United State*	Environmental Monitoring	TS PIC 0064
Environmental Protection	Systems Laboratory	January 1981
Agency	P.O. Box 15027
las V e g a i NV 89)14
Septic Systems
Performance Analysis
King County, Washington
Volume I
pr#par«d for
EPA Region X

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epflcHV7
TS-PIC-0064
January 1981
Septic System
Performance Analysis
King County,
Washington
Volume I
by
E.T. Slonecker/S.J. Baker/P.M. Stokely
Imagery Analysis Section
The Bionetics Corporation
Warrenton, VA
Contract No. 68-03-2844
Project Officer
Frank R. Wolle
Environmental Photographic Interpretation Center
Environmental Monitoring Systems Laboratory
Warrenton, Va., 22186
ENVIRONMENTAL MONITORING SYSTEMS LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
LAS VEGAS, NEVADA 89114

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KING COUNTY SEPTIC SYSTEMS PERFORMANCE ANALYSIS
TABLE OF CONTENTS
I. INTRODUCTION
II. COMMUNITY SURVEYS/CLEAN WATER ACT
III. REMOTE SENSING AND SEPTIC SYSTEMS ANALYSIS
A.	HISTORY
B.	TECHNIQUE
IV. REMOTE SENSING AND ENVIRONMENTAL MONITORING - LIMITATIONS
V. ANALYSIS OF ENVIRONMENTAL CONDITIONS
VI. KING COUNTY SEPTIC SYSTEM PERFORMANCE ANALYSIS
A.	PROJECT PLAN
B.	PROBLEMS
C.	RESULTS
D.	FIGURES AND GRAPHS

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KING COUNTY SEPTIC SYSTEMS PERFORMANCE ANALYSIS
I. INTRODUCTION
This project was initiated in response to a request for technical
support by Roger K. Mochnick, Acting Chief, Environmental Evaluation
Branch, Region X Environmental Protection Agency. The Region X Office
is currently involved in the preparation of an Environmental Impact
Statement on water quality assessment and proposed wastewater treatment
facilities in the greater Seattle area of King County.
A necessary initial step in the E.I.S. process is the determination
of the present need for sewers and wastewater treatment facilities. This
is accomplished primarily by assessing the number of individual septic
system malfunctions, and determining their overall effect on the area's
water quality. This determination of present need and assessment of the
nature and number of individual septic system malfunctions can often be
difficult especially if -the issue is a controversial one within the
community. The data acquired, in these cases, from questionnaire and
ground-based surveys may not be completely reliable.
The Environmental Protection Agency's Environmental Photographic
Interpretation Center (EPIC) has developed a remote sensing technique for
determining septic system malfunctions and surfacing septic effluent.
This technique employs color and color infrared aerial photography to
detect changes in soil moisture, unusually lush growth, and other
visible "signatures" that are characteristic of septic system malfunction.
This program of aerial septic system analysis has been under continual
development since 1974 and has been successfully implemented in several
of the EPA's regions in support of Environmental Impact Statements, and
has been utilized in several communities to satisfy the need documenta-
tion requirement (PRM 78-9) of the 201 Construction Grants Program.

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II.. OCM^JNITY SURVEYS - LEGAL BASIS
As a result of the Federal Water Pollution Control Act (P.L. 92-500) and the'
1977 Clean Water Act (P.L. 95-217), the Environmental Protection Agency was given
the authority to grant funds for the construction of sewage collection systems.
Under the eligibility requirements far the construction grants program, the law
clearly states that the need for wastewater treatment facilities be proven by
documenting the number of septic field failures within the existing target area,
and assessing their effect on water quality and public health in general.
"New collector sewers should be funded only when the systems
in use (e.g., septic tanks or raw discharges fran hemes) for the
disposal of wastes fran the existing population are creating a
public health prcblsn, contaminating groundwater, or violating
the point source discharge requirements of the Act. Specific
documentation of the nature and extent of health, groundwater
and discharge problans must be provided in the facility plan.
Where site characteristics are considered to restrict tfte use
of on-site systems, such characteristics, (e.g., groundwater
levels, soil permeability, topography, geology, etc.) must be
documented by soil maps, historical data and other pertinent
information.
The facility plan must also document the nature, number
and location of existing disposal systems (e.g., septic tanks)
which are malfunctioning. A ccmnunity survey of individual •
disposed systems is reoatmended far this purpose, and is
grant eligible."
- Construction Grants
Program Becaiireroents Memorandum
PPM # 78-9
Originally, the only way to satisfy this program requirement was by
use of the doar-to-doar survey. However, it soon became evident that this
survey method required large oenndttments of personnel, time, money and
technical assistance. Also, there was often a question of validity because
sewer projects are often controversial within the ccmnunity. It soon became
apparent that an alternative survey method was needed.

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III. REMOTE SENSING AND SEPTIC SYSTEM ANALYSIS
History
Remote sensing was first used to analyze septic field problems in
Greensboro, North Carolina in 1974. Although the results of this initial
survey were not definitive, it did show promise that a specialized
technique for septic system analysis could be developed. Therefore,• the
Environmental Protection Agency's Environmental Photographic Interpreta-
tion Center (EPIC) initiated a research project to develop and refine the
interpretative and analytical technique for aerial septic field surveys.
In 1977, working in conjunction with Wright State University in Dayton,
Ohio, EPIC's imagery analysts discovered distinctive patterns of soil
moisture and vegetation growth and stress that were characteristic, of
septic field overflows. By employing stereo pairs of "false-color"
infrared and conventional color photography, an analytical technique was
developed that has since been proven to be 75% to 95% accurate, depending
on the climatic and soil conditions at time of overflight. After further
refining the technique, EPIC developed and produced several photo inter-
pretation "keys" on septic field analysis and tested them on seven com-
munities in EPA Region V. Region V reported in the EPA Journal (May
1980) a cost saving of $36 million dollars from this technique. In
early 1978 a test of EPIC's septic field technique was performed in
Hawkins, Greene and Union Counties in Tennessee. These communities were
chosen because of their geologic structure, soil and topographic condi-
tions, and their pressing operational need. After the analysis and
field check were performed, the results showed that EPIC's technique had
a confirmed accuracy, rate of 94.5% (55 suspected failures - 52 confirmed).
As a result, the aerial survey confirmed the hypothesis developed front
the analysis of soil and geologic data by public health officials: septic

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tank systems were not satisfactory for disposal of wastes within the
201 study area.
EPIC's remote sensing technique for septic field analysis has been*
widely used and has consistently performed in the 75% - 95% accuracy
range. It has been used repeatedly by EPA Region III, IV, and V as ail
integral part of the 201 Construction Grants Process.
Technique
EPIC's remote sensing technique for determining failing septic drain
fields requires the acquisition of both color (Ektachrome 2448) and color;
infrared (Ektachrome 2443) at a scale of 1:8,000. Each frame must be
overlapped to a sufficient degree so that the analyst may place them in
three dimensional stereo to acquire the necessary topographic information
Each lot of each house in the non-sewered sections of the 201 study area
in analyzed for signs of plant foliage distress and excessive soil mois-
ture level.
Distressed foliage appears different than the surroundings in both
color and color infrared photography. Where there is a high source of
nutrients, as in septic field failure, the enhanced growth is indicated
by a brighter red color in the color infrared photography. As the septic,
effluent nears the surface, the overabundance of nutrients causes the
vegetation to be stressed with a high growth rate until it finally dies
which would show as a pale gray or tan spot. Any actual surface outbreak
with standing septic effluent would appear as dark blue or black. The
classic septic system failure signature would display the following
characteristics:
(1)	Pink/red ptripes outline the tile field.
(2)	Perpendicular to the tile field, at one or more locations, is
a deep red plume, which flows downhill, as indicated by the

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stereo interpretation.
(3) At the center and at one or more locations within the plume,
are gray or black spots which show dead vegetation and the
surfacing effluent.
The actual failure signatures are seldom obvious and training is required
to produce a proficient interpreter. Similar signatures can be caused
by common occurances such as manure piles, compost heaps and animal
droppings. For these reasons field checking a percentage of the area
is always recommended.
• Failure of septic tank systems can usually be attributed to one or
more of the following causes:
(1)	The soil in the absorption field has too slow a percolation
rate to allow for adequate assimilation, filtration, and
biodegration of sewage effluent flowing into it.
(2)	The septic system is installed too close to an underlying
impervious layer.
(3)	The septic system may have been installed in an area where
the seasonal water table is too high for its designed use.

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(4)	The soil in the absorption field has too high a percolation
rate for effective attenuation of the septic effluent prior
to its reaching the underlying groundwater.
(5)	Mechanical malfunctions, or breakage, in the septic tank,
distribution box, and/or drainfield pipes have occured. '
(6)	Caustic, toxic or otherwise harmful substances which could
kill bacteria in the septic tank and/or absorption field,
and cause subsequent clogging, have been introduced into
the septic system.
(7)	All or part of the system has been improperly installed.
With respect to remote sensing of septic system failures, only those
malfunctions which are noticeable on the surface can be detected by
aerial imagery. Those failures which are related to sewage backing up
in the home, or too rapid transport through the soil into the ground-
water, cannot be detected through remote sensing, in these cases, septic
failures can only be determined by water quality analysis and/or the use
of a soil lysimeter, "septic snooper", or similar apparatus.
Based on the work undertaken to date, it has been determined that
all the primary surface manifestations that are associated with septic
tank and/or absorption field failures are the result of the upward move-
ment of partially treated or untreated wastwater to the soil surface,
and usually appear either directly above or adjacent to the component
parts of the septic system (i.e. the septic tank, the distribution box,
and the absorption field). More often than not, two or more of these
malfunctions will occur simultaneously at any given homesite. In some
cases, depending on the soil makeup of a given area, the outline of the
drainfield of a properly functioning septic system can still be dis-
tinguished on aerial imagery. This points to the need for tailoring
"photo-interpretation keys" to specific geographic areas.

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NOTE: At present, there is no photo-interpretation key for septic
systems performance analysis in the Pacific Northwest/EPA Region X
area. It had been hoped that this project would result in at least
the initiation of a key for this area. However, the fact that remote
sensing of septic field problems has never been attempted in this
area does not mean that the overall technique is invalid, but simply-
untested. Any given geographic area has individual, climatic, geo-
logic and soil characteristics that, once defined and understood, will
affect the interpretative process to some degree - but not necessarily
the validity of the overall technique. For example, it is possible in
shallow soils to find clear definition of septic systems by lush growth,
even though the system is functioning properly. However, this has been
observed in the past to be a result of a very dry climate, or an extend-
ed period of little or no rainfall, when the grass roots will reach for
available moisture. Since these conditions did not exist in King County
at the time of overflight, clear definition of the system is still con-
sidered to be an indication of seasonal failure.

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IV. REMOTE SENSING AND ENVIRONMENTAL MONITORING - LIMITATIONS
Although aerial sensing systems are one of the most important
environmental monitoring applications of the future, they are not
without drawbacks and limitations, some of them serious. A few of
these are:
WEATHER - Almost all sensing systems are affected a great deal by
meteorological conditions. Rain, snow, haze, clouds,
temperature, etc., all affect the availability, clarity
and resolution of the imagery. Often conditions must be
just right for acquisition to take place, high winds and
other weather factors may prohibit the flight of the air-
craft itself.
SEASONS - Naturally, when dealing with environmental factors, the
seasonal aspect is often of paramount importance. Stages
of growth, death, change, water table, water supply and a
host of other variable seasonal factors are central to any
analysis that deals with vegetation stress and growth.
TREE/CLOUD - Almost all imaging systems of high resolution are still
COVER
handicapped totally by cover characteristics. Heavy clouds,
thick haze, and extensive tree/crown cover prohibits inter-
pretation of all underlying characteristics.
Therefore, while remote sensing techniques provide an excellent
vehicle for monitoring and assessing environmental conditions and
standards, it is not a simple process and can only be accomplished
correctly with a great deal of forethought and planning. Depending on
the user requirements, there is almost certainly a significant period
of time that must lapse between the planning stage and the actual acqui-
sition of the imagery. This is required so that the proper meteorological

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and/or seasonal requirements can be met. This period of time is
often months and can extend over an entire year. If the imagery
is acquired at the wrong time or under the wrong conditions, the
information will be reduced significantly in value. It must be
»»¦
kept in mind that the use of remote sensing is a fragile process
and that the final product will only be as good as the planning
and preparation that preceeded imagery acquisition.

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King County, Washington
Analysis of Environmental Conditions
(source: U.S. Department of Agriculture, Soil Conservation Service.)
INTRODUCTION
The landform types and environmental conditions in the Puget
Sound area represent a dramatic departure from the eastern seaboard
and midwest regions where EPIC's remote sensing technique for septic
systems performance analysis was originally developed and refined.
Unfortunately, the full scope of these differences in soil types,
geologic structure and climatic conditions, was far greater than
originally anticipated, and seriously impacted the overall quality
of this study. The main reason that these differences were not fully
anticipated was primarily because there has been little or no environ-
mentally-based remote sensing conducted in the Pacific Northwest and
no definitive methodology has been established. As noted earlier, a
full understanding of various environmental factors is critical to
both the interpretation process and the timing of film acquisition.
This section will deal with the relevance of these environmental fac-
tors on general septic system performance and remote sensing analysis.
CLIMATE/TEMPERATURE/PRECIPITATION
Climatic conditions are extremely critical to any attempt at
environmental analysis via remote sensing. The primary focus here is
predictable patterns of vegetation growth. In septic system perfor-
mance analysis, the main concern is involved with the identification
of unusual patterns of vegetation growth and stress, caused by the
upward and/or lateral movement of sewage effluent in the general loca-
tion of the septic system filter field.
Climatic conditions in the study area are typical of the mild,
moist climate of the Puget Sound area. This climate is controlled

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by major air movements over the Pacific Ocean as they are influenced
by major land forms, particularly the Olympic and Cascade mountains.
The maritime air has a moderating influence, bringing warm moist air
to the region from the Southwest in the winter and spring, and cool,
drier air from the Northwest in the summer and fall. Because of this,
there is a well-defined dry season in the summer and rainy season in
the winter. Annual precipitation ranges from 35 inches in the lowlands
to 150 inches or more in the surrounding mountains. Fifty percent of
the annual precipitation falls during the four month period from October
to January and seventy-five percent during the six month period from
October thru March, with only five percent of total rainfall occuring
in the months of July and August.
Temperatures in the region containing the study area are consid-
erably moderate in comparison to other regions at similar latitudes
in the nation. In the warmest summer months, temperatures are generally
in the 70's with occassional short-term bursts into the 80*s. Tempera-
tures above 85 degrees are reached less than fifteen days per year.
Winter temperatures are in the 40's in the lowlands and decrease with
altitude, approx. 3 degrees F. for every 1000 feet of elevation. This
would indicate that a span of nearly 8 F. in average temperatures is
likely across the study area, which ranges in elevation "from 11 feet
near the Renton Treatment Plant to 2757 feet on the summit of Tiger
Mountains. Local temperature conditions vary considerably in the
study area depending on air, drainage, elevation, solar radiation, and
distance from the Sound. Mean annual temperatures for eleven recording
stations in and around the study area are illustrated in figure
Rainfall in the region containing the study area is generally less
intense than in most other parts of the nation, but the frequency of

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3
precipitation is greater. Total annual precipitation generally
increases with elevation. Precipitation is light in the summer,
increases in the fall, peaks in winter, then falls through spring,
with a sharp drop noted in early July (see figure 3).
During the wet seasonr rainfall is usually light to moderate in
intensity and continues for extended periods of time. Figures 4 & 5
contain information on average precipitation levels in and around the
study area.
Snowfall within the study area is generally very light, with snow
seldom remaining on the ground for more than a few days (except at the
higher elevations),
SOIL STRUCTURE/GEOLOGY
The soil types and underlying geologic structure are tremendously
important to both area-wide, on-site sewage disposal and remote sensing
analysis thereof. The types of soils and their relative percolation
rates, as well as the permeability of the underlying geologic structure,
affect not only septic system performance but also the type and occur-
rence of failure that the remote sensing analyst might expect to see.
GEOLOGY
The soil types and land features of the King County area were
formed largely by deposits of glacial drift laid down during the
Vashon Period bf the Fraser glaciation late in the Pleistocene era.
The majority of material left by the glacier are till, recessional out-
wash, pro-glacial lacustrine and outwash sediments. Following deglacia-
tion, alluvium accumulated in the valleys, and mudflow from Mount Ranier
(Osceola mudflow) covered a large area in the vicinity of Enumqlaw.
Figure _8_ shows the general location of the major geologic material
in the study area.

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4
This study's primary concern with the geologic structures is the
permeability of the substratum and its subsequent ability to adequately
filter sewage effluent prior to reaching groundwater supplies. This
is critical to water quality planning because, irregardless of the soil
structure, if the substratum'is relatively impermeable, then a high
occurrance of on-site septic system failure can be expected; if the sub-
stratum is too porous, then ground-water contamination can be expected.
However, because of the close association between soil types and geologic
material underneath - a discussion of the soils is also necessary.
SOILS
There are 39 soil series and 7 basic soil associations in the King
County area. However, the most predominant are the Alderwood soils
which occupy 52% of the study area. Alderwood soils are gravelly-sandy
loams with a thickness of 24 to 40 inches. Almost without exception,
the underlying substratum is a consolidated glacial till which has a
very low permeability or slow percolation rate. Since these soils are
very shallow, there are severe restrictions for on-site septic disposal.
Another major association is composed of mostly Everett soils and occu-
pies approximately 14% of the study area. Everett soils are also
gravelly sand that has a very high or rapid percolation permeability
through the substratum, creating a potential for groundwater contamina-
tion from on-site septic disposal due to inadequate attenuation of the
effluent prior to reaching the groundwater. The remainder of the study
area is composed of minor percentages of the other soils-but over 90%
are still classified by Soil Conservation Service as having severe
restrictions for septic tank filter fields because of either:
-	Permeability through substratum
-	Seasonal high water table
-	Extreme Slope
-	Permeability/pollution hazards
-	Flood Hazard

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A. Project Plan
On February 7, 1980, USEPA Region 10 submitted a request to
the Office of Monitoring and Technical Support, EPA, to initiate an
analysis of aerial photography for portions of King County, Washington
for failing septic systems* Final approval of costs and funding by
Region 10 was completed April 11, 1980.
The Environmental Photographic Interpretation Center scheduled
a photo mission to cover the study area at the first photo-weather
window. The photography was acquired on the 1st and 3rd of May, 1980.
The study area (see volume II, page 2), designated by Region 10 in
coordination with METRO (Municipality of Metropolitan Seattle), was
photographed with both conventional color film (Ektachrome 2448) and
color infrared film (Ektachrome 2443); a Zeiss aerial camera with a
9" format and a 6" focal length was used. The scale of the imagery
varied from 1:8,500 to 1:10,000. The overall quality and resolution
of the imagery was excellent.
B. Problems:
The most significant problem encountered was the short period of
time between project approval and the required completion date.- Due
to this scheduling, imagery acquisition had to be completed at a less
than optimum time. Ideally, imagery for this type of study is flown
when the water table is at a seasonal high, and it has been at least
3 days since the last rain. In this case, the water table was
approaching a seasonal low and it had rained on May 2nd, (the day
between flights) . This lead to a problem of excessive surface mois-
ture and areas of standing water.
A second desired condition when planning a photo mission for a
septic study is that the photography be acquired at a time prior to

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2
full leaf-on conditions for the trees. If the trees in the area
have leafed-out, in the denser areas it becomes extremely difficult
to analyze the imagery. These conditions all combined in the King
County study to form a situation where the standard failing septic
signatures were masked or camouflaged. The signs of failing septic
systems were not as strong, nor did they occur with the frequency
that was expected (considering the poor soil and geologic conditions
of the area).
A preliminary analysis of the imagery concluded that signatures
of septic-related problems could be identified. However, when field
checked, a number of these signatures proved to be unrelated to septic
system failures. Signatures indicating "seasonal stress" (see volume
II, page 3) were identified in an area that was sewered. (Sewered
areas are not usually included in study areas.)
In early May the King County Health Department had conducted an
extensive door-to-door survey in the Lake Desire area. EPIC's analysis
indicated that there were 25 signatures of surface failures in this
area. Only one of these corresponded with the Health Department survey.
A detailed explanation of the definition of a surface failure and how
the signatures appear on the imagery improved this correlation.
Further research, coordination and field checking resulted in an
agreement that the following factors contributed to a below-average
number of failure identifications:
1.	Scheduling requirements which resulted in the acquisition of
the photography at a less than optimum time.
2.	The inconsistent definition of the terms "surface", "seasonal",
and "stressed" septic failure. This inconsistency occurred between
EPIC's definitions for analytical purposes, and the Health Department's

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definitions for legal purposes.
3. The unique climate and geology of the Puget Sound area,
overall, EPIC's technique for the discovery of septic problems
was hampered by excessive moisture, a low water table and extensive
tree canopy throughout much.of the study area. Figure 1 shows that
even with these problems, EPIC was able to identify a total of 121
surface failures, 220 seasonal failures, and 463 signatures of sea-
sonal stress. The predominance of seasonal stress signatures was
the result of the conditions (discussed earlier) which effectively
masked and/or reduced the strength of the signatures. (See volume
II for specific signature locations and example photographs.)
While a vast array of problems surrounded this project, it is
the general opinion of the EPIC analysts that this report will pro-
vide valuable information for future studies of this type in the
Northwest, and will be helpful, in making long-range water-quality
planning decisions.

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RESULTS
Septic Systems Performance Analysis
King County, Washington
QUAD SHEET
AUBURN
BLACK DIAMOND
bothell
ISSAQUAH
KIRKLAND
maltby
maple valley
mercer island
redmdnd
renton
surface
FAILURE
24
1
3
31
3
8
15
12
7
17
SEASONAL
FAILURE
30
13
8
38
21
9
41
8
23
29
SEASONAL
STRESS
39
12
14
55
25
59
77
11
35
136
TOTAL
TOTALS
121
220
463
wnrp. The number of signatures applies only to the study area portion of each quad
sheet. See LOCATION DIAGRAM in Volume II for a graphic outline of the study
area and each individual quad sheet.
FIGURE 1.

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TEMPERATURE AVERAGES AND EXTREMES ("F)
en
Station
Data
JAM
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
DEC
ANNUAL
Bothell
Av. Max.
44.3
48.3
52.8
59.7
66.0
69.7
75.6
75.1
70.8
60.8
51.1
46.8
60.1

Av. Mln.
30.6
31.9
33.8
37.2
41.9
46.2
48.2
50.0
44.9
40.9
35.6
33.8
39.6

Mean
37.5
40.1
43.3
48.5
54.0
58.0
61.9
62.6
57.9
50.9
43.9
40.3
49.9

Highest
67
71
76
88
90
100
100
97
99
86
75
68
100

Lowest
-10
-6
8
20
23
31
35
33
28
21
0
5
-10
Buckley
Av. Max.
43.7
47.5
52.4
59.4
65.8
70.3
76i4
75.3
69.7
59.4
49.7
46.0
59.6
Av. Min.
31.9
33.3
35.2
38.6
43.4
47.0
49.8
49.9
46.8
42.2
.36.6
34.6
40.8

Mean
37.8
40.4
43.8
49.0 '
54.6
58.7
63.1
62.6
58.3
50.8
43.2
40.3
50.2

Highest
70
69
76
84
88
96
102
98
95
87
' 68
65
102

Lowest
-3
1
10
26
30
37
37
38
33
24
2
8
-3
Kent
Av. Max..
45.9
49.8
54.5
62.6
68,8
73.0
78.8
77.8
72.2
62.5
52.0
47.7
62.1

Av. Min.
32.2
33.9
35.5
39.0*
43.6
48.2
50.9
50.5
46.7
42.5
36.0"
34.4
41.1

Mean
39.1
41.9
45.0'
50.8
56.2
60.6
64.9
64.2
59.5
52.5
44.0
41.1
51.6

Highest
70
69
77
88
90
100
100
98
95
87
71
64
i 100

Lowest
3
-5
10
23
27
33
34
37
30
24
6
8
-5
Landsburg
Av. Max.
43.4
47.9
52.8
60.0
66.1
70.2
75.8
75.0
70.2
60.4
50.2
45.5
59.8

Avi Min.
30.5
31.7
33/8
36.7
41.5
45.6
48.0
47.6
44.6
40.3
35.0
33.1
39.0

Mean
36.9
39.8
43.3
48.4
53.8
57.9
61.9
61.3
-57.4
50.3
42.6
39.3
49.4

Highest
66
70
80
85
90
101
101
100
93
84
76
72
.101

Lowest
1
1
12
23
25
31
34
34
30
22
4
8
1
Palmar
Av. Max.
41.6
45.6
50.3
58.5
65.6
69.7
76.3
75.4
70.1
60.0
49.3
43.8
58.9

Av. Min.
30.2
31.6
33.5
37.0
42.2
46.1
49.8
49.8
47.1
42.4
36.5
• 33.6
40.0

Mean
35.9
38.6
41.9
47.8
53.9
57.9
63.1
62.6
58.6
51.2
42.9
38.7
49.4

Highest
66
66
78
88
91
100
101
101
95
85
74
64
101

Lowest
0
4
12
22
30
32
38
38
32
21
6
10
0
FIGURE 2.

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FIGURE 3.
TEMPERATURE AVERAGES AND EXTREMES (*F) continued
Station
Data
JAN
FEB
MAR
APR
MAY
JUH
JUL
AUG
SEP
OCT
NOV
DEC
ANNUAL
Puyallup Exp. Sta.
Av. Max.
45.9
49.6
54.1
61.8
68.5
72.4
78.3
77.6
71.8
62.2
52.1
48.0
o
61.9

Av. Hin.
31.3
33.1
35.0
38.. 2
42.5
47.1
49.2
48.7
45.8
41.7
35.6
33.7
40.1

Mean
38.6
41.3
44.5
50.0
55.5
59.8
63 .>
63.1
58.8
51.9
43.8
40.8
51.0

Highest
66
69
75
87
90
101
99
99
92
82
72
66
101

Lowest
-3
1
12
23
25
34
38
33 •
30
22
0
7
-3
Seattle Boeing
Av. Max.
45.2
49.5
54.3
61.8
68.5
73.1
78.4
77.1
71.5
62.3
52.4
47.3
61.8
Field
Av.* Min.
31.1
33.6
36.4
40.7
46.2
51.2
54.9
54.0
49.4
42.9
35.9
33.5
42.5

Mean
38.2
41.6
45.4
51.3
57.4
62.2
66.7
65.6
60.5
52.6
44.2
40.4
52.2

Highest
69
70
76
85
90
99
99
100
92
82
69
67
100

Lowest
3
4
16
28
30
37
44
43
33
24
8
11
3
Seattle City
Av. Max.
45.6
48.8
52.7
59.4
*65.7
69.6
75.1
73.9
69.0
60.4
51.8
48.0
60.0
Av. Min.
36.8
38.3
40.1
44.1
49.0
53.1
¦ 56.1
56.1
53.3
48.3
41.9
39.5
46.4

Mean
41.2
43.6
46.4
51.8
57.4
61.4
65.6
65.0
61.2
54; 4
46.9
43.8
53.2

Highest
66
70
75
87
92
100
100
97
92
78
70
65
ioo

Lowest
11
12
22
31
35
45
48
48
42
30
13
21
11
Saattle-Tacoma
Av. Max.
43.6
47.0
51.3
58.2
65.6
69.9
75.6
74.6
69.3
60.3
49.6
45.9
59.2
Airport
Av. Min.
33.0
34.5
36.2
,40.1
45.3
49.7
54.1
53.6
50.5
44.4
38.1
35.7
42.9

Mean
38.3
4Q.8
43.8
.49.2
55.5
59.8
64.9
64.1
59.9
52.4
43.9
40.8
51.1

Highest
61
68
71
77
93
90
97
99
89
80
65
60
-99

Lowest
12
18
23
30
33
41
46
45
39
33
23
10.
10
Seattle U of W
Av. Max.
45.6
49.2
53.7
60.8
67.0
71.5
76.6
75.7
70.7
61.8
51.8
47.8
61.0

Av. Min.
34.6
36.0
38.1
41.8
46.9
51.2
54.8
54.7
51.5
46.4
40.2
37.6
44.5

Mean
40.1-
42.6
45.9
51.3
57.0
61.4
65.7
65.2
61.1
54.1
46.0
42.7
52.8

Highest
68
71
75
88
90
98
98
96
96
88
67
65
98

Lowest
6
8
17
30
34
'36
41
46
39
29
10
15
6
Snoqualmia Palls
Av. Max.
43.8
47.7
52.8
60.8
67.1
71.1
77.1
76.3
70.2
60.3
50.5
46.0
60.3

Av, Min.
31.5
32.7
34.2
37.6
41.8
'46.1
48.9
48.5
45.2
41.1
36.1
34.5
39.9

Mean
37.7
40.2
43.5
49.2
54.5
58.6
63.0
62.4
57.7
50.7
43.3
40.3
50.1

Highest
66
67
77
90
90
99
99
102
93
84
75
64
102

Lowest
-1
-3
8
24
26
31
36
35
30
23
2
6
-3

-------
u
loo
ISO
loo
Bothell Buckley Landsburg Puyallup Sea-Tac U of W Sno. Falls j
Mean Growing Season (Days)	i
240 Days
207 Days
192 Davs
145 Days
157 Days
165 Days
156 Days
i%0 _		Snoqualmie Pass .	.•••*"%
_		Landsburg '	/ \
jig —		Buckley	\
6 ^		Bothell	/
114 -		Kent
<12 H
/
/
no -	\
x
•I	V	/
\
r\.
6

A
	/>>
			
4 -[
2 -i		
I—i—i—i—t—i—¦¦—¦ ' ' ¦ r7
JAN FEB MAR APR MAY JON JUL AUG SEPT OCT NOV DEC JAN
Average Monthly Precipitation (inches)
FIGURE 4.

-------
AVERAGE NUMBER OF DAYS WITH PRECIPITATION

JAN
FEB
MAR
APR
HAY
JUN
JUL
AUG
SEP
OCT
NOV
DEC
ANNUAL
.01 or more













Buckley
19
16
17
16
13
12
5
6
10
14
17
19
164
Kent
17
14
13
10
9
7
3
4
7
12
17
16
129
Puyallup Exp. Sta.
18
15
16
12
10
8
3
4
7
12
16
18
139
Seattle City
19
15
16
13
11
9
5
6
8
14
17
19
151
Snoqualmie Palls
20
17
19
16
14
11
5
6
10
16
20
21
175
Snoqualmie Pass
19
16
18
14
12
11
5
6
9
14
17
21
162
.10 or more













Buckley.
13
12
13
10
9
8
3
4
6
10
13
15
116
Kent
14
11
10
8
5
4
2
3
5
10
12
14
98
Puyallup Exp. Sta.
13
11
11
8
6
5
2
3
5
9
12
14
99
Seattle City
12
10
10
8
5
4
2
3
4
8
14
13
93
Snoqualmie Falls*
15
12
14
10
8
7
3
4
7
11
14
16
121
Snoqualmie Pass
18
15
16
12
11
9
4
4
8
12
15
*18
131
.50 or more













\Buckley
4
3
2
2
2
2
1
1
2
3
5
5
32
Kent
4
3
2
1
1
1
1
*
*
2
4
4
23
Puyallup Exp. Sta.
4
2
2
1
1
*
*
1
1
2
4
4
22
Seattle City
4
2
1
1
*
*
*
*
1
2
4
3
18
Snoqualmie Falls
7
4
4
3
2
2
1
1
2
4
6
6
42
Snoqualmie Pass
13
10
9
6
4
2
1
2
3
7
11
13
81
1.00 or more













Buckley
1
1
*
*
*
*
0
*
*
1
1
1
5
Kent
1
1
*
*
i>
0
*
0
0
1
1
1
5
Puyallup Exp. sta.
1
1
*
*
0
0
*
*
*
*
1
1
4
Seattle City
1
1
0
*
0
*
0
0
*
*
1
1
4
Snoqualmie Falls
2
1
1
*
*
*
*
*
1
1
3
1
10
Snoqualmie Pais
6
4
4
2
1
*
*
*
2
4
6
6.
35
FIGURE 5

-------
AVERAGE MONTHLY AND ANNUAL PRECIPITATION (Inches)
Eleva-
Station tion
JAN
FEB
MAR
APR
HAY
JUN
JUL
AUG
SEP
OCT
NOV
DEC
ANNUAL
Bothell
100
5.59
4.35
3.84
2.47
2.40
2.15
*B1
.99
1.88
3.80
5.18.
5.82
39.28
Buckley
685
5.59
4.71
4.94
3.86
3.13
3.36
1.25
1.41
2.77
5.15
6.23
6.91
49.31
Kent
40
5.81
4.16
3.69
2.37
1.82
1.67
.84
.89
1.76
4.06
5.26
6.15
38.48
Landsburg
535
6.97
5.63
5.76
4.02
3.23
3.31
1.34
1.64
3.39
5.80
7.26
8.13
56.48
Puyallup Exp. Sta.
50
5.63
4.66
4.14
2.64
2.02
1.81
.81
.96
2.03
3.95
5.45
6.40
40.50
Seattle toeing Field
14
5.46.
4.21
3.53
2.15
1.58
1.43
.66
.81
1.83
3.50
5.22
5.73
36.11
Seattle City
14
5.19
3.90
3.32
1.97
1.59
1.41
.63
.74
1.65
3.28
5.00
5.42
34.10
Seattle Maple Leaf Res.
422
4.98
4.12
3.11
2*. 08
1.76
1.57,1
.77
.85
1.62
3.28
4.87
4.77
33.78
Seattle Naval Air Sta.
21
4.85
3.73
3.20
2.09
1.80
1.59
.65
.89
1.86
3.44
4.75
5.24
34.09
Seattle-Tacoma Airport
386
5.73
4.24
3.79
2.40
1.73
1.58
.81
.95
2.05
4.02
5.35
6.29
38.94
Seattle U of W
112
5.02
3.93
3.28
2.16
1.84
1.62
.74
.75
1.72
3.42
5.01
5.47
34.96
Snoqualmie Falls
440
7.85
6.35
6.14
4.00
3.20
3.21
1.29
1.43
3.18
6.15
8.38
9.12
- 60.30
Snoqualade Pass
3,020
14.77
12.74
11.72
6.39
4.68
4.86
1.67
2.03
4.81
10.46
15.41
18.06
107.60
FIGURE 6.

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.EG END
ALDERWOOD
ORIDIA-SEATTLE-WOOD1NVILLE
BUCKLEY-ALDERWOOD
EVERETT
BEAUSITE-ALDER WOOD
ALDER WOOD-KITSAP-IN DIANOLA
PUGET-EARLMONT-SNOHOMISH
DATA NOT AVAILABLE

-------
I
—Geologic material in the King County Area.
FIGURE 8.
96

-------