An Integrated Framework for
Evaluating Wetland and Stream
Compensatory Mitigation -
Summary of Pilot Applications
SCCWRP Technical Report 1210
EPA-840-S-22001 | March 2022
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An Integrated Framework for Evaluating Wetland and
Stream Compensatory Mitigation - Summary of Pilot
Applications
Eric D. Stein1, Jeff Brown1, Tim Smith2, Cody Cox3, Nathan Nibbelink3, and Katie
Sheehan Hill3
Southern California Coastal Water Research Project, Costa Mesa, CA
2Minnesota Board of Water and Soil Resources
3University of Georgia, Athens
Brian Topping4, Palmer Hough4
4U.S. Environmental Protection Agency Project Managers
March 2022
SCCWRP Technical Report 1210
EPA-840-S-22001
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TABLE OF CONTENTS
BACKGROUND AND OBJECTIVES 3
OVERVIEW OF PILOT PROJECTS 5
Minnesota 6
Georgia 7
MAJOR OUTCOMES 9
Minnesota 9
Georgia 13
COMPATIBILITY OF DATA PRODUCTS 20
HOW PILOT PROJECTS HAVE SUPPORTED APPLICATION OF THE FRAMEWORK 21
Minnesota 21
Georgia 22
LESSONS LEARNED AND RECOMMENDATIONS 23
Scoping, Project Management and General Implementation 25
Technical Approach 27
Stakeholder Coordination and Outreach 27
FUTURE EFFORTS 29
Next Steps for Minnesota Program 29
Next Steps for Georgia Program 30
APPENDIX A: OVERVIEW OF MINNESOTA PILOT PROJECT 32
Section 1 Agency Overview 32
1.1 Key agencies and general structure 32
1.2 Authorities 33
1.3 General goals and mandates 34
Section 2 Overview of mitigation components of the state program 34
2.1 The Minnesota Wetland Bank 34
2.2 Number of Mitigation Sites included 35
2.3 Timeframe covered by assessments 35
2.4 Resources (staff, budget etc.) 36
Section 3 Objectives of the case study - what are you trying to accomplish 37
Section 4 Main Challenges 37
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Section 5 Approach and Strategy Used 38
5.1 Staffing 38
5.2 Software Used 39
Section 6 Outcomes 40
6.1 Products Produced 40
6.2 Capacities Developed 40
6.3 Partnerships or Leverage Opportunities Enhanced 40
Section 7 Lessons Learned 41
Section 8 Conclusions and Roadmap for the Future 42
APPENDIX B: OVERVIEW OF GEORGIA PILOT PROJECT 43
Section 1 Summary of state program assessing mitigation performance 43
1.1. Key agencies and general structure 43
1.2. Authorities 43
1.3. General goals and mandates 44
Section 2 Overview of mitigation components of the state program 46
Section 3 Objectives of the case study - what are you trying to accomplish 46
Section 4 Main challenges 47
Section 5 Approach and strategy used 49
5.1. How was it staffed? (internal, contractors) 49
5.2. Software used 49
5.3. Process (e.g., stakeholder coordination, key agencies coordinated with, guidance
docs used) 50
Section 6 Outcomes 51
6.1. Products produced 51
6.2. Capacities developed 52
6.3. Partnerships or leverage opportunities enhanced 52
Section 7 Lessons learned 53
7.1. What worked well/keys to success 53
7.2. Challenges/things you would have done differently 53
7.3. Recommendations for others 55
Section 8 Conclusions and roadmap for the future 55
8.1 Recommendations for next steps 55
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BACKGROUND AND OBJECTIVES
Compensatory mitigation is a commonly utilized strategy for offsetting unavoidable,
adverse impacts to wetlands, streams and other aquatic resources as a result of permitted
activities that affect aquatic resources. Program managers who are tasked with implementing
and overseeing compensatory mitigation for wetlands, streams, and other aquatic resources
often struggle to identify rigorous, standardized approaches for conducting monitoring and
performance assessments, and to access and manage data relevant to their compensatory
mitigation projects. To provide clearer recommendations and improve consistency of
compensatory mitigation performance assessments across the country, the United States
Environmental Protection Agency (USEPA) Office of Wetlands, Oceans, and Watersheds, in
partnership with the Southern California Coastal Water Research Project (SCCWRP) and the
Environmental Law Institute (ELI) developed a set of best practices for conducting
compensatory mitigation assessments and produced An Integrated Framework for Evaluating
Wetland and Stream. Compensatory Mitigation1.
The Framework includes a series of recommendations and best practices that states can use
to augment their existing programs and ultimately improve their effectiveness. Also included in
the proposed Framework are recommendations for data management that are aimed at helping
to improve data accessibility across agency programs and to the public. The proposed
Framework recommends that comprehensive compensatory mitigation evaluation include
assessments of both project and program performance. To achieve this, the Framework
recommends a flexible, modular approach that allows states to prioritize different modules
depending on their needs and the status of their existing assessment programs. Where feasible,
the Framework recommends implementation of all three modules to provide a comprehensive
evaluation of program performance.
1. Compensatory mitigation site performance ("Performance"): This module evaluates the
success of mitigation projects relative to defined ecological endpoints (e.g., morphology,
habitats, species, communities), functional goals and permit requirements. This module
can also help assess factors that influence mitigation success and the length of time
necessary to achieve desired targets.
2. Program effectiveness ("Effectiveness"): This module evaluates the overall effectiveness
of the regulatory program at achieving programmatic goals, such as no-net loss, specific
area goals, and/or desired ecological targets at reach, watershed and regional scales.
3. Resiliency of compensatory mitigation practices ("Resiliency"): This module evaluates
likely long-term trajectories of compensatory mitigation sites at achieving functional
replacement of aquatic resource impacts. This includes the role of adaptive
1 Stein et al. (2022) An Integrated Framework for Evaluating Wetland, and. Stream Compensatory
Mitigation. EPA-840-S-22001.
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management ability to adapt for climate change effects, and vulnerability to future
degradation due to changing land use, climate, and management practices.
To facilitate implementation of the Framework, USEPA funded two pilot projects in the
states of Minnesota and Georgia aimed at demonstrating one or more modules of the
framework and/ or implementation of an open data system to produce data products based on
monitoring data that can be used to inform decision making.
Both pilot projects focused on developing data management systems intended to improve
access to information on compensatory mitigation projects, facilitate information sharing among
agencies and programs and provide easier access of this information to stakeholders, and the
public at large. Improved information access will allow agency staff to better address all three
modules of the Framework.
This report provides a summary of the two pilot projects, lessons learned, and example
products. Details of each pilot study are provided as appendices. These pilot studies are initial
steps toward achieving the overall goals proposed in the Framework. Future efforts will be
necessary to incrementally advance the ability of both programs to fully evaluate compensatory
mitigation program effectiveness. The pilot projects provide examples of a state with a robust
wetland regulatory, monitoring and assessment program (Minnesota) and a state that relies
almost entirely on the Federal agencies for wetland protection and mitigation (Georgia). The
results of these pilot studies, and the associated lessons learned and recommendations, can
provide examples and ideas for other states as they contemplate implementation of the
Framework and work to advance the capacity to address key management questions
nationwide.
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OVERVIEW OF PILOT PROJECTS
Minnesota and Georgia provide useful similarities and contrasts in their existing
programmatic structure for regulation and implementation of compensatory mitigation and in
their approaches to the pilot projects. Mitigation banking is the predominant strategy used in
both states, with Minnesota having one of the most active and robust wetland banking markets
in the country with an estimated 400 wetland banks approved since inception of the Minnesota
State Wetland bank in the 1990s and Georgia having 190 banks listed in the Army Corps of
Engineers (ACOE) Regulatory In lieu fee and Bank Information Tracking System (RIBITS).
However, the regulatory structure differs between the two pilot projects. In Minnesota, the
wetland banking program is administered by the Minnesota Board of Water and Soil Resources
(BVVSR, a state agency) through their Wetland Conservation Act (WCA) authorities, in
coordination with the ACOE (although the scope and scale of the state program is much
broader). In contrast, the role of the state is quite limited in Georgia, with the ACOE assuming
the lead oversight role for compensatory mitigation. Reflecting this difference, Minnesota has a
much more robust wetland mitigation monitoring and assessment program and consequently
more state agency capacity for assessment and data management compared to Georgia. Despite
these differences, both states need to improve their data management infrastructure to be able
to answer key questions about compensatory mitigation performance, program effectiveness
and resiliency, and chose this as the focus of their pilot studies. Minnesota hired a third-party
contractor to develop the data management system, whereas the Georgia system was developed
by faculty and staff from the University of Georgia. Figure 1 depicts the status of each state
relative to the implementation process outlined in the Framework. The general implementation
process was structured to provide the information necessary to efficiently address all three
modules for a comprehensive evaluation of program performance. Individual programs may
focus on different steps in the process depending on their needs and priorities.
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A
• prograrnrnati c goal s
• current conditions and
needs
A
Infrastructure
Development
• protocols and procedures
• datatemplates and
checkers
• reference networks and
arnbientassessement
Operationalization
• institutional partnerships
• sharedfunding
mechanisms
• outreach and reporting
Georgia
Minnesota
%
FIGURE 1: Status of development of the two pilot project states relative
to the implementation process outlined in the Framework (Stein et al.
2022).
Minnesota
Minnesota state agencies and the ACOE have worked together for many years to increase
consistency between state and federal policy regarding compensatory wetland mitigation
programs and mitigation bank implementation. State agencies account for the majority of
waters/wetlands permitting and compensatory mitigation requirements. For example, the
Minnesota Board of Water and Soil Resources (BWSR) approved 175 wetland replacement plans
in 2018 and has processed approximately 305 wetland banking transactions per year
(withdrawals, deposits, and transfers) between 2015 and 2019. Responsibility for the monitoring
of wetland replacement sites is divided based on the time that has elapsed since construction.
The establishment period, roughly defined as the time from construction through the fifth full
growing season, is conducted by the mitigation project sponsor and reviewed by the ACOE,
BWSR, the Department of Natural Resources, and the local government unit with jurisdiction
over the site under WCA. After the establishment period, BWSR takes over long-term
monitoring with the focus primarily on compliance with the conservation easement recorded in
favor of the State of Minnesota.
Once the establishment period has concluded, permittee responsible mitigation sites are
only monitored if a regulatory agency randomly conducts an inspection or if a specific issue is
identified that requires attention. Follow-up assessments to evaluate resiliency and overall
functional condition for permittee responsible mitigation are infrequently performed by state
and local agencies implementing WCA. Wetland bank sites in Minnesota are subjected to a
more structured inspection approach because of a rule that requires BWSR to periodically
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inspect wetlands associated with the wetland banking program to ensure that easement
conditions are being met. Data on all wetland banks is managed and organized by BWSR.
Building on recent efforts funded by US EPA, BWSR is in the process of developing a more
comprehensive long-term monitoring approach that will assess resiliency at mitigation sites at
regular intervals using standardized methodologies. Additional details on the Minnesota
program are available in Appendix A.
The Minnesota BWSR is developing a new Monitoring Data Management System (MDMS)
to improve their ability to organize, track and report monitoring data from wetland mitigation
sites. The current pilot study supports this larger effort through support of the following tasks:
(1) developing the specifications and work flow processes for the monitoring module in the
database; (2) developing standardized forms and processes for the collection of wetland
mitigation monitoring data; (3) compiling wetland mitigation site metadata; (4) building the
MDMS; and (5) testing the monitoring module and refining any data collection, submission, or
standardization processes. The final version of the monitoring module will be driven by
electronic data flow that is stored, presented, and accessed in a geospatial format. The stored
data would be accessible via a web-based application operated and maintained by BWSR.
Georgia
Georgia's compensatory mitigation program is administered by the ACOE Savannah
District under the auspices of the Clean Water Act Section 404 program. The mitigation banking
program in the state is quite robust because the Savannah District was an early adopter of the
banking concept and began permitting mitigation banks in the early 1990s. However, the State
of Georgia has no written guidance, policy or regulatory program that regulates impacts to state
waters2. Monitoring of mitigation banks occurs pursuant to the Savanah District's Standard
Operating Procedure for Compensatory Mitigation, associated guidance, and individual
banking instruments. There is currently no central database for cataloging monitoring data.
Prior to 2018, compensatory mitigation in Georgia was governed by the Savannah District's
2004 Standard Operating Procedure for Compensatory Mitigation (2004 SOP). Under the 2004
SOP, each bank was responsible for its own data management (typically in Excel or ArcGIS) and
there was no standard approach to organizing monitoring reports and data. Monitoring data
was typically submitted as hard copy reports and had to be extracted and manually entered
before it could be analyzed. In 2018, the Savannah District adopted a new SOP for
Compensatory Mitigation (2018 SOP). The 2018 SOP is a major overhaul of compensatory
mitigation in the state. It moves the District to a more function-based approach to mitigation,
using the Hydrogeomorphic Approach for wetlands (HGM) and the Stream Quantification Tool
for streams (SQT) as the frameworks for calculating credits for wetland and stream mitigation
2 The State of GA has a Stream Buffer Variance program. The Georgia Erosion and Sedimentation Act (12-
7-1) requires a 25-foot vegetated buffer along all state waters and a 50-foot vegetated buffer on state-
designated trout streams. A variance may be obtained to allow impacts within these buffers under certain
circumstances. Such a variance must be applied for and ultimately approved by the Georgia
Environmental Protection Division. However, this program does not include a compensatory mitigation
element.
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projects in the state. The Savannah District also reworked its monitoring and performance
requirements in 2018 with the 2018 Draft Monitoring Guidelines and Performance Standards for
Freshwater Wetlands and Non-Tidal Streams (2018 Monitoring Guidelines). Under the 2018
Monitoring Guidelines, monitoring data must now be submitted electronically via Excel
spreadsheet tools. Neither the 2004 SOP nor the 2018 SOP or associated guidance require long-
term performance or resiliency monitoring beyond that required by permit conditions.
Additional details on Georgia's program are available in Appendix B.
The goal of the pilot project was to build a prototype database and a web interface that
supports existing compensatory mitigation data while also providing a template for desired
new data collection. Specific tasks included: (1) bring together a working group of diverse
stakeholders involved in compensatory mitigation programs in Georgia to address the diverse
needs and common structures across stakeholders; (2) assess practices and standards for current
mitigation data collection, reporting, and use and inventory available datasets; (3) construct a
pilot geospatial database for mitigation monitoring and evaluation; and (4) generate a plan for
scaling up based on stakeholder input and challenges confronted during pilot database
construction. To accomplish these goals, 14 stakeholders involved in compensatory mitigation
in Georgia were assembled for two workshops to provide insight into the state of current data
collection and analysis, identify available datasets to populate the database, define database
goals and priorities, and provide feedback on database elements during the development
process. Due to the lack of consistency in historical data collection and reporting in Georgia
prior to the implementation of the 2018 SOP, the team focused much of their database
development efforts on creating data reporting standards for a range of metrics to facilitate
future analysis. Therefore, the priority of this pilot project became developing tools and
standards to facilitate future data analysis, rather than entering and analyzing trends in historic
data to draw conclusions about the effectiveness of compensatory mitigation programs in
Georgia.
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MAJOR OUTCOMES
Minnesota
The MDMS functionality allows users to upload vegetation and hydrology data associated
with long-term monitoring of wetland sites in Minnesota. For mitigation sites, long-term
monitoring data is associated with other information about the site in the BWSR wetland
banking application using a system derived site identification number as the primary key. The
site identification number is assigned during the regulatory review process and is used to link
all information in the BWSR wetland banking application collected during the mitigation site
lifecycle. This includes tabular and geospatial information about the review process,
monitoring, credits and transactions, and compliance inspections. Wetlands that are not
mitigation sites (reference or conservation) can also be assigned a site identification number in
the system to enable data uploads in the condition monitoring module. Using the site
identification number users can access the condition monitoring features of the application and
initiate the data upload process. The landing screen for uploading data, referred to as the
Condition Monitoring Header, is shown in Figure 2.
« Back to List
Condition Monitoring ID: 1340
Site ID Type Of Site
4953 q Replacement Site
Condition Monitoring Header Assessment Area Vegetation Hydrology
Monitoring Year Data Collected during Monitoring Period
2019 Vegetation
Save Condition Monitoring I Cancel
Created By
Created By Created Date
Add Monitoring Note
FIGURE 2: Minnesota Condition Monitoring Header landing page for uploading
monitoring data.
Using the data entry fields on the Condition Monitoring Header the user provides the year
monitoring data was collected and the type of data collected. Data uploads are then completed
using the Assessment Area and Vegetation tabs for vegetation data and the Hydrology tab for
water level measurements. Data upload is accomplished using standardized Microsoft Excel
spreadsheet templates for both types of data. Currently BWSR has developed five vegetation
upload templates (each recognizing different data collection methods) and two hydrology
templates (one for time series data and one for manual readings). The user interfaces for each
data type request additional information from the user to further define the data collection
methods and areas of the site where the information is collected. For vegetation data, the
Assessment Area tab is used to identify the boundaries of the area encompassed by the
monitoring using a GIS mapping tool as well as the opportunity to upload maps (in pdf format)
that show transect, meander, or plot locations within the assessment area. Specific information
about the vegetative data collected within the assessment area is entered under the Vegetation
tab. An example of the data capture screen for a circular plot with a 5-foot radius in a sedge
meadow community is provided in Figure 3. After entering the descriptive information about
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the sample method, the user can upload data using the templates mentioned previously. All
data submitted for upload are reviewed by an automatic data checker to ensure basic quality
assurance requirements are satisfied before files are accepted into the MDMS. The MDMS
provides specific information on fields that failed the data check to assist users with making
corrections. Hydrology data entry is completed following a similar process under the
Hydrology tab.
Sample ID Information
Assesment Area ID
Sample ID
4953 - 1
V
WEME-1
Community Type
Sample Method
2 - Fresh Wet Meadow
V
Meander v
Date Sampled
Plot Type Meander Type
08/06/2019
~
I
Circular Rectangle 1 Timed Not
Plot Circular Radius (ft)
Plot Rectangle Dimension (ft)
0
I 0
Meander Timed (minutes)
Meander Species
Shoreline Species
30
ALL
V V
Point Intecept Length (ft)
Point intecept Interval (ft)
0
0
Belt Transect Width (ft)
Belt Transect Length (ft)
0
0
Percent Bareground
Percent Litter Cover
I Percent Bareground J
Percent Inundated
Average Inundation ((in) or N/A)
Cancel
Upload Sample
Choose File No file chosen
FIGURE 3: Example MDMS data capture screen for vegetation data.
An overview of the data compilation, upload, and checking process used in the MDMS is
shown in Figure 4.
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FIGURE 4: Overview of data submittal and automated checking process.
The MDMS will be linked with a relational database3 maintained by the Minnesota Pollution
Control Agency to share hydrology data for mitigation sites with other groundwater data
collected and managed by the State of Minnesota. Ultimately, the monitoring data from the
MDMS will be publicly available through the Minnesota Cooperative Groundwater Proeram
managed by the Minnesota Department of Natural Resources. Through their web application
the public can view the location and type of monitoring well data available across the state
(Figure 5). Data can also be downloaded in several formats for further analysis.
3 The Minnesota Pollution Control Agency uses WISKI, a data management platform developed by
Kisters, to store and analyze water resources data.
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Cooperative Groundwater Monitoring (CGM)
Map View Table View Feedback
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FIGURE 5: Minnesota web viewer for accessing groundwater monitoring data.
When completed, a public facing web interface will show the locations and types of
condition monitoring data available across the State. Users will be able to identify sites of
interest and download the selected hydrology and/or vegetation data (Figure 6). The interface
also will include information on the location of approved wetland mitigation banks using
geospatial data collected and maintained by BWSR as part of the agency's wetland banking
review process and easement compliance activities.
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FIGURE 6: Interactive public viewer map showing attribute information. The header in
the map interface has links for downloading data.
Georgia
The Georgia pilot project developed products under each of its objectives that will provide
key benefits to compensatory mitigation evaluation both in Georgia and nationally. The Georgia
team hosted two stakeholder workshops to bring together a working group of diverse
stakeholders involved in compensatory mitigation programs to address needs and common
structures across stakeholders (Objective 1). The workshops included members of 14
organizations involved with or interested in compensatory mitigation in Georgia, and provided
a forum for participants to share insights into the state of current data collection and analysis,
identify available datasets to populate the database, define database goals and priorities, and
provide feedback on database elements during the development process (Objective 2). The team
compiled a spreadsheet of available spatial data for each bank to highlight locations where
spatial data is missing in current state databases to improve future data management (e.g.,
missing boundary polygon).
The main product developed through this project is a pilot interactive mitigation evaluation
database for the state of Georgia (Objective 3). The database will be published online, allowing
access to mitigation data upload, download, and visualization by all members of the Georgia
mitigation community including bank providers and regulatory agencies. The construction of
this database is a key step in the development of mitigation data entry standards for the state of
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Georgia. The web database application was developed using the RSQLite4 and R Shiny5
packages in the open-source statistical program R6.
The first tab of the online database (Figure 7) includes an interactive map depicting Georgia
mitigation banks, which allows users to zoom into areas of interest within the state. The
interactive map allows users to click on icons representing each bank to view site-level
information (e.g., acres, date established) and turn on other key spatial layers (e.g., service
areas) for the state of Georgia by checking boxes next to the name of each spatial layer in the
panel to the left of the map. Menus on the side panel also allow users to zoom to specific service
areas or banks of interest (Figure 8). Additionally, users can upload shapefiles containing the
locations of individual sampling sites within banks using the "Browse" button at the bottom of
the side panel on this tab. These shapefiles will ultimately be appended to a layer that will be
displayed on the map in this tab in future iterations of the database.
FIGURE 7: Georgia bank sites viewer.
4 KiriU Milller, Hadley Wickham, David A. James and Seth Falcon. 2020. RSQLite: 'SQLite' Interface for R.
R package version 2.2.1. https://CRAN.R-project.org/package=RSQLite
5 Winston Chang, Joe Cheng, JJ Allaire, Yihui Xie and Jonathan McPherson. 2020. Shiny: Web Application
Framework for R. R package version 1.5.0. https://CRAN.R-project.org/package=shiny
6 R Core Team. 2020. R: A language and environment for statistical computing. R Foundation for
Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
An Integrated Framework: Pilot Applications » March 2022
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FIGURE 8: Map zoomed into the AA Shaw mitigation bank.
The database also includes eight data entry tabs that facilitate the upload of multiple types
of data (e.g., vegetation, ground cover, groundwater hydrology, surface water hydrology,
macroinvertebrates, wetland large woody debris, stream large woody debris, and habitat-
assessment characteristics) into the database in standardized formats. On each tab, data can be
uploaded either as a batch by uploading a CSV file or entered manually as individual records in
a standardized form (Figure 9), When the user browses and selects a CSV file for batch upload,
the contents of the file will be previewed at the top of the screen (Figure 10). Data is appended
to the database when the user clicks the "Upload" button in the batch entry box or the "Submit"
button at the bottom of the form. While the batch upload tool is likely to be used for the vast
majority of data uploads, the inclusion of the manual data entry form on each tab was deemed
useful because it provides a helpful visualization to orient new users and facilitated discussion
about field modification with stakeholders during database development.
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s Map Vegciatan Ground -
? Water Hydrology MawomverteBrates Wi
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±, Download Data Entry Template
A Download M
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Community Type
Common Name
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£ Download Metadata
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Date
Time
Bank
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Sampling Plot
-
FIGURE 10: Example batch data upload.
QAQC protocols within the data entry forms were developed to flag potentially erroneous
records before they are entered into the database. In the manual data entry forms, field text
changes from black to red to alert the user that entered data is outside of the acceptable range
(Figure 13). Additionally, if the user attempts to upload data with QAQC issues, an error
message will be produced when the "Submit" button is pressed, alerting the user that the data
failed a QAQC check and cannot be appended to the database. An additional message alerts the
user to the specific field(s) that failed the QAQC check (Figure 14). The user must resolve these
QAQC issues to successfully upload data to the database. The batch data upload tools require
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data to pass the same QAQC protocols and produce similar error messages highlighting cells
that failed the protocols, forcing the user to correct the data to successfully upload it.
Temperature (degrees C)
pH
DO (mg/L)
Water Quality:
15
20
6
FIGURE 11: Example of field highlighted to alert user to QAQC issue ("pH" text in red).
Submit
There are problems with the entered data that prevented them from being imported into the database.
Resolve these errors before attempting to resubmit.
Entered pH value outside reasonable range (0-14).
FIGURE 12: Example of data submission error due to failing QAQC check.
To supplement the database, metadata spreadsheets for each data entry type, which include
QAQC protocols, units, and descriptions of all fields included in the database, are available for
download in the side panel of each tab (Figure 13). Additionally, to facilitate batch uploads,
CSV data templates can be downloaded from the side panel of each tab, allowing users to
ensure that fields are formatted correctly prior to entering and attempting to upload data
(Figure 14).
A B C D E F G H
1 Variable
Code
Question Type
Data Type
Min
Max
Units
Options
2 Date
DateV
Date
Date
1/1/1900
current date
N/A
N/A
3 Time
TimeV
Numeric
Numeric
0:00
24:00
24-hour format
N/A
4 Bank
BankID
Dropdown
Text
N/A
N/A
N/A
AA Shaw, Alaculsy, etc.
5 Assessment Area/Monitoring Unit
veg mu
Text
Text
N/A
N/A
N/A
N/A
6 Plot
PlotlDV
Text
Text
N/A
N/A
N/A
N/A
7 Latitude
PlotLatV
Numeric
Numeric
30
35
Decimal Degrees
N/A
8 Longitude
PlotLongV
Numeric
Numeric
-86
-80
Decimal Degrees
N/A
9 Reference Site
refSiteV
Checkbox
Numeric
0
1
N/A
0 = FALSE, 1 = TRUE
10 Ecoregion
ecoRegV
Dropdown
Text
N/A
N/A
N/A
Piedmont (ecoregion 45), Southeastern Plains (ecoregion 65), Blue Ridge
11 Sub-region
subReg65V
Dropdown
Text
N/A
N/A
N/A
Dougherty Plains (65g), Tifton Upland (65h), Atlantic Southern Loam Plain
12 Community Type
CommTypeV
Dropdown
Text
N/A
N/A
N/A
Freshwater Wetland, Saltwater Wetland, Riparian Zone, Upland Buffer
13 Genus
GenusV
Dropdown
Text
N/A
N/A
N/A
All plant genera included in USACE-NWPL list for GA
14 Species Scientific Name
SpSciV
Dropdown
Text
N/A
N/A
N/A
All plant species included in USACE-NWPL list for GA
15 Common Name
SpCommV
Auto-fill
Text
N/A
N/A
N/A
N/A
16 Height
tHeight
Numeric
Numeric
0
200
Feet
N/A
17 DBH
DBH
Numeric
Numeric
0
100
Inches
N/A
18 Age
tAge
Numeric
Numeric
0
1000
Years
N/A
19 Indicator Status Rating
IndStatusV
Dropdown
Text
N/A
N/A
N/A
OBL, FACW, FAC, FACU, UPL
20 Planted or Volunteer Status
PlantVol
Dropdown
Text
N/A
N/A
N/A
Planted, Volunteer
21 Exotic/Invasive Species
ExlnvV
Checkbox
Numeric
0
1
N/A
0 = FALSE, 1 = TRUE
22 Soil Series
soil Series V
Text
Text
N/A
N/A
N/A
N/A
23 jAdditional Comments
commentv
Text
Text
N/A
N/A
N/A
N/A
FIGURE 13: Excerpt from the Georgia vegetation metadata spreadsheet.
An Integrated Framework: Pilot Applications » March 2022
17
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A
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DateV
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3
4
5
FIGURE 14: Excerpt from the Georgia vegetation data template.
The database also includes a tab allowing users to view, query, and download existing data
stored within the database (Figure 15). On this tab, options are organized under headings for
each data type (e.g., vegetation, ground cover, etc.) Under each heading, data can be viewed by
clicking the "View Data" button, queried by field using dropdown menus (e.g., bank name),
and downloaded by clicking on the ''Download Data" button. The final database tab allows
users to plot data stored in the database to facilitate visualization and analysis of data trends
(Figure 16). This tool allows individual data fields to be selected for analysis and additional
fields to be selected to group data. It also allows the user to specify the type of plot to use for
data visualization.
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\rtew Ground Cover Data
A Download Ground Cover Data
FIGURE 15: Data viewer tab, which allows data to be viewed, queried, and
downloaded.
An Integrated Framework: Pilot Applications » March 2022
18
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ly Debris Strea
Habitat Assessment Data Viewer Graphical Analysis
Select Options
Boxplot
I-
FIGURE 16: Graphical analysis tab, which allows data to be plotted for trend analysis.
Finally, the Georgia team produced a plan for scaling-up the database based on stakeholder
input, lessons learned, and capacities developed through this pilot project (Objective 4). The
plan for scaling-up the Georgia database was divided into three phases. Phase 1 encompasses
pilot database development, which was accomplished under Objective 3 of the current project.
Phase 2, which will last two years, will focus on implementing a soft launch of the database,
beta testing, and iteratively building-out the database based on stakeholder feedback. During
this phase, the team will work with USACE and other partners to lay the groundwork for
requiring database use as part of the formal reporting process under mitigation evaluation
guidelines, select a permanent host for the database, and design a funding model for long-term
maintenance and hosting of the database. Phase 2 will conclude with the launch of the finalized
database for use by all partners and the transition to the permanent hosting arrangement. Phase
3, which will begin at the conclusion of Phase 2, represents long-term hosting and maintenance
of the database. This phase will require regular maintenance and user support,
software/hosting updates, and adapting the database to meet evolving user needs. We estimate
that these Phase 3 tasks will require about 20% of a data manager's time. Specific details about
the plans for scaling-up and implementing Georgia's database can be found in Appendix B. The
plans will also be circulated to all members of the Georgia mitigation community.
An Integrated Framework: Pilot Applications » March 2022
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COMPATIBILITY OF DATA PRODUCTS
A long-term goal of the Framework is to develop capability to combine mitigation datasets
from different state programs to be able to compare results among regions and assess overall
condition on a regional or national level. To combine datasets from different agencies, the data
needs to be in a similar format, or have data structures that can easily be matched or
transformed (e.g., units) to correspond with variables across agencies. We used the preliminary
results from the two pilot projects to evaluate the ability to combine data sets and to inform
recommendations for future development of data tools.
In this section we evaluate the ability and effort required to combine completed vegetation
data templates from mitigation projects in Georgia and Minnesota. This included one Excel file
of database output from GA that had data for two example mitigation plots, and nine Excel files
from MN, each with data for a separate plot.
Direct merging of all files as they currently exist is not possible, mostly due to differences in
the assessment endpoints used. Some of the files expressed vegetation as a density (number of
individual plant species per unit area), while other files used absolute cover (%) of each species,
and one dataset used height and age (counts would be available by adding up the individuals
of a species). These differences presumably reflect different mitigation performance objectives
or data collection methods. Combining all datasets would be possible if a standard unit of
measurement was used for each species, to derive either counts or percent cover for the data.
Other key differences among the files were the inclusion/ omission of a sample date column
and columns for site coordinates. Sample date is usually an important variable to include with
all field data. It can be used to help combine additional indicators from a particular sampling
period, or to help keep track of a mitigation project's age and succession. GIS data on the other
hand may be included with the field data or maintained in a separate file that can be referenced
by a plot (subplot) identification code.
The last difference to note among datasets is that some files had vegetation strata (e.g., tree,
herbaceous, shrub-sapling) in separate sheets, while other files combined all strata
measurements into a single sheet. While this would require additional effort to combine
datasets, the type of data structure to use should be left to each agency to decide.
In conclusion, use of standard data templates and metadata forms made it easy to access
and interpret the data from each state program. However, the ability to combine data sets to
provide more integrative assessments would require states to adopt common data formats and
assessment endpoints. Standard data formats developed through the National Wetlands
Condition Assessment and National Rivers and Streams Assessment could form the basis of
such standardization in the future.
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HOW PILOT PROJECTS HAVE SUPPORTED APPLICATION OF THE
FRAMEWORK
The intent of each pilot project was to demonstrate how investing in data management can
help address the core questions of the Framework and establish a foundation for continued
development of state capacity to evaluate mitigation program effectiveness.
1. How successful are mitigation sites/banks at achieving their ecological goals?
2. How effective has the overall program been at achieving its stated goals with respect to
aquatic resource protection?
3. How resilient are compensatory mitigation sites/banks at replacing the intended
functions over the long term?
Minnesota
With the enactment of WCA in 1991, the State of Minnesota expanded protection to
wetlands not covered under a more limited permit program focused on lakes, streams, and
large wetlands with persistent surface water. The new law established a goal of no net loss of
the State's remaining wetlands. The comprehensive state approach to wetland protection
combined with the requirements of the Clean Water Act Section 404 permitting program have
created a regulatory framework where most wetland impacts require authorization as well as
replacement of lost functions. With over 25 years of experience implementing these programs
Minnesota has a wealth of information from which to evaluate the success in meeting protection
goals such as no net loss. Since the inception of WCA data show that the State has met the goal
of no net-loss of wetland area statewide, but it is unclear if wetland quality and function have
been maintained. A review of wetlands between 2006-2014 observed no-net loss in area;
however, concerns were raised regarding loss of wetland function due to conversions of
wetland type7. A more recent study concluded that quality of depressional wetland mitigation
sites 7-16 years after restoration was similar to quality observed in naturally occurring wetlands
within the same region8. The evaluation of mitigation project success on a comprehensive,
statewide basis has suffered from the same challenges seen in other states: disorganized data
storage, varying report formats and mediums, and the absence of a structured approach and
staff dedicated to a programmatic review of mitigation performance and assessment.
7 Kloiber, S.M. and D.J. Norris. 2017. Monitoring Changes in Minnesota Wetland Area and Type from
2006-2014. Wetland Science and Practice 34: 76-87.
8 Strojny, C., J. Overland, and T. Smith. 2020. Assessing Wetland Quality of Depressional Wetlands to
Refine Restoration Requirements and. Strategies. Report for Grant No. CD-00E02072). Minnesota Board of
Water and Soil Resources. https://bwsr.state.mn.us/sites/default/files/2020-ll/CD%20-
% 2000E02072 % 20Final% 20Project % 20Report % 2030Qct20.pdf
An Integrated Framework: Pilot Applications » March 2022 21
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This pilot study has moved Minnesota forward in this context by supporting development
of a data management system that, coupled with planned changes to the monitoring and
reporting done during the mitigation site establishment period, will allow regular evaluations
of program effectiveness and site resiliency. In addition, the structure of the MDMS allows for
these evaluations to be conducted by agency staff directly involved in program implementation
as well as individuals and organizations external to the regulatory programs. Although this
pilot was specifically directed at building the infrastructure to collect and store mitigation site
data and did not involve collection of field data to assess performance, BWSR is engaged in
other efforts partially funded by the EPA to assess resiliency of mitigation sites. The data
produced by these parallel efforts will be the first uploaded to the MDMS beginning in 2021.
When the upload is completed, the MDMS will have vegetation community data for over 50
wetland bank sites across the state and hydrology data from 15 of these sites. Without
development of the MDMS this information would be mostly unavailable outside of BWSR and
would likely be lost for future assessments of resiliency because of the challenges associated
with storage.
Georgia
Analysis of historical (pre-2018) mitigation data has been an immense challenge for agencies
because the data were usually submitted in hard copy or PDF reports, meaning that data must
be extracted and entered manually, which is a very inefficient process, and coupled with the
volume of reports generated makes analysis very challenging. While the initial goal for the GA
pilot database project was to begin addressing this issue by populating the database with
historical data from a subset of sites to provide preliminary assessments of the ecological effects
and resiliency of mitigation banks in Georgia, the project shifted focus away from this objective
at the recommendation of several of key stakeholders, who believed that the lack of historical
data standardization would make analysis of trends difficult or potentially misleading.
Stakeholders noted that there historically was no standardized way to organize monitoring
reports and collect and report many types of mitigation data in Georgia, and that the regulatory
and scientific framework for data collection and reporting has evolved considerably over time,
which would make comparisons between banks over time difficult to interpret. Thus, the pilot
project focused largely on developing data compilation and entry standards to facilitate upload
of current and future data into the electronic database, which will facilitate future mitigation
evaluation in Georgia and permit the effectiveness of mitigation banks to meet ecological goals
to be better assessed.
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LESSONS LEARNED AND RECOMMENDATIONS
The two pilot projects were largely successful in that they (1) increased awareness and
knowledge among agency staff and key partners on the needs and importance of managing
compensatory mitigation data in a systematic way; (2) produced prototype systems that vastly
improved data management capabilities; (3) provide a foundation for continued development
and implementation of data management systems that will enhance the ability to answer the
key management questions about compensatory mitigation program effectiveness; and (4) serve
as examples for other states and programs that are considering developing their own wetland
data management systems.
These projects generated important lessons that can inform continued pursuit of the goals of
the Framework nationwide. The lessons learned, and associated recommendations have been
grouped into three major categories of project management, technical approach, and
stakeholder coordination (Table 1).
TABLE 1: Summary of key challenges and potential solutions identified during the
case studies
Issue
Potential Solution
Project Management and Scoping
1
Desired objectives and product end points
may not be clearly defined at the onset of
the project from an IT/ database
architecture perspective
Clearly relate effort to programmatic goals.
Consider utilizing user stories and clear
descriptions when documenting
specifications and work flows to provide as
much detail as possible early in the process
2
Data access tools may be inconsistent with
agency permissions and data policies
Scope development efforts to address access
needs, such as server and firewall issues.
Consult early to ensure appropriate data
access specifications are included
3
Data products and formats may not
directly address key questions
Include end users in development process
4
Third party IT contractors have limited
familiarity with program scope and
operations
Consider requiring vendors to have subject
matter experts on team
5
Concern over the ability to manage and
update the system over time as
technology changes
Explore the use of standard formats or off-
the-shelf applications with standard
approaches vs. customized development
6
Costs and staff capacity for long term
hosting and maintenance
Identify an agency hosted site or third party
location (e.g., university) with dedicated
funding or revenue source (e.g., fees)
Technical Approach
An Integrated Framework: Pilot Applications » March 2022
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Issue
Potential Solution
/
DiHiLullies in including legacy da La due
to changes in data collection metrics,
standards, and quality
Ideality aad priorilize key legacy da la sels
aad provide resources to digitize; focus
database oa preseat/ future rather thaa
trying to retrofit old data
8
Challenges with assessing long-term
function/performance
Connect products with other available,
current monitoring programs/data
9
Mechanism for data sharing/ exchange
with RIBITS or other data systems
Establish uaiversal digital object ideatifier
(DOI) or other uaique ideatifiers and ideatify
key data fields aad coordinate via web
services or applicatioa program interfaces
(APIs)
10
Requirements for spatial and tabular data
upload/ storage are very different and
could require different user interfaces
Ideatify data types aad aeeds early aad
collaborate with IT staff to develop a
workflow process aad schematic that defines
desired iaputs aad outputs and the
relatioaships betweea spatial aad tabular
data.
11
Long-term monitoring data and
mitigation site establishment data may
have different objectives and/ or varying
collection methodologies
Ideatify core set of moaitoring data for short-
aad loag-term assessmeats aad develop
staadardized methods
12
Need to make data collected at multiple
sub-sites within each bank site (e.g., veg.
plots) spatially explicit to facilitate post-
hoc analysis, but these locations do not
exist in single, standardized database
Create tool to allow baaks to upload sub-site
locatioas directly into the database as
shapefiles or provide the ability to directly
eater spatial information via points or
polygoas
14
Monitoring approaches are not
standardized, and data collected for many
metrics (e.g., vegetation) are not
submitted in standardized formats across
banks.
Create staadardized data eatry forms as part
of the database using most up to date
staadards. Require data uploads to be
staadardized using either dowaloadable
excel templates or a user interface within the
applicatioa. Doa't focus oa matching
specifics from pre-existing data sheets
15
Need capability for "batch data upload
tools" for many data entry types that
require numerous inputs per site (e.g.,
macroinvertebrates, hydrology,
vegetation) so that records don't need to
be entered one at a time
Prioritize batch upload tool developmeat
aad creatioa of dowaloadable excel
templates to standardize formatting over
developmeat of single-entry forms in
database app
Stakeholder Coordination and Outreach
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Issue
Potential Solution
lb
Coordination wilh oilier bLilc agenues
collecting and managing similar
monitoring data
Identify PLXJs Ihroughoul sidle dgenues
with overlapping program areas early in
process and involve IT staff in these
discussions
17
Need to identify sentinel/ reference sites
with good long-term datasets to guide
planning/ assessment of other sites
Explore opportunities to partner/leverage
other programs that may provide sentinel
sites, e.g., ambient monitoring program,
conservation programs. Consider
development of regional reference site
networks using a fee-based approach
18
Stakeholders' primary goal for the
database is the ability to
obtain/ download raw data. Online
analytical tools are a secondary priority.
Focus on aspects of the database that
facilitate dataset querying and acquisition
first, then create a few key example analytical
tools, which can facilitate future discussion
about developing an expanded suite of tools
19
Skepticism in user community about
quality of older/ existing data
Focus on future data collection and prioritize
a selected set of past data to determine
challenges and identify benefits of analyzing
older data
20
Achieving consensus from stakeholder
community on data input structure,
priorities, and functionality of the
database
Conduct outreach workshops to gain input
and investment in products early in the
process. Meet with key personnel to discuss
examples and ideas for standardization and
implementation protocols
21
Creating time-efficient opportunities for
regular stakeholder engagement and
feedback on database development.
Prioritize regular meetings with small
groups of key stakeholders to share
development progress and solicit feedback,
which can allow more time for dialogue and
reduce "information overload." Provide
regular email updates to keep stakeholders
engaged during periods when there is less
tangible progress to showcase.
Scoping, Project Management and General Implementation
Agreeing on a clear set of goals and expectations and selecting (or building) the right project
team are important early steps that influence progress and ultimate success of the project. Both
teams emphasized the importance of early and frequent communication with their stakeholders
to clearly define goals and establish a common vision for the desired outcomes and
functionality. This vision is often refined over the course of a project, so ongoing
communication is critical for ultimate success. The Georgia team invested time with
stakeholders and end-users to build consensus around focused goals and well-defined end
An Integrated Framework: Pilot Applications » March 2022
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products. This not only built support for the project but established common expectations for
the functionality of the products relative to the ability to address agreed upon questions/needs.
However, they focused much of their effort on less frequent, larger stakeholder meetings and
would have benefitted from increased communication with small groups of key stakeholders at
more regular intervals between larger meetings to create more opportunities for iterative
feedback on database development.
The Minnesota team outsourced the technical work to a third-party vendor. The Request for
Proposal that was published for the wetland application did not require that the developer have
individuals with wetland regulatory program familiarity or experience on their team nor did it
require expertise working with GIS/Mapping programs. These were both identified as desired
qualifications but were not required. The selected vendor did not have this expertise on their
team which created significant communication issues associated with wetland mitigation
terminology and familiarity with general program workflows. As a result, BWSR staff had to
invest additional time to correct issues with functionality stemming from lack of subject matter
expertise by the contractor.
Using off-the-shelf platforms for developing the data management system generally results
in lower cost and greater longevity regardless of whether the work is done in house or
outsourced. There are numerous data platforms that are commonly used and can be easily
customized. These systems are typically more stable over time and can be more readily
updated. Using such systems also reduces the likelihood of creating a system that is difficult to
update or becomes obsolete due to its reliance on specific expertise or familiarity. However, the
Minnesota case study lost some of the flexibility associated with developing a standalone
version of their data system because vendors and state information technology staff gravitated
towards consistency in approach for the entire application rather than making use of off-the
shelf software that may have been more efficient or practicable for a single purpose application.
Finally, because all systems must be maintained and updated over time, it is critical to
identify the intended long-term steward of the products and involve them in the scoping
process. This will ensure that ease of maintenance is considered in the design and improve
familiarity with the ultimate product by the entity ultimately charged with implementation. For
states such as Minnesota that have an established program and internal state capacity, long-
term stewardship can be incorporated into existing information technology programs and
maintained using state resources or permit related fees. For states such as Georgia that lack an
established program, a third party, such as university or local agency or conservancy may be
able to serve as a long-term data steward. Reaching this stage in Georgia will require a two-year
intermediate phase focused on a soft launch of the database, beta testing, database build out,
and implementation. This phase will require a full-time database manager, along with
additional staff support and web hosting service fees, which in total are estimated to cost
approximately $120,000 annually. Long-term hosting and management of the database beyond
the intermediate phase will require funding for a web hosting service and a significant portion
of a database manager's time (estimated approximately 20%) to perform regular maintenance
and user support, software and hosting updates, and adapt the database to evolving user needs,
An Integrated Framework: Pilot Applications » March 2022
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which is estimated to cost approximately $26,000 annually. For such a program to succeed
permitting agencies (e.g., ACOE, State programs) should require mitigation monitoring data to
be submitted to the designated database in specified formats (or using specified templates). In
addition, the data stewardship entity will need a funding mechanism to maintain the data
system (e.g., fees, grants, or dedicated internal funding).
Technical Approach
Creating standard data templates and mechanisms for data queries, access and linkages can
address many of the technical challenges associated with developing data management
systems. Both pilot projects identified a broad range of data types that can be produced in
different formats (e.g., tabular, spatial, time series). Creating standard data templates in flat-file
format was found to provide the maximum flexibility in accommodating a variety of data types.
This approach can accommodate batch upload of data in addition to data entry via a user
interface, which was a desire articulated by many stakeholders. Standard data templates also
allow for the development of automated data checkers and automated data analysis, which can
improve data quality and support timely and readily available data analysis.
Both pilot projects also identified a priority for providing linkages with other data systems
through web services or application program interfaces (APIs). Such linkages can support
connections with other data sets, such as hydrology data sets collected by the Department of
Natural Resources in Minnesota. They can also make it easier to connect with existing wetland
data sets, such as those maintained by US Fish and Wildlife Service and private bankers in
Georgia.
How to accommodate legacy data was a challenge for both case studies. There is broad
agreement of the important context provided by historic data sets, particularly for questions of
resiliency and long-term success. However, integrating these data sets is challenged by lack of
compatibility in data formats or unavailability of older data in digital form. One potential
solution is to identify priority legacy data sets and use them to demonstrate the process,
challenges, and benefit of incorporating them into contemporary data systems. These initial
experiences can be used to determine which data sets provide sufficient benefit to warrant the
investment necessary to integrate them into current data systems and to develop a strategy for
accomplishing this integration. It has a secondary benefit of aiding in tool development by
providing test data that can be used to refine data structures and analytical methods.
Stakeholder Coordination and Outreach
Conducting outreach workshops to gain input and investment in products early in the
process is critical to eventual acceptance and use of any data management system. Both pilot
study teams met with key personnel to discuss examples and ideas for standardization and
implementation protocols early in the process. The Georgia team would recommend balancing
larger workshops with more frequent, targeted meetings with key stakeholders to allow more
opportunities for specific feedback on database development and modification and reduce
An Integrated Framework: Pilot Applications » March 2022
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"information overload." In Minnesota, additional coordination would have been beneficial as
well. Because of scheduling issues during development of the MDMS, BWSR staff was not able
to include a stakeholder coordination task in the contractor's scope of work and was forced to
independently make decisions on data collection methods, standardization, and reporting that
may have been better discussed in a broader interagency forum. In the future, they recommend
a more coordinated up-front approach to identify stakeholder needs in advance of project
scoping and establishment of a standing interagency workgroup to provide input when needed
during the process. This would also be beneficial in adjusting agency policy to orient the state
and federal wetland mitigation programs to direct monitoring data towards the local data
management system and having it serve as a repository for all long-term monitoring data.
Sentinel sites provide important context for assessing resiliency of compensatory mitigation
sites and long-term program success. These sites can often come from other programs such as
ambient monitoring under water quality programs, status and trends sites, or conservation sites
from wildlife or sensitive species protection programs. Considerable long-term benefit can be
achieved by broadly surveying agency and community programs, watershed plans, and
stakeholder groups to identify candidate sentinel sites with permanent protection or
management. This allows targeted effort and resource allocation at sites with the greatest
potential benefit for long-term monitoring. Early and ongoing communication helps identify
these partnership opportunities, build collaborations, and account for data sharing between
programs in design of the data management system from the onset of the program
development process. For example, in Minnesota the Department of Natural Resources has
assumed the lead role in establishing wetland hydrology reference sites across the state to
gather data that can be used in permit decisions, mitigation site assessment, and long-term
trend analysis. Other state and federal agencies have participated in the site selection process
and the data will be available through the State's Cooperative Groundwater Monitoring
Program.
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FUTURE EFFORTS
Conclusion of the pilot project does not constitute completion of the desired work for either
state. Both states hope to build on the foundation of their initial efforts and continue to enhance
their data management systems to support evaluation of compensatory mitigation. Future
efforts will include:
• Expanding standard data templates and checkers to include additional data types
• Providing expanded functionality for batch uploads of data
• Improving capacity to accept and manage geospatial data
• Retrofitting historical data for inclusion in the data management system
• Expanding data query capabilities to better cross-link different data types and sources
• Developing tools to facilitate graphical analysis of data trends
• Automating routine data analyses to hasten output to end-users
• Securing commitments and funding for long term hosting and stewardship
• Enhancing dynamic data linkages with other data systems to better leverage data
between programs
Robust data management is an important tool for full implementation of all three modules
of the Framework, performance evaluation, program effectiveness assessment, and
determination of long-term resiliency. A mature compensatory mitigation evaluation program
will include infrastructure, staffing, funding, and partnerships necessary to support all three
modules and to provide ready access to the data and information produced through these
evaluations. This will in turn allow for ongoing program refinement and ongoing evaluation.
As states work to improve their capacity for managing and analyzing data to assess
compensatory mitigation effectiveness, USEPA will need to develop tools and approaches to
synthesize state data into regional or national data sets. This will involve aligning and
reconciling data fields, checking data accuracy and completeness, and compiling metadata
(among other challenges). Only through development of these tools will larger/national
evaluations of compensatory mitigation program effectiveness be possible.
Next Steps for Minnesota Program
Technical
• Link the newly developed database to a groundwater monitoring database managed by
other state agencies such that hydrology data collected at wetland mitigation sites will
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be stored in a larger statewide database that can be accessed through a web-based
application.
• Develop capacity for vegetation data to be accessible to external users (outside of BWSR)
through a web-based interface. Although this data will not be integrated with wetland
condition data collected by other agency staff in Minnesota it does provide a platform to
build on and satisfies a short-term goal of organizing the data and making it available
through a web-based interface.
• Upload data collected as part of recent long-term monitoring studies. Working with the
other state and federal agencies in Minnesota establish a requirement for mitigation sites
leaving the establishing monitoring period to provide standardized vegetation and
hydrology data that will serve as a baseline for future monitoring as part of assessing
site resiliency.
• Establish a process for determining historical wetland mitigation sites for which
establishment data will be obtained from files and loaded into the MDMS.
• Develop automated quality control process to verify well identification number
provided by the MDMS user is associated with the location information for the
identification number in the state database.
Testine / Refinement
• Develop a protocol to integrate taxonomic changes into the MDMS data checker.
• Increase MDMS functionality by adding the ability to calculate standard metrics of
interest such as percent native cover, native species richness, and measures of floristic
quality.
• Enhance user interface for accessing uploaded vegetation and hydrology data through
improvements to BWSR website and GIS web maps.
Outreach
• Once long-term monitoring data processes have been established and successfully
implemented, efforts will be directed toward integrating reporting and data collection
from the establishment period into the MDMS so that all monitoring data for mitigation
sites can be collected and stored in one location.
• Provide training to stakeholders on access to, and use of, the MDMS to increase
awareness and familiarity.
Next Steps for Georgia Program
Technical
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• Develop general user instructions document to serve as a database homepage to guide
new users.
• Work with stakeholders to fine-tune QAQC protocols for specific data fields and locate
missing spatial data (e.g., bank boundaries) for inclusion in the database.
• Expand QAQC protocols (e.g., coordinate system) for sampling site shapefile upload
tool.
• Create additional query fields in data viewer tab to allow users to better filter data by
fields of interest.
• Expand pilot graphical analysis tool to better allow users to explore trends in data.
• Decide on best way to link vegetation data with soil series (currently there is a
placeholder text field).
Testine / Refinement
• Allow stakeholders to begin uploading sample datasets to beta test database and allow
them to provide feedback on processes that were unclear or bugs that they encountered,
which can then be iteratively addressed.
Outreach
• Circulate plan for beta testing, "going live," and scaling up the database within Georgia
mitigation community.
• Once technical and testing objectives have been accomplished, share the link to the
online database with all stakeholders in the GA mitigation community and encourage
them to begin uploading recent datasets.
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APPENDIX A: OVERVIEW OF MINNESOTA PILOT PROJECT
Section 1 Agency Overview
1,1 Key agencies and general structure
Alterations to lakes, rivers, streams and wetlands in Minnesota are regulated by a mix of
programs administered by state and local governments. The main state water/wetland
regulatory programs in
Minnesota is described briefly below.
• CWA Section 401 - authorizes state agencies to impose conditions or prevent issuance of
Section 404 permits to ensure compliance with state water quality requirements;
administered by the Minnesota Pollution Control Agency (MPCA).
• Public Waters Permit Program (PWPP) - regulates alterations to the course, current or
cross section of public waters and public waters wetlands; administered by the
Minnesota Department of Natural Resources (DNR). Public waters are a defined subset
of all lakes, streams and wetlands meeting certain criteria.
• Water quality standards - regulates point source and non-point source discharges and
physical alterations of wetlands. Generally applied through other regulatory programs,
such as National Pollutant Discharge Elimination System (NPDES) permits or Section
404 permits. Administered by the MPCA.
• Wetland Conservation Act (WCA) - regulates draining, filling, and in some cases
excavation in all wetlands exclusive of public waters wetlands; administered by local
governments with oversight from the Minnesota Board of Water and Soil resources
(BWSR). In state statute and rule, authorizations under WCA to impact wetlands are not
referred to as "permits" - impacts are authorized under exemptions, no-loss
determinations and wetland replacement plans.
Although the agencies administering each of these programs have the authority to require
mitigation to offset approved impacts to waters/wetlands by far the most active program with
respect to mitigation is WCA. Referred to as wetland replacement under this program, WCA
requires that no person may impact a wetland, wholly or partially, without being eligible for an
exemption, receiving a no-loss determination, or first having a wetland replacement plan
approved by the local government unit. The requirement for replacement for most wetland
impacts under WCA creates a significant demand for wetland replacement. In calendar year
2018, WCA local government units approved 175 replacement plans (i.e., permits) resulting in
84.23 acres of wetland impact. This does not include wetland impacts associated with local
government road improvement projects which, based on historical wetland credit usage, would
double this impact amount. Responsibility for the monitoring of wetland replacement sites (i.e.,
mitigation site) is divided based on the time that has elapsed since construction. The
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establishment period, roughly defined as the time from construction through the fifth full
growing season, is done by the mitigation project sponsor with review and oversight provided
by ACOE, BVVSR, DNR, and the local government unit with jurisdiction over the site under
WCA. After the establishment period, BWSR takes over long-term monitoring with the focus
primarily on compliance with the conservation easement recorded in favor of the State of
Minnesota.
1.2 Authorities
1.2.1 Minnesota Wetland Conservation Act
The Minnesota Wetland Conservation Act (WCA) was enacted in 1991 to protect wetlands
not protected under DNR's public waters permit program and to provide no net loss of
Minnesota's remaining wetlands. The basic requirement is that "[w]etlands must not be drained
or filled, wholly or partially, unless replaced by restoring or creating wetland areas of at least
equal public value under a[n approved] replacement plan." (Minn. Stat. § 103G.222, subd. 1(a)).
As a result of legislation adopted in 2000, the WCA also applies to excavation in permanently
and semi permanently flooded areas of types 3, 4, and 5 wetlands (See Minn. Stat. §103G.222,
subd. 1).
1.2.2 Minnesota DNR Public Wafers Permit Program (MnDNR PWPP)
Work in public waters has been regulated by the Minnesota Department of Natural
Resources ("DNR"), or its predecessor the Department of Conservation, since 1937. The basic
rule is that a public waters work permit must be obtained from the DNR for work affecting the
course, current, or cross-section of public waters, including public waters wetlands (See Minn.
Stat. § 103G.245, subd. 1(2)). This would include, for example, work involving draining, filling,
excavating, and placing structures in public waters wetlands.
Public waters wetlands are a subset of the broader category of "public waters" regulated by
the DNR, which includes most lakes and larger streams and rivers. Public waters and wetlands
have been inventoried by the DNR and are shown on maps for each county. Public waters
wetlands are defined in statute as follows:
"Public waters wetlands" means all types 3, 4, and 5 wetlands, as defined in United
States Fish and Wildlife Service Circular No. 39 (1971 edition), not included within the
definition of public waters, that are ten or more acres in size in unincorporated areas or
2-1/2 or more acres in incorporated areas."
In general, PWPP rules stipulate that, "The commissioner may not issue a permit that causes
pollution, impairment, or destruction of the air, water, land, or other natural resources so long
as there is a feasible and prudent alternative consistent with the reasonable requirements of the
public health, safety, and welfare."
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1.3 General goals and mandates
The purpose of the WCA is to:
a. achieve no net loss in the quantity, quality, and biological diversity of Minnesota's
existing wetlands;
b. increase the quantity, quality, and biological diversity of Minnesota's wetlands by
restoring or enhancing diminished or drained wetlands;
c. avoid direct or indirect impacts from activities that destroy or diminish the quantity,
quality, and biological diversity of wetlands; and
d. replace wetland values where avoidance of activity is not feasible and prudent.
Applicants seeking to impact a wetland where submission of a replacement is required must
demonstrate that they have exhausted all possibilities to avoid and minimize wetland impacts
according to the sequencing requirements codified in rule. In addition, the applicant must also
provide information documenting that the replacement site meets the standards and guidelines
in rule to ensure adequate replacement of wetland function and value.
Section 2 Overview of mitigation components of the state program
2.1 The Minnesota Wetland Bank
Under Section 404 of the Clean Water Act and Minnesota state regulatory programs,
unavoidable wetland impacts are potentially subject to compensatory mitigation unless a
specific exemption from this requirement exists. As the name implies, the goal of compensatory
mitigation, or wetland replacement, is to compensate for or replace the functions and values
that the impacted wetland provides. Minnesota state agencies and the ACOE have worked
together for many years to achieve consistency between state and federal policy regarding
compensatory wetland mitigation, and the ability of the COE to adapt their more flexible policy
to changes in WCA rules has contributed to this consistency. In most instances, wetland
mitigation projects that meet state requirements will also meet federal requirements and vice
versa. Minor differences are generally the result of inconsistencies between COE, St. Paul
District policy and WCA rules, rather than conflicts between state statutes and the Federal
Mitigation Rule.
Both the state and federal regulatory programs in Minnesota have a stated preference in
regulation/rule for mitigation that is completed in advance of the authorized impacts.
Although some permittee responsible, or project-specific, mitigation is still used today the vast
majority of the wetland mitigation in Minnesota is accomplished through wetland banking.
Minnesota has one of the most active and robust wetland banking markets in the country with
an estimated 400 wetland banks approved since inception of the Minnesota State Wetland bank
in the 1990s. The strong demand for credits affects both the project development part of the
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program and the transaction side of the program. The state has documented a significant
increase in the number of wetland bank documents submitted for review over the past three
years with just over 80 different submittals in 2019. On the transaction side, staff at BWSR have
processed approximately 305 wetland banking transactions per year (withdrawals, deposits,
and transfers) between 2015 and 2019. Despite a strong wetland banking program and the high
volume of wetland banking activity BWSR is pursuing an in-lieu fee (ILF) program. The ILF is
specifically designed to service public transportation projects to assist local and state road
authorities with obtaining mitigation credits for projects in a predictable and efficient manner.
2.2 Number of Mitigation. Sites included
Once the MDMS is open for production in 2021, BWSR staff will begin entering data for sites
that have been the focus of three recent USEPA grants focused on long-term condition
monitoring of restored wetlands. Two of these grants are directed specifically at vegetative
quality and the other is looking at hydrology. Results from the completed study can be found
on BWSR's website. This BWSR led effort will result in long-term vegetative monitoring data
(from 5 to 15 years post-construction) for approximately 50 wetland bank sites to be publicly
available. In addition, hydrology data for 15 wetland bank sites in southern and southwestern
Minnesota will also be uploaded and available. The MDMS also will be accessible for other
agency staff and consultants to upload data on a voluntary basis. Additional coordination will
be conducted in the near future to establish and implement procedures that will require
wetland bank sponsors to collect and submit monitoring data into the MDMS for their projects
as part of each site's monitoring requirement.
2.3 Timeframe covered by assessments
Post-construction monitoring of mitigation sites in Minnesota is the responsibility of
multiple parties depending on the type of compensation site and the time that has elapsed since
construction was completed. All mitigation sites in Minnesota are monitored from the time
construction activities are completed (earthwork and initial vegetation establishment) until the
site has met performance standards as determined by the federal, state, and local agencies with
jurisdiction over the site. This is referred to as the establishment period. For wetland banks,
both the federal and state programs require the site to be monitored for five years unless there is
justification for a longer duration (e.g., wooded sites or bog restorations). Permittee responsible,
or project specific, mitigation sites have less stringent monitoring requirements but still must
demonstrate that the site has achieved the functional goals established in the approved
mitigation plan. Establishment period monitoring is the responsibility of the wetland bank
sponsor or the permittee in the case of project specific mitigation. Once the establishment
monitoring period has ended the site enters what is referred to as the long-term monitoring
phase. Long-term monitoring is handled differently for project specific and wetland banking
sites.
Once the establishment period has concluded project specific mitigation sites are only
monitored if a regulatory agency randomly conducts an inspection or if a specific issue is
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identified that requires attention. Follow-up assessments to evaluate resiliency and overall
functional condition for permittee responsible mitigation are infrequently performed by state
and local agencies implementing WCA. Specifics regarding follow-up assessments by federal
agency staff are not available but is assumed they are equally as infrequent.
Wetland bank sites in Minnesota are subjected to a more structured inspection approach
because of a rule that requires BWSR to periodically inspect wetlands associated with the
wetland banking program to ensure that easement conditions are being met. The frequency is
not specific in rule but BWSR has loosely adopted an approach that sets a goal of conducting at
least a desktop review of each site every three to five years. Site visits are conducted where a
desktop assessment identifies a potential issue at a site. The periodic inspections have not been
focused on collecting site data to assess wetland condition in the context of resiliency. Instead,
the inspections have focused on easement violations such as encroachment, vegetation
alteration, signage requirements, trails, and structure maintenance and modification. BWSR's
approach to long-term monitoring changed significantly in 2016 when the EPA awarded a
Wetland Program Development Grant (WPDG) to assess the long-term condition of wetland
mitigation sites, wetlands restored for other conservation programs, and unrestored reference
wetlands. The study, which concluded in 2020, focused on the mixed woods plains and
temperate prairies ecoregions of Minnesota and documented vegetative community condition
at 32 wetland bank sites. Although resiliency is not mentioned specifically in the grant
application, one of the primary objectives of the 2016 study is to assess this mitigation site
attribute by focusing on sites that were 7-16 years post restoration. The study focused on
depressional wetlands and found mitigation sites to have similar floristic quality as naturally
occurring sites. In recognition of the value of the 2016 study, BWSR has received additional
WPDGs from the EPA to study hydrology of restored sites in the same geographic area of the
2016 effort (focusing on many of the same sites) and to continue vegetative condition
assessments throughout the rest of the State. Although these efforts are heavily subsidized
through the award of EPA WPDGs, BWSR intends to use these initial studies as the baseline for
a more comprehensive long-term monitoring approach that will assess resiliency at mitigation
sites at regular intervals using standardized methodologies.
2.4 Resources (staff, budget, etc.)
BWSR is responsible for oversight of implementation of the WCA in Minnesota. This
includes the day-to-day operations of a statewide regulatory program but also the responsibility
for managing the State Wetland Bank and satisfying the requirements in statute and rule for the
monitoring and enforcement of conservation easements. BWSR employs a Wetland Mitigation
Monitoring Specialists who is the agency lead for planning, developing, and managing
monitoring programs for wetland mitigation sites. These tasks are split between programs
focused on long term monitoring of mitigation sites and those associated with establishment
monitoring of BWSR sponsored wetland banks. Currently, this employee spends approximately
60% of their time annually on long term monitoring activities. The Wetland Mitigation
Monitoring Coordinator position is supplemented by seasonal hires who are hired to conduct
monitoring during the growing season in Minnesota (April through September). These seasonal
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staff typically add 0.5 to 1.0 full-time employees to BWSR each year. Additional staff assist with
planning and implementing hydrology monitoring activities. Without this assistance it would
be difficult to conduct site inspections at more than 10 to 15 sites annually.
Section 3 Objectives of the case study - what are you trying to accomplish
The study will enhance BWSR's ability to effectively manage monitoring data collected at
wetland mitigation sites by developing a comprehensive data management system specifically
for wetland mitigation sites. The ability to collect, organize, and make monitoring data available
for analysis will help inform future program policies regarding compensatory mitigation.
Minnesota has invested considerable resources in monitoring the status and trends of wetlands
but lacks the ability to efficiently collect and integrate data from mitigation sites to evaluate
overall program success and to integrate our mitigation programs with other status and trends
data.
A new data management system, referred to as the Monitoring Data Management System
(MDMS), will be integrated into the framework of a new wetland mitigation database currently
being developed by BWSR. Funding for the study was used for five specific tasks. These
include: (1) developing the business requirements of the monitoring module in the database; (2)
developing standardized forms and processes for the collection of monitoring data; (3)
compiling wetland mitigation site metadata; (4) building the MDMS; and (5) testing the
monitoring module and refining any data collection, submission, or standardization processes.
Consistent with the preliminary recommendations in the soon to be published technical report
addressing the evaluation of stream and wetland compensatory mitigation, the final version of
the monitoring module will be driven by electronic data flow that is stored, presented, and
accessed in a geospatial format. The stored data would be accessible via a web-based
application operated and maintained by BWSR. BWSR currently provides wetland bank credit
availability and site location information in a similar manner using a web-based tool on our
agency website. Providing access to monitoring data would benefit local, state and federal
agencies involved in the regulatory programs in Minnesota as well as researchers, academics,
and other individuals and/ or organizations interested in assessing the success of mitigation
activities.
Section 4 Main Challenges
The opportunity to develop the MDMS came at a time when BWSR was planning for
replacement of its FoxPro based wetland banking database. Combining these two projects into
one single project resulted in several significant challenges. Those associated with the MDMS
are described below.
Development Schedules and Prioritization of Functionality: The more comprehensive
database replacement project involved the development of an application with five functional
areas, or modules, with the MDMS being housed within the monitoring module. The
development schedule provided by the vendor had the modules built in series which resulted
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in a silo approach and impacted the schedule when a module fell behind. Further, because other
modules were determined to be higher priority for implementation of the State's wetland
mitigation program the MDMS was pushed back in the schedule and was eventually released as
part of the second version of the wetland application because of scheduling issues.
Qualifications of the Development Team: The Request for Proposal that was published for
the wetland application did not require that the developer have individuals with wetland
regulatory program familiarity or experience on their team nor did it require expertise working
with GIS/Mapping programs. These were both identified as desired qualifications but were not
required. The selected vendor did not have this expertise on their team which created
significant communication issues associated with wetland mitigation terminology and
familiarity with general program workflows.
Software Requirements/Options: As part of a larger database project, some of the flexibility
associated with developing a standalone version of an MDMS like application was lost because
vendors and state information technology staff gravitated towards consistency in approach for
the entire application rather than making use of off-the shelf software that may have been more
efficient or practicable for a single purpose application.
Other challenges not necessarily associated with the development approach are described
below.
Aeency Coordination and Consideration of Future Directions: Support for development of
the MDMS was consistent throughout BWSR and other regulatory agencies in Minnesota.
However, agreement on assessment methodologies and reporting protocols was not sought and
obtained prior to initiation of the MDMS build. Instead, BWSR relied on its experience with
conducting wetland condition assessments as the basis for setting the standards for the MDMS
with respect to data upload especially data associated with vegetation. While this is not
anticipated to be problematic from an agency coordination and concurrence standpoint there
were situations where the MDMS build forced BWSR staff to make decisions on data collection
methods, standardization, and reporting that may have been better discussed in a broader
interagency forum. A more coordinated up-front approach to the MDMS and a standing agency
workgroup to provide input when needed during the process would have been useful during
the process. This would also be beneficial in adjusting agency policy to orient the state and
federal wetland mitigation programs to direct monitoring data towards the MDMS and having
it serve as a repository for all long-term monitoring data.
Section 5 Approach and Strategy Used
5,1 Staffing
Staffing support for the MDMS study was focused on the vendor development approach
used for the larger BWSR database replacement project. Using a competitive request for
proposal process, a third-party vendor was selected through a submission evaluation process
that included members with expertise in information technology and wetland banking subject
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matter experts (preferred but not required). The contract, and communications with the vendor,
was managed by Minnesota Information Technology Services (MNIT) who is the information
technology agency for Minnesota's executive branch. MNIT provided a dedicated project
manager and access to several staff who are assigned to a BWSR support team that aids with the
development of new applications and the maintenance of existing ones. The Wetlands Section at
BWSR provided a single point of contact that was familiar with the existing wetland banking
application and the wetland banking program in general. This person provided direct input to
the development process but also was responsible for obtaining input from other BWSR
Wetlands Section staff when necessary. A summary of the MNIT/BWSR development team is
provided in the table below.
TABLE A1: Summary of Minnesota Development Team.
Position
Agency
Roles/Responsibilities
Membership
Project Manager
MNIT
Manages contract, liaison
between vendor and State
agencies
Standing
Application
Support
Specialist
MNIT
Provides technical input
regarding state data
management requirements and
standards.
Standing
GIS Specialist
MNIT
Provides technical support
regarding geospatial data, data
standards, and workflow
processes
Standing
Wetland
Mitigation
Coordinator
BWSR
Wetland mitigation program
subject matter expert
Standing
Various
BWSR
Wetland mitigation subject
matter experts (monitoring,
plant identification, hydrology,
etc.)
As needed
5.2 Software Used
The MDMS is part of a larger effort by BWSR to replace an existing FoxPro application that
was used to manage wetland banking activity in Minnesota regulated under WCA. The goal of
the larger project was to replace the existing FoxPro application with an Oracle (or other) based
solution that is able to meet all activities and specifications required by BWSR. The respondents
to the State's RFP were given the flexibility to propose to develop/modify an existing
application (if licensed to do so) or to build a new application as long as it could be
demonstrated the solution would meet all business requirements and meet or exceed
performance expectations.
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The selected vendor chose to develop the wetland application on a Windows .Net platform as a
web hosted service on the internal BWSR network with server-side session-based
authentication. The web components will be Angular developed with a focus on security and
accessibility so the application will meet current State of Minnesota standards. The application
data will be hosted in an Oracle 12.x relational database.
Section 6 Outcomes
6.1 Products Produced
The MDMS consists of an Oracle based electronic data upload and retrieval system designed
specifically for data associated with long-term monitoring of wetland mitigation sites. The
application accepts vegetation and hydrology data for sites for multiple monitoring
periods/ events. General information regarding the mitigation site is in the application prior to
monitoring or will be entered by BWSR to establish the site in the MDMS. Users have the
opportunity to upload maps identifying the assessment area and sample locations for
vegetation data. Hydrology data is associated with a well location and will be identified as time
series data or manual readings. Data previously entered in the application will be displayed to
users through a public GIS interface that shows the location of the mitigation sites in Minnesota
and the types of data available at that location. For data retrieval, users will be directed to the
Cooperative Groundwater Monitoring application for hydrology data, or an interactive site
with filters for vegetation data downloads.
6.2 Capacities Developed
Development of the MDMS provides BWSR, and the State of Minnesota, the ability to
compile, save, and make available long-term wetland mitigation site data. This is a significant
improvement over the hard copy and/or disorganized electronic filing systems that exist
currently. The MDMS allows monitoring data to be linked digitally with the wetland banking
database where information on the site, conservation easement, and credit transactions are
maintained. Further, the MDMS will be linked to spatial data for wetland mitigation site
easements that is obtained during the establishment of the mitigation site as well as compliance
data collected as part of BWSR's statutory responsibility to periodically inspect easements for
these sites. The MDMS will bring these previously disconnected agency processes together
thereby increasing BWSR's ability to assess the success of the wetland mitigation program.
6.3 Partnerships or Leverage Opportunities Enhanced
The State of Minnesota has three agencies participating in the regulation and assessment of
wetlands. As expected, this has created silos between the programs with respect to the
collection, storage, and availability of monitoring data. Efforts to address the barriers associated
with wetland monitoring data began many years ago and progress has been made. However,
many challenges remain and one of the most significant from a regulatory program perspective
was the vast amount of data collected each year for the monitoring of wetland mitigation sites
and the inability to access and make use of this information for purposes other than single site
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evaluations. This pilot study identified several opportunities to share this information outside
of the regulatory arena. First, the MDMS will be linked to a groundwater monitoring database
managed by other state agencies such that hydrology data collected at wetland mitigation sites
will now be stored in a larger statewide database that can be accessed through a web-based
application. Second, vegetation data will now be accessible to external users (outside of BWSR)
through a web-based interface. Although this data will not be integrated with other wetland
condition data collected by agency staff in Minnesota it does provide a platform to build on and
satisfies a short-term goal of organizing the data and making it available through a web-based
interface.
Section 7 Lessons Learned
The MDMS process was part of a larger database development project undertaken by BWSR
to replace and upgrade an outdated application. In some ways, this combined approach was
beneficial and in others it was a detriment to MDMS development. Combining the MDMS with
a broader scale project was beneficial from a cost and staffing perspective because it took
advantage of a dedicated team of IT program staff. It also allowed the architecture of the MDMS
to be designed and integrated into the larger database as part of the build process as opposed to
being done separately and facing limitations from existing applications. The downside of this
approach were the competing priorities and schedules associated with other parts of the
application. For example, the most important part of the application was the wetland bank
accounting and transaction module. Because of its importance, this module was prioritized over
other functional areas and had more of an influence on schedule and resource decisions. This
ultimately led to work on the MDMS being deferred to make sure higher priority functionalities
were completed and implemented on schedule.
The MDMS was completed using a third-party vendor selected using a competitive
selection process. The request for proposal did not require respondents to have wetland
banking expertise as part of their team (it was identified as a preferred quality). In hindsight,
this stands out as our biggest mistake with the pilot. Bridging the knowledge gap between the
world of wetland mitigation and information technology is a significant challenge and one that
should not be overlooked. Requiring a third party vendor to have a member(s) of their team
familiar with wetland mitigation or wetland regulatory program work flows would save staff
time for the agencies involved in the project as well as reduce the number of iterations during
review that result from basic misunderstandings. Other relevant lessons learned from this
project are listed below.
• Invest ample time in defining business requirements and work flows before starting the
project. Although there will always be items that require further definition during the
process, spending time up front to establish a workflow and system components will
reduce the time spent sorting out basic questions later.
• Utilize user stories (narrative case studies) from subject matter experts to illustrate
processes for those unfamiliar with wetland mitigation.
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• Utilize staff from other agencies who have worked through similar processes and can
share their experiences. Minnesota is very active in developing applications to collect
and store natural resource data. The MDMS process benefitted from work done by other
agencies but many of these similar efforts were unknown at the beginning of the
process.
Section 8 Conclusions and Roadmap for the Future
The MDMS is the first step in a comprehensive reevaluation of tracking mitigation site
monitoring. The MDMS moves long-term monitoring of these sites in Minnesota from a
disorganized multi-media approach to a centralized digital storage and access portal.
Integrating vegetation and hydrology data with geospatial attributes from the mitigation sites
will improve the quality and usability of the data while improving accessibility for users
outside of BWSR. BWSR's near-term goal is to upload long-term monitoring data collected as
part of recent studies and establish a requirement for mitigation sites leaving the establishing
monitoring period to provide standardized vegetation and hydrology data that will serve as a
baseline for future monitoring as part of assessing site resiliency. Once long-term monitoring
data processes have been established and successfully implemented, efforts will be directed
toward integrating establishment reporting and data collection into the MDMS so that all
monitoring data for mitigation sites can be collected and stored in one location.
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APPENDIX B: OVERVIEW OF GEORGIA PILOT PROJECT
Section 1 Summary of state program assessing mitigation performance
1.1. Key agencies and general structure
Georgia's compensatory mitigation program is administered by the U.S. Army Corps of
Engineers (ACOE) Savannah District under the auspices of the Clean Water Act Section 404
program, with minimal involvement by state agencies. The mitigation banking program in the
state is quite robust, since the Savannah District was an early adopter of the banking concept
and began permitting mitigation banks in the early 1990s. Today, the vast majority of
compensatory mitigation in Georgia occurs in mitigation banks. Monitoring of mitigation banks
occurs pursuant to the District's 2018 Standard Operating Procedure for Compensatory
Mitigation, associated guidance, and individual banking instruments. There is currently no
central database for cataloging monitoring data, and no long-term performance or resiliency
monitoring is required beyond that dictated by permit conditions.
1.2. Authorities
Compensatory mitigation in Georgia is almost entirely conducted pursuant to the Clean
Water Act Section 404 program administered by the USACE Savannah District. State agencies
have a very limited role - the Georgia Environmental Protection Division (EPD) of the state's
Department of Natural Resources may impose conditions on or prevent issuance of 404 permits
under Clean Water Act Section 401, require compensatory mitigation as a condition of stream
buffer variances required under the state's Erosion and Sedimentation Act, or require
compensatory mitigation as a component of consent orders. Compared to what is required
under the 404 programs, however, the compensatory mitigation resulting from these authorities
is quite small.
The USACE Savannah District began its wetland mitigation program in the early 1990s, and
approved Georgia's first mitigation bank in 1992. In 2000, it became one of the first ACOE
districts in the country to include streams in its program. Today, the Savannah District, which
encompasses the entire state of Georgia, relies on mitigation banks for the vast majority of
compensatory mitigation required for 404 permits. The Savannah District allows both public
and private entities to own and operate 404 mitigation banks. Public entities owning banks
include the Georgia Department of Transportation and some local and county governments.
Private entities include mitigation banking firms, private landowners, timber companies, and
Georgia Power. The Savannah District also oversees the state's In-Lieu Fee (ILF) program,
which is sponsored by the Georgia-Alabama Land Trust (GALT). GALT collects fees from 404-
permittees when there are no available mitigation credits in the permitted project's service area;
when enough fees in that service area are collected, GALT requests proposals to develop a
mitigation project there.
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1.3, General goals and mandates
Mitigation bank development is currently guided by the USACE Savannah District's 2018
Standard Operating Procedure for Compensatory Mitigation (2018 SOP). Mitigation bank
performance monitoring is guided by the Savannah District's 2018 Draft Monitoring Guidelines
& Performance Standards for Freshwater Wetlands and Non-Tidal Streams (Monitoring
Guidelines). These guidelines are designed to support the District's Freshwater Wetland HGM
(Hydrogeomorphic) for Georgia and its Georgia Interim SQT (Stream Quantification Tool),
which are used to calculate permitted projects' mitigation debits and compensatory mitigation
project credits under the District's 2018 SOP, described below. The Monitoring Guidelines cover
the following areas:
• General monitoring requirements
• Evaluation of normal precipitation and growing season
• Freshwater wetland monitoring
o Vegetation monitoring
o Prevalence index
o Wetland hydrology monitoring
o Large woody debris monitoring
• Non-tidal stream monitoring
o Vegetation monitoring
o Vegetation monitoring in streamside vegetation zones
o Vegetation monitoring in riparian zones
o Stream channel geomorphology and stream hydrology monitoring
o Biological monitoring
o Stream water quality monitoring
o Large woody debris monitoring
• Freshwater wetland mitigation performance standards
• Non-tidal stream mitigation performance standards
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Monitoring reports are submitted annually; parameters are assessed according to the
following tables from the Monitoring Guidelines:
TABLE B1: Post-construction monitoring schedule for freshwater mitigation projects in
Georgia.
Wetland Monitoring
Parameter
Years
preceding interim credit release
As-Built
Continuous
Annual
Bi-annual
Vegetation
X
X
Hydrology
X
Prevalence Index
X
X
Wetland Monitoring
Parameter
Years following interim credit release
As-Built
Continuous
Annual
Bi-annual
Vegetation
X
Hydrology
X
Prevalence Index
X
Large Woody Debris
X
TABLE B2: Post-construction monitoring schedule for non-tidal stream mitigation
projects in Georgia
Stream Monitoring
Parameter
Years
preceding interim credit release
As-Built
Continuous
Annual
Bi-annual
Hydrology
X
Geomorphology
Channel cross-sections
X
X
Longitudinal profiles
X
X
Vegetation
X
X
Biology
(macroinvertebrates)
x<1>
Stream Monitoring
Parameter
Years following interim credit release
As-Built
Continuous
Annual
Bi-annual
Hydrology
n/a
X
Geomorphology
n/a
Channel cross-sections
n/a
X
Longitudinal profiles
n/a
X
Large woody debris
n/a
X
Vegetation
n/a
X
Biology
(macroinvertebrates)
n/a
X
Sponsor may initiate biological monitoring at any time following construction, so long as s/he
has at least two consecutive years of biological sampling that demonstrates attainment of interim
success criteria prior to seeking the interim mitigation credit release
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The Monitoring Guidelines outline the following general requirements for annual
monitoring reports:
• An executive summary that describes the overall monitoring results, including
hydrologic monitoring, vegetation monitoring, large woody debris monitoring,
geomorphological monitoring, water quality, and macroinvertebrate monitoring (as
applicable), areas of concern (e.g., exotic/invasive vegetation, stream instability,
nuisance herbivory, etc.) and any adaptive management activities undertaken during
the previous year (e.g., supplemental planting, reconstruction or modification of
structural habitat features, etc.).
• Results of any monitoring parameters required to demonstrate project specific
performance standards.
• Performance standards, as provided in the Mitigation Work Plan or in the permit
conditions, must be restated verbatim in each monitoring report.
• Each monitoring report should include a discussion/presentation of the current year's
monitoring data in context with data collected during all previous years. Summary
tables must include summary data from all previous years.
Section 2 Overview of mitigation components of the state program
Section 404 mitigation requirements in the Savannah District are guided by its SOP. In 2018,
the District issued a new SOP to replace the previous version, which had been in place since
2004. The goals of the 2018 SOP are to "1) provide stakeholders with a consistent, repeatable,
functionally-based mitigation credit assessment methodology for aquatic resources; and 2)
establish a transition to functionally-based credit types to facilitate in-kind replacement of
aquatic resources." It establishes what the District describes as a functional approach to
mitigation, which was not utilized in the 2004 SOP and is identified as the preferred type of
mitigation approach in the USACE and U.S. Environmental Protection Agency's 2008
Compensatory Mitigation Rule. The 2018 SOP uses Excel spreadsheet tools, the
Hydrogeomorphic Approach (HGM) for wetlands, and the Stream Quantification Tool (SQT), to
calculate credits awarded to wetland and stream mitigation projects in the state.
Section 3 Objectives of the case study - what are you trying to accomplish
The primary objectives of this project were to 1) bring together a working group of diverse
stakeholders involved in compensatory mitigation programs in Georgia; 2) assess current
practices and standards for mitigation data collection, reporting, and use; 3) construct a
prototype database that includes basic data analytics and a web interface to support existing
data in support of compensatory mitigation evaluation; and 4) provide a template for future
needs and develop a plan for scaling up the database statewide and broadening the analytical
and visualization tools based on shared objectives developed with stakeholders.
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Partners:
1. Athens Land Trust
2. Georgia Department of Natural Resources - Coastal Resources Division
3. Georgia Department of Natural Resources - Wildlife Resources Division
4. Georgia Department of Natural Resources - Environmental Protection Division
5. U.S. Environmental Protection Agency
6. Georgia Department of Transportation
7. Georgia Environmental Restoration Association
8. Georgia/ Alabama Land Trust
9. Georgia Power
10. Oconee River Land Trust
11. The Nature Conservancy
12. U.S. Army Corps of Engineers
13. U.S. Fish and Wildlife Service
14. University of Georgia
Section 4 Main challenges
This project encountered several key challenges. One key project objective was to upload
historical (pre-2018) data into the database to assess the effectiveness of the Georgia mitigation
program at achieving ecological goals and to identify trends over time. However, we decided
not to pursue this objective during this pilot project due to challenges posed by working with
historical mitigation data. In Georgia, data has primarily been submitted and archived in PDF
format. Thus, entering data into the database from historical records must be done manually in
a time-intensive process. We were further dissuaded from focusing on historical data due to
concerns raised by key stakeholders about the lack of standardization and quality of historical
data and changes in sampling protocols over time, which could limit analysis. These factors led
us to decide to use this pilot project as an opportunity to promote data standardization moving
forward, consistent with the USACE Savannah District's 2018 mitigation and monitoring
guidance, rather than spending significant effort to enter and standardize historical data with
little perceived benefit. Additionally, the relative lack of standardization of historical data
reporting and recent implementation of new guidelines (2018 Monitoring Guidelines) required
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our team to work with partners to iteratively develop standard data reporting protocols and
forms, rather than using pre-existing data forms for database development.
The development of the database also presented us with a series of challenges. We chose to
develop the database in-house using a combination of the RSQLite9 and R Shiny10 packages in
an effort to offer the greatest database flexibility, easy interfaces with multiple other platforms,
and ultimately the best user experience. However, this undertaking required training and a
period of working through a learning curve for project personnel to become proficient with
database development using this software. Additionally, since locations of sampling sites
within mitigation banks have historically been recorded in PDF reports, a high priority of
stakeholders was to develop a database tool to upload spatial data. Uploading the data is not a
significant issue by itself, but determining the ideal way to load and assure the quality of many
types of spatial data (per mitigation project) posed some significant challenges. While we
ultimately decided on a fairly straightforward approach for the pilot database, some additional
complexity and utility could be added with the input of users as this pilot is scaled up.
Determining the best strategies and schedule for effective communication with stakeholders
also proved to be a challenge, as meeting time had to be balanced with time spent on database
development. This challenge was heightened by the need to adapt our plans to navigate the
COVID-19 pandemic, which virtually eliminated our ability to conduct in-person meetings with
stakeholders and required us to negotiate the challenge of hosting online meetings with an
array of stakeholders, each with different agency mandates on permissible meeting platforms.
We decided to hold two general stakeholder meetings, where we solicited feedback on database
goals and progress, and conducted several follow-up meetings with key stakeholders. While the
general stakeholder meetings provided our team with valuable information in a time-efficient
format, it was a challenge to allow adequate time for discussion by a range of stakeholders with
varying levels of specialization on a range of topics. In an effort to maximize efficiency, we also
packed a substantial amount of information into each meeting, which may have resulted in
"information overload" and some of the key takeaways were not as well communicated as
desired. Additionally, the project would have benefitted from more frequent communication
with key stakeholders to solicit input on database features. While this was our intent, early
staffing challenges slowed initial progress on the database. Then, as database development
accelerated, our desire for progress overshadowed reconnecting with key stakeholders, thus
missing opportunities for iterative feedback. However, we ultimately were able to increase
opportunities for feedback from stakeholders late in the project and respond with substantial
changes and improvements. Moving forward, frequent feedback between the development
team and key stakeholders will be prioritized.
9 Kirill Miiller, Hadley Wickham, David A. James and Seth Falcon. 2020. RSQLite: 'SQLite' Interface for R.
R package version 2.2.1. https://CRAN.R-project.org/package=RSQLite
10 Winston Chang, Joe Cheng, JJ Allaire, Yihui Xie and Jonathan McPherson. 2020. Shiny: Web
Application Framework for R. R package version 1.5.0. https://CRAN.R-project.org/package=shiny
An Integrated Framework: Pilot Applications » March 2022 48
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Section 5 Approach and strategy used
5. v was it staffed? (internal, contractors)
The Georgia mitigation evaluation database project was developed internally and staffed
exclusively with University of Georgia personnel. Nathan Nibbelink, a professor in the Warnell
School of Forestry and Natural Resources at UGA, served as the principal investigator on the
project and was tasked with overseeing project administration and directly supervising and
assisting in database development, facilitating stakeholder meetings, and generating reports.
Katie Sheehan Hill, a research professional in the Odum School of Ecology's River Basin Center
and Carl Vinson Institute of Government at UGA, served as the co-PI on the project and
provided expertise on the mitigation banking system in Georgia and facilitated connections
with key stakeholders. Maxwell Kleinhans, a research professional in the River Basin Center,
provided expertise in developing the initial database framework. Cody Cox, a research
professional in the Warnell School of Forestry and Natural Resources, managed day-to-day
operations on the project, coordinated meetings with stakeholders, developed meeting agendas,
and produced meeting summary reports. He also took over database development after the
preliminary structure was created by Kleinhans and assisted in report writing.
5.2. Software used
The Georgia mitigation evaluation database was developed exclusively within the open
source statistics software, R11. We used the RSQLite package12 within R to construct a SQL
database to store data on a range of metrics related to mitigation evaluation. The SQL database
was then integrated into a user-friendly app developed using the R Shiny package13 in program
R, which permitted a visualization of bank sites within the state of Georgia, along with key
bank data, data entry forms (individual records and batch upload) for multiple types of data
(e.g., vegetation, hydrology, macroinvertebrates, large woody debris, and habitat assessment), a
data query and download tool, and a tool that interfaces with the ggplot214 package to plot data
for graphical analysis of data trends. This database app will be published online on a password-
protected website after final approval of the partners. Initially the site will be hosted by Dr.
Nibbelink's Spatial Analysis Lab at the University of Georgia until a permanent host is selected
by the partners.
11 R Core Team. 2020. R: A language and environment for statistical computing. R Foundation for
Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
12 Kirill Miiller, Hadley Wickham, David A. James and Seth Falcon. 2020. RSQLite: 'SQLite' Interface for
R. R package version 2.2.1. https://CRAN.R-project.org/package=RSQLite
13 Winston Chang, Joe Cheng, JJ Allaire, Yihui Xie and Jonathan McPherson. 2020. Shiny: Web
Application Framework for R. R package version 1.5.0. https://CRAN.R-project.org/package=shiny
14 H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016.
https://ggplot2.tidyverse.org
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5. cess (e.g., stakeholder coordination, key agencies coordinated with, guidance
docs used)
The Georgia mitigation evaluation database project began with a review of relevant
literature to provide a foundational understanding of the current state of mitigation banking
and evaluation in Georgia and identify goals for the future. The key piece of literature for
understanding mitigation data collection standards in Georgia is a document produced by the
Savannah District of the USACE in 2018 (Draft Monitoring Guidelines & Performance
Standards for Freshwater Wetlands and Non-Tidal Streams, 2018), which provided new
statewide requirements. The draft final version of the Integrated Framework for Evaluating
Wetland and Stream Compensatory Mitigation (Stein et al. 2018), co-produced by members of
the Southern California Coastal Water Research Project, Environmental Law Institute, and U.S.
Environmental Protection Agency, supplied us with valuable examples of the range of
mitigation evaluation practices occurring in various states and provided insights into goals for
national-level synthesis.
Concurrent with our literature review, we researched platforms for developing and hosting
our online database, and settled on using R Shiny for database development due to the
flexibility that it offered as a free, open source program that would permit in-house database
development and hosting. We then built a simple demonstration database as a vehicle for
stakeholder feedback. For this initial version, we used template data sheets provided in the
USACE 2018 guidance to guide construction of data input forms for both wetland and stream
mitigation projects.
In May 2020, we held our first stakeholder meeting, which was attended by key personnel
from 14 different organizations involved or interested in compensatory mitigation in Georgia.
During this meeting, we acquired stakeholder feedback on the current state of mitigation
evaluation in Georgia, including data collection and dataset availability, and discussed
stakeholder database goals and priorities. At this meeting, we also provided a brief
demonstration of an early version of our online database and solicited stakeholder feedback on
its design. We subsequently conducted follow-up meetings with two key stakeholders (USFWS
and Georgia Environmental Restoration Association) about data availability and potential
sentinel sites to use in the database. We then synthesized all feedback and developed a brief
summary report, which was sent out to all stakeholders.
Following these meetings, we entered a phase of intense database development in the fall of
2020. Based on our stakeholders' recommendations that historical data was not collected
consistently and would not be useful for analysis, we focused our database efforts on
developing standards for current and future data collection and entry and developing tools to
facilitate analysis in the future. We then held a second stakeholder meeting in January 2021 in
which we provided a more in-depth demonstration of our fleshed out database and solicited
stakeholder feedback to better tailor the design to their needs and goals. Subsequently, we
developed a meeting summary document, which we sent to all of our stakeholders. Following
the stakeholder meeting, we conducted a follow-up meeting with key stakeholders (USACE,
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EPA) to discuss specific recommendations for adding additional data entry forms, fields, and
tools to ensure that the database better aligned with their goals. We used the feedback provided
by stakeholders in our meetings to guide our process of expanding and revising our pilot
database during the winter/spring of 2021. We then held an additional meeting with key
stakeholders (USACE, EPA) in April 2021 to highlight expansions and revisions made to the
database during the previous months based on their feedback and solicit an additional round of
feedback, which we incorporated into the final version of our pilot database. We intend to post
the pilot database online to allow stakeholder beta testing during summer 2021.
Section 6 Outcomes
6. ducts produced
Through this project, we developed a range of products that will benefit compensatory
mitigation evaluation both in Georgia and nationally:
• The primary product developed from our efforts on this project is an interactive
mitigation evaluation database for the state of Georgia. This interactive database will be
published as an R Shiny app online to facilitate use by the mitigation community in the
state. Key features of the database include:
o An interactive map of mitigation banks and sampling sites within the state,
which includes information (e.g., acres, date established) for each site and other
key spatial layers (e.g., watersheds and ecoregions).
o Data entry tools to facilitate the upload of multiple types of data (e.g., vegetation,
hydrology, macroinvertebrates, large woody debris, and habitat assessment
characteristics) into the database as either individual records or batch uploads.
o A tool allowing shapefiles of sampling sites within banks to be uploaded into the
database by users, since these have historically only been reported in PDF
reports, which will facilitate future analysis.
o A data viewer that permits data visualization, query by a range of fields, and
download.
o A pilot graphical analysis tool for data trend visualization.
• We also developed metadata spreadsheets for each data entry form, which can be
downloaded from the corresponding database tab, and include information about each
data entry field, such as data type, data range, and lists of options for categorical fields.
• We created downloadable Excel templates for each data entry form, which can be
downloaded by users from the appropriate database tab, to standardize data entry for a
range of mitigation evaluation criteria (e.g., vegetation, hydrology, macroinvertebrates,
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large woody debris, habitat assessment characteristics), to facilitate data entry and
future analysis.
• Additionally, we developed a spreadsheet listing the availability of spatial data for each
bank site, which highlighted where spatial data is incomplete in current state databases,
such as missing bank boundary shapefiles or banks not listed in RIBITS.
• Finally, we produced summary documents from the two stakeholder meetings that we
conducted, which synthesized valuable insights from 14 organizations that comprise a
large portion of the Georgia compensatory mitigation community on a range of topics,
including current data collection and use, current dataset availability, database goals,
and feedback on database progress.
mcities developed
This project greatly enhanced the capacity to collect, share, and analyze mitigation data in
Georgia through the development of standardized data entry forms, interactive maps, and data
query and download tools, which will enhance access to data for all stakeholders in the Georgia
mitigation community. Since we decided to develop the database in-house, this project
provided the opportunity for project personnel at UGA to expand our capacity for database
programming, management, and online application development using the R Shiny and
RSQLite packages in the open source software program, R. This adds to our past experience
with ArcGIS Online, VB for Applications, Python, and other tools to bring even more capacity
to our ability to build and host geospatially-enabled database tools to enhance environmental
management and decision-making.
6.3. Partnerships or leverage opportunities enhanced
This project helped UGA to develop important partnerships in the compensatory mitigation
community within Georgia and to better connect mitigation evaluation efforts in Georgia to best
practices being promoted or used in other states through review of the draft final version of
Stein et al. (2022) document and meetings with teams from other states. This project allowed us
to develop connections with a team undertaking a similar project in Minnesota and with
national-level partners at the Southern California Coastal Water Research Project and EPA to
better understand how Georgia fits in, and how we can contribute to (and learn from) national
advances in mitigation evaluation. Our two stakeholder meetings and additional individual
follow-up meetings helped us develop connections with 14 organizations involved with
compensatory mitigation in Georgia, who provided us valuable insight and feedback during the
course of our database development to allow our final product to best suit the needs of the
Georgia mitigation community.
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Section 7 Lessons learned
7.1. What worked well/keys to success
While our model for soliciting stakeholder feedback could have been improved (see 7.2,
below), we believe that a key benefit of our in-house, user-driven approach avoids many of the
pitfalls often associated with outsourcing database development. Based on our observation of
other efforts, we were less prone to forcing elements into preconceived best practices from the
computational world (often useful for "big data" with millions/billions of records), and more
likely to make decisions that highlighted key needs of stream and wetland mitigation programs,
for which databases are relatively modest in size, and thus optimal efficiency can be traded off
for a better user experience. However, this decision required us to overcome a learning curve to
gain experience using some newer (to us) packages for database programming. Our decision to
use open-source software for database development will allow it to be more easily managed
and expanded in the future. Another element that was key for project success was creating
opportunities for stakeholder engagement and input during the database development process.
While the project could have benefitted from more frequent engagement with key stakeholders,
our meetings did provide us with a wealth of information and increased interactions late in the
project resulted in a cycle of iterative feedback that increased the alignment between the
database structure and stakeholder goals. Our two general stakeholder meetings also provided
our team with valuable information about current data collection and analysis in Georgia,
challenges in utilizing historical data for analysis, and preferences for database layout and
development priorities. This input shaped our prioritization of project components, such as
focusing more on setting standards for the present and future than loading historical data and
helping to ensure that the pilot database will meet user needs to the greatest extent possible.
7.2. Challenges/things you would have done differently
While we made considerable progress during this pilot project, we experienced several
notable challenges that can serve as valuable learning opportunities for other states undertaking
similar database development, particularly where little historical regulation or oversight has
occurred. The biggest challenge we faced early in the project was in working with historical
data to meet broader project objectives of evaluating performance, effectiveness, and resiliency
of compensatory mitigation in Georgia. Due to stakeholder concerns about data consistency and
accuracy, we ultimately decided not to focus on including historical data to analyze trends in
mitigation in our pilot database and instead used the development of the database as an
opportunity to promote better standardization going forward. Including historical data in the
database was further complicated by the fact that most historical mitigation data were
submitted and archived in PDF format, which would require data to be manually entered into
the database; a time-consuming process in which stakeholders saw little benefit relative to our
other goals. The lingering lack of standardized data reporting in Georgia presented us with an
additional challenge because we had to develop data entry standards for several metrics and
new data entry forms as part of the database development, rather than using pre-existing forms
as templates. Additionally, since most sampling sites within mitigation banks have historically
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only been identified in PDF reports and have not been compiled into existing geospatial
databases, rather than creating a layer with locations of sampling sites in the database for user
analysis, we were tasked with developing a tool to allow users to upload site locations of
multiple feature classes (e.g., point, line, polygon) into the database, which required the
development of additional QAQC procedures to ensure proper formatting of fields and
coordinate systems. Our decision to develop the database in-house greatly increased our
flexibility and ability to iteratively modify the database based on stakeholder feedback.
However, these benefits did come with a learning curve, as previously mentioned. We do,
however, think that the choice of platform was a good one in looking to the future, and served
to add capacity for us to do more of this work.
We learned a few lessons that would lead us to make some different decisions in the
database development process if we had it to do over again. These lessons primarily related to
how we solicited stakeholder feedback in the database development process. We had
anticipated that our first stakeholder meeting would provide important information about
current data collection and analysis, available datasets for populating our database, and
stakeholder visions for the database itself, which would guide our database development. Thus,
we spent a relatively small portion of the meeting time actually performing a database
demonstration and soliciting feedback on design elements, and only presented a relatively bare
bones version of the database. While the meeting did provide valuable information on all topics
presented, we likely would have benefitted from presenting a more fleshed out version of the
database at this juncture and setting aside more time for direct feedback on its layout because
most of the feedback that we received at the first meeting was more conceptual, and we found
that a lot more ideas about the database structure and details emerged during our second
meeting, held several months later, when we spent most of the meeting time soliciting direct
feedback on design elements of a much more fleshed out version of the database. Had we
presented some of these elements earlier, it might have provided us with more concrete
database-specific feedback earlier in the process, which would have allowed more opportunities
for iterative feedback during the development process and would have saved us from spending
considerable time on elements deemed less important by the user community, such as matching
the exact formatting details of existing data collection forms, since not all users use the exact
same forms and would prefer to focus on batch upload of data. Additionally, "information
overload" in large stakeholder meetings may have reduced the utility of these meetings.
Originally, stakeholder meetings were designed as in-person, half-day workshops. Due to
scheduling issues and "zoom fatigue" during the COVID-19 pandemic, the meetings were
instead scheduled as shorter online sessions, which were not ideal.
Additionally, we would have benefitted from setting aside more time throughout the
database development process to meet with key stakeholders to workshop elements of the
database, including communicating more regularly about other project developments (e.g., key
takeaways from meetings with national/MN teams) and more effectively sharing timelines and
expectations. While more frequent meetings do require a diversion of time away from direct
database development, they would have increased development efficiency in the long run by
steering our efforts towards features of greater user priority, and thus avoiding sinking time
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into less important details. Due to early staffing challenges and learning curves, progress was
initially slow. Nonetheless, more frequent communication during this period, followed by
frequent opportunities for feedback as our progress accelerated would have been valuable. We
ultimately achieved a higher level of feedback and iterative improvements late in the project,
but would improve the model of engagement significantly if we could do it again.
7.3, Recommendations for others
Our primary recommendation is that communication with stakeholders is the biggest key to
successfully and efficiently developing a database that meets the needs and goals of a diverse
mitigation community. Creating opportunities to understand goals and priorities can inform
database development and providing further opportunities for feedback throughout the
development process can ensure that the database matches the needs of the community.
Section 8 Conclusions and roadmap for the future
Despite its robust number of mitigation banks, Georgia is still early in the process of
improving the consistency and effectiveness of mitigation evaluation. Our approach to building
a standardized, accessible database to better enable effective mitigation evaluation could be
used as a roadmap for other states at a similar stage in the process. The development of
standardized data entry forms and a queryable database through this effort will greatly
improve the capacity for future evaluation of mitigation outcomes in the state. While significant
progress was made on a functional database during the timeframe of this pilot project,
additional work is needed to beta-test, publish, and scale-up the database to maximize its utility
for mitigation evaluation in Georgia. We estimate that this process will take 2 years and require
a full-time database manager/programmer. During this time period, the database manager
would continue to build out and troubleshoot the database iteratively through user feedback,
while developing additional query and analysis tools to facilitate future mitigation evaluation
and assist with the upload of new (and high quality historical/sentinel site) mitigation data into
the database. Having a full full-time database manager will enable a soft implementation phase
that permits "on call" revisions and troubleshooting and culminates in dissemination to all
partners with the expectation that they commit to using the new system. If the University of
Georgia is selected to continue to develop the Georgia mitigation database, we could serve as
the database host during that time period, which would allow time for the stakeholder group to
determine (and secure funding) for a long-term host. Regardless of who is selected for the next
phase of this work, UGA is committed to hosting the pilot database and logging feedback from
partners for up to one year from project completion, and sharing all project components with
anyone who would pick up the work moving forward.
8.1 Recommendations for next steps
Below we describe our recommendations for two additional phases of this work. We also
propose a timeline and budget. However, budget projections are flexible, depending on the
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needs/ desires of project partners, and the numbers reflect estimates based on salaries and time
of personnel at the University of Georgia.
Phase V. Pilot database development - complete
Phase 2: Soft launch, beta testing, build-out, and implementation (2 years)
Soft launch - Key partners would be selected to be beta testers of the database. We
would propose a launch meeting with partners to highlight initial functionality and set
goals for the build-out, including any initial modifications and additional functionality.
After the launch meeting, partners would meet monthly to review progress and adjust
goals as needed. In between meetings, the database manager would work on agreed-
upon tasks and be on call for questions, edits, and suggestions as they arise. Phase 2
would also include working with USACE and other partners to lay the groundwork for
requiring use of the database as a part of formal reporting under mitigation evaluation
guidelines. Finally, during Phase 2, the database development team would work with
partners to select a permanent host and design a funding model for long term
maintenance and hosting of the database. By the end of Phase 2, the goal would be to
fully launch the database tool for use by all partners and transition to the permanent
hosting arrangement.
TABLE B3: Estimated Phase 2 budget for Georgia.
PERSONNEL
SALARY
(monthly)
TIME
(months)
SALARY
FRINGE
RATE
Yearl
Year 2
Total
Database manager
5,000
12
60,000
38.00%
82,800
84,870
167,670
Staff support (proj mngmt,
communications)
3,400
2
6,800
46.00%
5,667
2,607
8,273
PERSONNEL SUBTOTALS
88,467
87,477
175,943
SUPPLIES
R-Shiny Apps Hosting
Service
99
12
1,188
1,188
2,376
Sub-TOTAL UGA Direct
Costs
89,655
88,665
178,319
Indirect Costs (IDC) est @
35%
31,379
31,033
62,412
TOTAL
121,034
119,697
240,731
Phase 3: Long term hosting and maintenance
Long term maintenance could take several forms, depending on the needs of the
partners. We feel that this type of database will always require a minimum level of
maintenance and user support, considering the variety of data types, necessary
software/hosting updates, and evolving user needs. Based on communications with Eric
An Integrated Framework: Pilot Applications » March 2022
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Stein's team, we are estimating high at about 20% of a data manager's time, plus some
minor additional staff support and web app hosting services. These estimates could be
revisited and revised as appropriate during Phase 2 as the project team considers
funding models and needs for long term support.
TABLE B4: Estimated Phase 3 budget for Georgia
PERSONNEL
SALARY
(monthly)
TIME
(months)
SALARY
FRINGE
RATE
Yearl
Year
2
Total
Database manager
5,000
2.5
12,500
38.00%
17,250
17,681
34,931
Staff support (proj mngmt,
communications)
3,400
0.5
1,700
46.00%
1,417
652
2,068
PERSONNEL SUBTOTALS
18,667
18,333
37,000
SUPPLIES
R-Shiny Apps Hosting
Service
99
12
1,188
1,188
2,376
Sub-TOTAL UGA Direct
Costs
19,855
19,521
39,376
Indirect Costs (IDC) est @
35%
6,949
6,832
13,781
TOTAL
26,804
26,353
53,157
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