 acres. This reduction in the average size
of land class patches implies fragmentation of the natural environmental. The potentially adverse
impact of fragmenting the natural environment has a high likelihood of occurrence especially since
this decreased is biased high because the permit dataset used was only 60% complete.
g. Percent of the Landscape
The percent of the landscape in the West Virginia portion of the study area that each land class patch
type occupies is presented in Table III.C-2. Table III.C-2 includes the percent of the landscape of
each land class patch type using the WV GAP Dataset prior to application of the 60% complete
permit dataset. The greatest change is in the mining - barren class patch type which shows a 1.9%
increase in area following application of the permit dataset. The greatest potential adverse impact
is experienced by the diverse mesophytic forest type with a reduction in area of 1.3%.
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Table III.C-2
Land Class Patch Type Percent of Landscape, WV
Land Class Patch Type
Shrubland
Woodland
Water
Highway
Powerlines
Populated
Urban (all 3 types)
Rowcrop - Ag.
Pasture - Grassland
Mining - Barren
Planted Grass
Conifer Plantation
Floodplain Forest
Forested Wetlands
Shrub Wetlands
Herbaceous Wetlands
Cove Hardwoods
Diverse Mesophytic Forest
Hardwood - Conifer Forest
Oak Forest
Mtn. Hardwood Forest
Mtn. Hardwood - Conifer Forest
Mt. Conifer Forest
Percent of the Landscape
Pre-Impact
(WV GAP Dataset)
1.0
0.2
1.0
<0.1
0.3
0.2
1.2
<0.1
3.2
2.6
<0.1
<0.1
0.6
<0.1
<0.1
<0.1
11.7
61.6
1.0
6.4
8.6
<0.1
<0.1
Condition from 10 yrs of
Issued Permits
0.9
0.2
1.0
<0.1
0.3
0.2
1.2
<0.1
3.5
4.5
<0.1
<0.1
0.6
<0.1
<0.1
<0.1
11.3
60.3
1.0
6.3
8.4
<0.1
<0.1
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IV. UNCERTAINTY SECTION
A. AQUATIC IMPACTS
1. Direct Stream Loss
a. Permit Boundaries
Calculation of direct stream loss based on the entire permit area may overestimate actual direct
impact. As can be seen from the West Virginia specific analysis, an additional 100 miles of direct
stream impact is calculated when the permit area is used as opposed to a sum of the direct impact
based on valley fill area and extraction area. This auxiliary area is occupied by support areas, erosion
and sedimentation control facilities haul roads and areas included within the permit because of
geometry but not disturbed by mining activities. Direct impacts to streams could occur from activity
within the auxiliary area such as sediment ponds and haul roads. The sum of these auxiliary areas is
generally small relative to the entire permit area; however, this could overestimate the direct stream
loss.
b. Stream Network
The miles of stream is calculated based on a given stream network. Different stream lengths result
when different measuring sticks are used. The calculated miles of stream differ between a synthetic
stream network and if one were to calculate the miles of stream based on USGS topographic maps.
Also, there can be length differences between synthetic stream networks generated in slightly
different ways or quantified in slightly different ways because the stream length is greater when
greater stream sinuosity. Therefore, there is uncertainty in the miles of direct stream impacts. There
is less uncertainty in the percent of direct stream impacts.
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The GIS stream network was generated from DEM data using standard ARC Info commands. The
streams are "synthetic" in that they were not generated by conversion of existing maps, such as
orthophotographs or USGS 7.5' quad sheets, into digital format. Rather, they were generated using
a digital elevation model (DEM). A DEM is a digital representation of the earth's surface based on
a regular series of sample elevation points organized in a 30x30 meter grid. OEM's can be used to
model the direction of water flow and accumulation of flow.
For the data used in the cumulative impact study a contributing area of 30 acres was selected to
generate a stream. There is some uncertainty is this selection given that permits in Kentucky have
indicated perennial streams in watersheds smaller than 10 acres. Therefore; the synthetic stream
network may underestimate stream length.
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B. TERRESTRIAL IMPACTS
1. Forest Loss
a. Permit Boundaries
The forest loss was calculated based on permit boundaries. As can be seen from the West Virginia
specific analysis, 0.8% of the forest loss was due to auxiliary areas (outside of the mineral extraction
and valley fill areas). It is an overestimate to assume that the entire area within the permit boundary
will be disturbed. Also, mine areas and fills on permit application maps are often altered during the
life of a mine; therefore, the extent of mine extraction area or valley fill used in this study has
uncertainty.
b. Kentucky Permit Data
Mine permit polygons in Kentucky were based upon four years of mining permits. Since the other
three states had permit data for a ten year time period the Kentucky Permit area and forest loss were
multiplied by 2.5 to approximate mine disturbances in a ten year time frame. This adjustment for
Kentucky has no spatial placement. There is uncertainty in what land cover type will be disturbed
by the actual mines. Kentucky presently is 92.8% forested (NLCD). This suggests that there is a
high likelihood that the forest land cover will incur the projected potential adverse impact.
Multiplying the four year permit data by 2.5 to approximate ten years of mining Permit also assumes
that mining in Kentucky will continue at the same rate for the last six years of the projection. This
also leads to some uncertainty in the data.
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c. Timber Harvesting
Mountaintop mining is not the only activity affecting the landscape in the watersheds studied. Forest
harvesting is widespread. The wood products industry plays an important role in West Virginia's
economy accounting for 11.2% of the state's manufacturing employment (this figure excludes
furniture and paper.) The economic importance of this industry is growing . Greenstreet and
Cardwell (1997) reported a 40% increase in payroll employment between 1980 and 1995. Much of
West Virginia's forests are single cohort stands of merchantable size containing high value species
such as oaks, black cherry, yellow-poplar, sugar maple, and white ash. 66% of the state's forests are
owned by non-industrial forest land owners, 24% are owned by corporations, and just 6% are publicly
owned (Birch, 1996.) Between 1975 and 1989 the percentage of private forest land owners planning
to harvests timber rose from 8% to 35% (Birch and Kingsley, 1978; DiGiovanni, 1990 as reported
by Fajvan et al., 1998)
In West Virginia the most prominent harvest technique is diameter limit cutting (WV Asst. State
Forester, personal communication.) This method selects trees based on stem diameter. For instance
all merchantable trees greater than 12" diameter are removed. As large, high value species are
disproportionately removed from the stand, species composition shifts to less desirable species such
as red maple. Decreases in average stand diameter occur as well as changes in stand density and
structure (Fajvan et al., 1998.) Oaks and hickories are highly valued commercially however they also
provide an important habitat component to many species of wildlife. With fewer mast producing
trees in the residual stands some wildlife populations may experience declines. From an economic
standpoint potential future stand value may be decreased. According to Dwyer and Kurtz (1991)
"... all too often [diameter limit harvesting] is used as an expedient means to liquidate the future stock
of potentially high quality timber supply to improve short-term returns to the purchaser." In sum,
diameter limit harvesting is widespread and it has ecological and economic impacts that may combine
with impacts from mountaintop mining to exacerbate cumulative effects on the environment and local
communities.
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d. Temporal Misrepresentations
Forests are the post-mining land use on many of the mined sites used in this analysis. Forest
regeneration on mined sites was not considered in the analysis of forest loss from the issued permits
or for the proj ected future condition. Thus, future conditions may have forests on some of the current
mine permit areas and this is not accounted for in the analysis. This suggests that forest loss has been
overestimated to some extent. Handel (2001) showed that forest regeneration on mined sites is slow;
therefore, the likelihood that the projected potential adverse impact to forests will occur is still
relatively high.
2. Non-forest Land Cover Class Change
a. Underestimations Due to Scale
The potential adverse impacts to non-forested land cover classes could be grossly underestimated for
land cover classes that are common at a small scale. For example, there are probably many home
sites that would classify as low intensity residential that are undetectable and therefore unmapped in
the National Land Cover Dataset because they are located within a broader land cover type like the
deciduous forest. Urban/recreational grasses and emergent herbaceous wetlands are two other land
cover that may be under-represented due to this matter of scale.
b. Temporal Misrepresentations
The potential adverse impacts to the transitional and pasture/hay land cover classes may be
underestimated due to difficulties projecting these land cover classes on a temporal scale. Many of
the mine sites that appear in the pre-impact condition will be reclaimed to grasslands in the near
future. This reclamation is not accounted for when projecting potential adverse impacts from the
permit data or when projecting the future condition. In the same respect, the surface
mining/quarries/gravel pits may be overestimated in the permit condition and projected future
condition.
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c. Other Land Use Changes
Other land use changes like timber harvesting, commercial development, residential development,
etc. are not projected in this analysis. The lack of these other land use changes should be considered
when evaluating the projected potential adverse impact from mining under the permit condition and
the proj ected future condition. Any where in this report where a percent land cover is change is noted
in this report the reader should consider there is potential for other land use changes to alter the
recorded percent. For this reason, in this report potential adverse impacts were recorded as an area
(ac) impact when possible.
3. Grasslands as Indicators of Past Mining Impacts
The assumption that all grasslands (pasture/hay and transitional cover classes) in the study area are
indicators of historic mining results in an overestimation of past mining impacts. Literature review
does indicate that natural grasslands are uncommon in the study area; however, there is no way to be
certain that all grasslands in the study area are historic mining sites. A more accurate representation
may have been to designate all grasslands above a certain coal seem elevation and of a minimum size
as grasslands indicating past mining impacts. This exercise was not done due to project schedule
constraints.
The reader should be aware that this number is an overestimation of past mining impacts. Abandoned
farm sites and herbaceous floodplains are two examples of the grasslands cover that would result in
an overestimation with this metric. Yuill (2002), reporting on the West Virginia portion of the study
area only, indicated that agriculture decreased from almost a million acres in 1950 to about 246,000
acres presently. These abandoned agricultural lands may now be another land use (i.e. residential,
commercial) but some may be transitional lands that are part of the calculation to approximate past
mining impacts. However, Yuill (2002) also estimated 244,000 acres of West Virginia has been
disturbed by past or current mining by compiling various data sources including land cover categories
such as grassland/pasture. The Yuill (2002) study seems to support the use of transitional and
pasture/hay land cover classes as indicators of past mining.
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4. Impacts to Riparian Habitats
a. Uncertainty in the Data
This metric was calculated from the 60% complete permit dataset. Therefore, the potentially adverse
impact that was calculated is an underestimation of the expected. Riparian habitats used in this
analysis were those identified in the WV GAP Dataset (refer to Section II. Methodology for
specifics). This dataset differs from the WV GAP land use dataset that was used for modeling other
impacts and it includes many of the land use classes used in the other analyses. Thus, impacts to
riparian habitats presented herein may be expressed as impacts to other patch types (i.e. Diverse
mesophytic forest, Floodplain forest) in other places in this document.
b. Problems in Defining Riparian Habitat
Riparian habitats are defined as those habitats located on the banks of a natural watercourse (Stiling,
1996). Larger watercourses have broader, more defined riparian areas. For example, a river flowing
through a valley may have a riparian corridor that is hundreds of feet broad on either side. On the
other hand, a small headwater stream flowing down a steep-sided valley may have a riparian area of
only a few feet broad. Because of this, many of the riparian areas of the study area may be under-
represented in the data.
To help appreciate the extent of potential adverse impacts to riparian habitats of the study area the
reader should refer to the stream impact results. The direct impacts to first and second order streams
also have impacts to riparian habitats that likely are lacking from the data. These potentially adverse
impacts probably constitute a very small area and if included would not change the results
substantially.
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5. Potential Ecological Condition
a. Factors Associated with Calculation and Application
Potential Ecological Condition (PEC) is a value calculated to determine the ecological health of a
defined landscape scale, usually the watershed level. This cumulative impact study evaluated
potentially adverse impacts on a broader scale (state by state and four-state study area). The detailed
West Virginia analysis did provide watershed level PEC results. From these the relationship between
PEC and percent forest cover was used to approximate PEC scores at a study area level. These
results are by no means an accurate account of PEC of the study area but are presented here to
represent the general trend in PEC decline as forest cover declines.
Other factors associated with PEC calculation (refer to II. Methodology) are omitted from the
approximation of PEC at the study area level. Since percent forest cover explains most of the
variation in PEC value (refer to Figure III.C-1) it is assumed that the approximated PEC values are
accurate representations and worthwhile to be used to show a declining trend in PEC value with
declining percent forest cover.
b. Lack of Pre-Impact Value
PEC of the study area was not calculated using the pre-impact data. The best approximation of pre-
impact PEC of the study area was obtained through a scatter plot of PEC values vs. percent forest
cover for the 63 watersheds in the West Virginia portion of the study area (Figure III.C-1). The
results do not allow for a true comparison of pre- and post-potential adverse impact of PEC values.
As stated above, however, since PEC and percent forest cover are strongly positively related the
approximation presented here is worthwhile to be used to show a declining trend in PEC value with
declining percent forest cover.
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6. Forest Edge
Forest edge was calculated from the 60% complete permit dataset for the West Virginia portion of
the study area. For this reason, the forest edge results are likely an underestimation of the potential
adverse impact. Another consideration of forest edge is that beyond a certain threshold as forest is
loss the ability for forests to have an edge is loss. That is, at some point, the amount of forest edge
in a forest that is being continually fragmented, will eventually begin to decrease because there isn't
enough forest to sustain an edge. Graphically it would appear as a bell-shaped curve.
7. Number of Patches, Mean Patch Size, and Percent of the Landscape
Patch metrics (Number of Patches, Mean Patch Size, and Percent of the Landscape) were run on the
60% complete permit dataset resulting in an underestimation of the potentially adverse impacts. The
FRAGSTATS software quantified patch metrics within each of the 63 watersheds of the in the West
Virginia portion of the study area. This watershed approach differs from most of the metrics
presented in this report which are at the state or four-state study area lev el. To convert the watershed-
based results to a result for the West Virginia portion of the study area each of the 63 watersheds
results were tallied for each metric.
V. DISCUSSION
A. ECOLOGICAL SIGNIFICANCE OF METRICES
ASSOCIATED WITH THE AQUATIC ENVIRONMENT
1. Summary and Discussion of Results of Aquatic Metrices
Direct impacts to 1,208 miles of streams is estimated based on the last 10 years of digital permit data.
If mining, permitting and mitigation trends stay the same, an additional thousand miles of direct
impacts could occur in the next ten years. The watersheds with the greatest miles of streams impacted
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and percent of stream length impacted are presented on Figure V.A-1. The majority of the streams
directly impacted are headwater streams. Figure V. A-2 presents ranges of miles of direct stream
impacts.
2. Consequences of Altering Ecological Processes in Aquatic Systems
a. Considerations in the Cumulative Impact Assessment of Ecological Process Effects
The array of effects that mountaintop mining and valley fill activities may pose can be incredibly
complex. Inherent to this complexity is a tendency for these effects to combine with and/or
compound one another. In aquatic systems, the adverse effects of mountaintop mining and valley fill
activities may combine to create a larger net negative effect than if considered singularly. This is an
additive process referred to as a cumulative effect.
Cumulative effects are broadly defined by the Council on Environmental Quality (CEQ) guidelines
for implementing the National Environmental Policy Act (NEPA) as "the impact on the environment
which results from the incremental impact of the action when added to other past, present, and
reasonably foreseeable future actions regardless of what agency or person undertakes such other
actions" (40 CFR 1508.7). Within the context of this cumulative impact study, cumulative impacts
were assessed for a 63 watershed area, representing a subset of the entire MTM/VF study area.
An additional component of cumulative effect, are the underlying adverse effects that may compound
one another, creating net negative effects of a different, and potentially more intense, nature. This
is a multiplicative process referred to as synergism. Cumulative effects within or among watersheds
can cause unacceptable changes to downstream aquatic, terrestrial, and human resources. Cumulative
impacts from changes in topography and land cover may result in the elimination of large tracts of
habitat necessary for native forest-interior species and may result in micro-climatic changes.
The cumulative effects in aquatic ecosystems may not only affect aquatic resources. By their nature,
the cumulative effects of mountaintop mining and valley fill activities upon aquatic systems can
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extend to affect the environmental health of ecosystems outside the aquatic realm. This is due
primarily to the extensive and complex interconnectedness between terrestrial and aquatic
ecosystems. Physical, chemical, and biological changes to aquatic systems can affect water quality,
water quantity, and aquatic life. This in turn may lead to changes in the natural environment such
as forest communities (floral and faunal), microhabitats; and rare, threatened and endangered species.
These effects may compound further and ultimately affect the human environment.
The cumulative effects analysis of aquatic systems performed in this study focused on direct impact
to stream systems through actual loss of stream length. No attempt was made to assess stream length
that may become impaired as a result of indirect effects from filling or mining.
It is also necessary to consider the secondary effects of activities associated with mountaintop mining
and valley fill activities. Secondary effects are actions which, in this case, are conducted in support
of establishing or operating a mine, and are defined by CEQ as those that are "caused by an action
and are later in time or farther removed in distance but are still reasonably foreseeable" (40 CFR
1508.80). These activities such as clearing sites, building access or haul roads, and drainage or
sediment control systems, can cause alterations in the topography and drainage patterns of mined
areas. There are also changes in vegetation and ground cover that are associated with mountaintop
mining. The possible cumulative effect from similar or multiple proj ects has been raised as a concern
for analysis in these watersheds. No quantitative evaluation of secondary effects was performed in
this cumulative impact study.
b. Ecological Process Effects in Aquatic Systems
This section focuses specifically in the cumulative impacts to headwater streams and their associated
watersheds from mining and associated activities. One useful approach to evaluating cumulative
impacts focuses on an evaluation of ecological processes. USEPA (1999) lists a total of 10 ecological
processes that effectively capture ecosystem functioning and should be evaluated for adverse effects.
These processes include:
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1. Habitats Critical to Ecological Processes
2. Pattern and Connectivity of Habitat Patches
3. Natural Disturbance Regime
4. Structural Complexity
5. Hydrologic Patterns
6. Nutrient Cycling
7. Purification Services
8. Biotic Interactions
9. Population Dynamics
10. Genetic Diversity
Two of these processes are associated largely with terrestrial systems in the MTM/VF study area.
These include pattern and connectivity of habitat patches and natural disturbance regimes. Impacts
to these ecological processes have been discussed in terrestrial-related sections of this document.
Impacts from MTM/VF activities to the remaining eight ecological processes will be summarized in
this section as part of the evaluation of cumulative impacts.
Impacts to ecological processes may result from direct activities or indirectly from alterations
resulting from direct activities. This is true both for primary impacts from mining and from
secondary impacts which include items such as road building, changes in residential patterns etc. that
may occur as a result of the mining activity. The most significant direct impact to headwater stream
systems is the direct filling of the steam and watershed during mining activities. Other direct impacts
would result from secondary activities such as logging or road building but in terms of total impacts
to this ecosystem, impacts from filling would be far more extensive and long lasting. Indirect impacts
from filling include impacts that affect the ecological process in the stream system downstream from
the filled area. These impacts largely result from direct changes in the stream system's flow regime,
thermal regime, water chemistry or sediment load from mining. A cascading series of indirect effects
may result from changes to any one ecological process.
Habitats Critical to Ecological Processes
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At the level of a landscape or region, certain natural habitat types are especially important for the
ecological functioning or species diversity of the ecosystem. Unusual climatic or edaphic (soil-
based) conditions may create local biodiversity hotspots or disproportionally support ecological
processes such as hydrologic patterns, nutrient cycling, and structural complexity. For these reasons,
preservation of specific habitats (usually the remaining natural areas within the landscape) should be
a priority (USEPA, 1999).
Within the landscape, certain habitats disproportionately contribute to ecosystem functioning. In
general, these are the remaining natural areas, especially those that integrate the flows of water,
nutrients, energy, and biota through the watershed or region (Polunin and Worthington, 1990).
Headwater stream systems naturally provide these listed functions. (USFWS, 1999).
Headwater streams are destroyed by filling. The fisheries and streams technical studies in support
of the MTM/VF EIS support that the functions of these systems may be impacted for considerable
downstream distances by upstream fills. Cumulatively, many activities, in addition to filling,
resulting from mine construction may result in destruction or degradation of the headwater stream
systems. Although data are lacking on the magnitude of mining impacts compared to other major
alterations in land use such as forestry, the permanent nature of filling would suggest that MTM/VF
impacts of critical headwater stream systems constitute one of the most major threats to this system
in the study area.
Structural Complexity
At the local scale, ecosystems possess a natural complexity of physical features that provides for a
greater variety of niches and more intricate interactions among species. Local structural complexity
increases with more snags in the forest, and more woody debris in the stream. At other scales,
spatial heterogeneity is equally important, affecting a wide range of ecological processes from
predator-prey interactions to energy transfer among ecosystems (USEPA, 1999). Considerable
experimental evidence supports the concept that physical structure may prevent generalist foragers
from fully exploiting resources and thus promote the coexistence of more species (e.g., Werner,
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1984). Simply put, complex habitats accommodate more species because they create more ways for
species to survive (Norse, 1990).
Headwater stream systems are known to be structurally complex. The structural complexity of
headwater streams may be negatively impacted by several indirect effects from MTM/VF. Stream
sections downstream from fills may be subjected to increased sedimentation from improper
placement of sedimentation ponds, sedimentation pond failure or from post mining run off.
Sedimentation may also result from runoff from areas being logged prior to mining. Sedimentation
may fill pool areas and smother riffles and snags, decreasing the structural complexity of the stream.
Technical studies performed for the MTM/VF EIS indicate that both stream flow and stream
temperature may become more constant in streams sections downstream from fill. Although these
changes may not impact the physical complexity of streams, there may be subtle decreases in
availability of niches that occur from decreasing the normal flow and thermal fluctuations inherent
in headwater stream systems.
Timber harvesting or tree removal is generally performed prior to mining. Timber harvesting may
be limited to the area of coal extraction, or may extend down the watershed from the anticipated toe
of fill. This activity would impact the leaves and woody material available for deposition into a
stream. A decrease in these materials would impact the stream's structural complexity by reducing
the material available for forming leaf packs, snags, or other woody-material related stream
structures. Woody material in these systems is also responsible for retaining small volumes of water
into micro-pools which represent an additional source of structural complexity (Wallace, 1992).
Several of the impact factors mentioned including sedimentation and reductions in the inputs of
leaves and woody material would not be limited to mining impacts only. These types of impacts
would also occur from other activities such as forestry.
Hydrologic Patterns
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Ecosystems possess natural hydrologic patterns that provide water for organisms and physical
structure for habitats. This cycle of water is also the vehicle for the transfer of abiotic and biotic
materials through the ecosystem. The natural hydrologic patterns of an ecosystem include the
magnitude, frequency, duration, timing, and rate of change (flashiness) of water flow.
The range of hydrologic variability in streamflow quantity and timing can be thought of as a "master
variable" affecting biodiversity and ecological integrity in riverine systems (USEPA, 1999). The
natural flow of a river varies on a time scale of days, seasons, years and longer (Poff et al. 1997).
There are five critical components of the flow regime (Poff and Ward, 1989, Richter et al., 1996):
Magnitude
• Frequency
Duration
• Timing
Rate of change (flashiness) of hydrologic conditions
These components interact to maintain the dynamics of in-channel and floodplain habitats that are
essential to aquatic and riparian species (Poff et al., 1997).
Hydrologic modeling studies performed for the MTM/VF EIS found that peak storm water flows are
slightly higher during and after mining. Hydrologic results from a separate field study indicate that
fills tend to increase the base flow of the stream and decrease the peak flow during a storm event.
Water temperature in streams in filled watersheds was less variable than in unfilled watersheds.
These types of impacts appear to be unique to MTM/VF activity in the study area. Other activities
which might affect hydrologic patterns, such as agricultural practices or water withdrawals, are not
major activities in the study area. Alterations in hydrologic patterns may have further impacts on
other ecological processes and are discussed under those processes. For both direct and indirect
impacts to ecological processes resulting from alterations in hydrologic patterns, MTM/VF would
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appear to be the major impact producing activity in the study area.
Nutrient Cycling
Ecosystems have evolved efficient mechanisms for cycling nutrients, which combined with sunlight
and water determine the productivity of the systems. The natural flow or organisms, energy, and
nutrients is essential for maintaining the trophic structure and resiliency of the ecosystem. Reduction
or augmentation of nutrient inputs to ecosystems can drastically alter these trophic interactions and
ultimately the quality of the environment. The input and assimilation of nitrogen is the most common
measure of nutrient cycling, but the dynamics of other essential compounds are also important.
Nutrient cycles are the processes by which elements such as nitrogen, phosphorus, and carbon move
through an ecosystem. This cycling is critical to the functioning of ecosystems; otherwise essential
elements and nutrients would continue on a relentless flow downhill, depleting ecosystems uphill
(Noss and Cooperrider, 1994). But terrestrial and aquatic systems have developed mechanisms that
slow the movement of water, nutrients, and energy to the sea. Vegetation of all types intercepts
nutrient-rich waters and bind materials in place. Anadromous fishes and other migrating species
move major amounts of biomass and minerals upstream, but the role of animals in moving nutrients
uphill has received relatively little study.
Trophic interactions within ecosystems (e.g., the food chain of plant-herbivore-carnivore) are the
most visible part of the cycling of energy and nutrient within ecosystems. Changes in the input or
export of nutrients within ecosystems can affect the status of these trophic levels and can have
ramifications for biotic interactions as well as ecosystem functioning. Less obviously, decomposers
(such as invertebrates and microorganisms) serve the critical role of recycling dead material at each
stage of the nutrient cycle and ultimately supply the soil nutrients that feed the plants that capture the
sun's energy. Many small streams have a nutrient base of leaves and downed wood that feeds insects
shredders and collectors. When this nutrient base is diminished by the removal of downed wood or
logging of forests, production rapidly declines.
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Impacts from MTM/VF activities to the ability of headwater streams to maintain their nutrient
cycling function are of great concern. The loss of the nutrient cycling function of the portion of
headwater streams from direct filling may represent a substantial loss of energy to the entire aquatic
system within and beyond the watershed containing the fill. This direct loss may be compounded by
the further impairment of the aquatic community downstream from fills. Studies seem to suggest that
the impacts to the aquatic community downstream from fills may result from water quality impacts
due to filling which may be extremely difficult or impossible to correct.
The combination of the direct fill impacts which decrease nutrient cycling and indirect impacts
through impairment of the aquatic community downstream from fills may result in a substantial
impact to the nutrient cycling function in headwater streams. This impact has proven difficult to
study directly. There is ongoing debate among regulators and scientists on the best way to collect
quantitative evidence for the possible occurrence and the severity of the potential impact to nutrient
cycling functions of headwater streams. Although this impact is difficult to demonstrate empirically,
substantial evidence exists in the primary literature demonstrating that shifts in the aquatic
community structure impact the ability of streams to process leaves and woody material, thereby
decreasing the input of energy to downstream areas. This evidence supports ongoing concerns over
impacts from MTM/VF to the nutrient cycling process.
Other activities, such as logging, also pose potential threats to the nutrient cycling function of
headwater streams in the study area. However, the permanent nature of filling compared to the more
temporary and possibly more manageable impacts from forestry, would suggest that MTM/VF
impacts of to the nutrient cycling function of headwater stream systems constitute one of the most
major threats to this system in the study area.
Purification Services
Ecosystems naturally purify the air and water. They also detoxify and decompose both natural and
manmade wastes. Purification processes are necessary for the normal functioning of ecosystems;
they break down harmful concentrations of toxic materials and refertilize soils and sediments through
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the action of microbes and other organisms. The capacity of ecosystems to assimilate and recycle
waste material depends on physical, chemical, and biological mechanisms; this capacity may be
exceeded by anthropogenic inputs depending on system-specific conditions.
Headwater stream systems do not have a tremendous capacity to provide purification services.
However, although this ecological process is not one which requires protection for headwater
streams, the absence of streams to provide this service reflects the sensitivity of this system to inputs
of a variety of toxic materials. Surface mining releases a variety of potentially toxic materials into
the environment including metals and mineral constituents such as sulfates which may act by altering
physical characteristics of water (e.g. pH or specific conductance). Headwater streams, with their
innately limited buffering capacity and lack of ability to sequester and precipitate out contaminants,
tend to be at risk from any input of toxic materials.
In contrast, wetlands are among the most effective ecosystems for removing pollutants and purifying
wastes. Wetlands operate through a series of interdependent physical, chemical and biological
mechanisms that include sedimentation, adsorption, precipitation and dissolution, filtration,
biochemical interactions, volatilization and aerosol formation and infiltration (USEPA, 1999).
Constructing wetlands has been suggested as a possible mitigation measure for impacts to headwater
streams. While this issue is complex, there may be promise in constructing wetlands in stream
channels of streams impacted by MTM/VF or at the toe of fill where groundwater emerges into
stream channels to improve the water quality of streams downstream from fill areas. The success of
these wetland systems to improve water quality would be highly dependent on the toxicity of the
water initially.
Biotic Interactions
The interactions, including the antagonistic and symbiotic interactions, among organisms are some
of the most important, but least understood, factors influencing the structure of natural ecosystems.
Because these interactions have evolved over long periods of time, the deletion of species from or
the addition of species to an ecosystem can dramatically alter its composition, structure, and function.
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Biotic interactions that are particularly important in maintaining community structure or ecosystem
function are described as "keystone" interactions (USEPA, 1999).
Section LA. describes biotic interactions common in headwater streams. Other Sections in Chapter
I discuss various vertebrate species including birds, salamanders and newts and mammals which
require interactions with the aquatic environment in order to maintain their lifecycle. Biotic
communities have been demonstrated to occur in the uppermost reaches of watersheds, even in
"ephemeral" stream zones which flow only as a result of rain or snow melt. Filling eliminatesl
aquatic and aquatic-dependant interactions that would formerly have occurred in the filled area. In
areas downstream from fills, changes in the macroinvertebrate and fish communities have been
observed. (USEPA, 2000 and Stauffer, 2000). Any change in community composition may
potentially have impacts to biotic interactions beyond that measured in the community composition
study, but these interactions are often difficult to demonstrate.
Many other impact producing factors in the study area may cause environmental changes that would
result in alterations or simplifications in biotic communities and associated biotic interactions.
Although data are lacking on the magnitude of mining impacts compared to other major alterations
in land use such as forestry, the permanent nature of filling would suggest that MTM/VF impacts to
biotic interactions in headwater stream systems, including interactions linking terrestrial biota to the
aquatic environment, constitute one of the most major threats to this system in the study area.
Population Dynamics
The population is a critical unit, not only for evolutionary change, but for the functioning of
ecosystems. Population numbers alone do not adequately reflect the prospects for species or the
continued performance of their ecological role. Information about life history and population
dynamics, such as dispersion, fertility, recruitment, and mortality rates, is critical to identifying
potential effects on population persistence and ecological processes. Key factor analysis can
determine which links in these dynamics primarily affect population success, while population
viability analysis can predict the amount and distribution of habitat needed to maintain healthy
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populations (USEPA, 1999).
When populations are lost, the local adaptations of these populations are lost, the ecosystem functions
performed by these populations cease, and ultimately species may go extinct. In general, the risk of
losing populations (and with them ecological integrity) is greatest when populations are small, but
even large populations may have critical components of their life histories of population cycles that
make them especially vulnerable (USEPA, 1999).
Direct and indirect impacts affecting population dynamics are of great concern for the headwater
stream systems in the study area. As discussed in Section LA., these biotic systems are
characteristically locations with high numbers of endemic, unique and rare populations of
macroinvertebrates, amphibians and fish. These populations tend to be small and highly specialized
for life in the headwaters environment. Species with these traits tend to be sensitive to relatively
small changes in their environment (Stein et al., 2000). Some species in headwater streams may have
distributions limited to only one or several watersheds. With such a small geographic range, fill
activities from one mine may impact the entire population.
MTM/VF activities may impact population dynamics through indirect as well as direct impacts.
Examples of changes that might occur include the following. Changes in contaminants or in thermal
regime may affect survivorship and reproduction. The number of individuals available for
recruitment may also decrease. The increase in base flow may eliminate intermittent flow areas
which serve as refugia for amphibians from fish. The loss of autochthonous input from concurrent
timber harvesting may decrease the habitat types available which may impact reproductive success
for some species. Finally, egg mortality may increase from increased sedimentation.
Many other impact producing factors in the study area may cause environmental changes that would
result in altered population dynamics and the extirpation of populations of some species. Although
data are lacking on the magnitude of mining impacts compared to other major alterations in land use
such as forestry, the permanent nature of filling would suggest that MTM/VF impacts to population
dynamics in headwater stream systems constitute one of the most potentially adverse threats to this
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system in the study area.
Genetic Diversity
Diversity at the genetic level underlies the more visible diversity of life that we see expressed in
individuals, populations, and species. Over evolutionary time, the genetic diversity of individuals
within and among populations of species contributes to the complex interplay of biological and
nonbiological components of ecosystems. The preservation of genetic diversity is critical to
maintaining a reservoir of evolutionary potential for adaptation to future stresses.
Genetic diversity originates at the molecular level and is the result of the accumulation of mutations,
many of which have been molded by natural selection. The genetic variants found in nature are
integrated not only into the physiological and biochemical functions of the organism, but also into
the ecological framework of the species. The genetic diversity of a species is a resource that cannot
be replaced (Solbrig, 1991). Genetic diversity enables a population to respond to natural selection,
helping it adapt to changes in selective regimes. Evidence indicates that a reduction of genetic
diversity may increase the probability of extinction in populations.
Many of the factors that would affect genetic diversity have been discussed for population dynamics.
Extirpating populations as well as species would result in decreases in genetic diversity in the study
area. Direct filling of streams reduces the numbers of individuals of rare and endemic species thereby
reducing its genetic diversity or even causing it to become extinct. Indirect impacts from mining
through alterations in water chemistry, stream flow or the aquatic thermal regime may also negatively
impact populations reducing genetic diversity.
The southern Appalachians have been identified by the Nature Conservancy as one of the hot spot
areas in the United States for rarity and richness (Stein et al., 2000). This region is known to have
the highest regional concentration of aquatic biodiversity in the nation. For this reason, it is
hypothesized that impacts which result in decreases in genetic diversity, as measured by loss of
species, loss of populations or loss of genetic variants, would have a disproportionately large impact
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on the total aquatic genetic diversity of the nation.
B. ECOLOGICAL SIGNIFICANCE OF METRICS ASSOCIATED
WITH THE TERRESTRIAL ENVIRONMENT
1. Ecological Significance of Forest Loss
Based on permits issued in the last ten years and an assumption of similar permits in the next ten
years, mountaintop mining has the potential to adversely impact 380,547 acres of forest in the four-
state study area. Table V.B-1 outlines the projected terrestrial impacts in the four-state study area.
Table V.B-1 projects the future terrestrial condition using the issued permit data and a long-term
future proj ection which is 2X the permit data proj ection. The data show that forest loss is associated
with an increase in the quarry/strip mines/gravel pits land cover type. When adding past, present, and
future forest impact; the study area estimated forest impact is 1,408,372 acres. This impact acreage
errs toward overestimation as described in the uncertainty section.
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Table V.B-1
Predicted Terrestrial Impacts
Kentucky Portion of the Study Area
Forest Cover (ac) [4 yr permit data x 2.5]
Forest Cover (%) [4 yr permit data x 2.5]
Forest Loss (ac) [4 yr permit data x 2.5]
Grassland as indicator of past mining impact
(ac)
Quarry/strip mines/gravel pits (ac) [4 yr permit
data x 2. 5]
Tennessee Portion of the Study Area
Forest Cover (ac)
Forest Cover (%)
Forest Loss (ac)
Grassland as indicator of past mining impact
(ac)
Quarry/strip mines/gravel pits (ac)
Virginia Portion of the Study Area
Forest Cover (ac)
Forest Cover (%)
Forest Loss (ac)
Grassland as indicator of past mining impact
(ac)
Quarry/strip mines/gravel pits (ac)
Baseline
Condition
(NLCD)
6,400,838
92.8
—
268,603
37,710
Baseline
Condition
(NLCD)
960,455
89.5
—
59,173
1,208
Baseline
Condition
(NLCD)
1,166,652
86.5
—
129,110
18,982
Condition
from
Issued
Permits
6,145,256
89.3
255,582
267,414
271,972
Condition
from
Issued
Permits
951,301
88.6
9,154
58,980
10,601
Condition
from
Issued
Permits
1,137,428
84.3
29,224
128,120
49,458
Projected
Future
Condition
5,889,674
85.6
511,164
—
—
Projected
Future
Condition
942,147
87.8
18,308
—
—
Projected
Future
Condition
1,108,204
82.1
58,448
—
—
81
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Table V.B-1 continued
Predicted Terrestrial Impacts
West Virginia Portion of the Study Area
Forest Cover (ac)
Forest Cover (%)
Forest Loss (ac)
Forest Loss from Valley Fills (ac)
Forest Loss from Mineral Extraction Area (ac)
Forest Loss from Auxiliary Areas (ac)
Grassland as indication of past mining impact
(ac)
Quarry/strip mines/gravel pits (ac)
Entire Study Area
Forest Cover (ac)
Forest Cover (%)
Forest Loss (ac)
Grassland as indicator of past mining impact
(ac)
Quarry/strip mines/gravel pits (ac)
Baseline
Condition
(NLCD)
2,703,677
93.8
—
—
—
—
86,777
45,715
Baseline
Condition
(NLCD)
11,231,622
92.1
—
543,663
103,615
Condition
from
Issued
Permits
2,617,065
90.6
86,587
18,338
45,544
22, 705
86,164
133,155
Condition
from
Issued
Permits
10,844,519
88.9
380,547
540,678
403,810
Projected
Future
Condition
2,530,478
87.5
173,174
—
—
—
—
—
Projected
Future
Condition
10,457,416
85.7
774,206
—
—
NLCD = National Land Cover Data Set
Figure V.B-1 depicts the 20 watersheds with the most potential adverse impact in terms of forest loss.
When this figure is compared to Figure II. A-1 one can see that the Northern Cumberland Mountains
Ecological Subregion has the greatest potential adverse impact in terms of forest loss (%). In
contrast, Figure V.B-2 depicts watersheds in the four-state study area with less than 87% forest cover.
The Northern Cumberland Plateau Ecological Subregion has the most watersheds with less than 87%
forest cover under the condition from the issued permits.
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a. Uniqueness of Habitats Within the Study Area
The study area is unique in that it contains a diverse flora and fauna with a mixture of northern and
southern species. The steep mountain slopes and deep valleys create a unique topography which
lends itself to the development of numerous microclimates. These microclimates are in part
responsible for the great variety of vegetative communities found within the study area. Each of
these vegetative communities provides forage, shelter, and nesting places for reproduction to
characteristic wildlife species.
The data suggests that five of the land use / habitat types of the West Virginia portion of the study
area undergo considerable changes under the long-term mountaintop mining scenarios. These five
habitat types and the species that they support are discussed below.
Diverse Mesophytic Hardwood Forests and Cove Hardwood Forests
Dominant among the land use types in the West Virginia portion of the study area is the diverse
mesophytic hardwood forest (61.6%). This forest type is among the most diverse forest type in the
southeastern United States, containing more than 30 canopy species (Hinkle et al.,1993). The
predominant species in the diverse mesophytic forest type are various maples (Acer spp.), yellow
poplar (Liriodendron tulipiferd) and beech (Fagus grandifolia); however, dominance is shared by
a large number of species including various oaks, hickories (Carya spp.), cherry (Primus spp.), and
black walnut (Juglans nigra), to name but a few. This forest type is characterized by a diverse
understory of trees that never attain canopy position such as dogwoods (Cornus spp.), magnolias
(Magnolia spp.), sourwood (Oxydendrum arboreum\ striped maple (Acer pennsylvanicum\ and
redbud (Cercis canadensis). Wildflowers are commonly found in this forest type because of the open
canopy in the spring.
The cove hardwoods are a type of mixed mesophytic hardwood forest. They are included here
because species common to the cove hardwoods are likely common to the mixed mesophytic
hardwood forest type as well due to their spatial relationship. Cove hardwoods are found in ravines,
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coves and along north-facing slopes. Species composition is generally very diverse with yellow
poplar, red oak (Quercus rubm), pin cherry (P. pennsylvanica), black cherry (P. serotina), paper
birch (Betulapapyrifera), yellow birch (B. alleghaniensis)., aspen (Populus spp.), sugar maple (A.
sacchamm), red maple (A. rubrum), and Eastern hemlock (Tsuga canadensis). Local species
dominance patterns are often small scale with significant species changes over relatively short
distances.
Due to the abundance and variety of fruits, seeds, and nuts the diverse mesophytic forest type
provides excellent habitat for wildlife and game species alike. Species of birds typically present
include the wood thrush (Hylocichla mustelina), Acadian flycatcher (Empidonax virescens), and blue-
gray gnat-catcher (Polioptila caeruled). Wildlife species richness of the mixed mesophytic forests
of the study area are considered one of the most diverse in the United States (Hinkle et al., 1993).
Mining-Barren Lands
The mining-barren lands patch type includes those areas where mining activities have significant
surface expression. Generally, vegetative cover and overburden have been removed to expose
deposits of coal, iron-ore, limestone, and other rocks and minerals. Included in this category are
inactive coal mines, quarries, gravel pits, etc. that lack sufficient vegetative cover for reclassification
in another patch type. Also included are those areas that for one reason or another, human induced
or not, are unable to support vegetation. These may be areas with thin soils, or sand or rock covered.
For the sake of this report, the increase in mining-barren lands recognized under many of the long-
term scenarios is associated entirely with coal mining. Other mining activities in the study area may
also lead to an increase in this patch type.
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Pasture-Grasslands
The pasture-grasslands land cover type includes pastureland, hay fields, old fields, abandoned farms,
and other herbaceous land cover areas (excluding wetlands). This is an important patch type in the
study area because many of the mine sites are converted to grasslands post-mining. Grasslands are
unique to the study area and historically were sporadic in distribution across West Virginia
(Strausbaugh and Core, 1997).
Grasslands provide food and shelter to a variety of wildlife, including game animals such as whitetail
deer (Odocoileus virginianus) and wild turkey (Meleagris gallopavo). This patch type also provides
habitat for a variety of songbirds that are rare in the study area. Included among these are the
grasshopper sparrow (Ammodramus savannarum), Henslow's sparrow (A. henslowi), and the
bobolink (Dolichonyx oryzivorus), each of which is listed as rare in West Virginia (Wood and
Edwards, 2001). These species may be listed as rare because historically their habitat is rare in the
state. As this patch type increases in abundance these species may well be removed from the list.
Oak Forests
The oak forest land cover patch occurs throughout much of West Virginia. These areas generally
occur on poorer/well-drained soils, ridges, or south and west facing slopes. Dominant species include
white oak (Q. alba), black oak (Q. velutina), chestnut oak (Q. montana), and red oak mixed with red
maple, yellow poplar, beech, and sugar maple.
Oak forests are important to wildlife because of their production of hard mast. Hard mast includes
acorns, walnuts, and other seeds from trees. Many wildlife species feed on acorns throughout the
year. Deer and squirrels are well known acorn feeders but even the lesser seen mice and many birds
depend on acorns for food throughout the year.
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b. Discussion of Wildlife Dependent on Forested Habitats
The WV Gap Dataset indicates that there are 26 distinct land use types in the West Virginia portion
of the study area and 16 of these are associated with the terrestrial habitat. The WV Gap data also
includes a list of species that are dependent upon each land use type / habitat. Table V.B-2
summarizes the WV Gap data for the terrestrial habitats of the study area.
Table V.B-2
Summary of West Virginia Gap Terrestrial Land Use Data and the Number of
Wildlife Species Associated with Each Land Use Class
Land Use Class
Diverse Mesophytic Hardwood Forests
Oak Forests
Pasture-Grasslands
Mountain Hardwood Forests
Hardwood-Coniferous Forests
Cove Hardwoods
Urban and Populated Lands
Mining-Barren Lands
Shrublands
Woodlands
Floodplain Forests
Mountain Coniferous Forests
Mountain Hardwood-Coniferous Forests
Row Crops- Agriculture
Conifer Plantations
Planted Grass
Size (ac)
1,852,790
193,833
97,620
31,633
864
350,861
44,163
78,377
30,196
5,170
17,384
864
793
1,638
168
390
No. of Species Associated with the
Land Use Class
Birds
131
106
72
114
124
93
17
24
102
54
110
81
107
49
95
11
Mammals
56
54
44
53
56
45
6
6
54
21
53
49
52
27
53
5
Herptiles
57
43
29
45
46
39
6
12
33
12
55
31
33
15
33
3
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The diverse mesophytic hardwood forest is the dominant habitat type in the West Virginia portion
of the study area. Table V.B-2 indicates that as many as 244 vertebrate species occupy the diverse
mesophytic hardwood forests of the West Virginia portion of the study area. In general, species
found within the diverse mesophytic hardwood forest are found in the other forest types. This is
supported by the data presented in Table V.B-3 which lists the number of bird species that each
habitat type (patch) shares with the mixed mesophytic hardwood forest patch type. Thus in a broad
sense, forest loss in the West Virginia portion of the study area has the potential of directly impacting
as many as 244 vertebrate wildlife species.
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Table V.B-3
Summary of the Avian Richness
of the West Virginia Portion of the Study Area
WV Gap Habitat Class
Barren-Mining Lands
Commercial
Conifer-Oak Forests
Conifer Plantations
Cove Hardwoods
Floodplain Forests
Planted Grass
Grasslands
Mixed Mesophytic Hardwoods
Mountain Coniferous
Mountain Hardwoods
Mm. Hardwoods-Coniferous
Oak Forests
Orchards
Pasture
Palustrine Emergent Wetlands
Palustrine Forested Wetlands
Palustrine Open Water
Palustrine Scrub-Shrub WLs
Row Crops
Rural Lands
Shrublands
Urban Lands
Woodlots
Total No. of
Avian Species
24
17
124
95
93
110
11
72
131
81
114
107
106
23
49
55
84
100
66
49
100
102
17
54
No. of Avian Species Shared With the
Mixed Mesophytic Hardwood Forest
16
10
117
84
93
108
6
44
—
71
114
98
105
21
30
26
77
70
52
30
73
79
10
51
Source: WV Gap Dataset
-------
Wildlife impacts in the West Virginia portion of the study area can be semi-quantified as done above
through the application of data available from the WV Gap Dataset. There is a high likelihood that
wildlife assemblages in Virginia, Tennessee, and Kentucky run a similar risk of potential adverse
impacts on wildlife assemblages as those in West Virginia since the ecological subregions, described
previously, do not follow political borders.
c. Important Wildlife That May Serve as Models or Ecological Indicators of Disturbance
Impacts on Forest Interior and Neotropical Migrant Bird Populations
West Virginia has a rich avian fauna with 183 known species of birds (WV Gap data). There are 131
species of birds known to inhabit the mixed mesophytic hardwood forests of the study area (WV Gap
data). Table V.B-3 summarizes the avian richness of the study area based on WV Gap habitat and
bird occurrence data. The data show that forested habitats of the study area are the most diverse in
terms of avian species richness and that shrublands, open water wetlands, and grasslands contain a
rich avian assemblage that differs considerably from that of the forests.
Table V.B-4 lists area requirements for the 19 neotropical migrant bird species included in Robbins
et al. (1989) study. This table lists the area where the maximum number of individuals is observed
and the area where 50% of the maximum number of individuals is observed for each species. Based
on these data, 14 of the 19 species require unbroken tracts of forest in excess of 7,413 ac (3,000 ha)
for a maximum probability of observation. The black-throated blue warbler {Dendroica
caerulescens) has the largest area requirement of the birds included in the study. This statement is
supported by the 2,471 ac (1,000 ha) area requirement for probability of observation 50% that of the
maximum.
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Table V.B-4
Forest Area Requirements for 19 Neotropical Migrant Bird Species
of the Study Area
Common Name
Acadian flycatcher
Great crested flycatcher
Blue-gray gnatcatcher
Veery
Wood thrush
Red-eyed vireo
Northern parula
Black-throated blue warbler
Cerulean warbler
Black-and-white warbler
Worm-eating warbler
Ovenbird
Northern waterthrush
Louisiana waterthrush
Kentucky warbler
Canada warbler
Summer tanager
Scarlet tanager
Rose-breasted Grossbeak
Area where probability of
observance is maximum (ac)
7,413+
178
7,413+
618
1,235
7,413+
7,413+
7,413+
7,413+
7,413+
7,413+
1,112
7,413+
7,413+
741
7,413+
7,413+
7,413+
7,413+
Area where probability of
observance is 50% max. (ac)
37
1
37
49
2
6
1,285
2,471
1,730
544
371
15
494
865
42
988
99
30
2
Adapted from: Robbins et al. (2000)
In general, watershed PEC values throughout the West Virginia portion of the study area, under the
issued permit condition, are good or excellent. PEC values range from 0.86 units to 1.93 units with
a mean value of 1.57 units (standard deviation 0.20 units). Forty-six of the 63 watersheds have PEC
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values of 1.62 or greater. This suggests that mountaintop mining alone may not have an adverse
impact on the biologic integrity of the West Virginia portion of the study area.
Although the data suggests that ample forest will remain in the West Virginia portion of the study
area to maintain relatively high PEC scores, impacts to many forest interior bird species are still
likely to occur. Take for example those species with breeding ranges that are restricted to or confined
mostly within the study area. Figure V.B-3 illustrates the breeding ranges of three forest interior bird
species (Louisiana Waterthrush, Worm-eating Warbler, and Cerulean Warbler) that may be affected
by mountaintop mining. The core of each of these species breeding ranges is within the study area.
Disturbances associated with mountaintop mining have the potential to adversely impact each of
these species breeding ranges. The above mentioned warblers inhabit upland forests while the
Louisiana waterthrush inhabits forested riparian habitats. The potential adverse impact of loss of
habitat for these species has extreme ecological significance in that habitats required by these species
for successful breeding are limited in the eastern United States.
Wood and Edwards (2001) provide evidence that mine sites that were converted to grasslands after
mountaintop mining provide habitat for a number of grassland bird species that are listed as "rare"
in West Virginia. These species are rare in West Virginia because historically grasslands are rare in
the state (Strausbaugh and Core, 1997). Some may argue that providing habitat for species listed as
rare is ecologically significant. However, these grassland species have substantial breeding habitat
in other parts of the United States. To illustrate this the breeding habitat of four grassland species
known to occupy the grasslands of post-mining sites (Dicksissel, Horned Lark, Eastern Meadow
Lark, Grasshopper Sparrow) is depicted on Figure V.B-4. The core breeding area for each of these
species is well outside of the study area.
In conclusion, the avian fauna of the study area is rich and contains a number of species with interior
forest requirements for successful breeding. Large tracts of intact forest are rare in the eastern United
States due to a number of land use change associated reasons. Mountaintop mining in the study area
has the potential to impact as much as 380,547 ac of forest. These impacts would result in
fragmentation of the environment into areas of forests and grasslands. The remaining forest patches
may provide proper habitat to maintain the population of most of the states avian fauna; however, a
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few species may be put into peril because their core breeding area is within the heart of the future
mountaintop mining area. Loss of these species has more ecological importance than providing
habitat for grassland species considered rare in the state because it suggests possible future
endangerment of some forest interior species as opposed to the potential gain of some disjunct
grassland species populations.
Impacts on Terrestrial Salamander Populations
Salamanders are an important ecological component in the mesic forests of the study area and are
often the most abundant group of vertebrates in both biomass and number (Burton and Lykens, 1975;
Hairston, 1987). Ecologically, salamanders are intimately associated with forest ecosystems acting
as predators of small invertebrates and serving as prey to larger predators (Pough et al., 1987).
Studies conducted in Eastern forests suggest that timber harvesting is detrimental to salamander
populations (Bennett et al., 1980; Pough et al, 1987; Ash, 1988; Petranka et al., 1999). Specifically,
Ash (1988) reported on the local extinction of Jordan's salamander (Plethodonjordanf) from clearcut
plots in North Carolina. Similarly, Petranka et al. (1993) found that forest floor salamanders were
more than twice as abundant in mature forests as in clearcut plots.
Clearcutting occurs prior to surface coal mining; therefore, studies described above suggesting that
timber harvesting is detrimental to salamander populations would seem to be applicable to the impact
from mountaintop mining. No studies could be found that specifically address the impact of
mountaintop mining on salamander populations. There are, however, many studies that present the
negative impact that acidification of the terrestrial environment, a phenomenon associated with
surface mining (Thomas et al., 2001 and references within), has on salamander populations (Dunson
et al., 1992, Wyman and Jancola, 1992; Home and Dunson, 1994; Frisbie and Wyman, 1995). One
of the greatest impacts that mountaintop mining operations have on the terrestrial salamanders of the
study area is the placement of fill in the valleys. This leads to the direct loss of salamanders under
the fill and to a change in habitat on top of the fill. Removal of forests and the establishment of
grasslands in once forested areas also leads to a decline in salamander populations. It has been
suggested that forest clearing (clearcutting) degrades the forest floor microhabitat by increasing
exposure to solar radiation and thus decreasing surface soil moisture thereby rendering it inhospitable
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to salamanders (Ash, 1988). This thesis has been supported within the study area. Handel (2001)
reports that soil moisture within remnant forests was significantly higher than that of nearby
reclaimed mine sites. Furthermore, Wood and Edwards (2001) observed a shift in the herpetofauna
community from amphibian dominated in the forests to reptile dominated in grasslands of mine sites.
Petranka et al. (1993) estimates that between 75% and 80% of terrestrial salamanders are lost
following clearcutting of mature timber stands. Furthermore, reestablishment of salamander
populations to pre-harvest conditions has been estimated to range between 20 and 70 years (Petranka
etal., 1993; deMaynadier and Hunter, 1995; Ash, 1997). Although these numbers differ and there
is debate in the scientific community over which is correct (Petranka, 1999), it can be concluded that
salamander populations suffer major setbacks in the years following forest removal. There is
evidence that terrestrial salamander populations do not become successfully established in nearby
forests as forest clearing is taking place (Hairston, 1987). Therefore, it can be concluded that
salamander populations become reestablished once forests become reestablished.
Handel (personal communication) suggested, based on the findings of his study of reforestation on
mined sites, that mined sites may take as long as 120 years or more to attain mature forest conditions.
From this, we can conclude that salamander populations in the study will be reduced in number and
biomass for a long period of time. This reduction in salamander populations may have negative
impacts on the species that depend upon them in the food web.
Thirty-one (31) species of salamanders are known from the West Virginia portion of the study area
(WV Gap data). Of these 25 species are known to inhabit the mixed mesophytic hardwood forest
while 21 species are known to occupy cove hardwood forests. Petranka (1993) presented a
conservative estimate that there are about 4,050 salamanders per acre of mature forest floor in Eastern
forests (10,000/ha). Applying this number to the 11,231,622 acre of forest in the study area yields
a conservative estimate of 36,390,455,280 salamanders in the study area. Assuming that 80%
(Petranka, 1993) of the salamanders are lost in the projected forest impact areas, approximately
1,232,972,280 have the potential of being adversely impacted. This equates to 3.4% of the entire
salamander population of the four-state study area. Species that are most likely to be affected are
those that are most abundant on the forest floor and along the riparian areas of the small headwater
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streams. These are predominantly the Plethodon and Desmognathus species.
2. Discussion of Habitat Changes and Interpretation of Significance
Habitat changes will occur in the study area and these changes will involve a shift from a forest
dominated landscape to a fragmented landscape with considerably more mining lands and eventually
grassland habitat (Figure V.B-5). This shift should lead to a shift in the floral and faunal components
of the ecosystem. For example, dry grassland species will dominate the once post-mined and forest
harvested sites. This will result in an overall reduction in the native woody flora as well as a
reduction in the spring herbs and other vegetative components characteristic to the study area
(Handel, 2001).
Wildlife shifts will include a shift from forest to grassland species. The abundance of grassland birds
will likely increase while many forest interior, neotropical migrant species will suffer losses in terms
of number (Wood and Edwards, 2001). There will likely be an increase in game species such as
whitetail deer and turkey due to an increase in grasslands and the diversification of the habitats. The
herpetofauna will likely undergo a shift from mesic favoring salamander dominated communities
along the riparian corridors of the small headwater streams and in the litter of the forest floor to a
snake dominated grassland fauna (Wood and Edwards, 2001).
3. Potentially Adverse Impact on Biodiversity
Biodiversity is the variety of organisms in an area. In this case, the area is defined as the four-state
study area; however, a better ecological boundary would be the Ecological Subregions described in
Table II. A-l. Biodiversity can be applied to various levels of biological organization but in the case
of assessing potential adverse impacts to biodiversity within the Ecological Subregions of the study
area only two levels of biological organization apply. Impacts to the terrestrial environment may
affect biodiversity of the at the (1) genetic and/or (2) species/population level. Species affected by
fragmentation within the Ecological Subregions would include those with specific requirements for
habitats that are lost and those with poor dispersal abilities.
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The direct loss of habitat and fragmentation of a once contiguous environment is considered by some
to be the most serious threat to biological diversity (Wilcox and Murphy, 1985). Unfortunately, the
result of anthropogenic changes on the natural environment takes time, which makes impacts difficult
to measure. The effects of habitat losses are likely to take generations, even centuries, before fully
realized (Tilman et al., 1994; Brown and Lomolino, 1998).
Wilcove (1987), recognizing this time lag affect on natural environments, presented a series of
sequential stages that are expected to occur following anthropogenic change to the natural
environment. These stages lead finally to biological collapse and begin immediately following
fragmentation of the natural environment.
1. Initial exclusion of some species when fragmented patches do not, by chance, include
any individuals of the species.
2. Extirpation due to a loss of resources. Many species require multiple habitats for
forage, shelter, and breeding purposes and some of the isolated patches in the
fragmented environment may not include all the needs of each species.
3. Small population problems such as a reduced gene pool, unbalanced population
demographics, and susceptibility to stochastic events (fire, severe weather, etc.).
4. Isolation effects like reduced gene flow and the increased frequency of deleterious
genes in the population.
5. Ecological imbalances associated with predator-prey relationships, host-parasite
relationships, and mutualisms. Furthermore, the fragmentation may lead to an
increase in invasive species, which could further help trigger local extinctions. This
stage may also include changes in the composition of the ecological communities,
where populations once low number become dominant and visa-versa.
Thus, we can conclude that fragmentation of the study area has the potential to impose considerable
impact on the terrestrial environment. Some of these impacts may be recognized immediately while
others may take tens or hundreds of years to surface.
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4. Carbon sequestration and the Forest Carbon Cycle
Energy flows and materials circulate through the global ecosystem. Essential nutrients and other
chemicals, including man-made materials, flow from the non living to the living parts of the global
ecosystem in a path know as the biogeochemical cycle.
The energy flow in terrestrial ecosystems depends on interactions between a number of
biogeochemical cycles such as the carbon cycle and hydrological cycles. Terrestrial ecosystems play
a role in the global carbon cycle. Carbon is exchanged between trees and the atmosphere through
photosynthesis and respiration. The cycling of carbon as carbon dioxide involves assimilation and
respiration by plants. Human activities affect the global carbon cycle. According to the
Intergovernmental Panel on Climate Change, from 1850 to 1998, approximately 270 GtC has been
emitted as carbon dioxide into the atmosphere from fossil fuel burning and cement production (TPCC,
2001).
Carbon dioxide is what is known as a greenhouse gas which means that it contributes to global
warming. According to the World Resource Institute (1997), drawing carbon dioxide out of the
atmosphere (sequestration) and into biomass is the only known practical way to remove large
volumes of this greenhouse gas from the atmosphere (June 2001). Reforestation could potentially
achieve significant carbon sequestration. It has been estimated that temperate forests sequester 1.5
to 4.5 tons of carbon per hectare per year as reported by the Intergovernmental Panel on Climate
Change (2000).
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104
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Figure II.A-1
Study Area
I I Study Area
State
Ecological Subregion - Section
| Allegheny Mountains
Hi Central Ridge and Valley
j Interior Low Plateau, Bluegrass
^H Interior Low Plateau, Highland Rim
gj Northern Cumberland Mountains
;2rj Northern Cumberland Plateau
= Northern Ridge & Valley
"~~ Southern Cumberland Mountains
^ Southern Llnglaciated Allegheny Plateau
N
A
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Figure III.A-1
Permit Locations
(' West Virginia
EIS Study Area
Permit Extent
Watershed Boundary
North Carolina
-------
Figure III.A-2 Typical MTM/VF Mine Site Layout
Reclaimed Areas Active Areas Future Mining
Production Areas
Development Areas
Valley Fills
Sedimentation Ponds
r
i
I Permit
I Area
I
I
I
I
I
J
Scale in Miles
0 0.5 1.0
Contour Interval = 40 feet
-------
-------
Figure III.C-1.
Relationship Between Forest Cover and Potential Ecological Condition
100.0 T
Denotes PEC of Study Area under pre-impact condition.
90.0 -
Denotes PEC of Study Area under permit issued condition.
Denotes PEC of Study Area under projected future condition.
o
U
o
fc
80.0 -
70.0 -
60.0
35.262x +32.293
R2 = 0.9229
0.5
0.7
0.9
1.1 1.3
PEC (value)
1.5
1.7
1.9
-------
-------
Figure V.A-1
Most Impacted Watersheds Based on Miles of
Direct Stream Impact or Percent of Direct Stream Impact
X
s~ ^ -• .
( r' ( A--
~ fi-*ZZ/ 5
r,f\ , J^'
f «. J"'1o;.:"'r -VJ'
-•i-!'
-------
Figure V.A-2
Miles of Stream Length Directly Impacted (By Watershed)
Miles of Directly Impacted Streams
0 (no impact)
1-5 miles
5-15 miles
15 miles and above
EIS Study Area
Watershed Boundarv
North Carolina
-------
Figure V.B-1
Most Impacted Watersheds Based on Percent Forest Loss
The 20 Most Impacted Watersheds in Percent Forest Loss
EIS Study Area
US EPA Region 3 CIS Team 11/19/2002 MFrank SIG1177 Mapttl 883
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^_
-------
Figure V.B-2
Watersheds With Less Than 87% Total Forest Cover
Watersheds Containing Less Than 87% Forest Cover
C3 wa
EIS Study Area
Watershed Boundary
US EPA Region 3 OIS Team 11/19/2002 MFrank SIO1177 Map#1882
-------
Figure V.B-3
Breeding Range Distribution of Forest Interior Bird Species Known to Occupy the Study Area
Louisiana Waterthrush
Worm-eating Warbler
101 »nd ttiair
IUo100
I 1 to -i-i
4to 10
I to *
Out ind (How
Cerulean Warbler
101 inn itcTt
31 lo 100
11 Id 90
•*!
-------
Figure V.B-4
Breeding Range Distribution of Grassland Bird Species Known to Occupy the Study Area
Honied Lark
Dickcissel
Eastern Me ado wl ark
101 )td lt*1t
•. 11 •• II .1
i: i.o
«to 10
Mot
tail laa UH«w
101 U«lb«T*
; I In 100
11 to 30
419 10
71» 3
Grasshopper Sparrow
101
31 U 100
II tO SO
410 JO
3 Id 3
One inn below
-------
3.000 i
2.000 -
Figure V.B-5
Percent Change in Cover Types
-5.000
D Open Water
• Low intensity residential
D High intensity residential
D Commercial / Industrial / Transortation
• Surface Mining / Quarries / Gravel Pits (X 100)
D Transitional
• Deciduous Forest
D Evergreeen Forest
• Mixed Forest
• Pasture / Hay
D Row Crops
• Urban / Recreational Grasses
• Woody Wetlands
• Emergent Herbaceous Wetlands
NLCD Land Use Categories
-------
Study Area - West Virginia
Land Use / Land Cover
(value)
11
21
22
23
32
33
41
42
43
81
82
85
91
92
(description)
Open Water
Low intensity residential
High intensity residential
Commercial / Industrial / Transortation
Surface Mining / Quarries / Gravel Pits
Transitional
Deciduous Forest
Evergreeen Forest
Mixed Forest
Pasture /Hay
Row Crops
Urban / Recreational Grasses
Woody Wetlands
Emergent Herbaceous Wetlands
Pre-lmpact
(ac)
16,622
16,110
86
9,310
45,715
19,441
2,396,893
52,910
252,519
67,335
17,048
128
1,354
1,383
Pre-lmpact
(%)
0.6
0.6
0.0
0.3
1.6
0.7
82.7
1.8
8.7
2.3
0.6
0.0
0.0
0.0
Post-Impact
(ac)
16,607
16,079
86
9,275
133,155
19,083
2,318,251
52,206
245,257
67,081
16,914
128
1,352
1,383
Change
(%)
-0.1
-0.2
0.0
-0.4
191.3
-1.8
-3.3
-1.3
-2.9
-0.4
-0.8
0.0
-0.1
0.0
Change
(ac)
15
31
0
35
-87,440
358
78,642
705
7,263
254
134
0
2
0
TOTAL
Total acres for study area:
Total acres for permit areas:
Total forested acres (41,42,43,91):
Total forested acres in permit areas:
2,896,857
100
2,896,857
2,896,857
90,104 (3.1% of total area)
2,703,677
86,587 (3.2% of total forest)
180
-------
Descriptions of GIS Mine Polygons Used in the Cumulative Impact Study
Kentucky
Original Source Description
The Department for Surface Mining Reclamation and Enforcement (DSMRE) currently
makes available scanned and georeferenced mining and reclamation plan maps and
annual underground maps for permits issued by the Department. Mining and reclamation
plan (MRP) maps are required to be submitted with an application for a permit to conduct
surface coal mining and reclamation operations in the Commonwealth of Kentucky.
MRP maps are generally drawn on an enlarged USGS seven and one-half (7 1/2) minute
topographic map at a scale of between 400 and 600 feet to the inch. Permitted surface
and underground mine boundaries and facilities associated with coal mining operations
are shown along with names and locations of streams and other bodies of water, roads,
buildings, cemeteries, oil and gas wells, public parks, public property, and utility lines.
The source of the GIS mine polygons for Kentucky used in this cumulative impact study
are the surface mining overlay maps maintained by the Kentucky Department of Surface
Mining Reclamation and Enforcement (DSMRE). These maps consist of frosted mylar
sheets that overlay 7 /^ minute USGS topographic maps. DSMRE staff draw permitted
surface and underground mine boundaries and selected other features in ink onto the
mylar. DSMRE GIS specialist scanned and georeferenced these mylar overlays, which
are now available to the pubic for downloading. Here is the site link where the scanned
may be downloaded: http://kydsmre.nr.state.ky.us/gis/data.htm. MRP maps
georeferenced beginning in July 2002, and all georeferenced underground maps are
projected in the NAD83 Kentucky Single Zone Coordinate System. MRP maps
processed prior to July 2002 were georeferenced in NAD83 Kentucky State Plane North
or South zone coordinates.
Currently six series of overlays are available both in hardcopy and digitally. Each series
represents a time period in the permitting of surface coal mining in Kentucky.
0 Series I: Areas permitted from 1977 to March 1, 1981, and which were active as
of January 1, 1981.
0 Series II: Areas permitted from 1961 to 1977, and which were inactive as of
January 1, 1981.
0 Series III: Areas permitted from March 1, 1981 through January 18, 1983.
0 Series IV: Areas permitted under the permanent program after January 18, 1983
and through April 1, 1986.
-------
0 Series V: Areas permitted under the new permanent program after April 1, 1986
and through August 1, 1995.
0 Series VI: Areas permitted after August 1, 1995 and through August 31, 1999.
0 Series VII Areas permitted after September 1, 1999 and through April 30, 2000.
(Series VII has been converted to GIS polygons by DSMRE.)
For the purposes of the cumulative impact analysis only the information from Series VI
and VII were used. Series VI consists of three primary overlay sheets: (1) Polygon
Layer - closed polygons - permit boundaries, etc... (2) Line Data Layer - lineal lines -
roads, conveyors, utilities, etc... and (3) Point Data Layer - small ponds, sampling sites,
mine adits, etc. Overlaying permits will be drawn on separate sheets of Mylar, thus there
may be more than one polygon layer sheet (Sheet 1, Sheet 2, etc...). Hatched lines
denote underground shadow areas. Areas of less than full recovery have a greater opening
between hatch marks and recovery percentage is indicated.
DESCRIPTION OF MAP SYMBOLS AND CODES
The mining overlay maps are identified by the 7 /^ minute quadrangle name. Alpha
characters are assigned to each permit number and appear as the first portion of the
attribute code assigned to each map feature. The alpha codes are generally listed in
alphabetic order and expand to multi-lettered codes (AA, BB etc.) to include all permits
pertaining to a given quadrangle. Alpha codes and the specific permit number to which
they correspond are listed at the bottom of the overlay. Adjacent maps that share the same
permit boundary have, in most cases, the same alpha code on both maps. The number
which follows the alpha code is a one-, two- or three-digit number defining the major
category in which a mining feature falls (i.e. mining, fill areas, haul roads, etc.). Often a
sub-category is used to describe a mining feature in greater detail. An example of a
feature attribute code is 'A-610'. The code refers to a sediment structure (6),
embankment type (10), within the permit number assigned 'A'. Areas common to more
than one permit number are labeled with the alpha character and feature attribute codes of
both permit numbers with a comma placed between them.
The permit features are drawn as dashed lines, solid lines, dash-dot-dot lines, or single
dots. Haul roads and railroads are drawn as dashed lines unless they correspond to the
permit boundary, in which case the permit boundary takes precedence. Features that
appear as solid lines or polygons include mining areas, fill/storage areas, permit boundary
areas, face-ups, and reference areas. Points are used to represent features of small acreage
such as sediment structures, monitoring points and underground mine openings. Hatched
lines indicate underground areas.
Due to the influx of new mining permits and the absence of some permits at the time of
drafting, these overlays are not 100% comprehensive. The updating procedure (acreage
additions and deletions) was initialized to keep the mining operations overlays as up-to-
date as possible.
-------
PERMIT MAPPING CODES
1—Contour Mining Area
2—Area Mining Area
3—Mountaintop Removal Area
4—Augering Area
5—Fill area
57 - General Fill/Spoil Storage Area/Refuse Area
58 -Hollow fill
59—Topsoil Storage
510—General/Temporary/Equipment Storage Area
6—Sediment Structure
69—Sediment Type
610—Embankment Type
611—Dugout
612—Rock Check Dam
613—Diversion Ditch
616—Combination Diversion Ditch
618—Pole Structure
620—Earth Dam
7—Access/Haul Road
8—Monitoring Point
81—Surface Water Monitoring Point
82—Biology Monitoring Point
83—Groundwater Monitoring Point
84—Geologic Sampling Point
85—Surface/Biology Monitoring Point
9—Permit Boundary Area
0—Other Features
06—Underground Mine Opening
Adits [Y] - leg of Y in direction of mine opening
Air shafts [V]
014—Reference Area
015—Face-Up Area / Re-grade Area
017—Wildlife Habitat
019—Railroad
021—Coal Stockpile
030—Underground Mine Area
040—Mine Management Area
050—Prep Plant
As previously mentioned, Kentucky DSMRE converted the Series 7 digital and geo-
referenced mylars to GIS polygons. Series 7 GIS data is described below:
-------
The GIS data consists of the boundaries of permitted surface and underground mines and
other selected features for permits issued between September 1, 1999 and April 30, 2000.
Kentucky DSMRE used Arc View 3.1 software to create the Series 7 GIS data.
Information describing each permit is contained in the dBASE file include the following:
SHAPE - layer type
CODE - mine feature*
FACILITYJD - mine feature id
PERMIT - permit number
* mine feature codes
FU Face Up
LO Load Out
MM Mine Management Area
PP Prep Plant
SA Surface Area
SBK Spoil Bank Fill
SC Surface Contour
SG Surface Auger
SM Surface Mountaintop
Slide Slide
Spoil Spoil
Stockpile Stockpile
UG Underground
Kentucky DSMRE forewarns the users of the digital information that the maps available
for download do not comprise a complete set of maps that may be available. Additional
hardcopies of these or other MRP or annual underground maps may be obtained by
contacting: Daryl Hines, Christina Rice, or Amy Covert at (502) 564-2320 in the
Kentucky Department for Surface Mining Reclamation and Enforcement.
Description of Digital Data Base Queried for the Cumulative Impact Study
Staff from OSM's Pittsburgh Office downloaded the Series VII and VI digital
information from KY DSMRE FTP server on October 7, 2002, and October XXX,
respectively.
The Series VII GIS data was filtered to retain only those mining disturbances associated
with surface mining activities. All polygons associated with the activities coded as "face
up", "load out", "prep plant", "surface auger", "slide", "stockpile", or "underground"
were deleted from consideration for the purpose of the cumulative impact analysis.
Further, using the boundaries of the EIS study area in Kentucky, a GIS specialist at OSM
Pittsburgh Office used readily available querying tools in ESRI ARCVIEW software to
-------
select only those surface mining permits that were located wholly or partly within the EIS
study area. This filtered digital data for Series VTI, which consisted of multiple polygons
for surface mines, were forwarded to EPA's Wheeling Office.
The Series VI scanned and georeferenced mylars posed a more challenging task. Staff
from OSM Pittsburgh Office used specialized software (Able Software R2V for
Windows) to convert the digital picture images (rasters) to vectorized features (polygons,
lines, and points). Once converted to GIS polygons, features representing surface mining
disturbances were retained and other disturbances (such as underground mining,
preparation plants, augering areas, face-up areas, stockpiles, ect) were eliminated.
Further, using the boundaries of the EIS study area in Kentucky, a GIS specialist at OSM
Pittsburgh Office used readily available querying tools in ESRI ARCVIEW software to
select only those surface mining permits that were located wholly or partly within the EIS
study area. This filtered digital data for Series VII, which consisted of multiple polygons
for surface mines, were forwarded to EPA's Wheeling Office.
Below is a list of digital mining polygons from Kentucky forwarded for inclusion in the
cumulative impact study.
SERIES 7 PERMITS
Permit ID
9180346
8885022
8970369
8988106
8970390
8980450
8640096
8600359
8600349
8130220
8605198
8950139
8980516
8980469
8600374
8130246
8130246
8600316
8070097
8980492
8675225
8485327
8600034
8365197
Permit ID
8670390
8980446
8665025
8070265
8670383
8670402
8980467
8480151
8610454
8970388
8985694
8480200
8360261
8670399
8970376
8970396
8980444
8980450
8800132
8980490
8580135
8980479
8970357
8585056
Permit ID
8980507
8600034
8985167
8675172
8930093
8950141
8800103
8800130
8605201
8980488
8605223
8985908
8678021
8985913
8480191
8615297
8980565
8660229
9180375
8630277
8605154
8130257
8480140
8980545
Permit ID
8970358
8130010
8360265
8660240
8955002
8070236
8980446
8670394
8360249
8980481
8800117
8600377
8260530
8670377
8600369
8130249
8670257
8615273
8130240
8160109
8920100
8360231
8130226
8480179
-------
SERIES 6 PERMITS
Permit
ID
864012
845005
1111111
4800093
4805070
4805074
6805009
6805012
6807001
8320043
8320144
8450050
8580151
8580152
8589999
8640096
8640107
8640115
8640117
8640124
8640132
8640135
8640142
8648016
Permit
ID
8649000
8800014
8800023
8800034
8800043
8800103
8800108
8800109
8800130
8805058
8805059
8805126
8805137
8805138
8805139
8805144
8805148
8805150
8807000
8880078
-------
Descriptions of GIS Mine Polygons Used in the Cumulative Impact Study
Tennessee
Original Source Description
The source of the GIS mine polygons for Tennessee used in this cumulative impact study
is the a digital geographic database of coal mining permit boundaries in Tennessee
produced by the U.S. Department of Interior, Office of Surface Mining Reclamation and
Enforcement (OSM) in Knoxville, Tennessee. It consists of georeferenced digital map
data and descriptive attribute data. OSM Knoxville Field Office Geographic Information
System (KFO GIS) Team developed this information from public records. The source for
most of these records is the permit application submitted by coal mining operators for
review and approval by OSM to conduct surface coal mining operations at specific
locations in the State of Tennessee. These materials are a working resource of OSM and
are contained in its file rooms and archives in paper format. Data contained in these
materials were converted to digital format generally through digitizing paper maps onto a
planimetrically correct base.
Selected features from the last approved Mining Operation Plan maps and Environmental
Resources maps contained within a permit application submitted by a coal mining
operator to the Office of Surface Mining (OSM) were manually digitized into an
individual coverage using the ArcEdit subsystem of Arclnfo Workstation. Each map was
georeferenced using geographic features found in common on both the paper manuscript
(map) and on Digital Raster Graphic (DRG) images of standard 7.5-minute series USGS
topographic quadrangle maps as displayed on a computer monitor. These DRGs were
acquired from the U.S. Tennessee Valley Authority and were transformed to Tennessee
State Plane, NAD 27 coordinate system by OSM. After initial digitizing on a standard
digitizing table, the digital data set was inspected on a computer monitor and visually
compared against the paper manuscript. Coverage feature classes were edited to correct
digitizing errors. Attribute data was added to describe features contained in the coverage.
Individual coverages were then posted to the Knoxville Field Office Geographic
Information System (KFO GIS). Each individual coverage was then incorporated into a
master coverage of similar features. All compilation, digitizing, and quality control were
performed by GIS specialists at the OSM in Knoxville, TN.
The accuracy of these digital data is based on features represented on source maps
supplied by various coal mining operators. In general, these features were drawn by hand
on paper reproductions of standard 7.5-minute series USGS topographic quadrangle maps
enlarged to a scale of 1"=400' and were submitted as Mining Operation Plan maps or
Environmental Resource maps in a permit application for approval by OSM to conduct
surface coal mining operations at a specific location. It is not known whether these paper
reproductions of the standard USGS topographic maps meet National Map Accuracy
Standards. OSM digitized selected features from each paper source map using a
minimum of four georeferenced control point locations (tics). Approximately 95 percent
-------
of the maps resulted in a Root Mean Square (RMS) error of less than 10 feet as reported
by the software during calibration. None exceeded 25 feet. The difference in positional
accuracy between the actual feature location on the ground and their digitized coordinates
as shown in this data set are unknown
This data set is a work-in-progress and represents the current amount of digital data
available for this theme at the time of its production. During production, selected paper
maps from individual permit applications are digitized in reverse chronological order
based on the permit and/or revision approval date. This method is used to ensure that data
resulting from the most recently approved permitting action for any given mining
operation is always available to KFO GIS users. As the general digitizing effort
continues, maps are retrieved from successively older permit applications for digitizing
and data entry. Current estimates of temporal coverage for this theme extend back to
approximately 1984. As new information is made available to OSM, and as resources are
available to capture this information into a digital format, this data set will be amended
with updated features from newly approved mining operations and also be revised to
include features from older mining operations.
Although these data have been processed successfully on a computer system at OSM, no
warranty expressed or implied is made by OSM regarding the utility of the data on any
other system, nor shall the act of distribution constitute any such warranty.
For further information about the coal mining data sets held by OSM, contact Bill Card,
Geographer, Office of Surface Mining, Knoxville Field Office, 530 Gay Street SW, Suite
500, Knoxville, TN 37902, telephone 865.545.4103, x. 134, fax 865.545.4111, e-mail
bcard@osmre.gov.
Description of Digital Data Base Queried for the Cumulative Impact Study
Staff from OSM's Pittsburgh Office downloaded the most current digital database from
Tennessee mining permits from OSM Knoxville Field Office FTP server on September
23, 2002. This database consisted of 816 mining polygons. Staff from the Knoxville
Field Office telefaxed a list of new mining permits issued by OSM from January 1992 to
date that were approved to use surface mining methods or a combination of surface and
underground methods to extract coal. The permits on this list met the criteria established
by the EIS Steering Committee for the cumulative impact study and was used to select a
subset of mine permit digital data polygons from the source database. Further, using the
boundaries of the EIS study area in Tennessee, a GIS specialist at OSM Pittsburgh Office
used readily available querying tools in ESRI ARCVIEW software to select only those
surface mining permits that were located wholly or partly within the EIS study area. This
filtered digital data, which consisted of 39 new surface mines, were forwarded to EPA's
Wheeling Office.
Below is a list of digital mining polygons forwarded for inclusion in the cumulative
impact study.
-------
Area Perimeter
30465400 41338.5
1035160
1 746640
15103300
2192200
6163980
5232260
3127850
5937830
5590310
9672760
3474050
5795880
21139800
14015400
7915880
4861450
12050700
49239200
4482470
41457200
25640600
6050420
3565400
16370900
26786700
17007500
31883600
24616600
2648310
12745900
6018640
9653380
36521400
15718800
23922900
15811500
10227800
12017900
6072.51
13837.1
18107.5
12866.7
24088.8
27300
54218.6
13173.5
26912.8
25563.8
20565.2
28318.9
143268
99090
42381.8
16927.3
63882.9
160020
26429.7
31645.1
23207.6
16749.5
30569.4
49242.5
65574.6
97312.6
111662
139962
13755.2
43582.5
51569.3
46303.8
113165
83907.7
112234
102234
33875.4
73438.7
Permit
2846
2853
2863
2876
2892
2904
2905
2923
2927
2929
2931
2938
2944
2947
2951
2952
2953
2955
2956
2957
2959
2981
2982
2983
2990
2994
3005
3008
3010
3013
3015
3045
3048
3054
TN-005
3058
3059
3052
2865
Acres
699.39
23.7639
40.0974
346.724
50.3259
141.507
120.114
71.8056
136.314
128.34
222.056
79.7532
133.059
485.303
321.75
181.724
1 1 1 .604
276.645
1130.38
102.903
951.727
588.627
138.899
81.8494
375.825
614.939
390.439
731.947
565.12
60.7968
292.605
138.169
221 .609
838.414
360.854
549.194
362.983
234.798
275.892
Issued Type
19930629 S
19980319
19940902
19920214
19920803
19920904
19920810
19960109
19931002
19930507
19940914
19950331
19940520
19951023
19960911
19950804
19961025
19971110
19951016
19960126
19970403
19970911
19970507
19960423
19970102
19960912
19970326
19970728
19980127
19980304
19980509
19980811
19990401
20000815
19930107
20001114
20010801
20010607
19920124
S
S
S
C
C
C
S
S
C
C
S
C
C
S
S
S
S
S
C
S
S
S
S
S
S
S
C
A
A
A
A
A
A
C
A
A
A
C
Permittee
Skyline Coal Co.
East Fork
Hood Coal Corp.
Skyline Coal Co.
Rich Resources I
Tennesse Consoli
Robert Clear Coa
Round Mountain M
Tennessee Consol
Robert Clear Coa
GatliffCoal Co.
Tennessee Consol
Robert Clear Coa
GatliffCoal Co.
Premium Coal Co.
Hood Coal Corp.
GatliffCoal Co.
GatliffCoal Co.
Tennessee Mining
Tennessee Consol
Skyline Coal Co.
Cumberland Coal
Tennessee Consol
Robert Clear Coa
Addington Enterp
Addington Enterp
Robert Clear Coa
Additngton Enter
Tennessee Mining
Tennessee Consol
Appolo Fuels Inc
Appolo Fuels Inc
Robert Clear Coa
Appolo Fuels Inc
GatliffCoal Co.
Mountainside Coa
Mountainside Coa
Mountainside Coa
GatliffCoal Co.
-------
Descriptions of GIS Mine Polygons Used in the Cumulative Impact Study
Virginia
Original Source Description
The source of the GIS mine polygons for Virginia used in this cumulative impact study is
the a digital geographic database of coal mining permit boundaries in Virginia produced
by the Virginia Department of Mines, Lands, and Minerals - Division of Mined Land
Reclamation (DMLR) in Big Stone Gap, Virginia.
It consists of geo-referenced digital map data and descriptive attribute data. ...
This data set is a work-in-progress and represents the current amount of digital data
available for this theme at the time of its production. ...
Description of Digital Data Base Queried for the Cumulative Impact Study
Staff from OSM's Pittsburgh Office downloaded the most current digital database from
Virginia DMLR FTP server on September 16, 2002. This database consisted of 2358
mining polygons. Staff from OSM Big Stone Gap Field Office identified the prefix in the
permit identification number (GIS Data Field "PERMIT") representing mines approved
to use surface mining methods or a combination of surface and underground methods to
extract coal: "11", "15", "16", and "17".
Mining permits approved by Virginia DMLR beginning from January 1992 to the most
current date were selected using information provided in the GIS database (GIS Data
Field "PEISSUEDT"). The permits on this list met the criteria established by the EIS
Steering Committee for the cumulative impact study and was used to select a subset of
mine permit digital data polygons from the source database. Further, using the
boundaries of the EIS study area in Virginia, a GIS specialist at OSM Pittsburgh Office
used readily available querying tools in ESRI ARCVIEW software to select only those
surface mining permits that were located wholly or partly within the EIS study area. This
filtered digital data, which consisted of multiple polygons for 98 surface mines, were
forwarded to EPA's Wheeling Office.
Below is a list of digital mining polygons forwarded for inclusion in the cumulative
impact study.
Permit Issue Date Surface Mine Description
1101530 6/21/1995 Mine#1
1101556 5/3/1996 JIM BELCHER FORK STRIP
1101736 1/26/2000 Burnt Poplar surface mine #1
-------
Permit
1101474
1101434
1101599
1101654
1101700
1101633
1101785
1101550
1101707
1101784
1101400
1101762
1101795
1601787
1101720
1101781
1101621
1101701
1601788
1101481
1101685
1101759
1101792
1101548
1101553
1101606
1101417
1101737
1101555
1101752
1101416
1101494
1101669
1101600
1101622
1101518
1101782
1501660
1101783
1101447
1101675
1701547
1101401
1101537
1101776
1101538
1501778
1101445
1101743
1101760
1101463
1101623
1601486
1101661
1101691
Issue Date
8/16/1993
10/5/1992
5/9/1997
8/25/1998
10/22/1999
4/23/1998
10/1/2001
12/21/1995
11/9/1999
9/28/2001
1/13/1992
11/9/2000
2/1/2002
11/16/2001
11/15/1999
8/28/2001
11/12/1997
11/5/1999
11/20/2001
9/21/1993
4/13/1999
9/28/2000
1/16/2002
11/29/1995
3/19/1996
7/7/1997
5/14/1992
1/28/2000
5/1/1996
7/26/2000
5/13/1992
3/2/1994
12/10/1998
5/21/1997
11/17/1997
11/30/1994
9/7/2001
10/15/1998
9/25/2001
12/1/1992
2/10/1999
11/9/1995
1/16/1992
9/14/1995
5/9/2001
9/22/1995
6/4/2001
11/23/1992
3/17/2000
10/20/2000
5/12/1993
12/1/1997
11/10/1993
10/19/1998
8/10/1999
Surface Mine Description
Dwale#7job
MINE #5
NEECE CREEK SURFACE MINE
Mine#1
Lower Elk Creek reserve
SYCAMORE STRIP
PHELPSNO. 1 MINE
LAUREL FORK STRIP
CLINTWOOD R-38
Bee Branch Surface
Guess Fork strip
PAW PAW STRIP
BEARWALLOW SURFACE MINE
Buckeye Branch - Caney Fork remining permit
Tilley Branch mine
Glamorgan Auger Mine #1
BULL GAP MINE
STARR BRANCH STRIP
CONVICT HOLLOW REMINING PERMIT
GREENBRIER CREEK MINE
LOVERS GAP #3 SURFACE MINE
LOVERS GAP #4 SURFACE OPERATION
Surface Mine No. 1
Lovers Gap surface mine
SHORTRIDGE BRANCH SURFACE MINE
Toms Fork North surface mine
HACKNEY HOLLOW SURFACE MINE
TARPON SURFACE MINE
STRIP #1
HURRICANE BRANCH STRIP #1
Rock Branch surface operation
CANE BRANCH MINE
STRIP #6
MINE#1
Georges Fork Surface Mine
RED ONION MINE
BIG CREEK SURFACE MINE
GEORGE'S FORK #2 MINE
ALLIED COAL MINE #2
STALLARD BRANCH SURFACE MINE
HIBBITTS GAP SURFACE MINE
HESS CREEK KENNEDY SEAM COMPLEX
NORTH FOX GAP SURFACE MINE
BOLD CAMP SURFACE MINE
Long Branch surface mine
Wampler Ridge surface mine
Straight Fork Surface Mine
COBRA PIT #1
BIRCHFIELD NO. 5
Backbone Ridge surface mine
TRACE FORK SURFACE OPERATION
TRACE FORK STRIP
Pardee No. 1 Strip
ROGERS RIDGE SURFACE MINE
TRACE FORK #3 MINE
-------
Permit Issue Date Surface Mine Description
1101549 12/20/1995 HART CREEK SURFACE MINE
1101673 1/12/1999 DARK HOLLOW STRIP #1
1101516 11/10/1994 Rabbit Ridge
1101779 6/11/2001 HONEY BRANCH REMINING PERMIT
1101740 2/22/2000 STRIP #9
1101460 2/25/1993 Mine #2
1101468 7/21/1993 Raging Bull adjacent areas
1101627 1/13/1998 TRACE FORK #2
1101763 11/13/2000 COON BRANCH SURFACE/AUGER MINE
1101607 7/9/1997 BLACK BEAR SURFACE MINE
1101694 9/17/1999 Sawmill Hollow mine
1101800 4/26/2002 AMOS RIDGE SURFACE MINE
1101521 1/23/1995 SCREAMING EAGLE #2 SURFACE MINE
1101699 10/18/1999 FORK RIDGE MINE
1601656 9/14/1998 Jr.
1501702 11/5/1999 BANNER #2 STRIP
1601738 2/1/2000 Stonega #1 Strip (Bluff Spur mine)
1601505 9/8/1994 MINE #49
1101774 4/26/2001 SAWMILL HOLLOW#2
1501773 4/10/2001 JR.
1101681 3/16/1999 BLACK BEAR #2 SURFACE MINE
1101602 5/23/1997 Silver Fox surface mine
1101671 12/30/1998 BANNER #1 STRIP
1601503 7/29/1994 SARGENT HOLLOW
1701766 11/21/2000 Jr.
1601876 10/4/2001 Stonega No. 2 Strip
1601576 9/27/1996 Black Creek surface mine
1101758 9/26/2000 Black Bear #3 surface operation
1101536 9/13/1995 DANTE REFUSE RECOVERY OPERATION
1101794 1/16/2002 Roda #2 Strip
1101620 11/6/1997 POSSUM TROT HOLLOW MINE
1601491 1/14/1994 AUSTIN POWDER HOLLOW SURFACE & DEEP MINE
1101492 2/15/1994 White Stallion
1101750 6/19/2000 KELLY BRANCH SURFACE MINE
1101580 10/29/1996 C & M #3
1601777 5/21/2001 BULL RUN SURFACE MINE
1601744 3/20/2000 STATE LINE STRIP
1601423 8/3/1992 EASTERN STRIP
1601466 5/26/1993 Western strip
1601519 12/14/1994 SOUTHERN STRIP
-------
Descriptions of GIS Mine Polygons Used in the Cumulative Impact Study
West Virginia
Original Source Description
The source of the GIS mine polygons for West Virginia used in this cumulative impact
study is the a digital geographic database of coal mining permit boundaries, coal
extraction polygons, and fill polygons produced by the West Virginia Division of Mining
and Reclamation - Information Technology Office. These datasets are derived from
hardcopy permit maps submitted to DMR. Hardcopy maps were scanned and
georeferenced prior to extraction of features via on-screen digitizing by West Virginia
University - Natural Resource Analysis Center. All datasets have been projected to UTM
zone 17,NAD27.
Description of Digital Data Base Queried for the Cumulative Impact Study
Staff from OSM's Pittsburgh Office downloaded the most current digital database from
West Virginia mining permits from West Virginia Department of Environmental
Protection website: http://129.71.240.42/data/omr.html. Three GIS data layers -- permit
boundaries, surface mine extraction areas, and valley fill areas - met the criteria
established by the EIS Steering Committee for the cumulative impact study. This data set
was filtered by using the last two digits of the permit identification number (the year the
permit identification number was assigned) to include only those activities associated
with new surface mining permitted after January 1, 1992. Further, using the boundaries
of the EIS study area in West Virginia, a GIS specialist at OSM Pittsburgh Office used
readily available querying tools in ESRI ARCVIEW software to select only those surface
mining permits that were located wholly or partly within the EIS study area.
Below is a list of 142 West Virginia mining permits forwarded for inclusion in the
cumulative impact study.
PERMITJD
S051799
S500997
S500999
S200995
S500593
S400597
S200599
S300599
S400401
S400497
S300495
PERMITJD
S302693
S502197
S302193
S502097
S502095
S402095
S502393
S502399
S502297
S302299
S503595
PERMITJD
S501592
S501400
S501494
S301496
S301492
S201496
S501796
S501798
S301794
S501694
S501194
-------
S200499
S300499
s1 00495
S300795
S400699
S200697
S400199
S300195
S200197
S300199
S500395
S400399
S400397
S300295
S501895
S501899
S501597
S401595
S201593
S301599
S401499
S301693
S401197
S501095
S501395
S401395
S301393
S501297
S501299
S201293
S301299
S502997
S502995
S502597
S502495
S502493
S502797
S502799
S303593
S303793
S503195
S503097
S503095
S503395
S503295
S357600
S500900
S400998
S200896
s1 00896
S500596
S400596
S300598
S300400
S200494
S500700
S300796
S200798
S400600
S400698
S300696
S400198
S400300
S500396
S500394
S500398
S200396
s1 00394
S400200
s1 00200
S300296
S200294
S501900
S501998
S401500
S501596
S501092
S401096
S201092
S501300
S501396
S401396
S301396
S201398
S401298
S201298
S402596
S502598
S502496
S302794
S502698
S102192
S402096
S302300
S402396
S502296
S503996
S503792
S403192
S503096
S503392
S504692
S505592
S505792
S506692
S507492
S501594
-------
-------
APPENDIX J
AOC DOCUMENTS
-------
-------
DEPARTMENT OF MINES, MINERALS AND ENERGY
DIVISION OF MINED LAND RECLAMATION
GUIDANCE MEMORANDUM1 No. 4-02
Issue Date: March 22, 2002
Subject: Approximate Original Contour Guidelines
The Department of Mines, Minerals and Energy (DMME), Division of Mined Land
Reclamation (DMLR) through this guidance memorandum is implementing the following
guidelines concerning approximate original contour on steep-slope surface mine operations while
providing a means for determining excess spoil quantities.
It is intended to improve consistency in the final configuration of areas restored to a
usable and productive post mining land use.
The basis of AOC lies in the federal Surface Mining Control and Reclamation Act of
1977. The federal Act requires that a mine site be regraded to AOC. The federal Office of
Surface Mining (OSM) recognizes that, in primacy states, the state regulatory authority is
primarily responsible for interpreting what constitutes AOC at a given mine site. Virginia's
requirements are set out in the Virginia Coal Surface Mining Control and Reclamation Act of
1979 (Act), as amended, and the Coal Surface Mining Reclamation Regulations (4 VAC 25-
130).
Virginia Requirements for Approximate Original Contour
Approximate original contour (AOC) is defined under Section 4 VAC 25-130-700.5 of
the regulations as -
"that surface reconfiguration achieved by backfilling and grading of the mined areas so
that the reclaimed areas including any terracing or access roads closely resembles the
general surface configuration of the land prior to mining and blends into and
complements the drainage pattern of the surrounding terrain, with all highwalls, spoil
piles, and coal refuse piles eliminated."
1 This Memorandum is to be considered a guideline issued under the authority of § 45.1-230.A1 of the Code of
Virginia which reads:
"In addition to the adoption of regulations under this chapter, the Director may at his discretion issue or distribute to
the public interpretative, advisory or procedural bulletins or guidelines pertaining to permit applications or to
matters reasonably related thereto without following any of the procedures set forth in the Administrative Process
Act (§ 2.2-4000 et seq.). The materials shall be clearly designated as to their nature, shall be solely for purposes of
public information and education, and shall not have the force of regulations under this chapter or under any other
provision of this Code."
-------
GUIDANCE MEMORANDUM No. 4-02
Issue Date 03/22/02
Subject: Approximate Original Contour Guidelines
Page 2
{tc Ml "Virginia Requirements for Approximate Original Contour}
Sections 4 VAC 25-130-816.102(a) and 4 VAC 25-130-817.102(a) of the regulations
provide backfilling and regrading standards for all disturbed areas of a permit. The AOC
standards must be achieved for all disturbed areas, except as allowed by subsection (k) of the
aforementioned regulations, when:
(1) the standards for thin overburden are met in 4VAC 25-130-816.104,
(2) the standards for thick overburden are met in 4VAC 25-130-816.105, or
(3) Approval is obtained from the Division for:
(a) Mountaintop removal operations in accordance with 4 VAC 25-130-785.14
(b) A variance from AOC in accordance with 4 VAC 25-130-785.16: or
(c) Incomplete elimination of highwalls in previously mined areas per 4 VAC 25-
130-816.106
AOC is to be met whenever there is no variance clearly defined in the approved permit
package.
To help decide if AOC is achieved in the permit proposal, DMLR considers, at a
minimum, the following three criteria:
(1) Surface configuration
(2) Drainage patterns
(3) Highwalls and spoil pile elimination
The Act requires that post mining areas have all highwalls and spoil piles eliminated.
Static safety factors of 1.3 or greater are required.
In reviewing a permit application, this static safety factor requirement can be considered
achieved by post mining slopes that are 2h: Iv. The post mining slopes may also match pre-
mining slopes that are steeper or flatter than 2h: Iv, as long as the minimum 1.3 static safety
factor is met. Access roads for the post mining land use should be limited to a 20 feet width. The
Division may approve greater access road width if it can be demonstrated that it supports the post
mining land use. Drainage controls and berms should be included and approved in the plans. In
order to determine if a proposed grading plan achieves AOC, both the pre-mining and post
mining cross sections should be submitted. These pre-mining and post mining cross sections
should match and be provided for all critical slope areas (i.e. finger ridges, significant slope
changes, etc.).
The following figures are provided to demonstrate some applications of these guidelines.
Three typical mining examples are presented. In each situation, the reclaimed configuration is
established by initiating backfilling operations at the location of the outcrop at the lowest seam to
be mined. A flat area may be left for an access road and drainage control. After these allowances,
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GUIDANCE MEMORANDUM No. 4-02
Issue Date 03/22/02
Subject: Approximate Original Contour Guidelines
PageS
the slope is then started upward on a 2h:lv slope (or equivalent premining slope), as long as the
1.3 static safety factor is met.
• Figure 1 demonstrates a steep slope/mountaintop mining operation that has been
returned to AOC.
• Figure 2 demonstrates a typical steep slope contour mine returned to AOC. In all
cases the highwalls must be eliminated. This may require slopes steeper than
2h:lv.
• Figures 3 and 4 demonstrate a finger ridge removal operation that has been
returned to AOC. For long finger ridge removal, cross sections should be
provided transversely through the length of the finger ridge showing a profile of
the ridge and perpendicular to the profile (i.e. parallel to the proposed highwall
from outcrop to outcrop). In all cases, highwalls have to be eliminated. Generally
for long finger ridges, the cross sections from crop to crop are used to establish
the post-reclamation profiles.
The boundary of the mined area is determined by vertically projecting a line from the
outcrop of the lowest coal seam mined. The mined area is shown on the following figures.
Individual mining areas within each permit area should be established. For contiguous mining
operations the mining should be considered one operation (Figure 5).
Again, although the two mined areas are combined for reclamation purposes, in order to
meet AOC, the Act requires each individual highwall be eliminated.
Final elevations are not controlling factors in determining whether an area has been
restored to AOC. The area need not be restored to the original elevations. The reclaimed area
may be somewhat lower or even higher than the original elevations. The key component in
determining AOC is the proposed configuration of the backfill. This configuration needs to
comply with the provisions detailed above.
Once the final proposed configuration is determined, the applicant should include
detailed spoil volume calculations based on site-specific materials, so that swell shrinkage and
bulking can be accurately predicted. The total spoil volume is calculated for the site. Next the
volume of material required to backfill the site to the approved AOC configuration is
determined. By definition, any excess material not required to return the site to AOC is excess
spoil and may be placed in approved excess spoil disposal sites.
An additional option for AOC includes landform grading. In this situation, the
permittee may use variations in slope to create contours that reflect more natural slopes. For
example, a permittee may place additional material on the bench area and reduce the slope of the
contour as long as he can show stability in that area. The operator may use excess spoil to
produce irregular shapes of natural stable slopes. These slopes would be characterized by a
continuous series of concave and convex forms, interspersed with swales and berms that blend
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GUIDANCE MEMORANDUM No. 4-02
Issue Date 03/22/02
Subject: Approximate Original Contour Guidelines
Page 4
with natural slopes. Landform grading may be employed as long as the volume of excess spoil
initially determined is not exceeded.
Slope drainage devices would follow natural slope drop lines to re-create natural original
drainage patterns. All spoil piles should be used in the grading. The surface configuration
criterion for meeting AOC will be met if the landforms constructed closely match undisturbed
areas, with curvilinear contours. Again, documentation of the mine area prior to disturbance is
essential for the support of the rationale for the post-mining configuration of landform grading.
As long as these landform-graded areas meet the criteria for AOC and the determined excess
spoil volumes are not exceeded, they would be accepted as AOC.
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GUIDANCE MEMORANDUM No. 4-02
Issue Date 03/22/02
Subject: Approximate Original Contour Guidelines
Page 5
Typical Mountaintop Operation
Premining Section
Postmining Section
Lowest seam to be mined
Typical postmining slopes are 2h: Iv
Drainage structure may be left
Terraces are acceptable
Fill Area
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GUIDANCE MEMORANDUM No. 4-02
Issue Date 03/22/02
Subject: Approximate Original Contour Guidelines
Page 6
Typical Contour
Premining Cross Section
Postmining Cross Section
Lowest coal seam to be mined
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GUIDANCE MEMORANDUM No. 4-02
Issue Date 03/22/02
Subject: Approximate Original Contour Guidelines
Page 7
Plan View
1"=50'
Premining
/
X
Figure 3
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GUIDANCE MEMORANDUM No. 4-02
Issue Date 03/22/02
Subject: Approximate Original Contour Guidelines
PageS
Typical Cross Sections
A-A 1"=50')
B-B (1"=505)
Figure 4
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GUIDANCE MEMORANDUM No. 4-02
Issue Date 03/22/02
Subject: Approximate Original Contour Guidelines
Page 9
Highwal
For contiguous operations the mined area will be combined for multiple seams when the
horizontal distances between the highwall of the lower operations and the outcrop of the higher
operation is less then 25 feet.
Figure 5
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GUIDELINES FOR DETERMINING
APPROXIMATE ORIGINAL CONTOUR IN KENTUCKY
I. SURFACE CONFIGURATION
The reclaimed area shall closely resemble the general configuration of
the land prior to mining. This does not mean that the post-mining contours
must exactly match the pre-mining contours, or that post-mining slopes must
be long and uninterrupted, if pre-mining slopes were. The general terrain,
post-mining, will, however, be comparable to the pre-mining terrain. If the
area was level or gently rolling prior to mining, it shall retain those features
after mining. Rolls, dips, crests, and slopes need not be restored in their
original locations. Level areas may be increased or terraces created, in
accordance with existing regulations, through formation of shorter, steeper
slopes, if the slopes are capable of supporting the post-mining land use and
blend in with the surrounding terrain. During the permitting process, the
permit applicant shall provide detailed cross-sections and contour maps
clearly depicting the pre-mining and post-mining surface configurations.
In accordance with 405 KAR 16:190, Section 2(4){a), the width of the
individual terrace bench shall not exceed 20 feet, unless specifically
approved as necessary for stability, erosion control, or roads included in the
approved post-mining land use plan.
The spoil balance calculations in the permit application will also be
used in determining the post-mining surface configuration.
2. SPOIL VOLUME
The permit application shall provide a justification for the balance of
backfill and excess spoil material by describing the site-specific reasons for
and means by which the proposed backfilling and grading plan will achieve
the surface configuration. Approximately 80% of the bank volume of spoil
must be returned to the mined area. Some flexibility in this percentage will
be recognized for site-specific and engineering considerations, and for
feasibility of the mining plan.
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The proposed design location and size of the fills shall be justified in
the permit application.
3. STABILITY
The spoil will be placed in the backfill area so that the outslopes of the
backfill do not exceed a 2h:lv slope unless established in the permit
application that the steeper slope backfill is necessary to reach the desired
configuration, and that slope stability can be maintained. The final backfill
configuration shall be designed and constructed so that the in-place spoil
will be stable. The final configuration must include allowances for the
approved design locations of post-mining features such as permanent water
impoundments, roads, and drainage control facilities, including but not
limited to diversions and terraces.
Fills shall have a stable final configuration, with outslopes not to
exceed 2h:lv, and drainage control structures placed and sized as
appropriate.
4. DRAINAGE CONTROLS
Establishing controlled drainage patterns is a major factor in the
determination and construction of the final design configuration. Hollows
and ridges below or above the mine areas have to be recognized and
accounted for in the design and reestablishment of drainage for the backfill.
The final drainage plan shall be incorporated into the final configuration so
that the reclaimed area blends into and compliments the drainage pattern of
the surrounding area. Water intercepted within or from the surrounding
terrain shall flow through and from the reclaimed area in an unobstructed
and controlled manner. The permit application review will consider the
reestablishment of the approximate watershed acreages within the mine area,
in order to reduce impacts to the hydrologic performance of the watershed.
5. HIGHWALLS and SPOIL PILES
All high walls, spoil piles, and depressions, except small depressions
approved in accordance with 405 KAR 16:190, Section 2(5) or 18:190,
Section 2(4), shall be eliminated in a manner which blends in with the
surrounding terrain.
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AOC Reclamation — Contour Strip
On Bench Diversion
Road for Maintenance
Berm
N.T.S.
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A.O.C. Reclamation - Area Mines
On-Bench
Structure
Permit Boundary
Outcrop
Barrier
Embankment Silt Structure
Coal Seams to
be removed
Post mining relief !s compressed
due to use of on—bench ponds,
diversions and roads.
On Bench Pond
&. Diversion
On Bench Diversion
Internal Access
Rood
N.T.S.
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A.O.C. Reclamation — Point Removal
Auger Limits
Outcrop
Barrier
Surface Disturbance Boundary
Backfill to
Uniform Slope
On bench diversion ditch and
access for maintenance.
Permanent
On Bench Pond
Berm
NJ.S.
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29 AOC and Excess
Spoil Disposal
CONTENTS
Durable Rock Fills
AOC/Excess Spoil Guidance (3/18/99 Draft)
AOC Final Version (7/19/00)
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Permit Handbook Section 29 - Excess Spoil Disposal
SUBJECT: Durable Rock Fills
DATE: November 13, 1992
The West Virginia Surface Mining Reclamation Regulations at 38-2-14.14(g)(7),
for durable rock fills, state in part that "the underdrain system may be constructed
simultaneously with excess spoil placement by the natural segregation of dumped
materials". This construction method results in the larger dumped rocks settling on the
bottom of the valley floor to form an adequate underdrain.
It has been observed during recent field visits, that a few durable rock fills were
being constructed using multiple side dumping points, which were located well ahead of
the developing toe. However, this construction method, also known as "wing dumping,
can create several types of problems.
Excessive side dumping of spoil creates increased disturbed area within the limits
of the fill that results in an increased sediment load upon the sediment control structure.
Additionally, when conditions arise which dictate that a durable rock fill cannot be
constructed to meet its original design capacity, any spoil which had been previously side
dumped ahead of the developing toe would than have to be rehandled and placed within
the confines of the fill. Thus, this practice can result in environmental problems and
unnecessary additional disturbance.
Therefore, for durable rock fills, it shall be the policy of this agency to limit side
dumping or "wing dumping" of spoil to a distance not to exceed 300 feet downstream
from the developing toe, as measured horizontally. The developing toe shall be defined
as that area which is clearly being formed by the dumping of materials from points
located near the center of the hollow.
NOTE: This is also in the I & E Handbook, Series 14
WVDEP 29-1
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Permit Handbook Section 29 - Excess Spoil Disposal
SUBJECT: AOC/Excess Spoil Guidelines
DATE: June 24, 1999
In order to establish a common beginning point for the AOC analysis, the
applicant is to be requested to supply calculations, maps and cross-sections which are
based upon the AOC/Excess Spoil Guidance of March 18, 1999. This will be in addition
to the demonstration of AOC calculations contained in the mine designs and proposal
maps submitted as part of the application. Other justification may be used; however, they
must yield same or similar results as this agency will use this document for comparison
as to whether AOC is achieved.
The foregoing information, together with information contained in the No
Practical Alternatives document, will be used to evaluate valley fill size, location, and
whether the backfilled area has been returned to AOC.
As always, the regulatory requirements of slope stability, drainage, etc., will apply
to the review of the application. This applies to all applications which have not been
approved.
WVDEP 29-2
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Permit Handbook Section 29 - Excess Spoil Disposal
SUBJECT: Final AOC Guidance Document Policy
DATE: June 5, 2000
Approval: Michael C. Castle, Director
Effective immediately, all surface mine applications submitted after March 24,
2000, must have the Final AOC Guidance Document policy used to determine the
adequacy of the AOC design and fill placement.
It is important to note that the Final AOC Guidance Document does not apply to
contour mines. Contour mining application (regardless of date of receipt) will be
reviewed using the existing AOC/Excess Spoil Guidance document which does apply to
contour operations.
WVDEP 29-3
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1. Introduction and Background 5
1.1 APPLICABLE PROVISIONS OF STATE LAW 5
1.2 PURPOSE, OBJECTIVES AND APPLICABILITY 5
2. AOC and Excess Spoil Quantity Relationship 7
2.1 ELEMENTS OF AOC DEFINITION 7
2.2 INTRODUCTION OF AOC MODEL CONCEPT 7
2.3 DEFINITION OF CONFIGURATION 8
2.3.1 Introduction 8
2.3.2 Total Spoil Material (TSM) 8
2.3.3 Original Contour (OC) 10
2.4 EFFECT OF PERFORMANCE STANDARDS ON BACKFILL VOLUME 10
2.4.1 Introduction 10
2.4.2 Stability Requirements (SR) 10
2.4.3 Drainage Control Requirements (DR) 11
2.4.4 Sediment Control Requirements (SCR) 11
2.4.5 Access/Maintenance Roads (AR) 11
2.4.6 Maximum Backfill Requirements (MBR) 12
3. AOC Determination (Mountaintop Mining) 13
3.1 INTRODUCTION 13
3.2 BACKFILL SPOIL DETERMINATION MODEL 13
3.3 EXCESS SPOIL DETERMINATION 13
3.4 ADJUSTMENT TO ES ANDBKF TO REFLECT OFF SITE DISPOSAL 14
3.5 ADDITIONAL BACKFILL CAPACITY REQUIRED BY AOC MODEL 15
3.6 SUMMARY OF VOLUME ALLOCATIONS 16
3.7 ISOLATED COAL SEAMS 16
4. Excess Spoil Disposal Area Definition 18
4.1 INTRODUCTION 18
4.2 EQUIVALENT SWELL HEIGHT 18
4.3 TARGET FILL ELEVATION 18
5. Excess Spoil Disposal Optimization (Mountaintop Mining) 19
5.1 INTRODUCTION 19
5.2 SPOIL DISPOSAL PLAN APPROVAL 19
5.3 PRESUMED CRITERIA TEST 19
5.4 "ESDA BANK" ANALYSIS 21
6. AOC Determination (Contour Mining) 24
7. Excess Spoil Disposal Optimization (Contour Mining) 25
8. AOC / Fill Optimization Panel 26
9. AOC Compliance/AOC Variance Requests 27
9.1 AOC COMPLIANCE DETERMINATION 27
9.2 AOC VARIANCE REQUEST EVALUATION 28
10. Permit Revisions and Amendments 29
10.1 MINE PLAN REVISIONS 29
10.2 PERMIT AMENDMENTS TO ADD MINERAL EXTRACTION 29
10.3 ADJACENT PERMITS OR PERMIT AMENDMENTS 30
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1. Introduction and Background
1.1 Applicable Provisions of State Law
Surface Mining Control and Reclamation Act of 1977 (SMCRA)
30 USC 1291 Section 701(2)
West Virginia Surface Coal Mining and Reclamation Act (WVSCMRA)
22-3-3(e)
22-3-13(d)(3)
22-3-13(b)(4)
22-3-13(b)(10)(B), (C), (F), (G)
West Virginia Surface Mining Reclamation Regulations (WVSMRR)
38 CSR 2-2.47
38 CSR 2-2.63
38 CSR2-5.2, 5.3, 5.4
38 CSR 2-8, 8.a
38 CSR 2-14.5
38CSR2-14.8.a
38CSR2-14.14
38CSR2-14.15.a
1.2 Purpose, Objectives and Applicability
An objective and well-defined method for determining post-mining land configuration is necessary to
assure compliance with applicable laws, provide an opportunity for early coordinated regulatory review,
and allow for meaningful and timely public input and transparent decision-making.
This method is referred to as the "AOC Process" throughout this document.
The AOC Process outlined in this document shall be undertaken for all proposed steep slope surface coal
mining applications. Steep slope operations are all operations where the natural slope of the land within
the permit area exceeds an average of twenty (20) degrees, as measured from the horizontal. The AOC
Process shall be completed before the issuance of a Surface Mining Application (SMA) number by
WVDEP.
Nothing in this AOC Process shall be construed to regulate the surface activity solely associated with
underground mining or coal refuse facilities.
This guidance document has been developed to accomplish the following objectives:
• Provide an objective process for achieving AOC while ensuring stability of backfill material and
minimization of sedimentation to streams.
• Provide an objective process for determining the quantity of excess spoil that may be placed in excess
spoil disposal sites such as valley fills.
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• Optimize the placement of spoil to reduce watershed impacts.
• Provide an objective process for use in permit reviews as well as field inspections during mining and
reclamation phases.
• Maintain the flexibility necessary for the operator to address site-specific mining and reclamation
conditions.
08/07/02 FINAL AGREED VERSION Page 27
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2. AOC and Excess Spoil Quantity Relationship
2.1 Elements of AOC Definition
The following terms are necessary for development of the AOC Process:
A. Configuration: - Configuration relates to the shape of the regraded or reclaimed area. In
addition to complying with the definition of AOC the reclaimed configuration must comply with
performance standards found in WVSCMRA, such as ensuring stability, controlling drainage, and
preventing stream sedimentation.
B. Stability: - Stability relates to the placement of material in the regraded or reclaimed area.
State regulations (see 38 CSR-2-14.8.a. and 14.15.a) require material to be placed in a manner
that achieves a minimum long-term static safety factor, prevents slides, and minimizes erosion.
C. Drainage: - Drainage relates to moving water from and within the regraded or reclaimed area.
Reclaimed drainage configurations must comply with performance standards found in
WVSCMRA, such as minimizing sedimentation, and restoring water quality and quantity.
2.2 Introduction of AOC Model Concept
The AOC Process includes the development a volumetric model referred to as the AOC Model. This
volumetric model provides a definitive and reproducible means to calculate the volumes of material that
can be backfilled or placed in excess spoil disposal areas. The volumes obtained from the AOC Model
are used as a volumetric basis for the actual mine configuration. The actual configuration of the final
mine plan may vary from the AOC Model except as described below.
Portraying these performance standards as variables in a model or formula provides an objective process
for determining what post-mining surface configuration meets the AOC definition, while complying with
the other performance standards in WVSCMRA. The following terms were developed and defined for
use in the AOC Model:
Configuration
OC Volume of material required to replicate the original contours of the undisturbed area proposed to
be mined. OC includes overburden (OB), interburden (IB), and coal in their undisturbed pre-
mining state.
TSM Total spoil material to be handled or available. This material will be classified as either backfill
material (BKF), excess spoil material (ES), or off site disposal material (OSDV)
Performance Standards
SR Backfill volume displaced due to compliance with Stability Requirements.
DR Backfill volume displaced due to compliance with Drainage control Requirements.
SCR Backfill volume displaced due to compliance with Sediment Control Requirements.
AR Backfill volume displaced due to compliance with Access / maintenance Requirements.
MBR Backfill volume displaced due to compliance with the reduction of peak backfill elevation to meet
Maximum Backfill Requirements.
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AOC Volume of backfilled spoil and configuration required to satisfy the definition of Approximate
Original Contour.
This document uses the above acronyms for illustrative purposes only and they are not intended to
represent standard engineering terminology. Instead, they illustrate the AOC Model process, rather than
quantifying each term in the formula. While the terms can be quantified individually, this is not required
by the AOC Model process. Use of the AOC Model results in a theoretical reclamation configuration that
can be quantified.
INSERT GRAPHIC 1
Figure 1: Details Of Backfill Volume Displaced When Complying With Performance
Standards
The following formula determines the amount of backfill that must be returned to the mined area to
satisfy AOC.
OC - (SR + DR + SCR + AR + MBR) = AOC
2.3 Definition of Configuration
2.3.1 Introduction
The following terms are used consistently in the AOC Model to define the condition of the mined area:
2.3.2 Total Spoil Material (TSM)
Total spoil material is all of the overburden and interburden that must be handled as a result of the
proposed mining operation. TSM will either be placed in the mined area, in excess spoil disposal sites
(valley fills), on pre-existing benches or in off-site disposal areas.
TSM volumes are determined by using standard engineering practice, such as average-end area, stage-
volume calculations, or 3-dimensional (3-D) grid subtraction methods. The Secretary must have adequate
information submitted by the applicant to properly evaluate TSM calculations. If the applicant uses an
average-end area method, cross-sections must be supplied for a base line or lines at an interval no less
than every 500 feet or more frequently if the shape of the pre-mined area is highly variable between the
500-foot intervals. If the applicant uses a stage-storage method, planimetered areas should also be
08/07/02 FINAL AGREED VERSION Page 27
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determined on a contour interval (CI) that is representative and reflects any significant changes in slope
(20' CI or less recommended). If a 3-D model is used, the pre-mining contour map and, if possible, a 3-D
model graphic should be provided. The grid node spacings used in generating volumetrics should be
identified. If digital data is used by the applicant, it should be in a format and on a media acceptable to
the Secretary.
TSM is determined by combining the overburden (OB) volume over the uppermost coal seam to be
excavated with the interburden (IB) volumes between the remaining lower coal seams, and then
multiplying this sum by a "bulking" factor (BF). Bulking factors are calculated by a two-step process: 1)
"swell" volume is determined from the amount of expected expansion of previously undisturbed natural
material through the incorporation of air-filled void spaces; 2) "shrink" volume can be calculated from the
amount the swelled material compacts during placement (reducing the void spaces and, consequently, the
volume). Thus, the bulking factor is the swell factor minus the shrink factor, which varies based on the
overburden lithology (e.g., sandstone swells more and shrinks less than shale). The applicant shall clearly
identify the value of BF used. Permit applications that propose a BF greater than 30% shall contain a
justification of the weighted bulking factor utilized-based not only on the weighting of individual swell
factors calculated for each major rock type to be excavated that will be placed in the backfill, but also on
the shrinkage or compaction factor due to spoil placement methods. In equation form:
(OB + IB) x (1 + BF)= TSM
Spoil Placement Areas - There are only three areas that TSM may be placed:
• backfill (BFA)
• excess spoil disposal areas (ESDA), i.e. valley fills.
• off-site disposal areas (OSDA)
BFA Backfill Area (mined area) is the area inside the outcrop of the lowest coal seam mined. (See
Figure 2)
ESDA Excess Spoil Disposal Area. The area outside of the mined area used for placement of excess
spoil. (See Figure 2)
OSDA Off-Site Disposal Areas include but are not limited to:
• unreclaimed mine sites not subject to SMCRA and State mining reclamation laws
that are permitted and bonded by the applicant for spoil disposal
• approved AML or bond forfeiture projects that require such additional spoil to
achieve final reclamation
• existing benches in accordance with 38 CSR-2.14.14.
• previously mined post SMCRA mined areas and excess spoil disposal areas that can
accommodate additional spoil disposal that do not change the toe location. These
areas shall be permitted and bonded by the applicant for spoil disposal.
The volume of spoil placed off-site shall be deducted from the spoil volumes in accordance with Section
4.3.
INSERT GRAPHIC 2
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Figure 2
2.3.3 Original Contour (OC)
The original configuration of the mine area is determined from topographic maps of the proposed permit
area. This configuration is developed through the use of appropriate cross-sections, slope measurements,
and standard engineering procedures. Sufficiently detailed topographic maps, adequate numbers of cross-
sections, or labeled 3-D model grids/graphics should be submitted that illustrate the representative pre-
mine topography and slopes. Digital data should be submitted with the application in a format and on a
media acceptable to the regulatory authority.
2.4 Effect of Performance Standards on Backfill Volume
2.4.1 Introduction
The spoil material displaced due to the performance standards is deducted from configuration volumes.
Each component occupies space in the mined area that could otherwise contain spoil material. The
Secretary shall assure that the AOC Model design includes only necessary and justifiable deductions
based on the following criteria.
2.4.2 Stability Requirements (SR)
The slopes of the spoil material placed in the backfill areas or excess spoil disposal sites must be stable.
Accordingly, the spoil material shall be placed in such a manner as to prevent slides or slope failures and
achieve a minimum, long-term static safety factor of 1.3 for the backfill.
For the purpose of determining the backfill volume for the AOC Model the backfill slopes shall consist of
a 2 horizontal to a 1 vertical (2H: IV) slope between the terraces plus a terrace of twenty feet width
constructed at each one hundred feet vertical rise above the toe of the backfill.
This shall constitute the standard template for defining the backfill volume. If the applicant demonstrates
that the overburden and interburden cannot attain a 1.3 factor of safety at 2:1 slopes, more gentle slopes
may only be justified by the submission of geotechnical test data and stability analyses to the Secretary.
The template only applies to the determination of backfill volumes for the AOC Process. The actual
configuration need not conform to the template or the "AOC Model".
INSERT GRAPHIC 3
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Figure 3
2.4.3 Drainage Control Requirements (DR)
Drainage structures are used to divert or convey surface runoff. For the determination of backfill volumes
for the AOC model, it is assumed that all drainage structures, except for clean water diversion ditches, are
integrated with the sediment control structures.
The integration of the drainage structure with the sediment control structures only apply for the
determination of backfill volumes for the AOC Model and the final design and configuration need not
conform to the AOC Model.
If the applicant proposes a diversion ditch to transport discharge from undisturbed areas, or from drainage
control structures, these structures must be properly designed to provide the required capacity and
designed using standard engineering practices and theory. When reviewing the size and placement of
these structures, the Secretary shall assess the design plans to assure the structures are no larger/wider
than necessary for proper design and comply with standard engineering practices.
The design of the drainage structures only apply for the determination of backfill volumes for the AOC
Model and the final design and configuration need not conform to the AOC Model.
2.4.4 Sediment Control Requirements (SCR)
For the determination of backfill volumes for the AOC Model, the design of the sediment control
structures shall include the drainage structures (except for diversion ditches). It is also assumed that the
sediment control structures are located at the toe of the backfill slopes on the pavement of the primary
mountaintop seam and on the seam mined for contour mining.
For the purpose of the AOC Model the design of the sediment control shall consist of a continuous ditch
around the perimeter of both the primary mountaintop seam and on the lowest seam mined for contour
mining. These structures must have a total design depth (including freeboard) of no less than 3 feet.
These structures must be properly designed to provide the required sediment storage capacity and
designed using standard engineering practices and theory.
When reviewing the size and placement of these structures used in the AOC Model, the Secretary shall
assess the design plans to assure the structures are no larger/wider than necessary for proper design and
comply with standard engineering practices.
The design of the sediment control structures only applies to the determination of backfill volumes for the
AOC Model. The final design and configuration need not conform to the AOC Model.
2.4.5 Access/Maintenance Roads (AR)
For purposes of this AOC Model, the applicant must justify, based on operation specific details, all access
and maintenance road and safety berm widths. Under no circumstances may the road width exceed 25
feet plus a maximum allowance of 10 feet (horizontal) for a safety berm. An allowance for roads shall be
provided for roads located on the primary mountaintop seam outcrop and along the outcrop of the lowest
seam mined for contour mining, or each outcrop for Multiple Contour Operations.
The Secretary shall also assess the road configuration to assure the roads and safety berms are no
larger/wider than necessary.
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The design of the roads only applies to the determination of backfill volumes for the AOC Model. The
final design and configuration need not conform to the AOC Model.
2.4.6 Maximum Backfill Requirements (MBR)
The crest of the backfill ridge must accommodate the mining equipment that transports and places the
spoil but the crest must not be unnecessarily wide. For purposes of this AOC Model, the backfill crest
width shall not exceed 100 feet. The applicant must justify, based on operation specific details, any
backfill crest width in excess of 30 feet.
The AOC Model can create an anomaly when the extent of the mined area is significantly increased due
to contour mining within the perimeter of valley fills. As the total mined area expands, the potential
backfill height increases. In certain instances, the AOC Model generates a peak backfill elevation that is
substantially higher than the surrounding terrain. To avoid this anomaly, an applicant shall not be
required to design backfill higher than the peak pre-mining elevation within the mined area for purposes
of calculating backfill volume and excess spoil volume using this model.
The MBR applies only for the determination of backfill volumes for the AOC Model. The final design
and configuration need not conform to the AOC Model as it does not establish a ceiling elevation above
which no backfill material can or must be placed in the actual Mine Plan. Incorporating the other
components of the AOC definition in the proposed final regrade configuration will prevent the
development of a flat plateau in the Mine Plan.
INSERT GRAPHIC 4
Figure 4. Restoring contours and meeting performance standards
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3. AOC Determination (Mountaintop Mining)
3.1 Introduction
Applying these performance requirements in the mine planning process will determine the amount of total
spoil material that must be retained in the mined area to satisfy the objective criteria for AOC. The
calculations and drawings developed through application of this plan are used to determine the volumetric
components of AOC.
3.2 Backfill Spoil Determination Model
The backfill material that will be placed within the mined area can be backfilled so that the resulting post-
mining configuration closely resembles the pre-mining topography, thus satisfying not only the access,
drainage, sediment, and stability performance standards of SMCRA and WVSCMRA, but also providing
flexibility and meeting the AOC requirements.
Restating the AOC Model from the previous section:
OC - (SR + DR + SCR + AR + MBR)= AOC
Step 1: Determine original or pre-mining configuration Original Contour (OC)
Step 2: Subtract from Original Contour:
Volume displaced due to Stability Requirements (SR)
Volume displaced due to Sediment Control Requirements (SCR) which include
Drainage Requirements (DR) except for clean water diversion ditches, as
defined above
Volume displaced due to Access Requirements (AR)
Volume displaced due to Maximum Backfill Elevation Requirements (MBR)
Step 3: The remaining volume is the initial backfill (IBKF) which is the spoil material placed in
the mined area prior to the placement of any excess spoil areas.
Therefore, the relationship becomes:
IBKF = OC - (SR + DR + SCR + AR + MBR)
3.3 Excess Spoil Determination
The parameters used in the AOC Model for determining the TSM also are used to determine the quantity
of excess spoil. This approach provides an objective process for determining what is excess spoil (ES).
The additional terms and concepts used are:
IBKF Volume of backfill or spoil material placed in the mined area prior to the placement of
any excess spoil areas
ES Volume of excess spoil remaining after satisfying AOC by backfilling and grading to
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meet SR, DR, SCR, AR, MBR
OSDV Volume of spoil material placed in an approved off-site location
The ES quantity, as determined by the following formula, is obtained by complying with the stability
standards and other performance standards.
The excess spoil relationships:
ES = TSM - IBKF
Therefore:
ES = TSM - (OC - (SR + DR + SCR + AR + MBR))
3.4 Adjustment to ES and BKF to reflect Off Site Disposal
Operations may use adjacent pre-existing benches (without coal removal occurring) as part of the
permitted area for excess spoil disposal. If pre-existing benches are to be used as excess spoil disposal
sites, the capacity of each pre-existing bench area must be calculated.
Additional off-site material disposal locations include Abandoned Mine Land (AML) sites, Bond
Forfeiture sites and civil works projects approved by the Secretary.
Excess spoil may be placed on adjacent, post SMCRA, mine sites that have suitable locations for spoil
disposal. Any such areas used for spoil disposal must be appropriately permitted and bonded.
The total quantity of off-site disposal volume (OSDV) shall be calculated and details shall be provided to
the Secretary. The information submitted shall be sufficient to allow the Secretary to review the
adequacy of calculation.
As an incentive to use previously disturbed areas, the quantity of off-site disposal OSDV shall be
deducted from the Total Spoil Material (TSM), resulting in a reduction in both the Excess Spoil (ES) and
the Initial Backfill (IBKF). The allocation of this volume shall be based on the ratio of Excess Spoil (ES)
to Total Spoil (TSM).
The deduction decreases the volume of Total Spoil Material; therefore, the new value for Total Spoil
Material (TSMN) is defined as:
TSMN= TSM-OSDV
The new value for the Excess Spoil volume (ESN) shall be defined as:
ESN= ES - (OSDV x (ES/TSM))
The new value for the Backfill volume (IBKFN) shall be defined as:
IBKFN= IBKF - (OSDV x (1 - (ES/TSM)))
If the applicant intends to use off-site disposal areas, all subsequent references in this document to ES and
IBKF shall be replaced with ESNand IBKFN.
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3.5 Additional Backfill Capacity Required by AOC Model
The AOC Model requires that the excess spoil disposal fill is raised to an elevation above the lowest seam
to be mined. The backfill slope must start at the vertical projection of the outcrop of the lowest seam
being mined. The toe of the slope may be set back from the vertical projection of the lowest seam by a
distance equal to the width of the sediment requirements (SR) plus the drainage requirements (DR). For
the purpose of the AOC Model the access roads shall be located on the excess spoil disposal area.
This concept determines the demarcation between the backfill area (BFA) and the excess spoil disposal
area (ESDA). (See Figure 6) This demarcation can be used consistently in any steep slope mining
situation, and is determined using the following process:
• Locate the outcrop of the lowest seam being mined within each excess spoil disposal area, whether
contour cut only or removal of the entire seam. (See Figure 6)
• Project a vertical line upward beyond the crest of the fill and backfill elevations (See Figure 7).
• The area where coal removal occurs, to one side of this line, is backfill area (BFA); and, the area on
the other side of the line, including the valley bottom, is excess spoil disposal area (ESDA) (see
Figure 7).
The initial volume of material placed on the mined area with no influence of any valley fills shall be
referred to as the Initial Backfill (IBKF).
The revised location of the toe of the backfill slope to the BFA / ESDA demarcation line, as a result of
the construction of an excess spoil disposal facility, results in additional backfill volume. This is referred
to as Additional Backfill (ABKF.)
The total volume of backfill material (BKF) placed in the backfill area (BFA) consists of the initial
backfill (IBKF) plus the additional backfill (ABKF). Therefore:
BKF = IBKF + ABKF
The volume of excess spoil remaining after deducting the total backfill volume shall be placed in an
excess spoil disposal facility. This volume of material is the Excess Spoil Disposal Volume (ESDV).
Establishing this boundary between excess spoil areas and backfill areas is the same procedure used in
determining where permanent diversion ditches must be located.
INSERT GRAPHIC 5
Section 6 and Section 7 of this guidance document contains an optimization procedure for mountaintop
mining and contour mining respectively, for excess spoil disposal plans. Successful optimization is
attained through elevating excess spoil fills to a target height above the mined area, thus converting a
portion of Initial Excess Spoil (IES) to additional backfill volume (ABKF) and thereby reducing the size
and impact of valley fills.
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3.6 Summary of Volume Allocations
Summarizing the previous terms and relationships, excess spoil is the total spoil produced from mining
the property less the amount that can be backfilled in the mined area:
IES = TSM - IBKF
Through the use of previously mined benches, AML projects, and other off-site disposal sites, the volume
of both Excess Spoil and Backfill may be reduced. As a result of these reductions:
ESN = TSMN - BKFN
If spoil is placed in the mined area, this volume is converted from IES to Additional Backfill volume
(ABKF). The Excess Spoil Disposal Volume (ESDV) is the Initial Excess Spoil (IES) less that volume
converted to backfill as ABKF.
IES = ABKF + ESDV
or
ESDV = IES - ABKF
Resolving the two relations defined above:
TSM - IBKF = ABKF +ESDV
or
TSM = ESDV + (IBKF + ABKF)
INSERT GRAPHIC 6
3.7 Isolated Coal Seams
After designing the optimized mine plan and spoil disposal plan, excess spoil disposal areas may cover
coal seams that will be rendered unminable once the fill is placed. Therefore, treatment of contour mining
in such seams as ordinary "mined area" under this model may create a disincentive to the recovery of that
coal.
In order to allow the extraction of coal that would otherwise be lost, the applicant may submit a request to
designate a contour-mined seam as "isolated". The Secretary may designate a contour-mined seam as an
"isolated coal seam" only if:
• the "isolated coal seam" is mined only within the excess spoil disposal areas
• that this "isolated coal seam" may not be added to the permit by revision or amendment or be
included in an adjacent permit
• no additional excess spoil disposal area may be permitted to accommodate spoil from future mining
of the "isolated coal seam"
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• the mineral removal area associated with the "isolated coal seam" contouring is not contiguous to the
primary mountaintop seam mineral removal area or to mineral removal areas related to other
contiguous contouring
• the "isolated coal seam" area could not reasonably be extended to become contiguous to the
mountaintop mined mineral removal area
In no event shall a contour mined area where the top of the highwall extends to within 50 feet vertically
of the elevation of the primary mountaintop seam be designated as an "isolated coal seam".
The Secretary may determine that the above criteria is satisfied and that, based on documentation
provided by the applicant only if this "isolated coal seam" could not be feasibly mined as an independent
or "stand-alone" operation. The mined areas of the "isolated" coal seam shall not be used to define the
lowest seam mined for demarcation between the ESDA and BFA.
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4. Excess Spoil Disposal Area Definition
4.1 Introduction
A standardized approaches for characterizing excess spoil disposal sites allows consistent and
reproducible analysis and calculation of both the Excess Spoil Disposal Volume (ESDV) and the
Additional Backfill (ABKF) volume resultant from the construction of excess spoil disposal site(s).
The calculations defined in this section are used for the excess spoil disposal optimization process
discussed in of this document.
4.2 Equivalent Swell Height
The equivalent swell height, in feet, (ESH) is calculated by dividing the total spoil material (TSM) (in
bank cubic feet) by the mineral extraction area, in square feet, (also termed Backfill Area BFA), and then
multiplying that value by the determined bulking factor (BF) as utilized by the applicant in the AOC
Model.
ESH = (TSM / BFA) x BF
For example, a bulking factor of 25% shall be expressed as 0.25 in this relationship.
4.3 Target Fill Elevation
The target fill elevation for each valley fill is defined as the sum of the average elevation of the outcrop of
the primary mountaintop seam within each valley selected for fill placement, plus the ESH. To simplify
volume calculations and solely for calculation, each excess spoil disposal area shall be assumed to have a
horizontal top surface.
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5. Excess Spoil Disposal Optimization (Mountaintop Mining)
5.1 Introduction
The procedure described in this section applies only to those watersheds in which mountaintop mining is
proposed. If mountaintop mining is not proposed in a specific watershed but other mining types (e.g.
contouring) are to be used, the excess spoil optimization procedure specific to those mining types shall be
employed for any fill within that watershed.
5.2 Spoil Disposal Plan Approval
An application for a mountaintop surface mine permit shall be deemed to have an optimized spoil
disposal plan only if the:
• plan satisfies the Presumed Criteria Test, or
• total non-mineral removal area affected by valley fills does not exceed the "Excess Spoil Disposal
Area Bank" (ESDA Bank) plus the Acreage Tolerance
Under unusual circumstances the AOC / Fill Optimization Panel may approve exceptions to fill
optimization as described in Section 8 of this guidance document. Mining operations receiving such
approved exceptions do not have optimized spoil placement plans.
If an applicant is seeking an AOC variance, the applicant must follow the appropriate procedures
described in Section 9.2 of this guidance document.
5.3 Presumed Criteria Test
The proposed excess spoil disposal plan in the AOC Model shall be presumed to be optimized if it meets
the Presumed Criteria Test. The excess spoil disposal plan is optimized with regard to spoil disposal and
the disturbed area associated with valley fills when every proposed valley in the AOC Model achieves the
"target fill elevation." This design approach establishes the toe of each valley fill.
Calculation of the "presumed criteria" valley fill toes shall comply with the following steps:
Step 1 Select the valleys to be considered or qualified for excess spoil disposal.
Step 2 Determine the maximum downstream toe location to be considered for each valley fill.
Environmental factors, statute, rules, property rights, operational issues, and other factors
will influence this location.
Step 3 Define the value for Excess Spoil (ES) based on backfilling with no valley fills. The
initial backfill volume (IBKF) will be determined using the AOC Model.
Step 4 Define the "equivalent swell height" (ESH)
Step 5 Define the average elevation of the primary mountaintop seam, upstream of the
maximum downstream toe (as defined in Step (2) in each valley selected for the
placement of excess spoil
Step 6 Determine the Target Fill Elevation (TFE) for the top of each excess spoil disposal
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structure. The TFE is the average elevation of the primary mountaintop seam plus the
equivalent swell height as defined in Step 4
Step 7 Draw a profile along each valley to be filled from the top of the backfill (from the first
iteration of the AOC Model) to the logical toe. The baselines should be oriented
perpendicular to the face of the anticipated valley fills at their logical toe
Step 8 Locate the toe for the Initial Increment for each fill. The toe location for the Initial
Increment shall be the lowest stratigraphically of either:
• the most upstream toe that complies with the geotechnical stability
requirements defined by the regulations
• 50 horizontal feet downstream of the outcrop of the lowest seam to be mined
Step 9 Calculate the excess spoil disposal volume (ESDV) and the additional backfill volumes
(ABKF) associated with the Initial Increment. For this optimization model only, assume
a constant valley fill front face slope for all valley fills and all "slices" of 2 Ah: Iv.
Step 10 Separate the remaining portions of all of the selected fills into equal length increments
referred to as "slices" (these slices are perpendicular to the baseline constructed in Step
7). These "slices" shall extend from the Initial Increment all the way along the profile to
the toe selected in Step 2. The slice length along the profile shall be selected by the
applicant but may be no greater than 500 feet. The slice length shall be consistent for all
fills and all slices.
Step 11 Calculate the excess spoil disposal volume (ESDV) and the additional backfill volume
(ABKF) associated with each "slice". As in Step 9, these volumes include the additional
backfill volumes defined by the AOC Process.
Step 12 Develop a matrix indicating the volume of excess spoil disposal volume (ESDV) and
additional backfill volume (ABKF) for each Initial Increment plus each of the "slices" for
each valley fill under consideration.
Step 13 Determine the volume of ES to be allocated to each fill and then select the applicable
number of slices to accommodate those volumes. The ES per fill will occur as both
ESDV and ABKF; i.e., the volume of additional backfill created by the fill must be
considered along with the excess spoil disposal volume.
Step 14 For the combination of the ESDV and ABKF required to contain the ES volume,
establish the toe location for each fill.
Step 15 Design the mine and spoil areas in any sequence or configuration as long as the toe
located in Step 8 does not move downstream and the design complies with Section 9.1 of
this document.
Step 16 Document compliance with the above criteria by preparing and submitting as part of the
surface mine application details of each valley fill model developed in Step 7. Each
model shall include a plan view and profile view at a scale of 1"=200' (or as otherwise
approved) and appropriate engineering calculations.
Positive Determination — If the proposed toe location for each valley fill is maintained at or upstream
of the toe location established for each valley fill in accordance with the above AOC Model procedure,
the Secretary shall find that the Excess Spoil Disposal Area ("ESDA") has been optimized.
Negative Determination - If any of the proposed valley fills have a toe location that does not permit the
fill to meet the Presumed Criteria Test as described, the Secretary shall notify the applicant that it must
submit calculations to define the ESDA Bank.
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5.4 "ESDA Bank" Analysis
If the proposed excess spoil disposal plan does not achieve a positive determination under the Presumed
Criteria Test, the excess spoil disposal plan will be evaluated using the ESDA Bank analysis. This
analysis employs the procedures defined in the preceding sections of the AOC Model except that the crest
elevation of each fill is fixed to calculate the ESDA Bank.
This procedure provides a standardized means of comparing and rating available excess spoil disposal
sites to achieve the most efficient placement of the excess spoil. Each fill is evaluated to determine its
spoil disposal capacity per specified length of valley. The total volume of excess spoil is then assigned to
the fills in descending order based on each fill's relative "efficiency." The result will be the optimum
placement of spoil in terms of cubic yards per acre of ESDA.
Calculation of the ESDA Bank shall comply with the following steps:
Step 1 Define the primary mountaintop mining seam. This is the lowest seam within each
proposed valley fill site that is being mountaintop mined
Step 2 Select the valleys to be considered or qualified for excess spoil disposal
Step 3 Determine the maximum downstream toe location to be considered for each valley fill.
Environmental factors, statutes, rules, property rights, operational issues, and other
factors will influence this location
Step 4 Define the value for Excess Spoil (ES) based on backfilling with no valley fills. The
backfill volume (IBKF) will be determined using the AOC Model
Step 5 Define the "equivalent swell height. "(ESH)
Step 6 Determine the Target Fill Elevation (TFE) for each excess spoil disposal structure. The
TFE is the average elevation of the primary mountaintop seam plus the equivalent swell
height as defined in Step 5
Step 7 Construct a straight baseline from the logical toe to the top of backfill (IBKF) generally
along the centerline of each valley to be filled. The baselines should be oriented
perpendicular to the face of the anticipated valley fills at their logical toe. Draw a profile
along the baseline for each valley to be filled from the top of the initial backfill.
Step 8 Locate the toe for the Initial Increment for each fill. The toe location for the Initial
Increment shall be the lowest stratigraphically of either:
• the most upstream toe that complies with the geotechnical stability
requirements defined by the regulations, or
• 50 horizontal feet downstream of the outcrop of the lowest seam to be mined
Step 9 Calculate the excess spoil disposal volume (ESDV) and the additional backfill volumes
(ABKF) associated with the Initial Increment. For this optimization model only, assume
a constant valley fill front face slope for all valley fills and all "slices" of 2 Ah: Iv.
Step 10 Separate the remaining portions of all of the selected fills into equal length increments
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referred to as "slices" (these slices are perpendicular to the baseline constructed in Step
7). These "slices" shall extend from the Initial Increment all the way along the profile to
the toe selected in Step 2. The slice length along the profile shall be selected by the
applicant but may be no greater than 500 feet. The slice length shall be consistent for all
fills and all slices.
Step 11 Calculate the excess spoil disposal volume (ESDV) and the additional backfill volume
(ABKF) associated with each "slice". As in Step 9, these volumes include the additional
backfill volumes defined by the AOC Process.
Step 12 Develop a matrix indicating the volume of excess spoil disposal volume (ESDV) and
additional backfill volume (ABKF) for each Initial Increment plus each of the "slices" for
each valley fill under consideration.
Step 13 Calculate the optimum configuration of fill "slices." This optimization shall be based on
the sequential inclusion of each Initial Increment for the valley fills under consideration.
The selection process shall continue until the excess spoil volume (including additional
backfill volume) equals the Excess Spoil (ES). If the sum of all the initial increments
equals or exceeds the ES volume proceed to Step 16.
Step 14 If the volume of all of the Initial Increments does not meet the ES volume, sequentially
include the increment with the greatest volume (excess spoil disposal volume (ESDV)
plus additional backfill volume (ABKF)). Continue to select the "slice" with the next
highest volume (naturally each fill must be selected in logical order). The selection
process shall continue until the excess spoil volume (including additional backfill
volume) equals the Excess Spoil (ES).
Step 15 If sufficient disposal volume is not available within the defined logical toes, the elevation
of the valley fill surface shall be increased, and the iterations run again, thus creating
further ESDV and ABKF.
Step 16 For the combination of the "Initial Increments" and "slices" required to contain the ES
volume, determine the total area used for excess spoil. This area is referred to as the
ESDA Bank. The ESDA Bank shall be the planimetric area of the excess spoil disposal
area portion of the valley fill. (i.e. the area outside the mined area but contained by the
fill between the toe and the outcrop of the lowest seam mined.)
Step 17 Develop the Mine Plan in any sequence or configuration as long as the area used for
excess spoil disposal does not exceed the ESDA Bank plus the specified acreage
tolerance. The only limitation on the design is that it must comply with Section 9.1.
Step 18 After the applicant has defined the excess spoil disposal areas for the Mine Plan, the total
area utilized for excess spoil under this configuration (Proposed Excess Spoil Disposal
Area) shall be compared to the optimum excess spoil disposal area (ESDA Bank.)
Acreage Tolerance: An acreage tolerance factor shall be applied to the ESDA Bank. The Acreage
Tolerance shall be ten percent (10%) of the area below the outcrop of the primary mountaintop seam but
contained within the valley fill footprints.
Positive Determination - The Secretary shall find that the Proposed Excess Spoil Disposal Area has been
optimized and permit review may proceed if the proposed excess spoil disposal area for the entire permit
area does not exceed the ESDA Bank plus the Acreage Tolerance.
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Negative Determination - If the application does not meet the above criteria, the Secretary shall issue a
written "notice of negative excess spoil optimization" to the applicant and the permit application shall be
submitted to an independent AOC / Fill Optimization Panel for consideration. Mining operations that
receive a negative determination do not have an optimized spoil disposal plan.
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6. AOC Determination (Contour Mining)
To be Completed
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7. Excess Spoil Disposal Optimization (Contour Mining)
To be Completed
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8. AOC / Fill Optimization Panel
In accordance with procedures described in Section 5 and Section 7 of this AOC Model, the Secretary
shall promptly notify an applicant when an application does not comply with the spoil optimization
guidelines. Upon receipt of a "notice of negative excess spoil optimization" the applicant may:
• Withdraw the permit application
• Revise the permit application to request an AOC variance
• Revise the permit configuration in order to meet the excess spoil optimization criteria, or
• Submit the excess spoil handling plan to the "AOC / Fill Optimization Practices Advisory Panel" (the
"Panel") for evaluation.
If the applicant submits the excess spoil handling plan to the Panel for evaluation, the Secretary shall
convene the Panel.
Following submittal of the excess spoil handling plan to the Panel, the applicant shall provide detailed
plans and calculations clearly stating why it believes the proposed permit configuration cannot be
optimized. Throughout the process, the burden of proof will remain on the applicant to justify its
proposal.
The Panel shall be comprised of, an appointee of Mountain State Justice, Inc. or its assigns, an appointee
jointly made by the West Virginia Coal Association and West Virginia Mining and Reclamation
Association, or its assigns, and a neutral member jointly selected by those panel members. The State will
pay reasonable hourly rates and expenses for panel members within the 60 calendar days of submission of
invoice.
The appointees must have a degree in Mining Engineering or Civil Engineering. The members need not
be registered professional engineers. The appointees may have no interest, financial or otherwise, in the
surface mining permit under review. If a conflict of interest arises, the panel member with the conflict
shall be replaced by an alternate appointed by the appropriate party.
A Panel meeting shall be scheduled and convened within twenty-one (21) days of the submittal of the
required information to WVDEP, as determined by the Secretary. The Panel shall hear the applicant's
argument in support of its plan. Following the meeting of the Panel, the Panel shall issue a written
recommendation within fifteen (15) days of the completion of the hearing. An exception to optimization
may be recommended only after the Panel makes specific and detailed findings that there is no reasonable
alternative to the exception. A majority vote of the Panel shall constitute a decision.
The "ESDA Limit" is the sum of ESDA Bank and the Acreage Tolerance, as established in Section 5.4.
For Mountaintop Mining the Panel may recommend by majority vote an exception of up to 10% greater
than the "ESDA Limit". When this occurs the fill placement is not optimized.
The Secretary shall not be bound by the recommendation of the Panel. However, if the Secretary does
not follow the recommendation of the Panel, the Secretary shall make written findings justifying his
decision. In no event however may The Secretary approve an AOC compliant plan for Mountaintop
Mining that is more than 10% greater than the "ESDA Limit."
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9. AOC Compliance / AOC Variance Requests
9.1 AOC Compliance Determination
This AOC Process provides an objective means of assessing compliance with AOC specifically for steep-
slope mining applications.
The "AOC Model" determined by the application of design components generates a volumetric
determination of AOC. The AOC Process does not require that the Mine Plan matches the configuration
of the "volumetric AOC Model".
The applicant shall submit detailed plans, cross sections and calculations as part of the permit application
to define the Mine Plan. This documentation shall provide a clear indication to the Secretary relating to
compliance with the tests detailed below. In addition, the documentation shall include the final
reclamation plan, which clearly indicates the proposed post mining configuration.
The Secretary has the authority to determine that the final reclamation plan is not compliant with the
AOC, even if is compliant with the volumetric requirements of the AOC Process (e.g. that it does not
satisfy the aesthetic components of AOC). In addition, the Secretary shall assure that the final
reclamation plan conforms to the following tests.
• Backfill Volume: The quantity of spoil material to be returned to the mined area (BKF) (or BKFN if
applicable) is calculated in Section 3.4. The final spoil balance and regrade design must demonstrate
that at a minimum this volume of spoil to be placed as backfill in the Mine Plan.
• Valley Fill Design: The spoil optimization procedures in this AOC Process establish the maximum
downstream toe location for each valley fill. Those maximum downstream locations must not be
exceeded in the final Mine Plan.
• Backfill Configuration: Strict adherence to the "volumetric AOC Model" will often result in a
reclaimed site that appears rigidly uniform and artificial. Therefore, applicants shall develop and
submit as part of the permit application regrade plans that address aesthetic values along with
engineering issues. This can be accomplished through the incorporation of landforms and other
creative types of landscaping. However, the applicant must comply with certain objective
configuration criteria that are established by this AOC Process.
• Watershed Pattern: The final "volumetric AOC Model" will create a readily identifiable ridge
system separating the regraded site into discrete watersheds. This general watershed pattern must
be maintained in the final Mine Plan. In those areas where the MBR constraint affects the AOC
Model, a series of subwatersheds that reflect the pre-mining watershed system are to be
established in the Mine Plan
• Backfill Inflection Points: A boundary is established in the AOC Model between the backfill
slopes and the generally level or moderately sloped areas used for access, drainage features, and
sediment control. This boundary is the demarcation between the Backfill Area (BFA) and the
Excess Spoil Disposal Area (ESDA). To maintain the general configuration generated by the
"volumetric AOC Model", this boundary is to be preserved in its approximate location in the final
mine plan. Approximate is defined as being within 100 feet of the location of the BFA / ESDA
boundary as defined in this AOC Process. Variations in elevation are allowable to promote
drainage and to provide flexibility in shaping the final regraded configuration as defined in the
Mine Plan.
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• Final Pit: It is recognized that it is not practical to fully restore the final pit area to the
configuration developed by the AOC Model due to the lack of available material. The inability to
meet the ideal configuration shall not require an AOC variance, if the applicant can demonstrate
in the Mine Plan that it has adequately addressed the issue of final pit reclamation through
measures such as downsizing the active pit as mining draws to a close. However, the final pit
regrade shall conform to the watershed pattern requirement and shall not result in any change to
the quantity of BKF placed in the mined area.
These criteria will provide the regulatory authority with an objective, quantifiable means of assessing the
Mine Plan's compliance with the approximate original contour requirements. For purposes of
incorporating environmental enhancements into the final reclaimed configuration, the Secretary may
allow a adjustment to the Backfill Volume test so that up to ten percent (10%) of BKF may be converted
to ESDV, provided that the toe of each optimized valley fill shall not be moved downstream.
This adjustment is granted to encourage stream restoration projects, wetlands development, and similar
aquatic habitat projects. The applicant is encouraged to restore streams by configuring the fills so that
there is a positive grade from one side of the fill to the other so that the lower side of the fill intercepts the
down dip pavement of the primary mining seam.
9.2 AOC Variance Request Evaluation
When an applicant applies for an AOC variance for a mountaintop surface mine, the applicant shall
include a complete excess spoil-handling plan that includes excess spoil optimization in compliance with
the AOC Process. This plan shall be based on returning the mined area fully to AOC and shall include all
calculations and other details needed to establish the ESDA Bank (AOC) without the AOC variance.
The ESDA Bank procedure shall be repeated using the proposed alternate post-mining configuration
instead of the AOC configuration to determine the corresponding Alternate ESDA Bank acreage. The
applicant shall present both analyses in a clear and organized manner, complete with all supporting
documentation. All variance requests shall indicate the additional excess spoil disposal area in excess of
that required to achieve AOC. This additional area is the difference between the Alternate ESDA Bank
and the ESDA Bank (AOC).
This procedure will provide the Secretary a quantifiable means of evaluating the impact of the alternate
post-mining configuration versus the projected impacts if the site were returned to AOC by providing a
specific additional acreage resulting from that variance request.
Any spoil disposal plan for which the Alternate ESDA Bank is greater than the ESDA Bank (AOC)
shall not be considered optimized.
08/07/02 FINAL AGREED VERSION Page 27
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10. Permit Revisions and Amendments
10.1 Mine Plan Revisions
The optimization of the excess spoil disposal area, as defined in Section 5 and 7, for a particular permit
remains valid only if the operation is in compliance with its approved mine plan.
The operator shall submit to the Secretary a semi-annual report certified by a Professional Engineer
registered in West Virginia, that the operation is in compliance with its spoil handling plan and that the
operation can maintain the excess spoil optimization plan as included in the permit.
The Secretary shall require a permit revision prior to the operator implementing any material changes in
the mine operation and mine plan. The operator must justify in the semi-annual report why any changes
are necessary. A material change is defined as any change that is greater than 5%. Changes include
• the volume of overburden generated
• the quantity of coal to be mined
• the spoil balance
• change the final regrade configuration so it does not comply with Section 9.1
• increase the ESDV
• move the toe of any valley fill downstream
• impact the approved excess spoil optimization plan
An operator who places spoil under a non-compliant spoil handling plan shall be deemed to be in serious
violation of its permit. The Secretary shall deem this as significant imminent environmental harm to land
and water resources and a cessation order shall be issued pursuant to 38 C.S.R. 2-20.3.a. 1.
The permit revision shall include the following:
• A description of the proposed change to the mine plan
• A revised and updated material balance
• The status of each valley fill, particularly those completed or in progress
• An updated AOC Process
• A revised excess spoil optimization evaluation
If using the ESDA Bank method, the volume of spoil already placed in any valley fill must be addressed
prior to completing the optimization process for any permit revision. This shall be done by determining
the minimum configuration of each fill that can accommodate the volume of material already placed, then
deducting the corresponding existing excess spoil disposal area from the calculated optimum before the
remaining area is reallocated.
10.2 Permit Amendments to add Mineral extraction
Mineral removal area added to an existing permit affects the material balance and consequently will
impact the excess spoil optimization plan.
08/07/02 FINAL AGREED VERSION Page 27
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Should the Secretary determine that the change to the spoil balance may have a significant effect on the
spoil optimization plan, the permittee shall be required to include an updated excess spoil optimization
plan. Significance is defined as increasing the ESDV by greater than 5%, or moving the toe of any valley
fill downstream.
If significant the permit amendment application shall include the following:
• A revised and updated material balance for the entire permit area
• The status of each valley fill, particularly those completed or in progress
• An updated AOC model that incorporates the amended permit area
• A revised excess spoil optimization evaluation for the total permit area
If using the ESDA Bank method, the volume of spoil already placed in any valley fill must be addressed
prior to completing the optimization process for the amendment. This shall be done by determining the
minimum configuration of each fill that can accommodate the volume of material already placed, then
deducting the corresponding existing excess spoil disposal area from the calculated optimum before the
remaining area is reallocated.
10.3 Adjacent Permits or Permit Amendments
The objective of this section is to ensure that segmented permitting actions such as a "string of pearls" is
not used to evade the intent of spoil optimization.
If an application for a permit by an operator is adjacent to or contiguous with another active permit or
permits controlled or operated by that operator, then the Secretary shall consider the operation as a "total
operation" if:
• Excess spoil disposal areas on the permit under consideration receive spoil from more than one
permit, or
• The post mining contours at the boundary between the permits are different from the pre-mining
contours. This means that if the regrade at the permit boundary continues between the two permits
and is continuous and different from the pre-mining elevation
• The operation does not have total independent utility, including sediment control structures and
access roads
If a permit is part of a "total operation" then the application shall meet the requirements of the AOC
Model for the "total operation" including the new permit under consideration. The AOC Model shall
consider the total volumes in the operation and shall either:
• Ensure that all fills meet the presumed criteria test, or
• Use the ESDA Bank analysis. In using the ESDA Bank any existing fills on the "total operation"
shall be deducted from the ESDA Bank before reallocation of any residual ESDA.
Nothing in this section shall be construed to limit Off Site Disposal Areas (OSDA).
08/07/02 FINAL AGREED VERSION Page 27
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ENGINEERING PROCEDURE 2.1
STEEP SLOPE MINING: AOC and EXCESS SPOIL DETERMINATION
I. Introduction and Purpose:
This procedure applies to steep slope mining operations that remove all or a large portion of the
coal seam or seams running through the upper fractions of a mountain and propose to return the
site to AOC. Such operations include mountaintop removal mines with variances from AOC,
contour mines, and mountaintop mines. Many variables, such as stability requirements, drainage
requirements, and sediment control requirements, affect or determine the postmining surface
configuration or shape of the land at a steep slope surface coal mining operation proposing to
return the site to AOC. Incorporating compliance with these performance standards into the
proposed permit application requires the applicant to carefully plan the mining and reclamation
phases of the proposed surface coal mining operation. This process includes, among other
requirements, plans showing: pre-mining contour maps; post-mining contour maps; cross-
sections and profiles; spoil volume calculations; drainage structure designs; sediment control
structure designs; access road designs (if justified); spoil placement sequences; and excess spoil
determinations and calculations.
II. Policy and Procedure - Mountaintop AOC Mines:
Determining AOC Configuration:
Sufficiently detailed topographic maps, adequate numbers of cross-sections, or labeled 3-D
model grids/graphics should be submitted that illustrate the representative pre-mine topography
and slopes of the proposed permit area. Digital data should be submitted with the application in
a format and on a media acceptable to the Knoxville Field Office (KFO).
After determining the premining configuration, the foundation for backfilling and grading is
determined. The foundation is the bench that will be the starting point for placing spoil material
in the mined out area to achieve AOC (see Figures 1 and 2).
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2000
1 8OO
1 6OO
1 4OO
1 2OO
1 OOO
Interburden;—
Coal Seams
//
Figure 1. Pre-mining configuration
2OOO
1 aoo
1 600
1 4OO
1 200
1 OOO
Undisturbed Area
Mountaintop Bench
Contour Bench
Figure 2. Foundation for backfilling and grading
From this starting point the configuration of the backfill is determined, allowing for stability
requirements, drainage requirements, and sediment control requirements. Following is a
discussion of how these requirements must be considered when determining the AOC
configuration.
Stability Requirements - Spoil must be placed in the mined out area in a manner that will result
in a 1.3 static safety factor.
Grading the backfill slopes (between the terraces) on a 2 horizontal to a 1 vertical ratio (2H: IV)
and placing terraces, where appropriate, is a generally acceptable practice, unless it results in a
safety factor of less than 1.3. Placing spoil on slopes steeper than 2H: IV is theoretically
possible, but MSHA recommends that slopes not be greater (steeper) than 2H: IV, because that
is the maximum safe slope for operation of tracked-equipment.
If the pre-mining slopes are less than 2H: IV (26.6°), the backfill slopes may be graded to match
the pre-mining slope. In this case the backfill slopes must be at least as steep as the pre-mining
slope unless the 1.3 factor of safety cannot be obtained. Steeper slopes are acceptable if stability
is demonstrated.
The top of the backfill can be no wider than is necessary for safely negotiating the largest
reclamation equipment utilized for the mine site. Areas larger than necessary to work this
equipment would need to be approved by KFO.
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Drainage Control Requirements - Drainage control may be allowed at the toe of the outslope.
Erosion control measures may be incorporated by providing twenty feet wide terraces every fifty
feet in vertical height. The size and location of these structures necessarily reduce backfill spoil
volume because of the flat area required to properly construct effective structures and meet
drainage requirements.
Sediment Control Requirements - As with drainage structures, the size and location of sediment
structures dictate the amount of flat area that will displace backfill spoil storage. When
reviewing the size and placement of these structures for adequacy in meeting effluent and
drainage control requirements, KFO will also assess the design plans to assure the structures are
no larger/wider than needed for proper design.
Access/Maintenance Roads - These structures are often necessary to gain access to sediment
control structures and reclamation areas. The size and location of these roads or benches will
vary throughout the minesite and should be based on documented need. If, for example, the road
purpose is for cleaning sediment structures, it will be a different size than a road used for main
terrace access. KFO will evaluate the necessity for roads in the final reclamation configuration
and approve only those widths necessary. Typically, a twenty feet wide access road is
acceptable.
Typical Backfill Configuration - The backfill slope, associated terraces, drainage conveyances,
and access roads will determine the ultimate backfill height for the mined area.
This final elevation may be lower than the pre-mining elevation, approximate the pre-mining
elevation, or exceed the pre-mining elevation. Applying these performance requirements in the
mine planning process will determine the amount of total spoil material which must be retained
in the mined out area. The resultant post-mining configuration should closely resemble the pre-
mining topography, thus satisfying not only the access, drainage, sediment, and stability
performance standards of SMCRA, but AOC as well, (see Figure 3).
MSHABerm Terrace //^2h
Sediment/ ^^^\
Drainage Ditch /^ L-20'-l
Access -^ Backfill Area
Road / /-" 2h
Mine Bench
Figure 3. Typical backfill outslope configuration
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As can be seen in Figure 4, this reclamation technique results in a configuration or shape that
closely resembles the pre-mining configuration.
1200
1000
Mountaintop bench
n • * u A ™- u urn Pre-mme topography
Pre-mme topography AOC backfill
Contour bench
Figure 4
Determining Spoil Volumes:
Total Spoil Material:
Total spoil material is all overburden handled as a result of the
proposed mining operation. The applicant must place total spoil material either in the mined area
or in excess spoil disposal sites (valley fills or pre-existing benches). Total spoil material is
determined by combining the overburden (OB) volume over the uppermost coal seam to be
excavated with the interburden (IB) volumes between the remaining lower coal seams. This
value is typically expressed as bank cubic yards (bey).
Total spoil material volumes are determined by using standard engineering practices, such as
average-end area, stage-volume calculations, or 3-dimensional (3-D) grid subtraction methods.
KFO must have adequate information from the applicant to properly evaluate spoil volume
calculations. If the applicant utilizes an average-end area method, cross-sections must be
provided for a base line or lines, at intervals no less than every 500 feet, or more frequently, if
the shape of the pre-mined area is highly variable between the 500-foot intervals. If the
applicant utilizes a stage-storage method, planimetered areas must be provided on a contour
interval that is representative and reflects any significant changes in slope (20' or less contour
interval recommended). If a 3-D model is used, the applicant should provide a pre-mining
contour map and, if possible, a 3-D model graphic. The applicant should identify the grid node
spacings used in generating volumetrics. If the applicant utilizes digital data, it should be in a
format and on a media acceptable to KFO.
Total spoil volume (TSV) is determined by calculating the in-situ overburden and interburden
volume, multiplied by a "bulking" factor (BF). Bulking factors are calculated by a two-step
process: 1) "swell" volume is determined from the amount of expected expansion of in-situ
material through the incorporation of air-filled void spaces; 2) "shrink" volume is calculated
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from the amount the swelled material compacts during placement (reducing the void spaces and,
consequently, the volume). Thus, the bulking factor is the swell factor minus the shrink factor,
which varies, based on the overburden lithology (e.g., sandstone swells more and shrinks less
than shales). Total spoil volume is reported in cubic yards (cy), in the following equation form:
(OB + IB) x BF = TSV
For example, if the in-situ volume of overburden material is 300,000 bey, the interburden
volume is 700,000 bey, and the weighted bulking factor is 125%, TSV would be determined as
follows:
(OB + IB) x BF = TSV
(300,000 bey + 700,000 bey) x 1.25 = 1,250,000 cy
Spoil Volume Required to Achieve AOC:
The applicant calculates the volume of spoil material required to be returned to the mined out
area based on the configuration of the reclaimed area as determined by considerations for
stability, drainage control, sediment control and access. These volumes are expressed as bulked
volumes.
Excess Spoil Volume:
Spoil material unable to be placed in backfill area is excess spoil, and must be placed in an
approved excess spoil disposal site(s) (see Figure 5). The excess spoil quantity is obtained by
determining the difference in the total spoil volume and the volume required to backfill the
mined area to AOC.
KFO will carefully evaluate the spoil balance information provided in the permit application to
assure that excess spoil volumes are accurate. Permits that propose to conduct mountaintop
mining operations, but change plans due to unanticipated field conditions, should submit permit
revisions containing revised volumetric calculations and excess spoil designs.
Mountaintop bench
Pre-mine topography Pre-mine topography
AOC Backfill ExCeSS Spoil / AOC Backfill
X Disposal Site J^/ Contour bench
Figure 5. Potential excess spoil disposal site
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Excess Spoil Disposal Sites:
Generally the volume of excess spoil, and/or mining logistics, requires more than one excess
spoil disposal site. Typically, in steep-slope regions of Appalachia, excess spoil is placed in
adjacent valleys. In areas where extensive "pre-law" mining has occurred, pre-existing benches
are also used. Performance standards for excess spoil disposal areas are found in 30 CFR
816.71-816.73 and in 30 CFR 816.74 for pre-existing benches.
The most common site selected to place excess spoil is in the adjacent valleys. The permit
application should contain the stage-storage-volume calculation for the valley capacity for
excess spoil storage dependent on toe location and crest (top) elevation.
If the applicant utilizes pre-existing benches as excess spoil disposal sites, he/she must calculate
the capacity of each pre-existing bench area. Typically these calculations utilize the average-end
area method, based on cross-sections representing the site configuration.
The applicant must design excess spoil fills in order to attain a long-term static safety factor of
1.5 and, if a durable rock fill, an earthquake static safety factor of 1.1. The applicant may
propose to construct terraces on the outslopes, where appropriate or required. The grade of the
outslopes, between the terraces, may not exceed 2H: IV. Additionally, where the natural slope in
the disposal area exceeds 36 percent, or such lesser slope as designated by the regulatory
authority, the applicant shall construct keyway cuts or rock toe buttresses to ensure stability of
the fill.
Determining the location of the toe of the fill requires the available backfill and excess spoil
material to balance. After this material balance is achieved, the applicant designs the excess
spoil disposal areas to accommodate this quantity of excess spoil. If the excess spoil disposal
site is a valley fill, this design will determine the height or elevation of the crest of the excess
spoil disposal site or fill. If the top of the fill elevation is above the elevation of the lowest coal
seam mined, as illustrated in Figure 6, then the applicant must reconsider the AOC or backfill
configuration.
Mountaintop bench
Pre-mine topography Pre-mine topography
A0(j backfill ValleyFill /AOC backfill
'"""~"~--^_ \ ^~i ~~-^ Contour bench
Figure 6. Sizing valley fills by material balance
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At this point the applicant must make a second determination of AOC to establish the final
reclamation configuration. Before performing a new AOC determination, the applicant will
determine the interface between the backfill area and the excess spoil disposal area:
Locate the outcrop of the lowest seam being mined
• Project a vertical line upward beyond the crest of the fill as shown in Figure 7.
Backfill in mined area
,/ /
_/ /
,/ /
Pre-mine topography // /
.s I
.S I
AOC backfill // I Pre-mine topography
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Pre-mining topography
2200 -
2000 -
18
1600 -
1400 -
1200 -
1000 -
IstAQCbackfil
Backfill
Excess spoil
2nd AOC backfill
Pre-mining topography
1st AOC backfill
-JL
Figure 8. Second iteration-placement of additional spoil material within the
mined area
Pre-mining Topography
Final Topography
Figure 9. Configuration after AOC process
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III. Policy and Procedure -Contour Mining Operations:
The AOC/excess spoil determination, described earlier, is used to determine AOC and excess
spoil volumes for contour surface mining operation as well.
A contour mine typically takes one (1) contour "cut" and progresses around the coal outcrop,
leaving a highwall and bench after the coal is removed. In reclaiming the site to AOC,
documentation is required showing drainage structure designs, access road requirements, and
properly designed sediment structures. A generally acceptable practice, unless it results in a
static safety factor of less than 1.3, includes grading the backfill slopes (between terraces) on a
2H: IV slope as shown in Figure 3. However, in all cases, the highwall must be eliminated. If
compliance with the other performance standards, i.e., drainage, access, and sediment control,
result in backfill out-slopes being steeper than 2H: IV, the application should contain adequate
documentation that the backfill configuration meets a 1.3 static safety factor. Documentation is
not required where slopes flatter than 2H: IV are proposed.
Whenever contour mining operations encounter long, narrow ridges or points (see Figure 10),
the same principles and performance standards apply, i.e. stability, drainage, sediment control,
and access requirements.
Figure 10
In order to determine the AOC configuration for a finger ridge mining operation, the applicant
must utilize orthogonal cross sections (see Figure 11). A single longitudinal cross section
running down the ridge line and perpendicular to the highwall is not adequate. Additional cross
sections perpendicular to the longitudinal cross section are also required to determine the final
backfill configuration. Often returning these sections to 2H: IV dictates the AOC configuration
and establishes the longitudinal profile (see Figure 11). The applicant must completely eliminate
the highwall.
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Final Grade Premining Grade
1900
1800
-1+00
\ }
v^
^
X^
!x
• »
s*
•^
^K
1+00 3+00 5
14+00
1900
1800
+00
Coal Seam
1 Highwall
Final Grade Premining Grade
2000 \ /
1101
1SOO
^
.X^
x^"^
^~
^~
•^
•^
N^
sN
^^s
^S
2000
1900
1800
1+00 3+00 5+00 7+00
7+00
x Final Grade / Premining Grade
2100
2100
1800
-1+00
1+00 3+00 5+00 7+00 9+00 11+00 13+00 15+00 17+00 19+00 21+00 23+00
Section X-X'
Figure 11
10
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IV. Policy and Procedure - Mining Operations with AOC Variances:
The determination of backfill and excess spoil volumes for mining operations proposing
variances from AOC are performed in essentially the same manner as described in Section III.
The difference in these calculations for AOC variances is that a certain volume of spoil material
becomes excess due to regrading to flat or gently rolling terrain in the process of attaining the
approved post-mining land use (PMLU). For instance, an AOC variance for an industrial area
would require only that amount of backfilling in the mined area necessary for drainage controls
or buried utilities for water and sewer lines. The mining plan would show the post-mining
configuration necessary to achieve a landform with appropriate infrastructure and site conditions
supporting the PMLU (see Figures 12 and 13).
2OOO
1 aoo
1 600
1 4-OO
1 2OO
1 OOO
Pre-mine topology
Mountaintop bench
Final Configuration /
Contour bench
Figure 12. AOC Variance—potential industrial example
1200
1000
Final Configuration
Pre-mine topology
Mountaintop bench
Contour bench
400
1200
I 600
2000
2400
3200
Figure 13. Other potential AOC variance configurations
KFO will carefully review the AOC variance plan to assure that excess spoil volumes do not
exceed the necessary amount required for the designated PMLU in order to minimize stream and
11
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terrestrial habitat degradation. AOC reclamation variance proposals must also conform with the
need, feasibility, financial assurance, and other demonstrations required by SMCRA Section
515(c)(3)and(e).
V. Related Procedures
• Slope Stability and Regulations Analysis Requirements - Engineering Procedure
8.1
• Excess Spoil - Engineering Procedure 3.0
MSHA Regulations
12
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APPENDIX K
FLOODING ANALYSIS
GUIDELINES
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Summary of Changes to Surface Mining Reclamation (38-2) Rule
March 7, 2003
Changed U. S. Soil Conservation Service to U. S. Natural Resources Conservation
Service and removed reference to Handbook throughout rules.
Page 22 - Insert New -3.7. d. A survey of the watershed identifying all man made
structures and residents in proximity to the disposal area to determine potential storm
runoff impacts. At least thirty (30} days prior to any beginning of placement of material.
the accuracy of the survey shall be field verified. Any changes shall be documented and
brought to the attention of the Secretary to determine if there is a need to revise the
permit.
Page 34 - 3.22.f.5.A. The plan shall contain a description of the measures, which will be
taken to replace water supplies that are contaminated, diminished, or interrupted to
include:
Page 34 - 3.22.f.5.A.l. Identification of the water replacement which includes
quantity and quality descriptions including discharge rates, or usage and depth to water;
Page 34 - 3.22.f.5.A.2. Documentation that the development of identified water
replacement is feasible and that the financial resources necessary to replace the affected
water supply are available: and
Page 44 - 3.31.a. To qualify as a Federal, State, County, Municipal or other
local government-financed highway or other construction project, the construction must
be funded fifty percent (50%) or more by the relevant government agency. Funding at
less than fifty percent (50%) may qualify if the construction is undertaken as an approved
government reclamation contract, and once Once the exemption is granted, the person
doing the construction must have on site available for inspection, the following:
Page 57- 58 - 5.4.b.4. Have the capacity to store 0.125 Acre/ft, of sediment for each acre
of disturbed area in the structures watershed; provided, that consideration may be given
for reduced storage volume where the preplan and site conditions reflect controlled
placement, concurrent reclamation practices, or use of sediment control structures;
provided further, that reduced storage volume will be approved only where the operator
demonstrates that the effluent limitations of subdivision 14.5.b of this rule will be met.
The disturbed area for which the structure is to be designed will include all land affected
by previous surface mining operations that are not presently stabilized and all land that
will be disturbed throughout the life of the permit. All sediment control systems for
vallev fills, including durable rock fills, shall be designed for the entire disturbed acreage
of the fill and shall include a schedule indicating timing and sequence of construction
over the life of the fill.
Page 58 - 5.4.b.l 1. Control discharge by use of energy dissipaters, riprap channels or
other devices to reduce erosion, to prevent deepening or enlargement of stream channels
and to minimize disturbance of the hydrologic balance. Discharge structures shall be
designed using standard engineering procedures. The location of discharge points and
the volume to be released shall not cause a net increase in peak runoff from the proposed
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Summary of Changes to Surface Mining Reclamation (38-2) Rule
March 7, 2003
permit area when compared to pre-mining conditions and shall be compatible with the
post-mining configuration and adequately address watershed transfer.
Page 62 - Insert New -5.6 Storm Water Runoff
5.6.a. Each application for a permit shall contain a storm water runoff analysis which
includes the following:
5.6.a. 1. An analysis showing the changes in storm runoff caused bv the proposed
operations') using standard engineering and hvdrologic practices and assumptions.
5.6.a.2. The analysis will evaluate pre-mining. worst case during mining, and
post-mining (Phase III standards) conditions. The storm used for the analysis will be the
largest required design storm for any sediment control or other water retention structure
proposed in the application. The analysis must take into account all allowable
operational clearing and grubbing activities. The applicant will establish evaluation
points on a case-bv case basis depending on site specific conditions including, but not
limited to. type of operation and proximity of man-made structures^
5.6.a.3. The worst case during mining and post-mining evaluations must show no
net increase in peak runoff compared to the ore-mining evaluation.
5.6.b. Each application for a permit shall contain a runoff-monitoring plan which shall
include, but is not limited to. the installation and maintenance of rain gauges. The plan
shall be specific to local conditions. All operations must record daily precipitation and
report monitoring results on a monthly basis and any one (1} year, twenty-four (24} storm
event or greater must be reported to the Secretary within twenty-four (24} hours and shall
include the results of a permit wide drainage system inspection.
5.6.c. Each application for a permit shall contain a sediment retention plan to minimize
downstream sediment deposition within the watershed resulting from precipitation
events. Sediment retention plans mav include, but are not limited to decant ponds,
secondary control structures, increased frequency for cleaning out sediment control
structures, or other methods approved bv the Secretary.
5.6.d. After the first dav of January two thousand four, all active mining operations must
be consistent with the requirements of this subdivision. The permittee must demonstrate
in writing that the operation is in compliance or a revision shall be prepared and
submitted to the Secretary for approval within the schedule described in 5.6.d. 1. Full
compliance with the permit revision shall be accomplished within 180 davs from the date
of Secretary approval. Active mining operations for the purpose of this subsection
exclude permits that have obtained at least a Phase I release and are vegetated. Provided,
however, permits or portions of permits that meet at least Phase I standards and are
vegetated will be considered on a case bv case basis.
5.6.d.l. Schedule of Submittal.
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Summary of Changes to Surface Mining Reclamation (38-2) Rule
March 7, 2003
5.6.d.l.a Within 180 days from the first day of January two thousand four
all active mining operations with permitted acreage greater than 400 acres must
demonstrate in writing that the operation is in compliance or a revision shall be prepared
and submitted to the Secretary for approval.
5.6.d.l.b Within 360 davs from the first dav of January two thousand four
all active mining operations with permitted acreage between 200 and 400 acres must
demonstrate in writing that the operation is in compliance or a revision shall be prepared
and submitted to the Secretary for approval.
5.6.d.I.e. Within 540 davs from the first dav of January two thousand four
all active mining operations with permitted acreage between 100 and less than 200 acres
must demonstrate in writing that the operation is in compliance or a revision shall be
prepared and submitted to the Secretary for approval.
5.6.d.l.d. Within 720 davs from the first dav of January two thousand
four all active mining operations with permitted acreage between 50 and less than 100
acres must demonstrate in writing that the operation is in compliance or a revision shall
be prepared and submitted to the Secretary for approval.
5.6.d.I.e. Within 900 davs from the first dav of January two thousand four
all active mining operations with permitted acreage less than 50 acres must demonstrate
in writing that the operation is in compliance or a revision shall be prepared and
submitted to the Secretary for approval. Provided, however, an exemption mav be
considered on a case bv case basis. Furthermore, haulroads. loadouts. and ventilation
facilities are excluded from this requirement.
Page 97 - 8.2.e. In order to promote the enhancement of food, shelter and habitat for
wildlife, the practice of creating a timber windrow is encouraged. All unmarketable
timber may be used to create a windrow within the permitted area as approved by the
Secretary in the mining and reclamation plan. The windrow shall be designed and
approved as part of a wildlife planting plan and authorized where the postmining land use
includes wildlife habitat. In planning and constructing the windrow, care shall be taken
not to impound water or and shall not be placed in such manner or location to block
natural drainways. The windrow shall be placed in a uniform and workmanlike parallel
line and located so as to improve habitat, food and shelter for wildlife. Areas in and
around the windrow shall be seeded after construction with approved, native plant species
to provide for erosion control and wildlife enhancement. Construction of the wildlife
timber windrow shall take place within the permit area and should be placed immediately
below or adjacent to the sediment control system, maintaining a sufficient distance to
prevent mixing of spoil material with the selectively placed timber. The placement of
spoil material, debris, abandoned equipment, root balls and other undesirable material in
the windrow are prohibited.
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Summary of Changes to Surface Mining Reclamation (38-2) Rule
March 7, 2003
Page 97- 9.1.a. Each surface mine operator shall establish on all regraded areas and all
other disturbed areas a diverse, effective and permanent vegetative cover of the same
seasonal variety native to the area of disturbed land, or introduced species that are
compatible with the approved postmining land use. Reforestation opportunities must be
maximized for all areas not directly associated with the primary approved post mining
land use. All revegetation plans must include a map identifying areas to be reforested.
planting schedule and stocking rates.
Page 99 - 9.3.d. second sentence In evaluating vegetative success, the Secretary shall use
a statistically valid sampling technique with a ninety (90) percent statistical confidence
interval from tho Handbook from tho Handbook.
Page 100 - 9.3.f. Where the post mining land use requires legumes and perennial
grasses, the operator shall achieve at least a ninety (90) percent ground cover and a
productivity level as set for in tho Handbookin tho Handbook by the Secretary during
any two years of the responsibility period except for the first year.
Page 148 - 14.5.h. Added to the end of the first sentence Provided, however, the
requirement for replacement of an affected water supply that is needed for the land use in
existence at the time of contamination, diminution or interruption or where the affected
water supply is necessary to achieve the post-mining land use shall not be waived.
Page 160 - 14.14.g. Durable Rock Fills.
14.14.g. 1. Fills proposed after January 1. 2004. the ¥be Secretary may only approve
the design, construction, and use of a single lift fill with an erosion protection zone or a
durable rock fill designed to be reclaimed from the toe upward, both consisting of at least
eighty (80) percent durable rock if it can be determined, based on information provided
by the operator, that the following conditions exist:
14.14.g. 1 .A. Examination of core borings and the geologic column show that the
overburden consists of durable sandstone, limestone, or other durable material in
sufficient thickness and amounts to generate spoil material that is eighty (80) percent or
greater durable rock. Where the fill will contain non-cemented clay shale, clay spoil, or
other nondurable material, such material must be mixed with the durable rock in a
controlled manner such that no more than twenty (20) percent of the fill volume is not
durable rock. Tests shall be performed by a Registered Professional Engineer and
approved by the Secretary to demonstrate that no more than twenty (20) percent of the fill
volume is not durable rock.
14.14.g. 1 .B. The durable rock shall not consist of acid-producing or toxic-
forming material, will not slake in water, and will not degrade to soil material. For
purposes of this paragraph only, soil material means material of which at least fifty (50)
percent is finer than 0.074 mm, which exhibits plasticity, and which meets the criteria for
group symbol ML, CL, OL, MH, CH, or OH, as determined by the Unified Soil
Classification System (ASTM D-2487).
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Summary of Changes to Surface Mining Reclamation (38-2) Rule
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14.14.g. l.C. The toe of the fill will rest on natural slopes no steeper than twenty (20)
percent.
14.14.g.2. Design Specifications and Requirements of Single Lift Fills with an
Erosion Protection Zone. In addition to the requirements of this subdivision, the design,
specifications and requirements of single lift fills with an erosion protection zone shall be
in accordance with the following:
14.14.g.2.A. Erosion Protection Zone.
The erosion protection zone is a designed structure constructed to provide energy
dissipation to minimize erosion vulnerability and mav extend bevond the designed toe of
the fill.
14.14.g.2. A.I. The effective length of the erosion protection zone shall be
at least one half the height of the fill measured to the target fill elevation or fill design
elevation as defined in the approximate original contour procedures and shall be designed
to provide a continuous underdrain extension from the fill through and beneath the
erosion protection zone.
14.14.g.2.A.2. The height of the erosion protection zone shall be sufficient
to accommodate designed flow from the underdrain of the fill and shall comply with
14.14.e.l. of this rule.
14.14.g.2.A.3. The erosion protection zone shall be constructed of durable
rock as defined in 14.14.g. 1. originating from a permit area and shall be of sufficient
gradation to satisfy the underdrain function of the fill.
14.14.g.2.A.4. The outer slope or face of the erosion protection zone shall
be no steeper than two (2) horizontal or one (1} vertical (2:11 The top of the erosion
protection zone shall slope toward the fill at a three (3) to five (5) percent grade and slope
laterally from the center toward the sides at one (1} percent grade to discharge channels
capable of passing the peak runoff of a one-hundred (100) year, twenty-four (24) hour
precipitation event.
14.14.g.2.A.5. Prior to commencement of single lift construction of the
durable rock fill, the erosion protection zone must be seeded and certified bv a registered
professional engineer as a critical phase of fill construction. The erosion protection zone
shall be maintained until completion of reclamation of the fill.
14.14.g.2.A.6. Unless otherwise approved in the reclamation plan, the
erosion protection zone shall be removed and the area upon which it was located shall be
regraded and revegetated in accordance with the reclamation plan.
14.14.g.2.B. Single Lift Construction Requirements.
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14.14.g.2. B.I Excess spoil disposal shall commence at the head of the hollow and
proceed downstream to the final toe. Unless required for construction of the underdrain.
there shall be no material placed in the fill from the sides of the vallev more than 300 feet
ahead of the advancing toe. Exceptions from side placement of material limits may be
approved bv the Secretary if requested and the applicant can demonstrate through sound
engineering that it is necessary to facilitate access to isolated coal seams, the head of the
hollow or otherwise facilitates fill stability, erosion, or drainage control.
14.14.g.2.B.2. During construction, the fill shall be designed and maintained in
such a manner as to prevent water from discharging over the face of the fill.
14.14.g.2.B.2.(a) The top of the fill shall be configured to prevent
water from discharging over the face of the fill and to direct water to the sides of the fill.
14.14.g.2.B.2.(b) Water discharging along the edges of the fill shall be
conveyed in such a manner to minimize erosion along the edges of the fill.
14.14. g.2.B.3. Reclamation of the fill shall be initiated from the top of the fill
and progress to the toe with concurrent construction of terraces and permanent drainage.
14.14.g.3. Design Specifications and Requirements for Durable Rock Fills
designed to be reclaimed from the toe upward. Durable rock fills that are designed to
be reclaimed from the toe upward shall comply with all requirements of this subdivision
including the following:
14.14. g. 3. A. Transportation of Material to toe of fill. The method of transporting
material to the toe of the fill shall be specified in the application and shall include a plan
for inclement weather dumping. The means of transporting material to the toe mav be bv
any method authorized bv the Act and this rule and is not limited to the use of roads.
14.14.g.3.A.I. Constructed roads shall be graded and sloped in such a manner
that water does not discharge over the face. Sumps shall be constructed along the road in
switchback areas and shall be located at least 15 feet from the outslope.
14.14.g.3.A.2. The constructed road shall be in compliance with all
applicable State and Federal safety requirements. The design criteria to comply with all
applicable State and Federal safety requirements shall be included the permit.
14.14.g.3.B. Once the necessary volume of material has been transported to the toe of the
fill, face construction and installation of terraces and permanent drainage shall
commence. The face construction and reclamation of the fill shall be from the bottom up
with progressive construction of terraces and permanent drainage in dumping increments
not to exceed 100 feet.
Old 14.14.g.2. becomes 14.14.g.4 and the rest of the 14.14.g. is renumbered
accordingly.
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Page 163 - 14.15.a.2. All permit applications shall incorporate into the required mining
and reclamation plan a detailed site specific description of the timing, sequence, and areal
extent of each progressive phase of the mining and reclamation operation which reflects
how the mining operations and the reclamation operations will be coordinated so as to
minimize the amount of disturbed, unreclaimed area, minimize surface water runoff,
comply with the storm water runoff plan and to quickly establish and maintain a specified
ratio of disturbed versus reclaimed area throughout the life of the operation.
Page 165 - 14.15.C. Reclaimed Area. For purposes of this subsection, reclaimed acreage
shall be that portion of the permit area which has at a minimum been fully regraded and
stabilized in accordance with the reclamation p\an±-&&4 meets Phase I standards and
seeding has occurred.
Page 167 - 14.15.g. Variance - Permit Applications. The Secretary may grant approval
of a mining and reclamation plan for a permit which seeks a variance to one or more of
the standards set forth in this subsection, if on the basis of site specific conditions and
sound scientific and/or engineering data, the applicant can demonstrate that compliance
with one or more of these standards is not technologically or economically feasible and
demonstrate that the variance being sought will comply with section 5.6 of this rule. The
Secretary shall make written findings in accordance with the applicable provisions of
section 3.32 of this rule when granting or denying a request for variance under this
section.
Page 173 - 17.1. Paragraph 2 inserted The Secretary shall establish a formula for
allocating funds to provide services for eligible small operators if available funds are less
than those required to provide the services pursuant to this section.
Page 189 - 20.6.a. Assessments. Assessment Officer Duties. For tho purposed
of this section, the assessment officer The Secretary shall not determine the proposed
penalty assessment until such time as tho Secretary has caused an inspection of the
violation te-be-has been conducted and the findings of that inspection are submitted to the
assessment officer Secretary in writing. The Secretary must conduct the inspection of the
violation within the first fifteen (15) days after the notice or order was served.
The assessment officer may continue conferences, conduct investigations, and interview
witnesses as necessary.
Page 190 - 20.6.c. Tho Secretary shall also give notice including any
worksheet, in person or by certified mail, to the operator of any penalty adjustment as a
result of an informal conference within thirty (30) days following tho date of tho
conference. The reasons for reassessment shall be documented in the file by the
assessment officer. The reason for reassessment shall be documented in the file by the
Secretary, (added before the last sentence)
Page 190 - 20.6.d. Notice of Informal Assessment Conference. The Secretary shall
arrange for a conference to review the proposed assessment or reassessment upon written
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Summary of Changes to Surface Mining Reclamation (38-2) Rule
March 7, 2003
request of the person to whom the notice or order was issued, if the request is received
within fifteen (15) days from the date the proposed assessment or reassessment is
received. Provided, however, the operator shall forward the amount of proposed penalty
assessment to the Secretary for placement in an interest bearing escrow account. The
Secretary shall assign an assessment officer to hold the assessment conference. The time
and place of an informal assessment conference shall be posted at the nearest Department
of Environmental Protection regional office to the operation, at least five days prior to the
conference date. Any person shall have the right to attend and participate in the
conference. Any person, other than the operator and Department of Environmental
Protection representatives, may submit in writing at the time of the conference a request
to present evidence concerning the violation(s) being conferenced. Such request shall be
granted by the assessment officer. Should problems arise due to scheduling, the
assessment officer may continue the conference to a later time and/or date as the
assessment officer deems necessary to honor other scheduled conferences.
Page 190 - 20.6.e. Informal Conference. An informal conference on the
assessment or reassessment must be scheduled within 60 days of the receipt of a request,
pursuant to paragraph (1) subsection (d) of section 17, of the Act. Failure to hold an
informal conference in the time limits specified in this subsection will not be considered
as grounds for dismissal of the assessment, unless the operator proves actual prejudice
and makes timely objection to the delay. The assessment officer shall consider all
relevant information on the violation including information which may be provided
pursuant to subdivisions 20.6.b and 20.6.d of this subsection. The assessment officer
shall also give notice including any worksheet in person or by certified mail, to the
operator of any penalty adjustment as a result of an informal conference within thirty (30)
days following the date of the conference. The reasons for the assessment officer's
action shall be documented in the file. Within thirty (30) days after the conference is
held the assessment officer shall either:
Page 191 - 20.6.f. An increase or reduction of a proposed civil penalty of more than 25
percent and more than $500.00 shall not be final and binding until approved by the
Secretary.
Remainder of subsection renumbered accordingly.
Page 191 - 20.6ij. Escrow. If a person requests an informal conference or judicial
review of a proposed assessment, the proposed penalty assessment shall continue to be
held in escrow until completion of the conference or judicial review.
Page 201 - 22.4.g.3.A. An impoundment designed without discharge structures
shall be capable of storing a minimum of two (2) six (6) hour duration probable
maximum storms. A system shall be designed to dewater the impoundment of the
probable maximum storm in ten (10) days by pumping or by other means. The
requirements of 38-4-25.14 shall also be met. Water shall bo removed from tho
impoundment to its lowest practical level within ten (10) days after the storm event by
pumping or by other moans if storm water reduces tho storage capacity to ono probable
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Summary of Changes to Surface Mining Reclamation (38-2) Rule
March 7, 2003
maximum storm or loss.—For existing structures exceeding the minimum 2 PMP volume
requirement, the dewatering system shall be installed when the containment volume is
reduced to 2 PMPs.
Page 202 - 22.4.1.6. Use of Corrugated Metal Pipes -Corrugated metal pipes, whether
coated or uncoated, shall not be used in new or unconstructed refuse impoundments or
slurry cells . If an existing corrugated metal pipe has developed leaks or otherwise
deteriorated so as to cause the pipe to not function properly and such deterioration
constitutes a hazard to the proper operation of the impoundment, the Secretary will
require the corrugated metal pipe to be either repaired or replaced.
Remainder of subsection renumbered accordingly
Page 210 - 24.3. Water Quality. A coal remining operation which began after February
4, 1987, and on a site which was mined prior to August 3, 1977, may qualify for the
water quality exemptions set forth in subsection (p), section 301 of the Federal Clean
Water Act, as amended or a coal remining operation as defined in 40 CFR Part 434 as
amended may qualify for the water quality exemptions set forth in 40 CFR Part 434 as
amended,.
Page 210 - 24.4.Requirements to Release Bonds. Bond release for remining operations
shall be in accordance with all of the requirements set forth in subsection 12.2 of this
rule and the terms and conditions set forth in the NPDES Permit in accordance with
subsection (pi section 301 of the Federal Clean Water Act, as amended or 40 CFR Part
434 as amended. Provided that there is no evidence of a premature vegetation release.
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JAMES E. BICKFORD ||( %j,\ p) PAUL E. PATTON
SECRETARY v?A TO /?/ GOVERNOR
COMMONWEALTH OF KENTUCKY
NATURAL RESOURCES AND ENVIRONMENTAL PROTECTION CABINET
DEPARTMENT FOR SURFACE MINING RECLAMATION & ENFORCEMENT
FRANKFORT, KENTUCKY 40601
CARL E. CAMPBELL
COMMISSIONER
January 25, 2000
Mr. William J. Kovacic, Field Office Director H
Office of Surface Mining
2675 Regency Road
Lexington, Kentucky 40503-2922
Dear Mr. Kovacic:
Enclosed is the Final Report of the Joint OSM Special Study on Drainage Control. This
report concludes the Special Study that was initiated by the 1996 Performance Agreement
Although the report does not find any major programmatic issues with drainage control
structures in Kentucky, we have taken steps to improve the modeling of drainage areas above
drainage control structures as well as improve inspection processes to ensure drainage areas are
in conformance with the approved permit.
Thank you for the participation of your staff in the conduct of the study as well as their
assistance in the compilation of the Final Report. If you or your staff have any questions, please
contact me or Mark Thompson.
Sincerely,
Carl E. Campbell
Commissioner
CEC/mwt/chs
C: Mark Thompson
Jeff Taylor
Keith Smith
Fred Craig
Enclosure
k
EDUCATION
An Equal Opportunity Employer M/F/D
Printed on CL,£; Recycled Paoer
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JOINT OSM-DSMRE SPECIAL STUDY
REPORT ON DRAINAGE CONTROL
FINAL REPORT
DECEMBER, 1999
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FINDINGS
The joint OSM-DSMRE Drainage Control Study Team (DCST) conducted
investigations into 10 mine sites that were alleged, via citizen's complaints, to have
caused or significantly contributed to downstream flooding and/or flood related adverse
impacts to citizens, property or the environment.
The study team found no corroborating evidence to support the allegation that
surface mining operations had an adverse impact on the flooding potential for citizens
and residences downstream, when DSMRE's hydrologic policies and procedures were
followed. The problems discovered in the course of this study appeared to result from a
failure to follow set guidelines either in the permitting process or in the on ground
reclamation process, or a combination of the two. In addition some areas of the SEDCAD
hydrology and flood potential modeling as presently applied were found to have possible
weaknesses. Also field personnel should more closely monitor the mining operations to
ensure that approved drainage schemes are being followed and that proper erosion control
devices are installed below spillways on steep slope areas.
Factual results garnered from the study indicate that the majority of the alleged
downstream flooding problems were more a result of localized, extremely heavy
precipitation events that led to flash flooding, which would have occurred with or without
the mining operations being present.
BACKGROUND
A joint special study was initiated, via the 1996 Oversight Agreement, to review
the adequacy of drainage control in watersheds impacted by surface mining. The pre-
determined focus of the study was to ascertain if mine drainage was causing or
contributing to off-site impacts to downstream areas. The field investigation parameters
included delineation and measurements of watershed boundaries, then comparing pre-
mine versus post-mining drainage patterns and volumes. Field reconnaissance would also
include verification that the sediment stmctures were properly built and certified, review
of the approved hydrology scheme in the permit, and an on-site inspection of the alleged
off-site damage. The-data collected was then evaluated to determine if the mining
operations had any effect on the downstream hydrology, particularly the flood potential
for the downstream citizens and property.
Team members were selected from both OSM and DSMPJi as a mixture of
engineers and environmental specialists from both agencies, ail with a minimum of at
least 15 years experience in mining reclamation and enforcement. Team members from
the Lexington Field Office of OSM were Gail Smith and Ralph Blumer. Field inspectors
George Morgan and Charles Saylor also participated in several of the investigations.
Team members from Kentucky DSMRE included Jesse Gilpin, Paul Travis, Jeff Hall and
Jeff Taylor.
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The study was initiated after both OSM and DSMRE received an increase in
citizen complaints that often involved life threatening, property damaging "washouts".
Several complainants were alleging that the large volumes of water they observed were
caused by the upstream mining operations.
The original intent of this study was to investigate 15 citizen complaints that
alleged flood damage caused by mining operations. However after three years of
monitoring complaints, only 10 sites with possible flood related damage have been
reported, therefore the team concluded the study at this point.
REVIEW FINDINGS
The basic responsibility of the DCST was to determine whether there was any
relationship between surface mining and reclamation processes and an increase in the
flood j>etential for areas downstream of these mining operations. .
The DCST conclusions are based on factual data gleaned from the on-site
investigations, as well as "Best Available Technology" (BAT) hydrology modeling and
any other sources of obtainable information. Sources other than those previously
mentioned include the approved drainage plan in the permit, rainfall data for the dates of
the flooding events and any first-hand eyewitness reports of these events.
Of the ten sites investigated in the course of the study, three of the cases resulted
in an actual increase in flood potential and enforcement action being taken by DSMRE.
In each of these three instances the mine operation had significantly increased the volume
of precipitation runoff flowing into an off-permit natural drain as compared to the pre-
mining baseline runoff. In each of these cases the permittee/operator failed to properly
follow the approved drainage plan in their reclamation operations. For more detailed
information on the individual site investigations, please seethe synopsis attached to this
report.
Statutes and regulations govercing mining require that runoff from disturbed areas
as defined in 405 KAR 16:070, Section 1 (l)(d), pass through a sediment control
structure prior to leaving the site. In order to comply with these requirements mine
operators usually permit and construct diversion ditches to divert any runoff to an
approved structure. This situation often causes a larger acreage of runoff than natural to
be concentrated to a narrow outlet, which is usually the spillway of the sediment
structure. Although energy dissipators such as riprap are used to prevent the eroding
effects below the spillway that sometimes occurs in these instances, heavy rainfall events
sometimes produce such large volumes of runoff that gully erosion occurs below the
spillway nevertheless. The study team found five of the ten sites investigated to have
sufficient erosion below the spillway to warrant issuance of a non-compliance (Note:
Two of these permits cited were a result of extreme rainfall events and not due to an
increase in the flood potential).
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The Division of Permits requires each permit applicant to prove by BAT
hydrology modeling that the drainage plan for each sediment structure will not have a
significant adverse impact on the hydrological balance of adjoining areas. This is usually
done by a computer program called SEDCAD, which has been utilized by mining
engineers in different forms for the last couple of decades. SEDCAD is a nationally
recognized computer hydrology modeling system developed by the University of
Kentucky- Biosystems and Agriculture Engineering Department. Mining engineers and
the Division of Permits reviewers use SEDCAD to determine the sizes, locations and
drainage areas of sediment structures in order to prevent any adverse impact to the areas
downstream from mining.
Data results from the study found no evidence that mining increased the flood
potential or had any adverse hydrological impact when a correctly permitted drainage
scheme-was followed. The three study sites on which enforcement actions were taken had
experienced an increase in the drainage area due to the post-mining backfilling and
grading configurations and/or extension of the diversions beyond designed limits, which
increased the watershed of the sediment structure to a level in excess of what was
approved in the permit package.
The regulations require that all mine operations control drainage to prevent an
increase of flooding potential. Mine engineers and Division of Permits reviewers
accomplish this by:
1) Estimating the premining drainage for the watersheds within the mine area using
BAT, and
2) Designing mine drainage and ponds in order that drainage from the impoundments
will not exceed the premining drainage from the watershed.
If the premining drainage is overestimated, drainage from the permitted ponds may
cause localized flooding that would not have occurred prior to mining. The accuracy of
the findings and conclusions of this report are dependent upon the accuracy of the
SEDCAD modeling, particularly the pre-mining data. As SEDCAD and other mine
engineering technologies advance, improvements in flood potential prediction and
analysis decrease any likelihood that mining might adversely impact a downstream
landowner or community. Recommendations # 1 through 4 in the concluding section of
this report hopefully will help to make flood potential prediction and modeling more
accurate fir future ruining permits.
A synopsis with the situations and conclusions of each site investigation is attached as
an addendum to this report.
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RECOMMENDATIONS
Although the study team found no major flaws in the methods DSMRE utilizes in
its hydrology modeling, some concerns and potential areas for improvement were noted.
(1) The study team recommends that the Division of Permits consider refusing to allow
permittees to use "instantaneous time of concentration" ( I-Tc) in the pre-mining
SEDCAD hydrology modeling. Discussions with Dr. Richard Warner of the University
of Kentucky, a co-creator of SEDCAD, and recent projects under the direction of Dr.
Warner have confirmed that the use of "instantaneous" can often cause elevated pre-mine
estimates of average runoff. When (I-Tc) is used in pre-mining hydrology modeling, the
model runs its program such that any and all rainfall that hits within the model watershed
is projected to be at the watershed outlet immediately. While this scenario is appropriate
for certain SEDCAD modeling situations, it artificially increases pre-mining peak .flows
and thus does not provide an appropriate base for comparison of post-mining discharge.
Obtaining the most precise pre-mine runoff data possible is essential to ensure that the
mine drainage schemes are designed to prevent adverse impacts to the hydrologic balance
and citizens and property downstream.
(2) The three sites from which enforcement actions (for an increase in flood potential)
were cited all had the same problem; a significant increase in the sediment's watershed
after backfilling and grading was completed. It is recommended that permittees and
especially field inspection personnel be reminded to ensure that the approved drainage
plan in the permit is followed, including diversion ditches.
(3) The DCST recommends that the permit 'method of operation' section be expanded to
include drainage scheme information that is pertinent to the proposed mining plan. For
example, it was noted and discussed on a few of the study sites that the approved
drainage plan was designed for only a maximum of 10 % disturbed area in a watershed.
Team members and Division of Permits representatives agreed that this is rarely an
accurate on-ground scenario. A majority agreed that the Division of Permits should
include information from the drainage plan that is associated with the method of
operation into both sections of the permit, making it easier for everyone to understand the
approved mining plan.
(4) The DCST's final recommendation is that closer scrutiny is given to ensure that
adequate energy dissipator/erosion control devices are used below spillways of dugout
structures, especially those that flow out to steep siope areas. The study team found some
areas that had moderate to severe erosion when the spillway emptied onto natural ground
where there was no previous natural drain, causing sediment deposition problems
downstream where the topography leveled off. A check of these areas on complete
inspections and/or after severe storm events should not be overly burdensome on
inspectors and could prevent damage to downstream landowners. It is recommended that
dugout structures be placed in pre-existing natural drains unless there is a substantial
reason it should be placed otherwise.
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It should be noted that the Division of Permits has already implemented one
recommendation of this team. In the early portion of this study it was discovered that
permittees were sometimes allowed to use different modeling programs for the pre-
mining versus the during-mining hydrology data. This appeared to be a possible loophole
for 'tweaking' of the hydrology data to allow a greater volume of runoff than would
otherwise be permitted. Paul Travis, an engineer and team member from the Division of
Permits, enacted a new reviewer policy to ensure that the pre and post-mining hydrologic
data were designed by the same methods.
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DCST SITE SPECIFIC RESULTS
1. Holston Mining P.N. 898-0349- Danny May Complaint- Flooding and sediment
deposition damage to property was alleged to be the result of Holston Mining's operations
approximately 1700 feet up the mountainside from Mr. May's residence.
The Drainage Control Study Team (DCST) could find no evidence to support Mr. May's
allegation that the mining and in particular SS# 38 was responsible for the flooding and
sedimentation deposits on his property. The team conducted a thorough investigation of the
mined watershed, SS# 38, and an on-ground reconnaissance of the hillside between the
minesite and Mr. Mays property. There was substantial erosion and debris spread all along
this area of Pike County, apparently due to an intense storm cell that dumped approximately
3 inches of rain in less than four hours. It appears that the flood damage was due to the large
precipitation event that flowed down the mountainside carrying sediment and debris with it.
The drainage area above Mr. May's property included both a gas well and' a logging
operation, which contributed to the sediment and debris deposited on Mr. May's yard.
SEDCAD modeling was conducted comparing pre-mine to post-mining effluent for a
25yr/24hr storm to determine if Holston Mining was responsible for increasing the flood
potential for the area downstream of SS# 38. The data results are as follows:
Pre-mine flow 17.17 cfs
During-mining 16.37 cfs
This data suggests that Holston Mining had a negligible effect on the flood
potential for the area downstream of SS# 38.
2. Coal Mac Tnc. P.N. 836-0229-Amarine Conn Complaint- Three silt structures were
involved, SS# 2, 2A, and 4. Alleged that mining had caused severe flooding in Ned's Fork
area of Floyd Co.
Residents of the Ned's Fork area alleged that two separate severe flood events had
occurred within the past year. The latest had occurred on August 8 , 1996, with floodwaters
jumping the ditchlines and almost washing away a car driven by Mrs. COM. The study team
conducted a thorough investigation of the mining area and the immediate downstream area,
including the Ned's Fork community. A video of the August 8 event was provided by Mrs.
Conn. A thorough investigation was initiated involving comparison of the pre-mine versus
the post-mining watershed, verification of the correct design and construction of the sediment
structures, accumulation of any local rainfall data, and interviews with citizens and mine
personnel.
As a precautionary measure the team did a cross-sectional profile survey of the Ned's
Fork area where floodwaters had overtopped the county road culvert just upstream from
Mrs. Conn's residence. Using a video taped by Mrs. Conn on the day of the flooding to
determine the height and volume of the floodwaters, the engineering results determined that
the county road culverts in this area were inadequate to handle a large storm event.
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SEDCAD results totaled at a point just below the confluence of all three structures found
Pre-mining = 441.28 cfs
During mining = 365.02 cfs
The team could find no violations or negligence on the part of Coal Mac, Inc., and its
mining operations in this area. The mined watershed was not changed from the pre-mine
configuration, and all silt structures appeared to be built and functioning adequately. Also
there was a large unmined area adjacent to the minesite and upstream of Ned's Fork that
apparently contributed to the flooding of the downstream community.
3. Kentucky May Coal Co. P.N. 898-0475- Marvin Bentley Complaint-Alleged that SS#4
deposited sediment in yard, created slumps and erosion on hillside below the pond, pond
leakage,.
An investigation of the site found a significant increase in the during mining as compared
to the pre-mining effluent flow in the watershed of SS#4 directly above Mi-. Bentley's
residence. Survey results showed an increase in the affected drain .acreagefrom 0.6 acres pre-
mine to an acreage of 4.21 acres after mining and diversions were completed. An on-site
inspection discovered that a diversion ditch feeding SS#4 had been extended approximately
150 feet further than approved in the permit plan, thereby causing the additional effluent.
SEDCAD runs taken at the discharge point of SS#4 were Pre-mine 1.36 cfs
During mining— 8.92 cfs
An additional SEDCAD run was conducted to determine the increased hydrological
impact at the toe of the slope behind the impacted residence, or approximately 800 feet
belowtheSS#4 spillway. Results of the SEDCAD runs were Pre-mine 21.69 cfs
During mining...29.59 cfs
Enforcement action was taken, and SS#4 and associated diversions have been eliminated,
returning the area to the approximate pre-mine drainage scheme.
4. Holston Mining P.N. 898-0349-Columbia Gas Complaint- Gas company alleged that
Holston caused slide and instability in gas-line bench from effluent and seepage emanating
from SS#37.
The DCST could not find sufficient evidence to link the gas bench slide and instability to
the mining operations, due in part to a photograph taken by the mine inspector showing the
gas bench sliding several months prior to the construction of SS#37. However, effluent
emanating from below the spillway outlet of SS#37 had caused guiiy erosion and exposure of
the gas line. A survey comparing the pre-mine versus the post mining watershed showed a
large increase in the post mining watershed of SS#37. SEDCAD data results for a 25 yr/ 24
hr event comparing the pre-mine vs. post-mine watershed were:
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Pre-mine 1.65 cfs
During mining..25.91 cfs
Enforcement action was taken, and Holston Mining repaired the gas line and gully
erosion on the gas bench, as well as returning the watershed of SS# 37 to pre-mine levels.
No further problems have been reported.
5. Alley-Cassetty Coal Company PN 816-0105- Earl Combs Complaint- Downstream private
lake alleged mine sediment muddying up lake. Also was concerned that sediment might
cause a fish kill.
Investigation found that an extremely heavy rain event (estimated between a fifty to one
hundred year storm event) combined with a large disturbed area caused a temporary overload
of the company's SS#1. This watershed area also had a considerable acreage of forested area
between the minesite and the lake that had some logging activity in the past. N3 violations
were cited. Lake cleared up quickly with no further problems.
6. Lodestar Energy, Inc. P.N. 836-0231-Raymond Ratliff Complaint- Mr. Ratliff alleged
runoff from the minesite, specifically dugout no. 8, caused erosion of his hillside and siltation
of his paylake.
Investigation by study team found that the operator had allowed an approximate 6 acres
increase in the drainage area feeding SS#8, thereby significantly contributing to erosion on
the hillside below the structure and potential siltation of the paylake. SEDCAD modelling
was based on the entire (mined and unmined ) watershed of the paylake.
SEDCAD results were Pre-mine 78.64 cfs
Post-mine 103.12 cfs
These results showed an approximate increase of runoff into the payiake of 3 1%. Based
on these findings enforcement action was taken and Lodestar Energy quickly complied to
return the drainage scheme to reflect the approved plan in the permit.
7. Miller Brothers Coal Inc. P.N. 897-0379-Claude Coots Complaint-Mr. Coots alleged
drainage from SS#2 caused erosion and water damage to his property.
Study team found the structure was leaking but not causing any erosion or other damage
to Mr. Coot's property. Company had made two previous unsuccessful attempts to seal the
structure. Decision was made to eliminate structure and return area to natural pre-mine
drainage. No further problems reported. No SEDCAD data required.
8. Coal Mac, Inc. P.N. 898-0517-Thacker and Woods Complaint-Alleged drainage from the
minesite and SS#1 responsible for downstream flooding to property-.
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Investigation results found no discernable mining related impacts to the downstream
hydrological balance. The causation of the flooding appeared to be the combination of a large
precipitation event (approximately 4.5 inches of rain in a 29 hr. period) and the junction of
two large watersheds less than 100 feet from the Thacker residence. SEDCAD modeling was
not necessary for this investigation.
9. Colonial Coal Corporation P.N. 898-0467-Numerous Complainants-Alleged flooding due
to mine and related silt structure.
Study Team investigation could find no causal relationship between the mined area and
the flooding downstream in relation to the hydrological aspects; however sedimentation and
debris washed downstream from the minesite did contribute to property damage downstream.
Some errors were found in the permit modeling in relation to sedimentology also. However,
the study could not find sufficient evidence to show that either the mining or the silt structure
involved had any effect on the flood potential for the affected areas downstream. The damage
once again appears to be the direct result of a severe storm cell that dumped somewhere in
the neighborhood of 5.5 to 6 inches of rainfall, according to local estimates. Since mining
had not increased the drainage area for this watershed, SEDCAD runs were not needed.
Problems with the permitted sedimentology modeling were forwarded to the Division of
Permits for review.
No further problems on this site have been reported.
10. Lodestar Energy, Inc. P.N. 836-0261-Confidential Complaint-Alleged flooding and
sedimentation of Stratton Branch downstream from silt structure #7.
The study teams investigation could find no evidence that Lodestar Energy's mining had
any significant impact on the flood potential for the Stratton Branch community. It appears
from talking to the inspector and the mine foreman that this particular flood event was the
result of a high intensity storm cell that produced large volumes of precipitation within a
relatively short period of t h e . A noii-compliance was issued by the state inspector for a
settable solids violation as a result of these events. SEDCAD results were as follows:
Premine 422.33 cfs
During mining .462.66 cfs
Although these results show a 9.5 % increase in flow from the mined area during a
precipitation event, this is not considered to be a significant increase and is within the
accepted margin of error for this program. This minesite has since been revegetateci and is
presently under construction as a future golf course and residential area. No further problems
have been reported.
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KY DSMRE •*-»-» OSM LEX @|002/005_
11/07/02 14:31 FAX 502 564 5698 UJMVIKB,
JAMES E. BJCKFORD fejf Hn |g| PAUL E. PATTON
SECRETARY Va-Js!l J& GOVERNOR
COMMONWEALTHCF KENTUCKY
NATURAL RESOURCES AND ENVIRONMENTALPROTECTION CABINET
DEPARTMENT FOR SURFACE MINING RECLWIATION& ENFORCEMENT
FRANKFORT, KENTUCKY40601
CARL E. CAMPBELL
COMMISSIONER
MEMORANDUM
TO: Technical Review Staff
FROM: Larry D. Adams, Direct-
Division of Permits
DATE: August 7,2002
SUBJECT: Sediment/ Flood Control Design Considerations
Mining disturbances have the potential to alter watershed characteristics and
increase peak flows due to changes in topography and vegetation. Whether or not
flooding occurs is a site specific circumstance based on the degree of flow alteration
caused by the mining activities and the downstream channel capacity and geometry, as
well as the influence of other manmade alterations to channels and flood plains (e.g.,
roads, culverts, stream crossings, bridges, residential or business fills encroaching on
stream beds, and other obstructions).
A Joint Special Study was conducted by OSM and DSMRE on drainage control at
ten mine sites in Kentucky. Site selection was based on citizen complaints alleging life
threatening "wash-outs" were caused by mining or mining otherwise significantly
contributed to downstream flooding. Of the ten sites investigated, three were determined
to have increased flood potential based on the operators failure to follow the approved
drainage plan. The report concluded that compliance with the approved regulatory
program effectively minimized flooding potential.
Recommendations of the Joint OSM -DSMRE Special Study Report on Drainage
Control are summarized as follows:
• Permitted worst case models must reflect on anticipated ground site conditions to
insure the adequacy of sediment / flood control measures, To assist in site
inspections, the method of operatipn should be expanded to include drainage
information.
EDUCATION
PAYS
An Equal Opportunity EmployerM/F/D
Printedon $j£) Recycled Paper
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KY DSMRE •"•» OSM LEX @] 003/005
11/07/02 14:32 FAX 502 564 5698 ~~ ~~ " ~
Sediment/ Flood Control Design Considerations
August 7,2002
Page 2
• Reclamation timing that is pertinent to the proposed mining plan. For example, if
end-dumped durable rock hollow fills are modeled with the lower lifts aged, the
hollow fill narrative must address the timing of reclamation. Alternatively, if the
applicant proposes to breakdown an end-dumped fill at the conclusion of mining
within the subject watershed, the worst case model should reflect the fill fully
disturbed, bare.
• Pre-mining, during mining hydrologic analyses must be modeled using the same
methodology to insure comparable peak run-off values. Pre-mining hydrologic
analyses should not typically be modeled with an instantaneous time of
concentration (Tc). When an instantaneous time o f concentration is modeled with
SEDCAD, the model immediately projects all rainfall within the subject
watershed to the outlet resulting in an elevated pre-mining run-off estimate.
While the use of an instantaneous time of concentration is appropriate in some
during mining models, it may artificially increase pre-mining peak flow and
would not provide an appropriate base for comparison of post-mining discharge.
• Energy dissipaters / erosion control devices should be required at pond outlets.
To the extent possible, on bench dugout structures should be located so as to
discharge into preexisting natural drains.
In addition to the study report recommendations, the following sediment / flood
control design considerations are to be implemented.
Hollow Fill Design and Modeling
1. In light of common end-dump hollow fill construction practices observed in the
mining industry, it is prudent, in assessing the projected hydrologic load on sediment
structures, to assume a default modeling configuration comprised of;
a) Fill at full capacity/size,
b) Surface condition of entire fill is bare spoil, no seeding/mulching, no final
grading, no terraces,
c) Slope and, more importantly, slope lengths used in Tc, Muskingum k, and
sedirnentology inputs should reflect absence of terraces, considering the full
lengths of the downstream face.
d) The remainder of the mining activity within the watershed should be modeled for
an acceptable worst-case estimation, and the pond performance assessed
accordingly.
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KY DSMRE w OSM LEX .
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Sediment/ Flood Control Design Considerations
August 7,2002
Page 3
2. The applicant/engineer may substitute a design modeling configuration for the
default scenario to only such degree that is supported by specific construction
practices and sequence as are delineated within the plans, specifications, and
drawings. Those specifications should address the following areas;
a) an estimation of the time to required for completion of the fill, from initial
clearing through final grading and establishment of vegetation,
b) Maximum height of fill/volume of fill to be exposed at arty time before initiation
of grading/vegetation,
c) Hollow fill aging (in the modeling) should reflect the reclamation pattern
described in the specifications, including variable cover conditions (based on
history) and including thernax^Tn\'im allowable height of the exposed fill face.
3. If there is more than one hollow fill within a drainage area, the narrative should
specifically address the relative reclamation status of the fills, either accounting for or
precluding multiple fill sites active at any time.
4. The specifications should clearly stipulate placement of the rock check structure
(below the toe of the fill) at the beginning of fill operations, and drainage structures
(perimeter diversions) as soon as practicable.
Contemporaneous Reclamation Variance
I. For applications containing a request for a contemporaneous reclamation variance,
additional information relating to potential storm flow increases and sediment
discharge should be considered. This information should address;
a) Consideration of sedimentology / hydrology impacts of extensive open pits or un-
vegetated area, along with any appropriate controls. Additional modeling
scenarios may be necessary to analyze during mining conditions versus
reclamation condition for worst case impacts.
b) Consideration of the worst case hollow fill status during development of the open
highwall.
Likewise, the applicant may choose to utilize a design modeling configuration taking
into account specific reclamation timing / sequence factors similar to that addressed
in hollow fill design and modeling considerations.
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Sediment/ Flood Control Design Considerations
August 7,2002
Page 4
Ponds in Series
1. Where ponds are proposed in series, extra diligence should be employed in assessing
the worst case sediment and storm load. This is particularly true for instances where
multiple on-bench dugout structures are proposed in support of a downstream
impoundment. Additional modeling scenarios may be necessary for fully assess the
projected load on the lowest downstream discharge point.
2. In no case should the watershed plan be approved based solely on a demonstration
showing all active disturbances above an upper level structure. Consideration must
be given to the predicted storm performance, sediment accumulation, and effluent for
the lowest structure in the watershed under the maximum predicted load for that
structure.
Proximity of Downstream Development
1. For watersheds vriih a higher risk of negative impacts due to flooding or inadequate
sediment controls (highly populated or developed areas, particularly if the natural or
constructed drainage course is only marginally adequate before mining), additional
precautions should be taken. These precautions should include;
a) Because of the potential impacts from high rainfall rates, particular care should be
employed in consideringthe watershed routing to, and through, the impoundment.
b) Recommendation should be made as to appropriate additional control measures,
such as on-bench rock checks, more aggressive reclamation provisions, and/or
additional sediment control measures.
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