HomeMy WebLinkAbout2005 WRIA 17 Watershed Temperature Study1
Quilcene and Chimacum Stream Temperature Analysis
WRIA 17 Watershed Temperature Study:
Data Collection and Analysis
Prepared for:
Port Gamble S'Kallam Tribe
Jefferson County
Washington Department of Ecology
9
PORT GAMBLE
S'KLALLAM TRIBE
April 7, 2005
Prepared by:
JEFFERSON COUNTY
CONSERVATION
DISTRICT
\Nf
Watershed Sciences, Inc.
Primary Investigators Include:
Ted Labbe, Port Gamble S'Klallam Tribe (PGST)
Glenn Gately, Jefferson County Conservation District (JCCD)
David Christensen, Jefferson County Conservation District (JCCD)
Matthew Boyd, Watershed Sciences (WSI)
Russ Faux, Watershed Sciences (WSI)
Final
Quilcene and Chimacum Stream Temperature Analysis
Table of Contents
Project Description ............................................................................. ..............................1
StudyArea ......................................................................................... ............................... l
Fisheries and Aquatic Habitat ............................................................ ............................... 2
ProjectObjectives ............................................................................. ............................... 5
Primary Questions to Be Addressed .................................................. ............................... 6
1. Data Type and Applications - Overview ....................................... ..............................7
1.1 Remote Sensing Data Types ........................................................ ............................... 7
1.2 Ground Level Data Types ........................................................... .............................12
2. Thermal Infrared Radiometry (TIR) Analysis ............................ .............................13
2.1 Methods ...................................................................................... .............................13
2.3 Results ........................................................................................ .............................19
2.3 Big Quilcene River ..................................................................... ............................... 20
2.4 Little Quilcene River .................................................................... .............................26
2.5 Leland Creek ............................................................................. ............................... 30
2.6 Tarboo Creek ............................................................................ ............................... 32
2.7 Chimacum Creek ....................................................................... ............................... 35
2.8 East Chimacum Creek ............................................................... ............................... 40
2.9 Summary of Survey Results ....................................................... ............................... 41
3. LiDAR Data Sampling and Analysis ............................................ .............................43
3.1 Stream Position and Data Nodes ............................................... ............................... 43
3.2 Stream Aspect ........................................................................... ............................... 45
3.4 Topographic Shade ...................................................................... .............................51
3.5 Near Stream Vegetation Height ................................................. ............................... 54
3.6 Historical Vegetation Analysis ................................................... ............................... 69
4. Flow and Temperature Data ......................................................... .............................72
4.1 Continuous Flow Measurements and Derived Flows ................. ............................... 74
4.2 Instantaneous Flow Measurements ............................................ ............................... 78
4.3 Bathymetry Data ........................................................................ ............................... 81
4.4 Continuous Stream Temperature Data ....................................... ............................... 96
4.5 Continuous Atmospheric Data .................... ............................... ............................106
5. Stream Temperature Model .......................... ............................... ............................110
5.1 Model Overview .......................................... ............................... ............................110
5.2 Calibration Methods .................................... ............................... ............................120
5.3 Validation Statistics ................................... ............................... ............................122
5.4 WRIA 17 Stream Temperature Model Scenarios ...................... ............................135
6. Discussion ........................................................ ............................... ............................167
References ........................................................... ............................... ............................170
Table of Figures
Figure 1. Historical Summer Chum Escapement (NOAA Fisheries Data) ..................................................... 3
Figure 2. Digital Orthophoto Quads .................................................................................................................
8
Figure3. TIR Images .......................................................................................................................................
9
Figure 4. LiDAR data for Little Quilcene River . ..........................................................................................
10
Figure 5. Continuous Temperature and Instantaneous Flow Measurement Sites ............ .............................12
Figure 6. Sensor mount used for the TIR and color video stream surveys . ..................................................
14
Figure 7. WIRA 17/East Jefferson County Study Area ..................................................................................
15
Figure 8. Various Color Maps and True Color Image ...................................................................................
18
Figure 9. Big Quilcene River longitudinal profile sampled from TIR data ..................... .............................20
Figure 10. TIR Image: Big Quilcene River Mouth . ......................................................................................
22
Figure 11. TIR Image: Big Quilcene River Springs/Seeps (river miles 1.2 and 1.3) ....... .............................23
Figure 12. TIR Image: Big Quilcene River Spring (river miles 1.5 and 2. 1) ................... .............................24
Figure 13. TIR Image: Big Quilcene River Spring (river miles 2.9) ............................. ...............................
25
Figure 14. TIR Image: Big Quilcene River, Unnamed Tributary (river miles 3.2) . .....................................
25
Figure 15. Little Quilcene River longitudinal profile ....................................................................................
26
Figure 16. TIR Image: Little Quilcene River Mouth .....................................................................................
28
Figure 17. TIR Image: Little Quilcene River at Leland Creek Confluence (river mile 1.6) .........................29
Figure 18. TIR Image: Little Quilcene River Channel Characteristics (river mile 2.2) ... .............................29
Figure 19. Leland Creek longitudinal profile sampled from TIR data ............................. .............................30
Figure 20. TIR Image: Leland Creek Channel Characteristics (river mile 1.4) ............... .............................31
Figure 21. Tarboo Creek longitudinal profile sampled from TIR data .........................................................
32
Figure 22. TIR Image: Tarboo Creek at mouth ..............................................................................................
33
Figure 23. TIR Image: Tarboo Creek Channel Characteristics (river miles 0.6 & 1.6) .... .............................34
Figure 24. Chimicum Creek longitudinal profile sampled from TIR data ....................... .............................35
Figure 25. TIR Image: Chimacum Creek at mouth ........................................................................................
37
Figure 26. TIR Image: Chimacum Creek Channel Characteristics (river mile 1.7) .......... .............................38
Figure 27. TIR Image: Chimacum Creek Channel Characteristics (river mile 2.8) .......... .............................38
Figure 28. TIR Image: Chimacum Creek Channel Characteristics (river mile 5.2) .......... .............................39
Figure 29. TIR Image: Chimacum Creek Channel Characteristics (river mile 8.2) .......... .............................39
Figure 30. East Chimicurn Creek longitudinal profile sampled from TIR data ............... .............................40
Figure 31. TIR Image: East Chimacum Creek Channel Characteristics (river mile 1.0) .. .............................41
Figure 32. LiDAR scene on Big Quilcene River near the Fish Hatchery .....................................................
43
Figure 33. LiDAR scene on Tarboo Creek. Digitized stream polyline segmented at 25 meter interval
provide nodes (blue dots) for sampling spatial data ................................................................................
44
Figure 34. Stream aspect is calculated by calculating the angle between two stream nodes .........................
45
Figure 35. Stream and valley aspect, along with absolute divergence between stream and valley
aspects......................................................................................................................................................
46
Figure 36. The procedure for sampling stream elevation involves twenty five discrete samples in a
radial pattern to locate the lowest datum .................................................................................................
48
Figure 37. Stream gradient\t and sinuosity ....................................................................................................
50
Figure38. Topographic Shade Angles ..........................................................................................................
53
Figure 39. Vegetation Sampling Methodology . ............................................................................................
55
Figure 40. Sampled Vegetation Height - Big Quilcene River (Note Missing LOAR Data) .........................
56
Figure 41. Sampled Vegetation Height Statistics - Big Quilcene River .......................................................
57
Figure 42. Sampled Vegetation Height - Little Quilcene River ....................................................................
58
Figure 43. Sampled Vegetation Height Statistics - Little Quilcene River ....................... .............................59
Figure 44. Sampled Vegetation Height - Leland Creek ................................................................................
60
Figure 45. Sampled Vegetation Height Statistics - Leland Creek ................................................................
61
Figure 46. Sampled Vegetation Height - Tarboo Creek ................................................................................
62
Figure 47. Sampled Vegetation Height Statistics - Tarboo Creek ................................................................
63
Figure 48. Sampled Vegetation Height - Chimacum Creek ............................................. .............................64
Figure 49. Sampled Vegetation Height Statistics - Chimacum Creek ............................. .............................65
Figure 50. Sampled Vegetation Height - East Chimacum Creek .................................... .............................67
Figure 51. Sampled Vegetation Height Statistics - East Chimacum Creek ..................... .............................68
Figure 52. Historical Riparian Vegetation Distribution (PGST Data) ............................. .............................70
Figure 53. Vegetation Species Average Growing Height Based Upon Measured Data in Pacific
NorthwestCoastal Areas ............................................................................................ .............................71
Figure 54. Gage Data (Department of Ecology, River and Stream Monitoring,
https:H fortress. wa. gov /ecy /wrx/ wrx/flows /station.asp ?sta= 17G060) ...................... ...............................
75
Figure 55. Big Quilcene River: Area Weighted Derived Flows ....................................... .............................76
Figure 56. Little Quilcene River: Area Weighted Derived Flows .................................... .............................76
Figure 57. Tarboo Creek: Area Weighted Derived Flows ................................................ .............................77
Figure 58. Chimacum Creek: Area Weighted Derived Flows ......................................... .............................77
Figure 59. East Chimacum Creek: Area Weighted Derived Flows .................................. .............................78
Figure 60. Instantaneous Flow Monitoring Sites .............................................................. .............................80
Figure 61. Little Quilcene River Bathymetry and Derive Trapezoidal Channel Shapes ..............................
89
Figure 62. Big Quilcene River Bathymetry and Derive Trapezoidal Channel Shapes .. ...............................
90
Figure 63. Tarboo Creek Bathymetry and Derive Trapezoidal Channel Shapes ........... ...............................
91
Figure 64. Chimacum Creek Bathymetry and Derive Trapezoidal Channel Shapes ..... ...............................
93
Figure 65. East Chimacum Creek Bathymetry and Derive Trapezoidal Channel Shapes ............................
94
Figure 66. Leland Creek Bathymetry and Derive Trapezoidal Channel Shapes ............ ...............................
95
Figure 67. Summary of Maximum 7 -Day Moving Average of Daily Maximums .......... .............................96
Figure 68. Big Quilcene River Continuous Temperature Data and 7 -Day Statistics ....... .............................98
Figure 69. Little Quilcene River Continuous Temperature Data and 7 -Day Statistics .. ...............................
99
Figure 70. Tarboo Creek Continuous Temperature Data and 7 -Day Statistics ............... ............................100
Figure 71. Leland Creek Continuous Temperature Data and 7 -Day Statistics ............... ............................101
Figure 72. Chimacum Creek Continuous Temperature Data and 7 -Day Statistics ......... ............................102
Figure 73. East Chimacum Creek Continuous Temperature Data and 7 -Day Statistics . ............................103
Figure 74. Leland Creek Air Temperature Data Comparison .......... ............................... ............................107
Figure 75. Chimacum Creek Air Temperature Data Comparison .... ............................... ............................108
Figure 76. Port Angeles Relative Humidity and Cloud Cover Data ............................... ............................109
Figure 77. Simulated Heat Transfer Processes: Big Quilcene River at Mouth, August . ............................113
Figure 78. Thermal Infrared Radiometer Data (July 29`", 2004 -2:00 -4:00 PM) ........... ............................117
Figure 79. Little Quilcene Validation Statistics ............................... ............................... ............................123
Figure 80. Little Quilcene Longitudinal Profiles Compared to TIR Data ....................... ............................124
Figure 81. Big Quilcene Validation Statistics .................................. ............................... ............................125
Figure 82. Big Quilcene Longitudinal Profiles Compared to TIR Data .......................... ............................126
Figure 83. Tarboo Creek Validation Statistics ................................. ............................... ............................127
Figure 84. Tarboo Creek Longitudinal Profiles Compared to TIR Data ......................... ............................128
Figure 85. Chimacum Creek Monitoring Sites ................................. ............................... ............................129
Figure 86. Chimacum Creek Validation Statistics (a) ...................... ............................... ............................130
Figure 87. Chimacum Creek Validation Statistics ( b) ...................... ............................... ............................131
Figure 88. Chimacum Creek Longitudinal Profiles Compared to TIR Data ................... ............................132
Figure 89. East Chimacum Creek Validation Statistics ( a) .............. ............................... ............................133
Figure 90. East Chimacum Creek Validation Statistics ( b) .............. ............................... ............................134
Figure 91. East Chimacum Creek Longitudinal Profiles Compared to TIR Data ........... ............................134
Figure 92. Little Quilcene Model Scenarios - Resulting Temperature Changes ............ ............................139
Figure 93. Little Quilcene Model Scenarios - 7 -Day Max Moving Ave of the Daily Max .......................140
Figure 94. Little Quilcene Model Scenarios - Longitudinal Profiles for Model Scenarios ........................141
Figure 95. Big Quilcene Model Scenarios - Resulting Temperature Changes ............... ............................144
Figure 96. Big Quilcene Model Scenarios - 7 -Day Max Moving Ave of the Daily Max ..........................145
Figure 97. Big Quilcene Model Scenarios - Longitudinal Profiles for Model Scenarios ...........................146
Figure 98. Tarboo Creek Model Scenarios - Resulting Temperature Changes .............. ............................149
Figure 99. Tarboo Creek Model Scenarios — 7 -Day Max Moving Ave of the Daily Max .........................150
Figure 100. Tarboo Creek Model Scenarios — Longitudinal Profiles for Model Scenarios ........................151
Figure 101. Chimacum Creek Model Scenarios — Resulting Temperature Changes (a) . ............................157
Figure 102. Chimacum Creek Model Scenarios — Resulting Temperature Changes (b) ............................158
Figure 103a. Chimacum Model Scenarios — 7 -Day Max Moving Ave of the Daily Max ..........................159
Figure 104. Chimacum Model Scenarios — Longitudinal Profiles for Model Scenarios ............................160
Figure 105. East Chimacum Creek Model Scenarios — Resulting Temperature Changes ..........................163
Figure 106. East Chimacum Model Scenarios — 7 -Day Max Moving Ave of the Daily Max (a) ...............164
Figure 107. East Chimacum Model Scenarios — 7 -Day Max Moving Ave of the Daily Max (b) ..............165
Figure 108. East Chimacum Model Scenarios — Longitudinal Profiles for Model Scenarios ....................166
Table of Tables
Table 1. Spatial Data Types and Associated Applications ................................................. ..............................7
Table 2. Waterbodies and Extents, and Times TIR Surveyed .......................................... .............................15
Table3. Atmospheric Conditions ...................................................................................... .............................19
Table4. TIR Accuracy Statistics ...................................................................................... .............................19
Table 5. Tributaries, surface springs, and other detected surface inflows ....................... .............................21
Table 6. Little Quilcene River tributaries, surface springs, and other detected surface inflows ...................26
Table 7. Stream Extent Digitized and Segmented into 25 meter Nodes .......................... .............................45
Table 8. Sampled Vegetation Height Statistics - Big Quilcene River .............................. .............................57
Table 9. Sampled Vegetation Height Statistics - Little Quilcene River ........................... .............................59
Table 10. Sampled Vegetation Height Statistics — Leland Creek ..................................... .............................61
Table 11. Sampled Vegetation Height Statistics — Tarboo Creek .................................... .............................63
Table 12. Sampled Vegetation Height Statistics — Chimacum Creek .............................. .............................66
Table 13. Sampled Vegetation Height Statistics — East Chimacum Creek ...................... .............................68
Table 14. Flow and Temperature Monitoring Locations and Site Identification ............. .............................73
Table 15. Instantaneous Flow Monitoring Sites ............................................................... .............................79
Table 16. Fitted Bottom Width and Side Slope Ratios (Z) .............................................. .............................82
Table 17. Seven (7) day moving average daily maximum (7 -day stat) temperatures ...... .............................97
Table 18. Model Validation Statistics .............................................. ............................... ............................122
Table 18. Little Quilcene River - Maximum Temperatures per Model Run ................... ............................137
Table 19. Little Quilcene River — Temperature Changes per Model Run ....................... ............................138
Table 20. Big Quilcene River - Maximum Temperatures per Model Run ...................... ............................142
Table 21. Big Quilcene River — Temperature Changes per Model Run ......................... ............................143
Table 22. Tarboo Creek - Maximum Temperatures per Model Run ............................... ............................147
Table 23. Tarboo Creek — Temperature Changes per Model Run ... ............................... ............................148
Table 24. Chimacum Creek - Maximum Temperatures per Model Run ......................... ............................152
Table 25. Chimacum Creek — Temperature Changes per Model Run ............................ ............................155
Table 24. East Chimacum Creek - Maximum Temperatures per Model Run ................. ............................161
Table 25. East Chimacum Creek — Temperature Changes per Model Run ..................... ............................162
Acknowledgments
Ted Labbe from the Port Gamble S'Klallam Tribe (PGST) provided project management
and oversight through its Department of Natural Resources, Habitat Program. Ted's
leadership and the Tribe's commitment to this project is evident in every phase.
Glenn Gately from the Jefferson County Conservation District (JCCD) helped design and
implement extensive monitoring for this project. His knowledge of the stream systems,
access, and past monitoring proved invaluable to the project.
Members of the WRIA 17 /east Jefferson County watershed planning unit helped in
scenario development and document review.
The Washington Department of Ecology recognized the value of determining
flow /temperature relationships and funded the effort with grant # G0400297.
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Project Description
The study area is located in the northeat region of the Olympic Peninsula (Washington)
and includes: Chimacum Creek, East Chimacum Creek, Big Quilcene River, Little
Quilcene River, Leland Creek and Tarboo Creek. Working together under the WRIA
17 /east Jefferson County watershed planning unit, the Port Gamble S'Klallam Tribe
(PGST) and Jefferson County Conservation District QCCD) initiated this joint project to
monitor and analyze summer stream temperature -flow conditions in these six priority
watersheds during 2004. Part of this effort includes data collection to acquire calibrated
thermal infrared radiometry (TIR) data in 28.5 miles of stream, collect and compile
additional field data (flow, morphology, riparian and temperature), and post - process
LiDAR data. These data will serve as primary inputs for hydrodynamic and water
temperature models developed to define June to October stream temperature flow
relationships.
JCCD and PGST lead this overall project (e.g., TIR acquisition and model
development/calibration efforts), collaborating with other W 17 PU stakeholders to collect
stream flow and temperature ground - truthing data. The Port Gamble S'Klallam Tribe
provided project management and oversight through its Department of Natural
Resources, Habitat Program.
As with any study, identifying analytical objectives and primary questions are important
initial steps. The scope of work outlines objectives, based on similar projects in other
watersheds and the field knowledge of JCCD and PGST of the target watersheds. The
primary objective is to collect data and perform analysis that evaluates flow, morpholog
and riparian influence of seasonal
temperature patterns. The methods used
include remote sensing, data processing
and deterministic modeling. All methods
are publicly available, open source and
peer reviewed, lending a scientific
credibility to this effort.
Study Area
The Quilcene, Chimacum, Leland and
Tarboo watersheds are located in
Jefferson County, on the northeast
portion of the Olympic Peninsula,
Washington. These watersheds drain
forested and agricultural lands with
varying degrees of anthropogenic
influences, including: flow reductions
and withdrawals, riparian vegetation
disturbance and morphology alterations.
Study Area
Targeted Stream Sections in Red
Port
1
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Water Usage
Surface and subsurface withdrawals are extensive in the study area (WRIA 17, 2003).
For example, consumptive water rights total more than 30 cfs on the Big Quilcene River
and more than 10 cfs on the Little Quilcene River. In addition, the Quilcene National
Fish Hatchery has water rights for 40 cfs from the Big Quilcene River and 25 cfs from
Penny Creek, though both volumes are returned to the river downstream from the
hatchery. Given that the Big Quilcene 90% exceedance flows in July and August are
estimated to be 66 and 36 cfs respectively, the impact of these potential diversions on
both physical and thermal habitats is targeted in this study. In addition to large surface
water withdrawals, there are also numerous small surface and groundwater withdrawals
for single and multi - family domestic use that may impact the stream flow conditions.
The alluvial unconfined reaches of the study reaches are connected to shallow
groundwater and experience varying levels of hyporheic exchange. The extent of
hyporheic influence on surface hydraulics and temperature patterns is often difficult to
quantify, along with subsurface hydraulics and thermodynamics. It has been shown that
surface and subsurface waters can exhibit a high degree of interrelated temperature
behavior in alluvial floodplains (Boyd et al., 2004, Poole and Berman 2001). It is also
established that shallow groundwater wells can effectively reduce surface flows in these
highly connected floodplains (Poole et al., 2002). Shallow groundwater exchange, both
heat and mass, are considered in this study.
Fisheries and Aquatic Habitat
The study area is home to native coho and chum salmon and sea -run cutthroat and
steelhead trout. Chinook and pink salmon also have limited use of the streams in the
study area (WRIA 17, 2003). Puget Sound chinook are present in WRIA 17, it is unclear
whether native chinook runs still exist in Hood Canal, since this stock has mixed
significantly with a variety of supplemented hatchery stocks.
Of the streams included in this analysis, summer chum salmon use the Big Quilcene
River, the Little Quilcene River and Chimacum Creek. Inconsistent adult chinook returns
to the Big Quilcene River and Tarboo Creek are likely comprised of artificially
supplemented stocks. Fall chum in the Quilcene Bay and Dabob Bay sub -basins are
considered healthy (WRIA 17, 2003). Coho stocks are depressed in Quilcene and Dabob
watersheds. Very little is known about winter steelhead populations.
General salmonid habitat requirements are described as follows in WRIA 17, 2003:
"Each species depends upon adequate freshwater flow and water quality, ample
spawning gravels, a functional riparian zone, and instream habitat structures such as
large woody debris, large boulders, and pools. All species also depend upon healthy and
productive nearshore and estuarine habitats, although chum and chinook salmon tend to
rely on these habitats for greater periods of time than do coho [and] steelhead... In the
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
nearshore and estuarine environments, high salt marsh, eelgrass, and shallow habitats
are critical to all species as they make the transition to the marine environment. "
Figure 1. Historical Summer Chum Escapement (NOAA Fisheries Data)
For the purposes of this study, we compared observed and modeled stream temperatures
to proposed Washington State water quality criteria, which were developed to protect
salmon and trout thermal habitat needs. The Washington State criteria require that the
highest 7 -day average of daily maximum (7- DADMax) water temperatures not exceed
16 °C to protect salmon and trout spawning, rearing, and migration. In addition, a
separate threshold of 13 °C applies in select streams with spawning populations of
threatened summer chum salmon and other sensitive stocks during the period September
15 to July 1. At the time of this study, these standards had not yet been formally adopted.
For more current information, please refer to the Washington Department of Ecology
water quality standards website: http: / /www.ecy.wa.goy /programs /wq /swgs /index.html.
Local observations indicate that for the Quilcene River system that summer chum salmon
spawning occurs between August 15th through October 15t'`, and September lst through
October 15th for the Chimacum stream system.'
1 Al Latham, Jefferson County Conservation District, e-mail communication.
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Salmon & Trout Thermal Needs
16 °C Rearing & Migration
All Study Streams
All Year
Summer Chum Salmon Thermal Needs
16 °C Rearing & Migration
All Study Streams
July 1St to September 15th
13 ()C Spawning &I ncubation
All Study Streams, Excluding East Chimacum
September 15th to July 1St
Note: The values above are used in this report to assess river temperature in relation to
the thermal limits for salmonid life stages. For chum salmon these are not regulatory
values. A compelling case can be made for slight variations in the timing of chum
salmon life stages. An effort has been made to balance literature /research values with
local observations.
Human activities and land uses have historically degraded salmon habitat. Some of these
activities continue today. Further, future pressures on habitat can be expected by
increases in population and development. "Forest practices, agriculture, rural
development and shoreline development have had negative effects. For example, timber
harvest on state and private forestlands, if not managed properly, can result in reduced
riparian habitat and increased sediment loads in streams. These changes can result in
higher water temperatures, lack of large woody debris, reduced woody debris
recruitment, and smothering of spawning gravels, all of which are detrimental to
salmonids" (WRIA 17, 2003).
An obvious habitat reduction stems from withdrawing surface water flows. The
reduction of both physical and thermal habitats associated with flow reductions is
implicated as critical for summertime salmonid uses, such as summer chum salmon.
Agricultural land use in the floodplains of many WRIA 17 sub - basins simplify
morphology through direct channelization and/or reduced bank stability that alters
entrenchment and meandering patterns. Reduced channel complexity is exacerbated by
road placement, draining beaver ponds, and removing/disturbing floodplain vegetation.
Residential development also reduces riparian function through activities that remove and
alter vegetation.
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Jefferson County, WA
WRIA 17 (2003) notes land use changes that are having positive impacts on habitat
quality (as taken directly, page 44):
X The US Park Service and US Forest Service lands in WRIA 17 have some of the
best habitat conditions in the watershed. The Park Service strives to maintain
natural habitats through preservation, and the Forest Service has implemented a
Riparian Reserve Program to provide functioning riparian habitat that ensures
conifer canopy cover for water temperature control, large woody debris
recruitment, streambank stability, and migratory corridors for wildlife species.
X Changes to forest practices regulations have improved protection of streams and
wetlands.
X Agricultural landowners have changed their management techniques and
implemented best management practices that improve and protect water quality
and fish habitat (Jefferson County Conservation District, 2003).
Project Objectives
This project is developed to spatially characterize surface water temperatures and stream
flow conditions over 28.5 miles of stream, employing thermal infrared radiometry,
networks of continuous temperature data loggers and stream flow gages, as well as
additional instantaneous flow measurements and miscellaneous habitat data. The
following objectives are designed to provide the W 17 PU with a tool for formally relating
stream flow to summer to fall water temperature dynamics. The W17 PU intends to use
these models to determine acceptable minimum instream flow levels for the purposes of
protecting aquatic ecosystems. The data collection and analysis completed in this study
may support the future restoration of these streams, all of which are formally listed for
temperature on the State of Washington's Clean Water Act 303(d) list of impaired
waterbodies.
The objectives of the proposed effort are outlined below:
• Spatially characterize surface water temperatures and stream flow conditions over
28.5 miles of stream, employing thermal infrared radiometry, networks of
continuous temperature data loggers and stream flow gages, as well as additional
spot flow measurements and habitat data.
• Using other available remote sensing and spatial data, characterize riparian
shading patterns, dynamic surface hydraulics, geomorphology, near- stream land
cover, and surface and subsurface water exchange patterns.
• Integrate collected and compiled data sets into a suite of models to simulate water
temperature dynamics in the target streams.
• Present the data and overall model to W 17 stakeholders, demonstrating its
application to in- stream flow setting scenario development. Train watershed
stakeholders in the use and manipulation of the integrated stream temperature -
flow models.
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Primary Questions to Be Addressed
• What are the seasonal patterns and spatial distributions of stream temperatures?
• How do existing land and water uses affect stream temperatures spatially and
temporally?
• What are the seasonal and spatial distributions of physical and thermal habitat?
• How do stream withdrawals affect physical and thermal habitat?
• Some scenarios create only a small temperature increase. Does that mean that it
doesn't affect fisheries?
• What are primary and secondary influences of land cover upon surface water
thermal habitat, as simulated by the model?
• Under what conditions can restoration efforts recreate pre - settlement physical and
thermal habitats?
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
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1. Data Type and Applications - Overview
1.1 Remote Sensing Data Types
Widely available ground level data sources include continuous temperature data, flow
rates (gage and instantaneous data) and stream morphology surveys. While these ground
level data are useful, their limited spatial distribution necessitates the development of
spatially continuous data. Exclusive use of ground level data forces extrapolation and
introduces errors. The widespread use of spatial data is required for a methodology that
captures the thermal uniqueness and variability inherent to the study area. Analytical
methods rely upon these data to characterize landscape and riverine features and quantify
their spatial distributions. Some description of the data sources and methods for
derivation is warranted (see the table below).
Table 1. Spatial Data Types and Associated Applications
Spatial Data Type Application
Orthophotography: Map land cover, stream position and morphology
LiDAR': Measure valley /channel morphology, land cover height and
density
Thermal Infrared: Surface water temperatures, direct observation, quantify
surface and subsurface inflows
1.1.1 Orthophotography
Spatial Data Extracted
• Preliminary Stream Mapping
Other Uses
• Cross -check LiDAR Data
A digital orthophoto quad (DOQ) is an aerial photograph digital image (without
displacements caused by the camera angle and terrain). DOQs are projected in map
coordinates, combining the image characteristics of a photograph with the geometric
qualities of a map.
Panchromatic DOQs were acquired in 2002 at 1 meter resolution. These photos were
used to digitize stream position, data that are then refined with LiDAR bare earth data. It
was difficult to distinguish features in Chimacum, Tarboo and Leland Creeks, along with
other areas where vegetation obscures the streams. In cases where the stream cannot be
visually identified, LiDAR data was the sole dataset used to map stream position.
2 LIDAR is an acronym for Light Detection and Ranging.
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DOQs were also used to visually inspect LiDAR data and to identify ground objects (e.g.,
trees, houses, road grades, etc.). The figure below displays DOQs for the entire study
area at various resolutions.
Figure 2. Digital Orthophoto Quads
(A) Entire Study Area (B) Zoomed to 1:10, 000 scale (C) Zoomed to 1:2, 000 scale (the
scale at which stream manning and data sampling is performed)
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1.1.2 Thermal Infrared Radiometry (TIR)
Spatial Data Extracted
• Longitudinal Temperature Patterns
• Groundwater and hyporheic flows
• Tributary temperatures
• Thermal refugia
Thermal infrared radiometry (TIR) data measures the skin water temperature (outermost
portion of the water column). Since water is nearly opaque to longer wavelengths (8-
l2µ) there is little penetration of the water surface. With a well mixed water column (as
occurs in flowing water), TIR effectively measures water column temperature. TIR data
is comprised of a digital image of recorded radiation across the full 12 -bit dynamic range.
When sampled with aerial platforms the digital imagery maintains a continuous image
overlap and less than 0.5 meter pixel. Measured values are directly converted to a
temperature from calibration with ground level monitors, matching TIR accuracy with
monitoring accuracy (approaching f0.5 0C). TIR data collection is usually timed to
capture near maximum daily stream temperatures with sampling occurring longitudinally
over the center of the stream channel and the sensor in a vertical position.
Figure 3. TIR Images
(A) Helicopter platform with TIR System (B) Little Quilcene River ground image (C) TIR
data collected at the mouth of the Little Quilcene River.
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Direct observation of spatial temperature patterns and thermal gradients is a powerful
application of TIR derived stream temperature data (Faux et al. 2001). Thermally
`interesting' areas can be identified in a longitudinal stream temperature profile and
related directly to specific sources (i.e. water withdrawal, tributary confluence, land cover
patterns, point sources, etc.). Subsurface flows (i.e. hyporheic, springs, seeps, etc.) are
usually apparent, and often dramatic, in TIR data. Major diversions of flow,
impoundments and channel modifications also create complex thermal patterns.
1.1.3 LiDAR
Spatial Data Extracted
• Final Stream Mapping
• Stream Gradient
• Topographic Shade
• Stream Bank Elevation
• Vegetation Height
Light detection and ranging (LiDAR) offers extremely accurate high - resolution elevation
mapping (Dubayah et al., 2000). LiDAR measures multiple light returns to the sensor.
Sample point density is a function of light returns to the sensor, but in general, is very
dense. The first return (reflected from a surface and received by the sensor) is from the
closest object to the sensor (likely the top of vegetation — Raw LiDAR). The last return
received by the sensor is usually from the object farthest from the sensor (likely the
ground — Bare Earth LiDAR).
Although, applications have been somewhat limited to date, LiDAR has been
demonstrated to map topographic detail with a high level of accuracy and resolution
(Lefsky et al. 2002, Boyd et al., 2004). LiDAR produces very large data sets that are
easily sampled in GIS. The use of LiDAR data in this project represents a significant
improvement over the methods employed using other elevation and simplified
morphology data (Spies et al. 2003). Further, the inclusion of LiDAR data is relatively
simple and efficient, given the sampling tools developed for Heat Source and other
applications (Boyd and Kasper, 2003). LiDAR data was collected for the entire study
area.
The LiDAR data was obtained during leaf -off conditions (December - March) in 2002.
The UDAR data has point spacing 1.5 m (4.9 ft) with 50% overlapping edges. The
bare earth sample density decreases considerably in dense vegetation. Bare earth LiDAR
data refers to the lowest return for a sample point, and raw data refers to the highest
return for a sample point. Automatic geometric filtering (virtual deforestation, or'VDF')
is used for bare earth data development. It is unclear whether this classification is
supervised and statistically tested. Documentation supplied with the data does not
include vertical or horizontal accuracy statistics.
Figure 4. LiDAR data for Little Quilcene River.
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1:1,000 scene in plan
view, oblique bare
ground and first
return data Raw data
points first return
and bare earth data)
were used to
generate a
triangulated
irregular network
(TIN) dataset that
interpolates
elevations between
sample points.3 A
one meter first return
and bare earth GRID
data sets was then
developed from the
TIN. All data
extraction sampled
the GRID data.
(A) Topo shaded first
return data
(B) Bare Earth Data
(C) First Return
Data
•.......
Shade Relief .,._
3 A triangulated irregular network (TIN) is a surface representation derived from irregularly spaced points with x, y
coordinates and a z value and break line features.
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1.2 Ground Level Data Types
1.2.1 Flow Data
PGST and JCCD collected flow data from numerous locations, as shown in the figure
below. Measurements were taken during a low flow condition in the last week of July,
2004.
1.2.2 Temperature Data
PGST and JCCD collected continuous temperature data from numerous locations, as
shown in the figure below. Hourly measurements were taken from May to October,
2004.
Figure 5. Continuous
Temperature and
Instantaneous Flow
Measurement Sites
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2. Thermal Infrared Radiometry (TIR) Analysis
Survey Date: July 29, 2004
Working together under the WRIA 17 /east Jefferson County watershed planning unit,
Watershed Sciences, Inc., the Jefferson County Conservation District, and the Port
Gamble S'Kallam Tribe embarked on a joint project to monitor and model summer
stream temperature -flow conditions in six priority watersheds during 2004. As part of
this study, airborne thermal infrared (TIR) data were collected on 28.5 miles of stream.
The TIR images provide information about spatial stream temperature variability and can
illustrate changes in the interacting processes that determine stream temperature. In most
cases, these processes are extremely difficult to detect and quantify using traditional
ground -based monitoring techniques.
The imagery and derived data generated from the TIR are contained in an associated
geographic information system (GIS) database. This report provides a detailed
description of the work performed, including methodology and quantitative assessments
of data quality. In addition, the report presents and discusses the spatially continuous
longitudinal temperature profiles derived from the imagery. These profiles describe how
temperatures vary along the stream gradient and are the basis for the follow -on modeling
effort. Sample images are also contained in this document. The images illustrate some
of the thermal features, channel characteristics, and hydrologic processes discussed in the
report. The images are not meant to be comprehensive, but provide examples of image
scenes and interpretations contained in the database associated with this report.
2.1 Methods
2.1.1 Data Collection
Instrumentation: Images were collected with TIR (8 -12µ) and visible -band cameras
attached to a gyro - stabilized mount on the underside of a helicopter. The two sensors
were aligned to present the same ground area, and the helicopter was flown
longitudinally along the stream channel with the sensors looking straight down. Thermal
infrared images were recorded directly from the sensor to an on -board computer in a
format in which each pixel contained a measured radiance value. The individual images
were referenced with time and position data provided by a global positioning system
(GPS).
Flight Parameters: The streams included in this study were surveyed at a target altitude
of 1200 ft above ground level (AGL). The flight altitude was selected to provide a
relatively high spatial resolution in the channel while still capturing side channels and
meander bends. With the exception of Leland Creek, all streams were flown in the
upstream direction. Leland Creek was surveyed downstream from Leland Lake to its
mouth.
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Figure 6. Sensor mount
used for the TIR and
color video stream
surveys.
Image Characteristics: Images were collected sequentially with 40% or greater vertical
overlap. The surveys in the east Jefferson County were conducted at 1200 ft above
ground level, presenting a ground width of approximately 130 meters with a spatial
resolution of ---0.4 meters.
Ground Control: Watershed Sciences deployed in- stream data loggers prior to the flight
in order to ground truth (i.e. verify the accuracy of) the TIR data. The data loggers were
placed at access points throughout the watershed with at least one instrument deployed
in each surveyed stream. The distribution of the in- stream data loggers allowed for
checking radiant temperatures at regular intervals over the duration of the survey.
Meteorological data including air temperature and relative humidity were recorded in the
basin using a portable weather station (Onset) located at the Jefferson County
International Airport.
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2.1.2 Study Area
Figure 7. WIRA 17/East Jefferson County Study Area
Table 2. Waterbodies and Extents, and Times TIR Surveyed
Ntime
uilcene R.
Extent
Mouth to Elbow Creek
River
Miles
6.4
Time 24111-
13:56 -14:13
-Big
Little Quilcene R.
Mouth to Dry Creek
6.9
14:18 -14:35
Leland•Cr.
Leland Lake to Mouth
4.3
14:38 -14:55
Tarboo Cr.
Mouth to Headwaters
6.4
14:58 -15:15
Chimacum Cr.
Mouth to Town of Center
9.3
16:04 -16:27
E Chimacum Cr.
Mouth to Headwaters
6.2
16:32 -16:46
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2.1.3 Data Processing
Calibration: Measured radiance values contained in the raw TIR images were converted
to temperatures based on the emissivity of water, atmospheric transmission effects,
ambient background reflections, and the calibration characteristics of the sensor. The
atmospheric transmission value was modeled based on the air temperatures and relative
humidity recorded at the time of the survey. The radiant temperatures were then
compared to the kinetic temperatures measured by the in- stream data loggers. The in-
stream data were assessed at the time the image was acquired, with radiant values
representing the median of ten points sampled from the image at the data logger's
location. Calibration parameters were fine -tuned to provide the most accurate fit
between the radiant and kinetic temperatures.
Interpretation and Sampling_ Once calibrated, the
images were integrated into a GIS in which an analyst
interpreted and sampled stream temperatures.
Sampling consisted of querying radiant temperatures
(pixel values) from the center of the stream channel and
saving the median value of a ten -point sample to a GIS
database file. The temperatures of detectable surface
inflows (i.e. surface springs, tributaries) were also
sampled at their mouth. In addition, data processing
focused on interpreting spatial variations in surface
temperatures observed in the images.
Geo- referencing: The images are tagged with a GPS
position at the time they are acquired. Since the TIR
camera is maintained at vertical down -look angles, the
geographic coordinates provide an accurate index to the
location of the image scene. Due to the relatively small
footprint of the imagery and independently stabilized
mount, image pixels are not individually registered to
real world coordinates. In order to provide further
spatial reference, the TIR images were assigned a river
mile based on a routed stream layer.
Temperature Profiles: The median temperatures for each sampled image were plotted
versus the corresponding river mile to develop a longitudinal temperature profile. The
profile illustrates how stream temperatures vary spatially along the stream gradient. The
location and median temperature of all sampled surface water inflows (e.g. tributaries,
surface springs, etc.) are included on the plot to illustrate how these inflows influence
the main stem temperature patterns.
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2.2 Thermal Image Characteristics
Surface Temperatures: Thermal infrared sensors measure TIR energy emitted at the
water's surface. Since water is essentially opaque to TIR wavelengths, the sensor is only
measuring water surface temperature. Thermal infrared data accurately represents bulk
water temperatures where the water column is thoroughly mixed; however, thermal
stratification can form in reaches that have little or no mixing. Thermal stratification in a
free flowing river is inherently unstable due to variations in channel shape, bed
composition, and in- stream objects (i.e. rocks, trees, debris, etc.) that cause turbulent flow
and can usually be detected in the imagery. Occurrences of thermal stratification
interpreted during analysis are identified in the results section for each survey.
Expected Accuracy Thermal infrared radiation received at the sensor is a combination of
energy emitted from the water's surface, reflected from the water's surface, and absorbed
and re- radiated by the intervening atmosphere. Water is a good emitter of TIR radiation
and has relatively low reflectivity (— 4 to 6 %). During calibration, a correction is included
to account for average background reflections. However, variable water surface
conditions (i.e. riffle versus pool), slight changes in viewing aspect, and variable
background temperatures (i.e. sky versus trees) can result in differences in the calculated
radiant temperatures within the same image or between consecutive images. The
apparent temperature variability is generally less than 0.6 °C (Torgersen et al. 2001).
However, the occurrence of reflections as an artifact (or noise) in the TIR images is a
consideration during image interpretation and analysis. In general, apparent stream
temperature changes of < 0.6 °C are not considered significant unless associated with a
surface inflow (e.g. tributary).
Differential Heatins: In stream segments with flat surface conditions (i.e. pools) and
relatively low mixing rates, observed variations in spatial temperature patterns can be the
result of differences in the instantaneous heating rate at the water's surface. In the TIR
images, indicators of differential surface heating include seemingly cooler radiant
temperatures in shaded areas compared to surfaces exposed to direct sunlight. Shape and
magnitude distinguish spatial temperature patterns caused by tributary or spring inflows
from those resulting from differential surface heating. Unlike with thermal stratification,
surface temperatures may still represent bulk water conditions if the stream is mixed.
Feature Size and Resolution: A small stream width logically translates to fewer pixels
"in" the stream and greater integration with non -water features such as rocks and
vegetation. Consequently, a narrow channel (relative to the pixel size) can result in
higher inaccuracies in the measured radiant temperatures (Torgersen et. al. 2001). In
some cases, small tributaries were detected in the images, but not sampled due to the
inability to obtain a reliable temperature sample.
Temperatures and Color Maps: The TIR images collected during this survey consist of a
single band. As a result, visual representation of the imagery (in a report or GIS
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environment) requires the application of a color map or legend to the pixel values. The
selection of a color map should highlight features most relevant to the analysis (i.e.
spatial variability of stream temperatures). For example, a continuous, gradient style
color map that incorporates all temperatures in the image frame will provide a smoother
transition in colors throughout the entire image, but will not highlight temperature
differences in the stream. Conversely, a color map that focuses too narrowly cannot be
applied to the entire river and will "washout' ' terrestrial and vegetation features. The
method used to select a color map for the report images attempts to accomplish both.
The map is based on using discrete colors to represent the range of water temperatures
observed during the analysis based on 1 °C or 0.5 °C increments and a linear gray scale to
represent temperatures above the maximum observed water temperature. The images
below provide an example of three different color maps applied to the same thermal
image.
Figure 8. Various Color Maps and True Color Image
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2.3 Results
2.3.1 Weather Conditions
Table 3. Atmospheric Conditions
7129104 at Je erson County International Airport
13:30
80.8
27.1
47.4
14:00
80.1
26.7
46.9
14:30
81.5
27.5
45.8
15:00
81.5
27.5
43.3
15:30
1 81.5
27.5
43.8
16:00
81.5
27.5
45.8
16:30
78.0
25.6
48.9
17:00
77.3
25.2
51.5
2.3.2 Thermal Accuracy
The table below summarizes a comparison between the kinetic temperatures recorded by
the in- stream data loggers and the radiant temperatures derived from the TIR images. At
some points, the table shows readings for the same sensor location at different times of
the day. These sensors were flown over on surveys of different streams due to the
proximity to both streams (e.g. near confluences). Multiple passes allowed additional
verification at different times of the day.
Table 4. TIR Accuracy Statistics
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Big uilcene River Av . Abs. Di . = 0.3 °C
ui10116
14:00
0.4
17.7
17.3
0.4
ui10286
14:06
2.6
16.5
16.4
0.1
ui10466
14:12
5.7
12.7
13.1
-0.4
Little Quilcene River /Leland Creek Av . Abs. Di . = 0.1 °C
1 u0104
14:22
0.8
18.4
18.4
0.0
le 0079
14:41
3.1
21.5
21.3
0.2
le 0383
14:54
0.8
18.6
18.8
-0.2
Tarboo Creek (Avg. Abs. Di . = 0.2 °C
tar0091
15:02
1 0.7
1 17.1
16.9
0.2
tar0247
15:08
1 3.2
15.0
15.1
-0.1
Chimacum /East Chimacum Creeks Av . Abs. Di . = 0.0°C
chim0197
16:11
2.1
18.7
18.7
0.0
chim0517
16:21
7.0
15.9
16.0
-0.1
echm03O6
16:42
4.4
15.8
15.8
0.0
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The average absolute temperature accuracies were within the desired accuracy of
f0.5 0C. The range of temperature differences was also consistent with those observed
during other surveys conducted in the region over the past six years.
2.3 Big Quilcene River
2.3.1 Longitudinal Temperature Profile
The figure below illustrates the median sampled temperatures plotted versus river mile
for the Quilcene River from the mouth to Elbow Creek (river mile 6.4). Tributaries and
other sampled inflows (i.e. springs /seeps) are labeled on the profile by river mile and
summarized in the associated table.
19
v
18
a�
m
m
17
L
m 16
a
E
m
m
15
.r
ca
14
3
y 13
12
Figure 9. Big Quilcene River longitudinal profile sampled from TIR data
O O O ti CO LO d' M N O
r r
Distance From Mouth (KM)
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Table 5. Tributaries, surface springs, and other detected surface inflows
Tributary
Hatchery Return (LB)
qui10294
4.3
2.7
16.1
16.3
-0.2
Unnamed (LB)
qui10297
4.4
2.7
15.4
16.3
-0.9
Unnamed (RB)
qui10326
5.2
3.2
14.9
15.1
-0.2
Spring
Spring (LB)
quil0161
1.6
1.0
15.9
17.2
-1.3
Spring (RB)
qui10182
2.0
1.2
13.4
16.9
-3.5
Spring (RB)
qui10187
2.1
1.3
15.7
17.6
-1.9
Spring (LB)
qui10210
2.3
1.5
12.8
17.1
-4.3
Spring/Seep (LB)
quil0250
3.3
2.1
15.7
16.3
-0.6
Spring (RB)
qui10253
3.4
2.1
14.6
16.7
-2.1
Spring (RB)
quil0308
4.6
2.9
13.5
15.7
-2.2
2.3.2 Observations and Analysis
Water temperatures in the Big Quilcene River exhibited an overall downstream warming
trend gaining -5.2 °C (12.5 °C -> 17.7 °C) over the surveyed extent. However, within this
general pattern, the Big Quilcene showed a high degree of local thermal spatial
variability. The local variability was due to a number of factors occurring along the
stream gradient.
Between river mile 6.0 and 4.0, the Big Quilcene River flowed through a relatively
confined canyon and stream temperatures showed a consistent increase from - 12.5 °C to
- 14.6 °C. Two tributary inflows were detected in this reach (miles 4.5 and 4.6), but were
not sufficiently visible to obtain an accurate temperature sample. From river mile 4.0 to
3.6, stream temperatures remained relatively consistent (- 14.6 °C) before increasing to
- 16.0 °C at river mile 3.3. Inspection of the imagery illustrated a clear shift in channel
morphology at river mile 3.6 from a relatively confined channel with immediate riparian
vegetation to more complex channel morphology with gravel bars and often multiple
channel paths. The relatively sharp increase in temperatures at this location indicates a
corresponding alteration in the thermodynamic processes that govern stream heating.
At river mile 3.2, an unnamed tributary contributes cooler water (14.9 °C) to the Big
Quilcene River and lowers main stem temperatures by - 0.9 °C. Downstream of this
tributary, seven spring inflows were detected, which contributed to localized temperature
differences in the stream. The springs varied in size and generally emerged from the
channel substrate suggesting the influence of hyporheic flow processes on local
temperature patterns (reference sample images). Smaller inflows were named
"spring/seeps" in this report and in the associated database to distinguish them from
larger, more distinct inflows. Multiple surface inflows were detected and sampled
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around the fish hatchery at river mile 2.7. The outflow of the hatchery was distinct in
the imagery; however, the origin of a cooler side channel along the left bank near the
hatchery (classified as an unnamed tributary) was less distinct.
2.3.3 Sample Images
The following pages contain images from the survey of the Quilcene River including a
brief discussion.
Figure 10. TIR Image: Big Quilcene River Mouth.
The image pair above shows the mouth of Quilcene River at Quilcene Bay. The
Quilcene River was 18.0 °C while Quilcene Bay varied from 21°C to 24°C.
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Figure 11. TIR Image: Big Quilcene River Springs /Seeps (river miles 1.2 and 1.3).
The image pairs above show the locations of springs /seeps at river miles 1.2 (top) and 1.3
(bottom). The spring in the top image is easily detected due to its cooler temperature, but
riparian vegetation and visible shadows make it difficult to determine its source. The
spring in the bottom image clearly emerges from the gravel bar at the downstream end of
the bend in the river.
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Figure 12. TIR Image: Big Quilcene River Spring (river miles 1.5 and 2.1).
The image pairs above illustrate the springs detected at river miles 1.5 (top) and 2.1
(bottom). In both cases, the cool water emerges on the downstream end of perennial side
channels indicating that these channels are important pathways for sub - surface flow
during the summer months.
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The image pair above shows the location of a spring on the right bank of the Big
Quilcene River at river mile 2.9.
The image pair above shows the confluence of an unnamed tributary (14.9 °C) on the
right bank of the Big Quilcene River at river mile 3.2. The tributary, which originates on
the NW slope of Mt. Walker, is a cooling source to the Big Quilcene River.
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2.4 Little Quilcene River
2.4.1 Longitudinal Temperature Profile
The figure below illustrates the median sampled temperatures plotted versus river mile
for the Little Quilcene River from the mouth to Dry Creek (river mile 6.9). Tributaries
are labeled on the profile by river mile and summarized in the table below.
Figure 15. Little Quilcene River longitudinal profile.
22
21
U 20
19
T) 18
0 17
CL
E 16
H
15
m
14
a�
13
U) 12
11
ill
■ 9.s
-+- Little Quilcene River ■ Tributary
■ 4.4
N r O O O P CO Cn � M N O
T ! T
Distance From Mouth (mile)
Table 6. Little Quilcene River tributaries, surface springs, and other detected surface
inflows
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2.4.2 Observations and Analysis
The Little Quilcene River was heavily canopied through much of the survey extent.
Despite the canopy, surface water was visible at regular intervals, which allowed for
almost continuous sampling of radiant temperatures and creation of the longitudinal
temperature profile. However, the canopy masked the edges of the stream and made it
difficult to detect and sample tributaries and other surface inflows. Only two surface
inflows were detected during the analysis of the Little Quilcene River. Both were
relatively small and contributed water that was cooler than the main stream. Mapped
tributaries such as Leland Creek, Howe Creek, and Ripley Creek were not visible at their
confluence with the Little Quilcene.
At the upstream end of the survey, water temperatures in the Little Quilcene River were
relatively cool (13.0°C at mile 6.8) and warmed downstream to 14.6 °C by mile 5.2.
Between mile 5.2 and 5. 1, water temperatures exhibited a sharp apparent increase of
— 1.5 °C. Inspection of the imagery and topographic base maps showed that Howe Creek
enters the Little Quilcene at this location, but was not visible through the forest canopy.
The dramatic increase in water temperatures at this location suggests a thermal response
to the inflow of Howe Creek, although this could not be verified.
Downstream of the Howe Creek confluence, water temperatures continued to increase
reaching — 18.0 °C at river mile 3.1. The longitudinal profile illustrated some local
thermal variations. However, these variations were at or just above the noise levels
typically associated with TIR remote sensing (i.e. t0.5 °C) and possible sources of
variability could not be identified from the imagery. Moving downstream, water
temperatures decreased by —1.2 °C between river miles 3.2 and 2.6 and remained
relatively consistent (f0.4 °C) to mile 1.9. Inspection of the topographic base maps shows
that this change in the temperature pattern begins as the Little Quilcene emerges from the
canyon and continues to the confluence of Leland Creek (mile 1.6). A small, unnamed
tributary was sampled at mile 2.7 and contributed cooler water to the main stream.
However, the overall change in the downstream heating rate suggests a thermal response
to the change in morphology possibly associated with some sub - surface discharge. From
river mile 1.6 (confluence of Leland Creek), stream temperatures increased steadily
reaching — 19.2 °C at Quilcene Bay.
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2.4.3 Sample Images
Figure 16. TIR Image: Little Quilcene River Mouth
The image pair above shows the mouth of the Little Quilcene River and Quilcene Bay.
The temperature of the Little Quilcene was 20.3 °C while Quilcene Bay's temperature
ranged from 24.5 °C to 26.5 °C.
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Figure 17. TIR Image: Little Quilcene River at Leland Creek Confluence (river mile 1.6)
The image pair above shows the confluence of the Little Quilcene River (17.7 °C) and
Leland Creek. Riparian canopy masked the mouth of Leland Creek, which prevented the
sampling of radiant temperatures at this location.
Figure 18. TIR Image: Little Quilcene River Channel Characteristics (river mile 2.2)
The image pair above shows characteristics of the Little Quilcene River at river mile 2.2.
The riparian canopy masked much of the stream surface. The stream surface was visible
at regular intervals, which allowed temperature sampling. However, the small size of the
stream, combined with the riparian canopy made it difficult to detect other surface
inflows and to assess channel characteristics.
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2.5 Leland Creek
2.5.1 Longitudinal Temperature Profile
The figure below illustrates the median sampled temperatures plotted versus river mile
for Leland Creek from Leland Lake (river mile 4.3) to the mouth. There were no
tributaries or surface inflows sampled during the analysis of Leland Creek.
27
26
v 25
v►
d
24
d
.�. 23
L
6.22
E
21
L
d
3 20
19
18
17
16
Figure 19. Leland Creek longitudinal profile sampled from TIR data
-* Leland Creek
0 0 0 0 0 0 0 0
t� W to M N O
Distance From Mouth (KM)
2.5.2 Observations and Analysis
The TIR survey of Leland Creek started at the outlet of Leland Lake. The surface
temperature of the lake was warm (- 26.1 °C), but there is evidence in the TIR imagery
that the lake is thermally stratified with cooler water at deeper depths. However, Leland
Creek flows from the surface of the lake and its initial temperatures are consistent with
the lake's surface. Surface water was only visible for —0.1 miles downstream of the lake
before the creek disappeared into a meadow /marsh (mile 4.1).
Moving downstream, surface water in Leland Creek was visible again closer to the
downstream end of the marsh, near Hwy 101 at mile 3.3. At this point, surface water
temperatures were — 19.6 °C, but increased sharply downstream reaching 22.8 °C at mile
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3.0. At mile 3.0, the surface water again disappeared into a meadow /marsh. While the
channel location was evident in the imagery, the stream had little or no visible surface
water between miles 3.0 and 2.3. From mile 2.3 to the Little Quilcene confluence,
Leyland Creek was small (relative to pixel size) and often difficult to detect through the
forest canopy. Consequently, radiant temperatures were sampled at irregular intervals
over this reach. The samples that were acquired showed that stream temperatures ranged
between 18.9 °C and 19.9 °C with no definitive pattern of heating or cooling.
2.5.3 Sample Images
Figure 20. TIR Image: Leland Creek Channel Characteristics (river mile 1.4)
The image pair above shows a portion of Leland Creek at river mile 1.4 with
characteristic channel conditions for the stream, including intermittent water and heavy
canopy.
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2.6 Tarboo Creek
2.6.1 Longitudinal Temperature Profile
The figure below illustrates the median sampled temperatures plotted versus river mile
for Tarboo Creek from the mouth to the headwaters (river mile 6.4). No tributaries or
other surface inflows were sampled during the analysis of Tarboo Creek.
Figure 21. Tarboo Creek longitudinal profile sampled from TIR data
21
-•- Tarboo Creek
20
0
0019
V
3 18
ca
L
L 17
E
as
L 16
d
w
3 15
d
14
N
13
12 1 �---
6.0 5.0 4.0 3.0 2.0 1.0 0.0
Distance From Mouth (mile)
2.6.2 Observations and Analysis
Surface water was intermittent in Tarboo Creek throughout most of the survey extent.
The combination of small stream channel, intermittent surface water, riparian canopy,
and generally low terrain relief presented operational challenges in following Tarboo
Creek. The survey was maintained through detection of the channel in the imagery and
course adjustments from a digital moving map display.
Only one radiant temperature sample was taken between river miles 6.0 and 3.8 due to an
inability to detect the stream surface through the forest canopy. In general, when the TIR
sensor is looking vertically down (i.e. at NADIR), the stream surface is detected
intermittently through the forest canopy. This is true even on very small streams.
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However, the surface of Tarboo Creek was rarely detected in the upper two miles,
suggesting the combination of a very reduced (or non - existent) surface flow with heavy
riparian canopy. When the stream was detected, such as the two samples at miles 3.8 and
3.7, the visible channel was very narrow. Surface water was progressively more
detectable downstream of mile 2.8 and water temperatures exhibited a general
downstream warming trend.
2.6.3 Sample Images
Figure 22. TIR Imager Tarboo Creek at mouth
The image pair above shows the mouth of Tarboo Creek, with the main stem
temperature ranging from 20.3 °C to 17.7 °C just upstream of the mouth.
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Figure 23. TIR Image: Tarboo Creek Channel Characteristics (river miles 0.6 & 1.6)
The image pairs above show typical channel characteristics of a small channel and heavy
canopy at river mile 0.6 (top) and a wet grass channel at river mile 1.6 (bottom). The
canopy and apparent lack of surface flow through some reaches made it difficult to
continuously map temperature patterns in Tarboo Creek.
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2.7 Chimacum Creek
2.7.1 Longitudinal Temperature Profile
The figure below illustrates the median sampled temperatures plotted versus river mile
for Chimacum Creek from the mouth to the city of Center (river mile 9.3). Only one
unnamed tributary (mile 9.3) was sampled during the analysis of Chimacum Creek.
Figure 24. Chimicum Creek longitudinal profile sampled from TIR data
`ZI
23
m22
CD
�o
m 21
.r
m
20
CL
E 19
H
18
m 17
16
15
14
-•- Chimacum Creek --m-Tributary j
CC 0 It M N O O O 1- CO O d M N V- O
r r r r r r �-
Distance From Mouth (KM)
2.7.2 Observations and Analysis
At the upstream of the survey (mile 9.3), water temperatures in Chimacum Creek were
- 16.0 °C. The survey ended at a point where the creek channel appeared as a ditch
flowing from the west and was joined by another ditch from the south. The southern
ditch was classified as a tributary and was considerably warmer (23.1 °C) than Chimacum
Creek.
Below the ditch (mile 9.3), the creek enters a wooded area where it was largely masked
by the riparian canopy. At the upstream end of the wooded area, the stream was still
visible through the canopy, allowing some temperature samples. At the downstream end
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(mile 8.8), the stream channel enters a field/meadow where surface water was only
intermittently visible. In this reach, the visible surface water generally occurred at
impoundments such as dams and road crossings. The relatively cool water temperatures
( <16.7 °C) at sampled locations suggest that there is some sub - surface flow through the
channel that is forced to the surface at the impoundments.
Although occasionally masked by riparian canopy, the surface water in Chimacum Creek
was visible again between miles 7.2 and 4.2 allowing temperature sampling at regular
intervals along the stream gradient. Through this reach, stream temperatures overall
increased from — 15.9 °C (mile 6.9) to 21.6 °C (mile 4.2). Within this reach, a variation in
the prevailing temperature trend was observed between miles 6.4 -> 5.4 where
temperatures were relatively consistent (- 17.4 °C).
From mile 4.2 to 3.8, Chimacum Creek is a straightened ditch with very little visible
surface water. No temperature samples were obtained through this reach. Near the town
of Chimacum, surface water was again visible and temperatures had cooled slightly from
upstream areas suggesting some sub - surface recharge to the channel at this location.
Surface water was intermittently visible through a wooded area downstream of the town
of Chimacum, but disappeared again near the confluence of East Chimacum Creek at
mile 3.3. Surface water was again visible at mile 2.4 where radiant temperatures were
measured at 18.4 °C. Water temperatures in Chimacum Creek remained between 18.4 °C
and 19.2 °C in the lower 2.4 miles with no definitive warming or cooling trend.
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2.7.3 Sample Images
Figure 25. TIR Image: Chimacum Creek at mouth
The image pair above shows the mouth of Chimacum Creek with the water temperatures
increasing from 18.7 °C to 19.6 °C at the mouth.
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Figure 26. TIR Image: Chimacum Creek Channel Characteristics (river mile 1.7)
The image pair above shows Chimacum Creek at river mile 1.7 which made a regulated
sampling interval difficult. The images are an example of how the riparian canopy
masked the stream channel in wooded areas along the creek.
Figure 27. TIR Image: Chimacum Creek Channel Characteristics (river mile 2.8)
The image pair above shows stream channel of Chimacum Creek at river mile 2.8. The
channel location is obvious in the TIR image due to cooler grass /vegetation. However,
there is not visible surface water, so the stream was not sampled in this reach.
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Figure 28. TIR Image: Chimacum Creek Channel Characteristics (river mile 5.2)
The image pair above shows the channel of Chimacum Creek at river mile 5.3. The
image illustrates general conditions through much of the open meadow reaches in
Chimacum Creek.
Figure 29. TIR Image: Chimacum Creek Channel Characteristics (river mile 8.2)
The image pair above shows an in- stream barrier at river mile 8.6. In this reach, surface
water was generally only visible below or above impoundments in the stream.
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2.8 East Chimacum Creek
2.8.1 Longitudinal Temperature Profile
The figure below illustrates the median sampled temperatures plotted versus river mile
for East Chimacum Creek from the mouth to the headwaters (river mile 6.2). No
tributaries or other surface inflows were detected during the survey of East Chimacum
Creek.
Figure 30. East Chimicum Creek longitudinal profile sampled from TIR data
24
23
v 22
as
a 21
20
19
CL
E 18
H
m 17
w
eo
16
d
4 15
to 14
13
12
-♦- East Chimacum Creek I
I*- O LO V M N r O
Distance From Mouth (mile)
2.8.2 Observations and Analysis
Although the TIR survey followed the full length of East Chimacum Creek, the stream
surface was very small and radiant temperature samples were taken at irregular intervals.
Only 15 temperature samples were acquired over the lower 4.2 miles. Of these, nine
samples (all upstream of river mile 0.8) were less than 16.7 °C. These relatively cool
temperatures suggest that the surface water visible in the imagery was predominately due
to sub - surface recharge from within the channel. In general, the channel characteristics
and spatial temperature response were similar to those observed in Chimacum Creek.
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2.8.3 Sample Image
Figure 31. TIR Image: East Chimacum Creek Channel Characteristics (river mile 1.0)
The image pair on the left shows a section of East Chimacum Creek where the channel
consists primarily of wet grass at river mile 1.0. The channel condition illustrated above
was characteristic of this stream.
2.9 Summary of Survey Results
The size and intermittent surface flow observed in Leland Creek, Tarboo Creek, and East
Chimacum Creek presented operational challenges, since these streams were often
difficult to follow in low relief, heavily canopied areas. However, the TIR survey
proceeded using the thermal imagery and digital maps to find the channel and was
ultimately successful in mapping spatial temperature patterns. Radiant temperatures
derived from the imagery were consistent with the target accuracy of t0.5 0C when
compared to the in- stream data loggers.
The Big and Little Quilcene Rivers were the only streams with visible continuous surface
flow (i.e., detected in the TIR data) throughout the surveyed extent. On the Big Quilcene,
a number of cold springs and seeps were detected within the hyporheic zone suggesting
that sub - surface discharge within this zone is an important component of the thermal
structure of the lower Big Quilcene River. The Little Quilcene River was smaller and did
not have the large alluvial gravel bars noted in the lower reaches of the Big Quilcene.
Consequently, no identifiable sub - surface discharges were observed in this stream.
However, the longitudinal temperature profile of the Little Quilcene River illustrates
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thermal response to surface inflows and shifts in the downstream heating rates associated
with transitions in morphology.
The other streams surveyed each had reaches with intermittent surface flow. The TIR
imagery illustrated thermal response to the surface/sub-surface exchanges that occurred
along the stream course. However, the occurrence of the surface water was often isolated
over relatively short (e.g. less than 1 mile) segments. Although intermittent flow and
masking of the stream surface by riparian vegetation resulted in often irregular sampling
intervals, enough temperature samples were obtained to provide a reasonable
representation of how temperatures vary along the stream gradient. In addition, color
video and TIR images provide a snap shot of stream and channel conditions during the
heat of the summer.
This report presents the spatial temperature patterns derived from the TIR imagery and
offers some hypotheses on the processes influencing spatial temperature patterns. These
hypotheses and observations are considered a starting point for more rigorous spatial
analysis, temperature modeling, and fieldwork.
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3. LiDAR Data Sampling and Analysis
Sampling of LiDAR first and last return data was performed using TTools 7.0, an
ArcView extension offering a suite of tools designed to automatically sample spatial data
sets used as inputs for Heat Source. TTools 7.0 is designed to assemble high- resolution
( <1:2,000 geographic scale) spatial databases.
Figure 32. LiDAR scene on Big Quilcene River near the Fish Hatchery
3.1 Stream Position and Data Nodes
3.1.1 Data Sources
• Orthophotography
• LiDAR
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3.1.2 Sampling Methods
Stream polyline accuracy is a function of the mapping scale and underlying data
accuracy. For example, a stream polyline at 1:100,000 mapping scale simplifies
sinuosity and has local horizontal inaccuracies (sometimes in excess of 200 feet). A
1:100,000 stream polyline will result in inaccurate reference points and oversimplified
stream position. A stream polyline digitized at <1:5,000 mapping scale will properly
identify stream position and will yield accurate reference points for sampling. Stream
digitizing was performed at a 1:1,500 scale using bare earth LiDAR data and 1 meter
contours developed from bare earth LiDAR data.
Digitized stream position is used to develop data nodes (reference points) for
sampled/derived data generated with the TTools extension. Once a stream polyline has
been digitized, it is segmented at 25 meter intervals to produce a point data layer
(shapefile). This point data theme is then used to sample other parameters (and data
generated is associated with these discrete points).
Figure 33. LiDAR scene on Tarboo Creek. Digitized stream polyline segmented at 25
meter interval provide nodes (blue dots) for sampling spatial data.
Area is obscured by vegetation and stream is small, making detection possible only with
bare earth LOAR data.
First Return Bare Earth Model
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3.1.3 Results
Table 7. Stream Extent Digitized and Segmented into 25 meter Nodes
Stream
Tarboo Creek
Leland Creek
Little Quilcene River
Quilcene River
Chimacum Creek
East Chimacum Creek
3.2 Stream Aspect
3.2.1 Data Sources
Length (1:5,000
Nodes
scaled)
11.225 KM
449
7.550 KM
302
11.300 KM
452
11.075 KM
443
23.875 KM
955
11.250 KM
450
• Stream Node Positions (from bare earth LiDAR data)
3.2.2 Sampling Methods
The stream aspect is defined as the angle that exists between the velocity vector ( U ) and
true north (0*). TTools calculates this angle as the angle between each of the stream data
nodes. Valley aspect is also sampled and assigned to stream data nodes. The divergence
(difference between stream and valley aspects) can then be used to calculate sinuosity
and is used directly for simulating hyporheic flows.
Figure 34. Stream aspect is
calculated by calculating the
angle between two stream
nodes.
Stream
kit Asped
_ 950
7
i
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3.2.3 Results
Figure 35. Stream and valley aspect, along with absolute divergence between stream and
valley aspects
Tarboo Creek
3M
~
— —
--
136
315
awsteem Aspect .VaNyAspeit
276.
8 226
t3fi
. "s.
'
n Is
N3
0
p
'.N h N I N h N n,'Nh Nh N h Nh HP N h Nh N
�8.
N !N P,.N h S7. h,NP M'hN AC4 N NN N
RIver RN
River KIN
Leland Creek
300
135
136
315
ewstramA.yect — VJIeVAspect
270
x'
90
225
CA
x,135
13a -
4
y:
m�46.
y
45
Q ._ eVq a2 aq �. aQ e2 —'
w •— eq _ e2 ^. a3 na - °Q - . a3 ni - _
Rver KM -.-
- - R.r KM
Little. River
360 _��._.._._ : °--- __�e:d�.._...._
-135
1e *ewn Pepect ^ Vakro ftect
315
270
ffi
225
go
180
ZS
r
8 136-
2'
V 0
>3
D
u
QQ. CI 9 rQ N.. S'Q iQ lq M M GQ fi W 'n dt I CQ 'n Q. q
M ee Nn eq I q q cQ I vQ 1q aD C'1 .Q IQ'aQ C! R d? -Cl. CQ F!
Rver KM
River KM
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Figure 35 (cont). Stream and valley aspect, along with absolute divergence between
stream and valley aspects
.bag Quileene River
360
360
31
360
315
- w� Stream A%pect
315
270
i
--MiNeyAspect
a
N
225
270
225
E c
11-9 iso
a
i3 225
' 180
.Jj1
..
E
180
3° 90
z.
1135
0 46
0
tz o 135
a 90
90.
45
0 46
0
0
^ED.- m.- _m�ro. -m ^EO ^d7- .- m.- .m ^a3. ^m '• ^. m^ m^ GD a0.7m.r•ro.�m'�m�-m ^ab- '-m ^ -m'�-
� -GG WGOOD:CD.M1.f�maD 4i Yi.Q -V (°): C/HN ^�.G.G �S]:G -W. Cp OD'f�Iti GD OD �[f Y'i7 !C a'; C'i Flyer KM KM Biver KM
Chimacum Creek
QM Q at
^_
Y flyer KM ^River KM
East Chimacum Creek
Streamf�ect — \,AIIeyAspect
360
31
e
.315 6
i
INTO
270
225
#8 225
TM
E c
11-9 iso
ISO
135
.Jj1
..
3° 90
z.
45
0 46
0
0
r2 �'1 aR �'2 aQ.�"k. OR t"L a4 r'!. 04 �'! aR �'t a4 M 04 cl aQ M M M
f
St
QM Q at
^_
Y flyer KM ^River KM
East Chimacum Creek
Streamf�ect — \,AIIeyAspect
360
31
2
2 315
.315 6
� 270
270
225
#8 225
TM
E c
11-9 iso
ISO
135
'S M 135
-C
3° 90
z.
45
0 46
0
0
r2 �'1 aR �'2 aQ.�"k. OR t"L a4 r'!. 04 �'! aR �'t a4 M 04 cl aQ M M M
Flyer KM River KM
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3.3 Stream Gradient and Sinuosity
3.3.1 Data Sources
• Stream Nodes Layer
• LiDAR
3.3.2 Sampling Methods
Stream elevation is measured from the bare earth LiDAR (1 meter DEM). To help find
the lowest pixel nearest to the stream segment node, TTools samples 25 pixels: the pixel
that falls directly on the stream segment node and two pixels in each direction
surrounding it. The lowest elevation sampled is assigned to the stream segment node.
Figure 36. The procedure for sampling stream
elevation involves twenty five discrete samples in
a radial pattern to locate the lowest datum.
Stream gradient is calculated from the elevation of the stream node and the distance
between nodes. Gradients are calculated as:
Stream Gradient Calculation,
S o - z; -z;.
—
i -i� •dx
Variables,
Measured /Known
dx : Distance Step (m)
i : Stream Data Node
i" : Last Stream Node Where (zi. > z; )
z : Elevation (s)
Calculated
SO: Stream Gradient (unitless)
(Eq. 1)
Stream sinuosity is determined from the absolute angle of divergence (the difference
between stream aspect and valley aspect) and distance between stream data nodes. From
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these data the stream length and valley length can be calculated, allowing the calculation
of sinuosity. Results are presented in Figure 37, page 50.
Stream Sinuosity Calculation,
i+10
dx
Sin = Lsheam _ i
i +10
Lvalley
COS(Bstream — evalley) dx
i
Variables,
Measured /Known
dx : Distance Step (m)
i : Stream Data Node
i +10: Stream Data Node 250 meters Downstream
Lstream :
Stream Length (m)
Lvauey :
Valley Length (m)
Bs�eQ1„ :
Stream Aspect (degrees)
evalley :
Valley Aspect (degrees)
Calculated
Sin: Stream Sinuosity (unitless)
(Eq. 2)
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3.3.3 Results
Figure 37. Stream gradient \t and sinuosity
Tarboo Creek
Leland Creek
Sbw96�y -.. ^"–iili%%f
w5�atios�r - °'C�ti+taen!
4 °^ �.
T5%.
4
7di95 - -
2
296
2
2d
1 :
Sl h,
#+f a r' @ Ci
Q
t -
!�
14 : Sd ii
ODS
PAV KM
Niter KM
LiWe Qudcene River
B4 Qu&rne iuver
i
3t?x
a
fO9G
o
soAi1 "aIyssO/y: "°` #teal4Mi
2$ai
�sl%1K3ily °– Grs4fsnf_-
G.
4
15%
2
3b6
2
bgts^yt Ba *r Ebb`
09 # 03. W .'"! W Ct.4f. S'2 {Q i�4. 14'0411@ OA a4 t4 64 M � -Ot 14 [9
�} �. W W $ @ h K # #.O' �fA Ri' V OY T7 SV N � e• C C
� Y�Sj r IKk •^. CT .• 1p v elE r. cR .- qq r. %P! r #.r q r � e.
�_ W � W W O8 W A n. O # W a �' +�i d0 i9 N �q n r �y C!
rdw VM
RAW KM
OUmacm Creek
zwt M#nac a C'ree'k
r�wSkaas� – °$vat$brk
ws5ire�eliyr - t3rasi
4
74%
4
2.594
ZO%
2
a59s
�a
1
OA%
9
ANAL
3�whwa ANAL
0."
�
c"�ri
a W ��Wa4 aeW a<kW c+a
as�4, rya, �p:od�r�� #afalk�fs+�vk9`�m�i��
+ �w�'+ �M�eBasata�eawr4 +gs�raa�aFwa4��ni
+- R�WW�mr .t« #rn+aeca�rvv�ranrr�Rrat�
MW KM
row KM
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3.4 Topographic Shade
3.4.1 Data Sources
• Stream Nodes Layer
• LiDAR
3.4.2 Sampling Methods
The maximum topographic shade angle is calculated to the east, south and west, relative
to the stream segment node. In each direction (east, south and west) TTools steps away
from the stream sampling the 1 meter bare earth LiDAR pixels for elevation and
calculating topographic shade angle. TTools records the value and the X and Y
coordinates of the point that represents maximum topographic shade angle. While this
description is fairly simple, the methodology is actually quite complex.
The overriding intent of topographic shade calculation focuses on locating the local
maximum associated with each data node in the three direction (East, West and South).
Generally, there are near field (stream bank, valley morphology, etc.) and far field (hills,
mountains, etc.) topographic features that combine to form topographic shade. In terms
of the local effect of topographic shade, only the highest directional topographic angle
(and not necessarily the highest topographic feature) is a controlling factor. With this
background, the search regime for the maximum topographic feature must include both
the near and far field.
Near - field: Far - Field:
Each of first 25 DEM User determines sample
cells is sampled. - distance and interval -
TTools records the max topographic shade angle.
Prepared by Watershed Sciences Page 51
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
The near field search is higher resolution, because the distance from the stream is small,
increasing the importance of even small elevation differences from stream banks and
morphology. The near field search directionally samples each DEM 1 meter pixel for a
total of twenty five pixels away from the stream. The highest near field topographic
shade angle, for all three directions, is stored in memory for each stream node.
The far field search for the maximum topographic shade angle typically targets large
features (hills, mountains, etc.) and spans greater distances from the stream. These
factors allow a more coarse sampling resolution (and allow greater sampling interval
distances). The higher of the two maximum topographic shade angles (near field and far
field) is entered in the stream node database as the greatest topographic shade angle. This
procedure is repeated for directions due east (90 °), south (180 °) and west (2700).
Topographic Shade Calculation,
OT =tan-' (�_LT T -Zi /
Variables,
Measured/Known
dx : Distance Step (m)
i : Stream Data Node
LT: Distance from Stream Data Node `i' to topographic feature
z: Elevation (s)
zT : Elevation of Topographic Feature (s)
Calculated
()T: Topographic Shade (degrees)
(Eq. 3)
Prepared by Watershed Sciences �� Page 52
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
3.4.3 Results
Figure 38. Topographic Shade Angles
Tarboo Creek
Leland Creek
-. 00 .:,
n- 50
2,40
`{
a
fr`
-
20
0
J
10 .
Potter KM ° � ° a' c°4
M ^ Q1
Flyer
ter
°
.6
Little Nicene Raver
Bag Quilcene Aver
00
so „
a
�. 50c
CD i
40
41
30`�n�.r.:'. ".
- a 30
0
ci
V
a
Flyer KM n N °� sx Wa
Po VN KM
to N
c
Chamacum Creek
East Chamacum Creek
00
s
v
50
"'�"c �' sr t
140
Crt
30
20
�. {�`
30
10
i"!ty NN W
IIVV
�
Q 6.
W
{•b�Q W
� V ' N a4 ...
W M1
9i m Q
S
Potter KM T ' W 40' ^�' m °t
- Flyer KM
KMS CR
c4 M . !ri
,°�°
IR
a
Prepared by Watershed Sciences Page 53
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
3.5 Near Stream Vegetation Height
3.5.1 Data Sources
• Stream Nodes Layer
• LiDAR
3.5.2 Sampling Methods
The role of near stream land cover in maintaining a healthy stream condition and water
quality is well documented and accepted in scientific literature (Beschta et al. 1987).
Near stream land cover has several influences upon the stream and the surrounding
environment that warrant listing:
• Regulating radiant heat in stream thermodynamic regimes.
• Channel morphology is often highly influenced by land cover type and
condition by affecting flood plain and instream roughness, contributing coarse
woody debris and influencing sedimentation, stream substrate compositions
and stream bank stability.
• Creating a thermal microclimate that generally maintains cooler air
temperatures, higher relative humidity and lower wind speeds along stream
corridors.
• Instream nutrient cycles are affected by near stream land cover.
With the recognition that near stream land cover is an important parameter in influencing
water quality, the development of land cover data sets should be a high priority. Variable
land cover conditions require a higher resolution than most currently available GIS land
cover data sources. To meet this need, LiDAR data are extensively utilized.
TTools relies on a radial sampling pattern for near stream land cover. Radial land cover
sampling occurs for every stream data node at four 15 meter intervals in the northwest,
west, southwest, south, southeast, east, and north east directions (North is not sampled
since the sun does not shine from that direction in the northern hemisphere, and shadows
will not be cast in a southerly direction). A database of land cover type is created for
each stream data node. The figure below shows the radial sampling pattern and example
of data sampling with LiDAR data.
Once vegetation height is sampled, it can then be averaged for the left and right banks.
This is done only for presentation purposed. All modeling uses the raw vegetation height
data.
Prepared by Watershed Sciences Page 54
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 39. Vegetation Sampling Methodology.
Prepared by Watershed Sciences Page 55
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
3.5.3 Results
tigure 4U. Sampled Vegetation Height -Big Quilcene River (Note Missing LiDAR Data
Prepared by Watershed Sciences Page 56
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Eigure
41. Sampled Vegetation Height Statistics - Big Quilcene River
Percentiles
2`ayY
Count
Max
Min
5th
25th
50th
50
95th
10.0 -11.0
No Data
No Data
No Data
,
No Data
No Data
No Data
No Data
3,.
_
? A Min
No Data
No Data
No Data
No Data
No Data
No Data
8.0 -9.0
No Data
No Data
No Data
No Data
a 5th Percentile
No Data
«+
40
7.0 -8.0
No Data
No Data
No Data
No Data
No Data
Y
No Data
25th Percentile
6.0 -6.3
308
28.2m
0.0M
0.0M
0.0M
0.1 m
0.9m
18.5m
5.0 -6.0
1,120
38.8m
0.0M
0.0M
30
0.1 m
0.5m
w 50th Percentile
4.0 -5.0
1,120
35.8m
0.0M
0.0M
(Median)
0.2m
1.2m
16.9m
3.0 -4.0
m 75th Percentile
44.6m
t31
20
0.0M
x` 95th Percentile
0.8m
21.0 m
2.0 -3.0
1,120
33.2m
0.0M
0.0M
�
0.1 m
e i
11.6m
1.0 -2.0
1,119
43.0 m
0.0M
0.0M
0.0M
10 Max
2.3m
19.4m
10
1,148
23.4m
0.0M
0.0M
0.0M
0.2m
0.9m
7.0 m
Total
7,055
44.6 m
0.0 m
0.0 m
0.0 m
0.2 m
0
14.9 m
O O
O
T!
CD ° o
o
CD
�A -
s Cb
s
ri o 6 06 d
°
C� Q M N
Ate' :6
s Cb ;
o ry �4.
r
River KM
r�
a
Table 8. Sampled Vegetation Height Statistics - Big Quilcene River
Prepared by Watershed Sciences Page 57
Percentiles
Rivermiles
Count
Max
Min
5th
25th
50th
75th
95th
10.0 -11.0
No Data
No Data
No Data
No Data
No Data
No Data
No Data
No Data
9.0 -10.0
No Data
No Data
No Data
No Data
No Data
No Data
No Data
No Data
8.0 -9.0
No Data
No Data
No Data
No Data
No Data
No Data
No Data
No Data
7.0 -8.0
No Data
No Data
No Data
No Data
No Data
No Data
No Data
No Data
6.0 -6.3
308
28.2m
0.0M
0.0M
0.0M
0.1 m
0.9m
18.5m
5.0 -6.0
1,120
38.8m
0.0M
0.0M
0.0M
0.1 m
0.5m
11.2m
4.0 -5.0
1,120
35.8m
0.0M
0.0M
0.0M
0.2m
1.2m
16.9m
3.0 -4.0
1,120
44.6m
0.0M
0.0M
0.0M
0.2m
0.8m
21.0 m
2.0 -3.0
1,120
33.2m
0.0M
0.0M
0.0M
0.1 m
0.6m
11.6m
1.0 -2.0
1,119
43.0 m
0.0M
0.0M
0.0M
0.2m
2.3m
19.4m
0.0 -1.0
1,148
23.4m
0.0M
0.0M
0.0M
0.2m
0.9m
7.0 m
Total
7,055
44.6 m
0.0 m
0.0 m
0.0 m
0.2 m
0.9 m
14.9 m
Prepared by Watershed Sciences Page 57
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 42. Sampled Veizetation Heisht - Little Ouilcene River
Prepared by Watershed Sciences Page 58
�
lo
o
0
JA
y�g
RiverKM
5'4
z
-
.X,
60 �`=+• i
"ar±Y 4"'a�k"'s �.-
's
9Yi'Y��i'
'v' ��'fl�"k
,tld
50
z
40
IM
30
_
C
cc
j�
LOY`
OP,t
�Oar
w�aom.
�
vo ao
River ACM
M M CO E
c- OD E E em u. 2 1. fV
O to I— Ua
Cj
C a
0
Prepared by Watershed Sciences Page 58
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
rigure
43.
Sampled Vegetation Height Statistics - Little Quilcene River
Percentiles
Rivermiles
Count
Max
Min
5th
25th
50th
75th
95th
11.3 -11.0
50
53.5 m
0.0 m
0.0 m
1.8 m
11.6 m
27.6
38.6
i� Min
1,120
48.0m
0.0M
0.5m
5.3m
40
36.5
9.0 -10.0
a 5th Percentile
45.3m
0.0M
0.0M
0.9m
9.4m
21.0
36.9
8.0 -9.0
1,120
ig 25th Percentile
0.0 m
0.0 m
0.1 m
0.8 m
10.0
29.9
7.0 -8.0
1,120
43.4 m
0.0 m
0.0 m
30
1.6 m
12.0
a 50th Percentile
+�
1,120
54.7 m
0.0 m
(Median)
0.1 m
0.7 m
5.1
22.0
■ 75th Percentile
1,120
46.3 m
0.0 m
0.0 m
0.2 m
t
20
34.6
4.0 -5.0
�. 95th Percentile :
�
0.0M
�
0.0M
0.2m
3.2
24.0
3.0 -4.0
1,120
iw Max
0.0 m
10
0.1 m
'
4.2
25.3
2.0 -3.0
1,120
41.7m
0.0M
0.0M
0.1 m
Y� r
2.9
24.1
1.0 -2.0
1,092
47.1 m
0.0 m
0.0 m
0.0 m
0.2 m
CD.
13.9
0.0 -1.0
ch
°o o
h"
0.0M
0.0M
p m o
�ry
2.8
Total
d
54.7 m
0.0 m
0.0 m
c5 d
�a4a
9.0
30.7
River KM
Table 9. Sampled Vegetation Height Statistics - Little Quilcene River
Prepared by Watershed Sciences Page 59
Percentiles
Rivermiles
Count
Max
Min
5th
25th
50th
75th
95th
11.3 -11.0
364
53.5 m
0.0 m
0.0 m
1.8 m
11.6 m
27.6
38.6
10.0 -11.0
1,120
48.0m
0.0M
0.0M
0.5m
5.3m
19.5
36.5
9.0 -10.0
1,120
45.3m
0.0M
0.0M
0.9m
9.4m
21.0
36.9
8.0 -9.0
1,120
46.9 m
0.0 m
0.0 m
0.1 m
0.8 m
10.0
29.9
7.0 -8.0
1,120
43.4 m
0.0 m
0.0 m
0.3 m
1.6 m
12.0
28.1
6.0 -7.0
1,120
54.7 m
0.0 m
0.0 m
0.1 m
0.7 m
5.1
22.0
5.0 -6.0
1,120
46.3 m
0.0 m
0.0 m
0.2 m
1.6 m
20.2
34.6
4.0 -5.0
1,120
44.6m
0.0M
0.0M
0.0M
0.2m
3.2
24.0
3.0 -4.0
1,120
42.6 m
0.0 m
0.0 m
0.1 m
0.5 m
4.2
25.3
2.0 -3.0
1,120
41.7m
0.0M
0.0M
0.1 m
0.4m
2.9
24.1
1.0 -2.0
1,092
47.1 m
0.0 m
0.0 m
0.0 m
0.2 m
1.0
13.9
0.0 -1.0
1,120
21.5m
0.0M
0.0M
0.0M
0.0M
0.4
2.8
Total
12,684
54.7 m
0.0 m
0.0 m
0.1 m
0.7 m
9.0
30.7
Prepared by Watershed Sciences Page 59
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
IM :. - — ,
Prepared by Watershed Sciences Page 60
+ „r
hx
w
t
�
T
k � 3
•
•
•
e
,
•
Prepared by Watershed Sciences Page 60
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Te 4S. Sampled Vegetation Height Statistics - Leland Creek
60 xL
is
Table 10. Sampled Vegetation Height Statistics - Leland Creek
Prepared by Watershed Sciences Page 61
Percentiles
Rivermiles
Count
Max
Min
5th
25th
50th
75th
95th
7.6 -7.0
616
30.9 m
0.0 m
0.0 m
0.0 m
0.1 m
0.2 m
1.4 m
6.0 -7.0
1,120
31.3m
0.0M
0.0M
0.1 m
0.3m
1.4m
14.4m
5.0 -6.0
1,120
28.2m
0.0M
0.0M
0.0M
0.1 m
0.7m
7.7m
4.0 -5.0
1,120
35.7m
0.0M
0.0M
0.0M
0.4m
2.1 m
17.2m
3.0 -4.0
1,120
45.3m
0.0M
0.0M
0.1 m
0.8m
10.1 m
29.8m
2.0 -3.0
1,120
39.8m
0.0M
0.0M
0.1 m
0.9m
9.0m
28.1 m
1.0 -2.0
1,120
47.2m
0.0M
0.0M
0.2m
1.0M
8.0m
28.2m
0.0 -1.0
1,148
40.5m
0.0M
0.0M
0.1 m
0.8m
7.8m
25.0m
Total
8,484
47.2 m
0.0 m
0.0 m
0.0 m
0.4 m
3.2 m
23.1 m
Prepared by Watershed Sciences Page 61
Quilcene and Chimacum Temperature Analysis Port Gamble S'KIal1am Tribes
Jefferson County, WA
Yigure 46. SatnDled Veeetation Height -Tarboo Creek
Prepared by Watershed Sciences Page 62
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 47. Sampled Vegetation Height Statistics - Tarboo Creek
Table 11. Sampled Vegetation Height Statistics - Tarboo Creek
Percentiles
Rivermiles
Count
Max
Min
5th
25th
50th
75th
95th
11.0 -11.25
280
24.1
0.0
0.0
0.0
> y
0.2
10.8
10.0 -11.0
1120
43.7
C
%
0.0
0.3
2.9
10.6
3
9.0 -10.0
1120
43.0
0.0
0.0
W Min
_
13.4
+ i
8.0 -9.0
1120
48.0
0.0
0.0
0.0
0.3
6.9
29.0
7.0 -8.0
1120
41.4
0.0
■ 5th Percentile
0.1
_
5.0
F
6.0 -7.0
1120
44.2
0.0
2
a
0.1
■ 25th Percentile
22.1
0
1120
37.9
0.0
0.0
0.0
0.1
2
z
4.0 -5.0
■50th Percentile
32.3
CD
0.0
5 k �, 'r' S+:{ I
¢��. ` x '� � � �' '�..�� x� � ,
(Median)
0.2
6.6
3.0 -4.0
� ~°
35.9
■ 75th Percentile
0.0
0.0
1
0.2
2.3
2.0 -3.0
1120
45.7
0.0
0.0
0.0
0.1
0.5
15.0
1.0 -2.0
1120
40.3
195th Percentile
0.0
0.1
0.9
_,.
28.1
0.0 -1.0
1120
40.8
0.0
�M
0.0
■ Max
10.1
29.2
Total
12600
48.0
0.0
0.0
0.0
0.2
i
23.4
N O O
° of
°
0 0 ^
cc
CO a o o M
LO
c7 N
River KM °
Table 11. Sampled Vegetation Height Statistics - Tarboo Creek
Prepared by Watershed Sciences Page 63
Percentiles
Rivermiles
Count
Max
Min
5th
25th
50th
75th
95th
11.0 -11.25
280
24.1
0.0
0.0
0.0
0.0
0.2
10.8
10.0 -11.0
1120
43.7
0.0
0.0
0.3
2.9
10.6
20.0
9.0 -10.0
1120
43.0
0.0
0.0
0.7
5.7
13.4
26.2
8.0 -9.0
1120
48.0
0.0
0.0
0.0
0.3
6.9
29.0
7.0 -8.0
1120
41.4
0.0
0.0
0.1
0.5
5.0
29.7
6.0 -7.0
1120
44.2
0.0
0.0
0.0
0.1
2.9
22.1
5.0 -6.0
1120
37.9
0.0
0.0
0.0
0.1
0.6
15.4
4.0 -5.0
1120
32.3
0.0
0.0
0.0
0.0
0.2
6.6
3.0 -4.0
1120
35.9
0.0
0.0
0.0
0.0
0.2
2.3
2.0 -3.0
1120
45.7
0.0
0.0
0.0
0.1
0.5
15.0
1.0 -2.0
1120
40.3
0.0
0.0
0.1
0.9
12.2
28.1
0.0 -1.0
1120
40.8
0.0
0.0
0.0
0.6
10.1
29.2
Total
12600
48.0
0.0
0.0
0.0
0.2
4.5
23.4
Prepared by Watershed Sciences Page 63
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Prepared by Watershed Sciences �� ��� Page 64
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Prepared by Watershed Sciences Page 65
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Table 12. Sampled Vegetation Height Statistics - Chimacum Creek
Percentiles
Rivermiles
Count
Max
Min
5th
25th
50th
75th
95th
23.0 -23.9
980
35.5 m
0.0 m
0.0 m
0.0 m
0.1 m
0.8 m
26.2 m
22.0 -23.0
1,120
28.5m
0.0M
0.0M
0.0M
0.0M
0.1 m
1.6m
21.0 -22.0
1,120
30.3m
0.0M
0.0M
0.4m
5.4m
10.9m
15.8m
20.0 -21.0
1,120
50.0m
0.0M
0.0M
0.8m
3.6m
8.9m
23.0m
19.0 -20.0
1,120
49.3m
0.0M
0.0M
0.7m
3.4m
11.6m
24.4m
18.0 -19.0
1,120
52.1 m
0.0M
0.0M
0.3m
1.2m
8.2m
25.7m
17.0 -18.0
1,120
43.1 m
0.0M
0.0M
0.0M
0.2m
5.6m
23.2m
16.0 -17.0
1,120
42.7m
0.0M
0.0M
0.0M
0.0M
0.2m
20.0m
15.0 -16.0
1,120
40.8m
0.0M
0.0M
0.0M
0.1 m
1.1 m
23.9m
14.0 -15.0
1,120
2.4m
0.0M
0.0M
0.0M
0.0M
0.1 m
0.3m
13.0 -14.0
1,120
12.7m
0.0M
0.0M
0.0M
0.0M
0.1 m
0.3m
12.0 -13.0
1,120
43.8m
0.0M
0.0M
0.0M
0.5m
6.2m
28.2m
11.0 -12.0
1,120
7.0m
0.0M
0.0M
0.0M
0.0M
0.1 m
0.6m
10.0 -11.0
1,120
15.5m
0.0M
0.0M
0.0M
0.1 m
0.2m
0.3m
9.0 -10.0
1,120
1.0M
0.0M
0.0M
0.0M
0.0M
0.2m
0.3m
8.0 -9.0
1,120
8.5m
0.0M
0.0M
0.0M
0.1 m
0.2m
0.4m
7.0 -8.0
1,120
9.6m
0.0M
0.0M
0.0M
0.1 m
0.2m
0.8m
6.0 -7.0
1,120
39.8 m
0.0 m
0.0 m
0.1 m
0.7 m
12.1 m
25.6 m
5.0 -6.0
1,120
27.7m
0.0M
0.0M
0.0M
0.2m
0.4m
6.2m
4.0 -5.0
1,120
32.1 m
0.0M
0.0M
0.1 m
0.4m
2.8m
19.2m
3.0 -4.0
1,120
41.4m
0.0M
0.0M
0.2m
2.3m
13.3m
26.0m
2.0 -3.0
1,120
49.4m
0.0M
0.0M
0.2m
3.5m
16.7m
26.4m
1.0 -2.0
1,120
45.5m
0.0M
0.0M
0.6m
6.7m
19.5m
32.1 m
0.0 -1.0
1,148
47.2m
0.0M
0.0M
0.1 m
6.0m
17.3m
32.9m
Total
26,768
52.1 m
0.0 m
0.0 m
0.0 m
0.2 m
3.2 m
22.8 m
Prepared by Watershed Sciences Page 66
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
rigure -*)U. Jambled Vegetation Hemht — East C;hlmacum Creek
'1"r.L 4 {
KP
N i
rdver KM I- '
�y,p tP1
'
VLU
60
50 ��
IM
ZQ
IM
IV
>
0
LP
a' o
m
CD CO -
U?
ti OD �
� ch
ui
River KM 00 0 E u
0 ,
a) N
PE LO r-.: �
Q4P
CN m N
O
Prepared by Watershed Sciences Page 67
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 51.
Sampled Vegetation Height Statistics -
East Chimacum Creek
4
Percentiles
Rivermiles
Count
Max
Min
5th
5
50th
75th
95th
11.0 -11.25
280
24.3m
0.0M
0.0M
0.0M
0.2m
1.0m
12.0m
10.0 -11.0
1,120
40.4m
0.0M
0.0M
f
0.2m
0.8m
14.1 m
9.0 -10.0
E
43.9m
0.0M
0.0M
0.4m
2.7m
13.8m
m Min
8.0 -9.0
1,120
32.5m
0.0M
Cs
0.0M
0.1 m
■ 5th Percentile
2
7.0 -8.0
1,120
27.1 m
Z
0.0M
3
a 25th Percentile
0.8m
10.6m
6.0 -7.0
1,120
2
0.0 M
0.0 M
v ■ 50th Percentile
0.0 M
0.1 m
(Median)
1
1,120
3.2 m
■ 75th Percentile
0.0 m
0.0 m
0.0 m
0.1 m
0.2 m
4.0 -5.0
1,120
95th Percentile
0.0M
0.0M
0.0M
0.0M
0.1 m
0.2m
3.0 -4.0
1,120
10.0m
0.0M
0.0M
■ Max
0.0M
r �
0.2m
2.0 -3.0
1,120
3.8m
0.0M
0.0M
0.0M
0.0M
0.1 m
0.2m
1.0 -2.0
LO
15.7m
0.0M
0.0M
0.1 m
0
?S A9
1.1 m
CP 0
0 0
22.4m
0.0M
0 o o
c o u q
N
0.3m
Qo'
cc U'j o
43.9 m
0.0 m
C4
0.0 m
0.1 m
River KM
c
Table 13. Sampled Vegetation Height Statistics - East Chimacum Creek
Prepared by Watershed Sciences Page 68
Percentiles
Rivermiles
Count
Max
Min
5th
25th
50th
75th
95th
11.0 -11.25
280
24.3m
0.0M
0.0M
0.0M
0.2m
1.0m
12.0m
10.0 -11.0
1,120
40.4m
0.0M
0.0M
0.0M
0.2m
0.8m
14.1 m
9.0 -10.0
1,120
43.9m
0.0M
0.0M
0.4m
2.7m
13.8m
27.2m
8.0 -9.0
1,120
32.5m
0.0M
0.0M
0.0M
0.1 m
0.3m
16.5m
7.0 -8.0
1,120
27.1 m
0.0M
0.0M
0.0M
0.1 m
0.8m
10.6m
6.0 -7.0
1,120
4.0 m
0.0 M
0.0 M
0.0 M
0.0 M
0.1 m
0.3 m
5.0 -6.0
1,120
3.2 m
0.0 m
0.0 m
0.0 m
0.0 m
0.1 m
0.2 m
4.0 -5.0
1,120
40.5m
0.0M
0.0M
0.0M
0.0M
0.1 m
0.2m
3.0 -4.0
1,120
10.0m
0.0M
0.0M
0.0M
0.0M
0.1 m
0.2m
2.0 -3.0
1,120
3.8m
0.0M
0.0M
0.0M
0.0M
0.1 m
0.2m
1.0 -2.0
1,120
15.7m
0.0M
0.0M
0.1 m
0.2m
0.3m
1.1 m
0.0 -1.0
1,148
22.4m
0.0M
0.0M
0.0M
0.1 m
0.3m
4.0m
Total
12628
43.9 m
0.0 m
0.0 m
0.0 m
0.1 m
0.2 m
10.9 m
Prepared by Watershed Sciences Page 68
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
3.6 Historical Vegetation Analysis
3.6.1 Data Sources
• Historical Vegetation Analysis — Port Gamble S'Klallam Tribe
• Bahls, P. and J. Rubin. 1996. Chimacum watershed coho restoration assessment.
report for Port Gamble S'Klallam Tribe
3.6.2 Sampling Methods
Historical riparian vegetation information suggest that the land cover distributions were
predominantly conifer, with some hardwood/conifer communities. Wetland and marsh
areas comprised a small (13 %) of the overall land cover distribution, although it is likely
that wetland communities were frequently located along stream corridors.
"While it appears that Tarboo was indeed dominated by conifer - spruce bottomlands,
Chimacum was not. There was a mosaic of large and small beaver ponds, huge open
areas of spirea and crabapple. The assumption that Chimacum was dominated by conifer
forest is probably not the case. However, there may have been alot more shrub shade and
cold water from springs and other storage behind beaver dams than there is now, but
complex."
( Bahls, e-mail communication)
Bahls and Rubin (1996) describe historical vegetative /morphologic conditions that trend
toward more woody riparian vegetation, relative to contemporary conditions. This
generalization holds for a much of the study area. However, some lower gradient areas,
especially Chimacum reaches, were dominated by non -woody wetland species, offering
complex alluvial morphology with frequent beaver disturbance, instead of the
contemporary single thread channels that prevail today.
Prepared by Watershed Sciences Page 69
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
3.6.3 Results
Figure 52. Historical Riparian Vegetation Distribution (PGST Data
The modeled vegetation scenarios are simplified to reflect a general increase in woody
vegetation and later seral stages, both indicative of the historical condition. It is
acknowledged that the scenarios are locally imprecise, under- and over - stating the
historical condition, depending on the location. At this time, it is not practical, or even
scientifically defensible, to simulate a true historical vegetation condition. In this
context, the simulated vegetation scenarios should be recognized as simple
approximations of increases woody vegetation. They are not accurate representations of
a historical condition.
Prepared by Watershed Sciences � � � �� � Page 70
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 53. Vegetation Species Average Growing Height Based Upon Measured Data in
Pacific Northwest Coastal Areas.
Prepared by Watershed Sciences Page 71
Chapman- Richards Asymptotic Non - Linear Regression Module
H =
1.37 +
(bo[1 — exp(b1 -D BH)]b2
)
(Richards, 1959)
DBH
Calculated Height
Species
Site Class
(inches) bo bl
b2
(feet) (meters)
Sitka Spruce
1 to 2
40.0 65.3 -0.012
0.968
155.1 47.3
Douglas Fir
1 to 2
19.1 85.6 -0.010
0.935
108.7 33.2
Western Hemlock
1 to 2
14.9 60.9 -0.022
1.078
122.6 37.3
Western Red Cedar
All
18.9 55.2 -0.012
0.911
78.9 24.1
Bigleaf Maple
All
11.3 30.2 -0.037
0.813
62.1 18.9
Red Alder
1 to 3
9.2 37.4 -0.023
0.762
46.2 14.1
50
45
40
35
v
r
30
m
=
25
c
3
20
v
15
L
Q
10
5
0
Sitka Spruce
Douglas Fir
Westem Westem Red
Bigleaf Maple Red Alder
Hemlock Cedar
Prepared by Watershed Sciences Page 71
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Page Left Bank Intentionally
Prepared by Watershed Sciences �� � Page 72
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
4. Flow and Temperature Data
Table 14. Flow and Temperature Monitoring Locations and Site Identification
Waterbody
Tarboo Creek
Little Quilcene River
Big Quilcene River
Leland Creek
Penny Creek
Howe Creek
Chimacum Creek
East Chimacum Creek
Bamhouse Creek
Naylors Creek
Putaansuu Creek
Station ID
Bahls Station 1
Bah1s Station 4
Bahls Station 11
Balhs Station 13
Balhs Station 18
Balhs Station 21
Balhs Station 23
Bahls Station 24
Bahls Station 25
JCCD_TB /0.9
JCCD_TB /2.4
JCCD_TB /4.0
JCCD_CY /0.1
Bahls Station 30
PGST_LQU
PGST_LQ2
PGST_LQL
USGS_LQS6
USGS_LQS7
PGST_BQU
USGS_BQS 1
PGST_BQM
PGST_BQ2
PGST_BQL
USGS_BQS5
PGST_LL2
PGST_LL3
PGST_LL4
PGST_LL5
USGS_BQS2
PGST_HOW
JCCD_CH /0.1
JCCD_CH /2.3
JCCD_CH /3.4
JCCD_CH /6.7
JCCD_CH /9.3
JCCD_ECH/0.2
JCCD_ECH/1.0
JCCD_ECH /5.3
JCCD_BH /1.0
JCCD_NA/0.2
JCCD PU /0.4
Description
At Mouth
Downstream Dabob PO Road
Downstream End of McDonald Property
Upstream Junction with Tributary on McDonald
Upper Yarr
Dabob PO Road
Edwards
Worthington
Center Road
Coyle (EF Tarboo) Creek
At ANE property
PTQ3000 Rd
Below Ripley Creek
Hwy 101
Center Road
Near McInnis Rd
Falls View Campground
Hiddendale
Hwy 101
Glen Logie Road
Rodgers Street Bridge
Power lines
Hwy 101
Deer Carcass
Leland Tributary, Larch Road
Upper Leland Tributary, Hwy 101
USFS Access Road
Prepared by Watershed Sciences Page 73
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
4.1 Continuous Flow Measurements and Derived Flows
4.1.1 Data Sources
• Washington DOE Gages (2004 Provisional Data)
• USGS 10 meter DEM
4.1.2 Sampling Methods
HEC- GeoHMS was used to calculate flow accumulations and delineate contributing
watershed drainage areas (see http: / /www.hec.usace. army .mil /software/hec- hms/hechms-
geohms.html). Continuous flow data measured at known gages were then extrapolated to
upstream and tributary areas using weighted drainage area, as follows:
where,
A.
Qi,t = A, QT,t
T
(Eq 5)
Qij: Flow at outlet of drainage area I, at time t (cros)
QT,t: Total flow at gage from all drainage areas, at time t (cros)
A;: Drainage area i (m2)
AT: Total drainage area above known gage (m)
Measured instantaneous values (late July PGST and JCCD measurements) were used to
check the accuracy of base flow estimates, and where deviations were observed,
additions /subtractions were performed so that flow estimated match. The volumes added
or subtracted from tributaries were accounted for in the upstream boundary condition, so
that the mass balance is preserved.
4.1.3 Results
State of Washington flow gages are located on each of the streams in the study area.
Flows range considerably. Based upon these data collected during the study period
(2004), the Big Quilcene and Little Quilcene Rivers median flows (as presented below)
of 42 and 17 cfs, respectively. Chimacum and Tarboo Creeks have median flows of 6
and 2 cfs, respectively.
Derived time series flow data are developed for modeled boundary conditions using
Equation 5.
Prepared by Watershed Sciences Page 74
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 54. Gage Data (Department of Ecology, River and Stream Monitoring,
3
0
LL
: / /fortress.
1000
100
10
sta =1
—Big Quilcene River —Little Quilcene — Chimacum Creek — Tarboo Creek
M v,"
b&6.- _�" . 'L jhkk- MMA
-- - - - -.. - -- --------------------------- --- ----
-- - --------- - - - - -- -- - - - - -- -
-��� -- - - - - -- - ------- hL- - - - - - - - - - w- - - - - ->A - - -- -- -� --
1
Median Flows
(6/1-9/30,2004)
River /Stream
(cfs)
r 00 to N
�j N
M Q N M
N
CO M O h '.t
r e V
C`
Little Quilcene
CA 00 W
0.48
Chimacum Creek
5.84
0.17
Tarboo Creek
2.39
0.07
2004
Gage
ID
Latitude
Longitude
River mile
Chimacum
17BO50
48 03'00" N
122 47'03"
W
0.3
Tarboo
176060
47 52'08" N
122 48'57"
W
0.5
Little Quilcene
17DO60
47 49'48" N
122 52'28"
W
0.7
Big Quilcene
17AO60
47 49'06" N
122 52'56"
W
0.2
Note: The flow drops in the Big Quilcene River provisional data (5/29 and 6/29) have
little impact the modeling since they are outside of the period of interest.
Prepared by Watershed Sciences f Page 75
Median Flows
(6/1-9/30,2004)
River /Stream
(cfs)
(cros)
Big Quilcene River
42.45
1.20
Little Quilcene
16.95
0.48
Chimacum Creek
5.84
0.17
Tarboo Creek
2.39
0.07
Note: The flow drops in the Big Quilcene River provisional data (5/29 and 6/29) have
little impact the modeling since they are outside of the period of interest.
Prepared by Watershed Sciences f Page 75
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
55. Bijz Quilcene Kiver: Area Weighted Venved Nows
— Measured: Big Quilcene River Derived: Upper (PGST_BQU) — Derived: Penny
1000
MI
0
LL
10
----------------------------------------------------------
-----------------------------------------------------------
Aely Error at Gage
1
O O N O cD CO O 1 M O 1 mt e— O
C D ` N N N N N
t` ti O O O O O O
2004
Figure 56. Little Ouilcene River: Area Weiehted Derived Flows
— Measured: Little Quilcene —Derived: Upper (PGST_LQU)
Derived: Leland (PGST_LEL) -o- Derived: Ripley
-p- Derived: Howe
1000
100
10
0
L 1
0.1
0.01
O O N O (O M
` N N z
CO CG W 1-
O 1- M
CO CN 04
2004
.0 aj � O W Sm
Prepared by Watershed Sciences Page 76
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
in
3 1
LL
42
v
3
0
LL
0.1
ihh7
10
1
r figure 57. Tarboo Creek: Area Weighted Denved Mows
Measured: Tarboo Creek ► Derived: EF Tarboo
—Derived: Upper (JCCD TB /4.0)
- -- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
-- - - -- - - - - -- -
-- - - 't - i� -.�J•
- - - - - - - Ay�N M A�N � N ----rti- - -- -- j'~ --- ^- --- --- - --
--
- ------------------
+.� * - - - - -�
� M 0 N O CC M O I M O 1 d' — � � � O
Z25 ('O ` N N ti ` N N Co ` - N M ` N N
c0 co co h i I- ao O ao CO CT> O O
2004
Eigure 58. Chimacum Creek: Area Weighted Derived Flows
— Measured: Chimacum Creek Derived: E Chimacum (ECH /0.2)
-- Derived: Trib (NA/0.2) Derived: JCCD CH /9.3
=tea
i
I
E�-
�-
PF
I
0.1
r CO u7 N O Co M O 1- M O I CO
` `
(O Co Co fz r- r- O 00 CO CO O O CA
2004
Prepared by Watershed Sciences Page 77
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 59. East Chimacum Creek: Area Weighted Derived Flows
i- Derived: E Chimacum (ECH /0.2) •- Derived: Lower E Chimacum (CH /0.1)
Derived: Upper E Chimacum (CH /3.3)
10.00 -r ----
1.00
0
---------- rti -_ `- _________ _-
_______ - -� _ __________ ______ ....._________
0.10
r CO Ln N 0) <O M
CEO CO W 0 C ~ �
O 1- CM O
Q Q aD
2004
4.2 Instantaneous Flow Measurements
4.2.1 Data Sources
• Port Gamble S'Klallam Tribe
• Jefferson County
• Bahls, 2002
0�0 a�0 CO O rn O> OM
4.2.2 Results
Instantaneous flow measurements are used to describe ungaged streams and inflows, as
well as upstream portions of the gaged streams /rivers. These data help validation of
simulated flows and derived flows.
Prepared by Watershed Sciences Page 78
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Table 15. Instantaneous Flow Monitoring Sites
Prepared by Watershed Sciences Page 79
Flow
ID
Date
Time
cfs
cros
PGST_LQU
7/23/2004
10:00
8.2
0.233
PGST_LQ2
7/23/2004
11:00
14.9
0.421
Little Quilcene River
PGST_LQL
7/23/2004
12:00
14.9
0.421
USGS_LQS6
7/22/2004
2:00
17.2
0.486
USGS_LQS7
7/23/2004
9:00
16.5
0.467
PGST_BQU
7/22/2004
13:35
56.5
1.599
USGS_BQS1
7/22/2004
10:45
51.0
1.444
PGST_BQM
7/22/2004
9:45
61.5
1.741
Big Quilcene River
PGST_BQ2
7/22/2004
14:30
56.6
1.602
PGST_BQL
7/22/2004
11:35
60.5
1.714
USGS_BQS5
7/22/2004
12:10
56.3
1.595
PGST_LL2
7/23/2004
13:30
1.1
0.031
PGST_LL3
7/23/2004
15:00
0.4
0.012
Leland Creek
PGST_LL4
7/23/2004
AM
0.004
0.000
PGST_LL5
7/23/2004
16:00
0.24
0.007
Penny Creek
USGS_BQS2
7/22/2004
10:50
4.51
0.128
Howe Creek
PGST_HOW
7/23/2004
9:00
5.73
0.162
JCCD_CH /0.1
7/23/2004
9:47
4.27
0.121
JCCD_CH /2.3
7/23/2004
10:10
3.04
0.086
JCCD_CH /3.4
7/23/2004
10:42
2.78
0.079
JCCD_CH /6.7
7/23/2004
13:00
2.17
0.061
Chimacum Creek
JCCD_CH /9.3
7/23/2004
14:18
0.82
0.023
NA/0.2
7/23/2004
14:36
0.215
0.006
PU /0.4
7/23/2004
13:38
0.130
0.004
BH /1.0
7/23/2004
12:22
0.015
0.547
JCCD_ECH/0.2
7/23/2004
11:33
0.61
0.017
East Chimacum Creek
JCCD_ECH/1.0
7/23/2004
12:02
0.75
0.021
JCCD_ECH/5.3
7/23/2004
11:24
0.63
0.018
Barnhouse Creek
JCCD_BH /1.0
7/23/2004
12:22
0.55
0.016
Naylors Creek
JCCD_NA/0.2
7/23/2004
14:36
0.22
0.006
Putaansuu Creek
JCCD_PU /0.4
7/23/2004
13:38
0.07
0.002
JCCD_TB /0.9
7/26/2004
11:46
1.49
0.042
JCCD_TB /2.4
7/26/2004
11:05
1.13
0.032
JCCD_TB /4.0
7/26/2004
10:10
0.46
0.013
JCCD_CY /0.1
7/26/2004
12:45
0.39
0.011
Bahls Station 1
7/22/2002
0.10
0.0026
Bahls Station 4
7/22/2002
0.02
0.0007
Bahls Station 6
7/23/2002
0.08
0.0022
Tarboo Creek
Bahls Station 11
7/24/2002
0.08
0.0024
Bahls Station 13
7/28/2002
0.10
0.0029
Bahls Station 18
7/30/2002
0.33
0.0093
BAN Station 21
7/31/2002
1.60
0.0454
Bahls Station 23
8/1/2002
0.27
0.0077
BAN Station 24
8/1/2002
1.13
0.0320
Bahls Station 25
8/1/2002
0.073
0.0021
Prepared by Watershed Sciences Page 79
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ti
.ti
qr
v
Ol
r.
bA
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O
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w
y
O
O
0
w
'z
o)
w
U
ti
F,
Q%
O
O
h
IP-
X
m�
„a
p z 2 m •••_ _•J,�
m m z z m
m m
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00
bA
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a
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
4.3 Bathymetry Data
4.3.1 Data Sources
• Instream Flow Measurements
4.3.2 Results
The `Channel Angle — z' represents the channel side slope ratio and can be used to
configure a basic trapezoidal channel dimension to match the basic channel geometry.
Channel profile information (measured when collecting instream flow data) is used for
estimating the channel side slope angle and bottom width of the channel (see Table
below). The derived channel shapes are shown over the known channel shapes in the
following figures.
Width Bottom
Prepared by Watershed Sciences Page 81
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Table 16. Fitted Bottom Width and Side Slope Ratios (Z)
WidthB.
Prepared by Watershed Sciences Page 82
ttoro
(m) Z1
ZZ
R
SE (m)
Little Quilcene @ PTQ3000 Rd
0
0.47
0.12
0.85
0.06
Little Quilcene below Ripley Creek
0
0.39
0.24
0.96
0.05
Little Quilcene @ Hwy 101
2.65
0.43
1.24
0.65
0.05
Little Quilcene @ Center Rd
2.13
0.14
0.32
0.87
0.06
Little Quilcene River nr McInnis Rd
1.46
0.16
0.12
0.95
0.02
Big Quilcene R @ Falls View Cmpgmd
9.53
0.09
2.00
0.90
0.07
Big Quilcene at Hiddendale
11.58
0.28
0.14
0.52
0.09
Big Quilcene River @ Hwy 101
11.58
0.78
0.049
0.86
0.06
Big Quilcene River @ Glen Logie Rd
7.25
0.44
0.21
0.85
0.07
Big Quilcene River @ Rodgers St Bridge
1.22
0.06
0.17
0.81
0.08
Big Quilcene River @ Power lines
1.83
0.05
0.05
0.89
0.03
Leland @ Hwy 101
1.98
0.33
0.33
1.00
0.00
Leland Creek @ Deer Carcass
1.28
0.22
0.23
0.88
0.02
Tarboo Creek - Bahls Station 1
4.00
0.25
0.63
0.83
0.21
Tarboo Creek - Bahls Station 4
5.10
0.52
0.52
0.92
0.13
Tarboo Creek - Bahls Station 11
4.05
1.11
1.23
0.87
0.09
Tarboo Creek - Bahls Station 13
1.70
0.37
0.47
0.85
0.13
Tarboo Creek - Bahls Station 18
1.20
0.98
0.65
0.95
0.10
Tarboo Creek - Bahls Station 21
3.65
0.30
0.97
0.95
0.06
Tarboo Creek - Bahls Station 23
2.10
1.08
0.78
0.90
0.10
Tarboo Creek - Bahls Station 24
3.80
0.28
2.60
0.95
0.07
Tarboo Creek - Bahls Station 25
2.50
0.90
0.72
0.93
0.09
Tarboo Creek - Bahls Station 30
2.58
0.34
0.56
0.91
0.11
Tarboo Creek - Station TB /0.9
2.13
0.30
0.15
0.78
0.01
Tarboo Creek - Station TB /2.4
1.22
0.34
0.34
0.95
0.01
Tarboo Creek - Station TB /4.0
0.82
1.20
3.61
0.86
0.01
Chimacum Creek - Station CH /0.1
2.74
0.35
0.64
0.77
0.11
Chimacum Creek - Station NA/0.2
0.49
0.66
3.28
0.83
0.01
Chimacum Creek - Station PU /0.4
0.58
0.66
1.31
0.78
0.02
Chimacum Creek - Station BH/1.0
0.55
0.87
0.37
0.73
0.03
Chimacum Creek - Station CH/2.3
3.05
0.43
0.16
0.84
0.03
Chimacum Creek - Station CH/3.4
3.05
0.17
0.21
0.88
0.04
Chimacum Creek - Station CH/6.7
2.56
0.14
0.26
0.93
0.02
Chimacum Creek - Station CH/9.3
0.37
0.11
0.24
0.89
0.01
East Chimacum Creek - Station ECH /0.2
0.98
1.15
0.09
0.87
0.01
East Chimacum Creek - Station ECH/1.0
0.98
0.25
0.42
0.94
0.02
East Chimacum Creek - Station ECH/5.3
0.18
7.22
0.30
0.95
0.01
Prepared by Watershed Sciences Page 82
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
r figure 66. Leland Creek Bathymetry and Derive 'Trapezoidal Channel
Hwy 101 Deer Carcass
Width (m)
0 1 2 3 0
0
-- --
0
0.005
0.02
.04
0
0.01
0.015
m 0.02
0.025
0.06
E 0.08
m 0.1
0.12
0.14
0.03
0.16
0.035
0.18
Width (m)
1 2
Prepared by Watershed Sciences Page 95
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
4.4 Continuous Stream Temperature Data
4.4.1 Data Sources
• Instream Temperature Measurements
4.4.2 Sampling Methods
Thermistors were deployed following Washington DOE protocols from May through
October.
4.4.3 Results
Port Gamble S'Klallam Tribe and Jefferson County staff deployed instream
thermographs from May to October, 2004. From these data, seven (7) day moving
average daily maximum (7 -day stat) temperatures were calculated and are presented in
Table 17.
Figure 67. Summary of Maximum 7 -Day Moving Average of Daily Maximums
(for July, August and September, 2004)
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Prepared by Watershed Sciences � � �� Page 96
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Table 17. Seven (7) day moving average daily maximum (7 -day stat) temperatures
ID
SITE NAME
Tem
erature Statistics °C
Absolute
Max
7-Day Ave. Max
July
Aug
Sept
PGST LEL
Leland Creek, Lower
20.3
18.7
17.5
14.5
JCCD LL /0.0
Leland Creek,RM 0.0
19.4
19.6
18.4
15.7
JCCD LL /1.8
Leland Creek, RM 1.8
20.4
19.4
18.6
15.3
PGST B L
Big uilcene, Lower
18.6
18.0
17.9
14.4
PGST B M
Big uilcene, Middle
16.8
16.3
16.4
13.1
PGST NFH
Big uilcene @ Hatchery
17.4
16.7
16.9
13.5
PGST B U
Big uilcene, Upper
13.6
13.3
13.4
11.1
PGST L CR
Little Quilcene @ Center Rd
19.4
18.4
17.4
14.1
PGST L U
Little Quilcene, Upper
15.6
14.7
14.4
11.6
JCCD L /1.6
Little Quilcene, RM 1.6
18.4
17.4
16.4
13.5
JCCD TB /0.9
Tarboo Creek, RM 0.9
17.4
16.7
16.4
14.2
JCCD TB /2.6
Tarboo Creek, RM 2.6
17.0
16.2
15.6
13.4
JCCD TB /4.0
Tarboo Creek, RM 4.0
15.7
14.6
14.1
12.4
PGST TB/Yarr
Tarboo trib at Yarr Farm
26.0
21.2
17.5
14.1
JCCD CH /0.1
Chimacum Creek, RM 0.1
19.7
18.7
17.4
14.6
JCCD CH/1.1
Chimacum Creek, RM 1.1
18.7
18.2
16.9
15.0
JCCD CH/3.9
Chimacum Creek, RM 3.9
22.2
21.2
18.6
15.6
JCCD CH/5.3
Chimacum Creek, RM 5.3
19.2
18.7
17.0
14.9
JCCD CH/6.1
Chimacum Creek, RM 6.1
19.0
18.1
17.0
13.8
JCCD CH/6.5
Chimacum Creek, RM 6.5
17.4
16.6
15.9
13.3
JCCD CH/6.7
Chimacum Creek, RM 6.7
16.4
16.0
15.2
13.1
JCCD CH /7.0
Chimacum Creek, RM 7.0
16.4
14.7
14.4
13.4
JCCD CH/9.0
Chimacum Creek, RM 9.0
16.4
15.7
15.1
12.7
JCCD CH/9.4
Chimacum Creek, RM 9.4
15.0
14.3
13.9
11.9
JCCD ECH/0.1
East Chimacum, RM 0.1
20.2
19.4
18.2
14.5
JCCD ECH/1.1
East Chimacum, RM 1.1
18.2
17.8
16.3
14.0
JCCD ECH/1.2
East Chimacum, RM 1.2
18.8
18.2
16.4
13.9
JCCD ECH /2.8
East Chimacum, RM 2.8
16.6
15.9
15.4
12.7
JCCD ECH/3.3
East Chimacum, RM 3.3
16.1
15.6
15.1
12.8
JCCD ECH /5.4
East Chimacum, RM 5.4
13.7
13.1
12.8
11.7
Possibly Out of Water
Prepared by Watershed Sciences Page 97
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 68. Big Quilcene River Continuous Temperature Data and 7 -Day Statistics
Prepared by Watershed Sciences H�Page 98
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 69. Little Quilcene River Continuous Temperature Data and 7 -Day Statistics
• Little Quilcene, Upper (PGST -LQU)
■ Litttle Quilcene, LQ 1.7
• Litttle Quilcene, Center Rd. (PGST -LQCR)
20
18
ems.. 16
z
E 14
f
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E
i
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Prepared by Watershed Sciences Page 99
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Jefferson County, WA
Figure 70. Tarboo Creek Continuous Temperature Data and 7 -Day Statistics
Prepared by Watershed Sciences Page 100
i
1.
rM
77:1
T
WIT
Pr
F&I
FA
Prepared by Watershed Sciences Page 100
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 71. Leland Creek Continuous Temperature Data and 7 -Day Statistics
Prepared by Watershed Sciences Page 101
MOM
III
4
Neill
-4
Elk
MAIN
41
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 72. Chimacum Creek Continuous Temperature Data and 7 -Dav Statistics
Prepared by Watershed Sciences Page 102
I�
,I
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Prepared by Watershed Sciences Page 102
Quilcene and Chimacum Temperature Analysis Port Gamble SKIallam Tribes
Jefferson County, WA
Figure 73. East Chimacum Creek Continuous Temperature Data and 7-Day Statistics
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Quilcene and Chimacum Temperature Analysis Port Gamble S'WIallam Tribes
Jefferson County, WA
4.4.4 Was 2004 a "normal' year for stream temperature?
Over the July through September, 2004 was slightly warmer than 2001 and 2002, and
more similar to 2003. July was warm and similar to 2003, with median values about 1 °C
warmer than 2001 and 2002. August temperatures were less than 2003, roughly
equivalent to 2002 and warmer than 2001. The coolest September temperatures of the
four year record occurred in 2004. In general, the summertime temperature trended
warmer in July, about average in August and cooler in September.
Inter - Annual Variation in Stream Temperature (°C) at Lower Big Quilcene Monitoring
Site (BQL) — 7 -Day Average of Daily Maximum (7- DADMax)
19 — - - - — - ---
M - 2001 —2002 —2003 —2004
18 -------------- . -- hp.
Ew .
125 17 ---------- t -. - -- - - -- - - -`� -----------------------------
c..
16 - - - - - -'- --- - - - - -- - -- - - -- -- -------------------
G15 - - -- - - - - - - - -- - - - - -- - - x -- -----------------
m�° 4-' 14 j t :
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13. = -- -- - - - - - -- -------------- - - - - -- --
Q 12
------- ----------------------------------------
---------
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iz � r O � � � O O �I 01
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9 14
`" 13
0
c 12
11
V
10
Median 2001 -2004 Inter - Annual Variation
July -Sept July August September
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The table below summarizes 7 -Day average of daily maximum (7- DADMax) water
temperatures measured at the lower Big Quilcene River location (BQL). Measurements
span the July through September, for 2001 through 2004, allowing inter - annual variation
comparisons.
Statistical Comparison of Inter - Annual Variation in Stream Temperature ( °C) at Lower
Big Quilcene Monitoring Site (BQL) - 7 -Day Average of Daily Maximum (7- DADMax)
Percentiles
Period
Year
Min
25th
50th
75th
Max
July
2001
12.3
13.6
14.2
14.9
17.7
through
2002
11.1
13.0
13.9
15.0
16.4
September
2003
12.6
13.7
15.2
16.3
17.0
2004
12.1
13.0
14.9
16.6
18.0
2001
12.4
13.6
14.4
15.1
16.1
July
2002
11.1
13.1
13.8
14.5
15.4
2003
12.6
14.6
16.3
16.6
17.0
2004
12.7
14.6
16.4
17.3
18.0
2001
13.4
14.2
14.9
16.3
17.7
August
2002
13.0
14.7
15.2
15.6
16.4
2003
15.1
15.5
15.9
16.2
16.8
2004
14.4
14.9
15.5
17.2
17.9
2001
12.3
12.8
13.6
14.1
14.7
September
2002
12.1
12.5
13.0
13.5
14.4
2003
12.7
13.0
13.6
13.8
15.7
2004
1 12.1
12.4
12.7
13.5
1 14.4
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4.5 Continuous Atmospheric Data
4.5.1 Data Sources
• Air Temperature Measurements in Forested and Open Areas
4.5.2 Sampling Methods
Same as Instream Temperature Measurements, excluding placement
4.3.3 Results
Air temperatures in forested and open areas diverged considerably, with open areas
recording warmer daytime temperatures and cooler nighttime temperatures. In the
Leland Creek comparison, open areas averaged up to 11 °C warmer in the daytime and
3 °C degrees cooler in the nighttime. In the Chimacum Creek comparison, open areas
averaged up to 3 °C warmer in the daytime and 3 °C degrees cooler in the nighttime. The
large difference likely reflects characteristics of the local site, such as degree of
vegetation cover. Third ordered polynomial regressions were fitted to the divergence
data with moderate correlation coefficients: 0.57 for Leland and 0.40 for Chimacum. The
poor correlation suggests significant inter -day variability between open and forested air
temperatures.
Hourly relative humidity and cloud cover data are available from Port Angeles and
Bremerton weather stations. The Bremerton weather station malfunctioned and failed to
record data during the month of August. Data from the Port Angeles weather station is
presented below and used in all of the models.
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Jefferson County, WA
Figure 74. Leland Creek Air Temperature Data Comparison
Prepared by Watershed Sciences Page 107
Leleand Creek: Air Temperature
35
•f
1 1
5
+ r
\ •�
f
\IN
30
/M1.S Yr 't`,1..
f
.p+"yr..l.
+t . r t
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r •t 411
ii\t
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R
25
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+ ttjj�l5
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t �
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I
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a
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5
0
LO N
ti �_ co N (O
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(Z h:. iz ; O a O
r
2004
Air Temperature Deviation Between Open Area and Forested Area
R2 = 0.57
16
14
0
12
c
10
•
•
•
v
8
c
6
d
•
4
•
�
2
L
E
0
F
'a
-2
-4
-6
0 4
8 12 16 20
Hour of Day
Prepared by Watershed Sciences Page 107
Leland (Forest) • - • - • • - Leland (Open)
•f
1 1
5
+ r
\ •�
f
\IN
•\ .f �. \
/M1.S Yr 't`,1..
f
.p+"yr..l.
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\ �J.1\
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r •t 411
ii\t
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+ ttjj�l5
r=
\ \ f fw .
\ ' y •
t �
\ t
I
\ ��
r
•
7 1 M
Prepared by Watershed Sciences Page 107
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 75. Chimacum Creek Air Temperature Data Comparison
Prepared by Watershed Sciences Page 108
Chimacum Creek: Air Temperature
35
r:
' Chim (Forest)
- - - - . - - Chim (Open)
30
ci
25
rI5
,
r
,
L
20
L
E
15
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m
,
/
a
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N
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r
2004
Air Temperature Deviation Between Open Area and Forested Area
R2 = 0.40
15
V
°
10
C
•
>
5
0
m
CL
E
•
m
~
L
-5
Q
-10
0
4
8 12 16
20
Hour of Day
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Figure 76. Port Angeles Relative Humidity and Cloud Cover Data
wa Cloud Cover —Relative Humidity
Suspect Data
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
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5. Stream Temperature Model
A detailed description of Heat Source, the model used in this analysis, is
presented in Appendix A.
5.1 Model Overview
Stream temperatures change in response to
heat transfer and mixing with tributaries
and groundwater. Heat sources4 and sinks5
from the atmosphere (solar radiation, heat
imparted from air temperature, evaporation
and other radiant sources), the alluvial
aquifer and the ground (heat transferred
between the stream and the streambed).
Ultimately these processes can be broken
down into heat transfer and mass transfer.
While these processes may seem complex,
humans are actually intimately familiar
with how water heats and cools. The
processes listed below are experienced by
humans in everyday life.
Heat transfer processes:
• Solar radiation is what you feel when exposed to the mid -day sun (and why we seek
out shade when we are hot),
• Thermal radiation is the heat you feel when you hold your hand close to a warm
object, without actually touching it (like a hot flame),
• Conduction is the warmth or coolness you feel when you touch another object (like
the top of your desk or when you jump into a cold lake),
• Convection is the transfer of heat that accompanies turbulent air over an object (just
like a convection oven),
• Evaporation is the cooling that results when water evaporates (which is the cooling
you experience when you perspire).
Mass transfer processes:
• Advection is the transfer of heat downstream carried by river flow (analogous to
being washed downstream)
• Dispersion is the mixing of heat due to turbulent flows (similar to the diffusion. This
is how you can smell perfume across a room),
• Tributaries can transfer heat when waters mix at different temperatures,
4 Sources of heat refer to heat gained by the stream
5 Sinks of heat refer to heat lost by the stream
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• Groundwater /Springs usually a source for cool water that mixes with streams.
Hyporheic Exchange is the transfer of water flowing through the sediments /substrate
with stream water. These flows tend to moderate heating and/or create cooling.
Research investigating hyporheic flows is relatively new and therefore many people
may not immediately be familiar with this process. However the cooling influence of
shallow groundwater or hyporheic flows is an integral part of properly functioning
alluvial stream systems.
Parameters that affect stream temperature
can be grouped as near stream land cover
(vegetation), morphology and hydrology.
Many of these stream parameters are
interrelated (i.e., the condition of one may
impact one or more of the other
parameters). These parameters affect
stream heat transfer processes and stream
mass transfer processes to varying
degrees. Regardless of scale, many of
these parameters exhibit considerable
spatial variability. For example, channel bathymetry measurements can vary greatly over
small stream lengths. To further complicate matters, some parameters can have a diurnal
and seasonal (temporal) component as well as spatial variability.
Water temperature change (AT,,,) is a function of heat transfer to a discrete volume and
may be described in terms of changes in heat per unit volume. With this basic conceptual
framework, it is possible to discuss stream temperature change as a function of two
variables: heat and mass transfer.
Water Temperature Change as a Function of Heat Exchange per Unit Volume,
oT « HHeat (Brown, 1969)
" Volume
• Heat transfer relates to processes that change heat in a defined water volume (or
mass). There are several thermodynamic pathways that can introduce or remove
heat from a stream. For any given stream reach heat exchange is closely related
to the season, time of day, the surrounding environment and the stream
characteristics. Heat transfer processes can be dynamic and change over
relatively small distances and/or time periods. Several heat transfer processes can
be affected by human activities.
• Mass transfer relates to transport of flow volume downstream, instream mixing
and the introduction or removal of water from a stream. For instance, flow from a
tributary will cause a temperature change if the temperature is different from the
receiving water. Mass transfer commonly occurs in stream systems as a result of
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advection, dispersion, groundwater exchange, hyporheic flows, surface water
exchange and other human related activities that alter stream flow volume.
The simple relationship presented by Brown (1969) demonstrates that large volume
streams are less responsive to temperature change, and conversely, low flow streams will
exhibit greater temperature sensitivity (and greater rates of stream temperature change).
Specifically, stream flow volume will affect the wetted channel dimensions (width and
depth), flow velocity (and travel time) and the thermal assimilative capacity6. Human
related reductions inflow volume can have a significant influence on stream temperature
dynamics, most likely increasing diurnal variability in stream temperature.
Heat Transfer Processes
Stream temperature change is an expression of heat exchange between a stream and its
environment. The heat transfer processes that control stream temperature include solar
radiation ( (Dsotar), longwave (thermal) radiation (Otongwave), streambed conduction
( (Dstreambed), stream/air convection (Ooonvedi.n) and evaporation (0evaporation) (Wunderlich,
1972, Jobson and Keefer, 1979, Beschta and Weatherred, 1984, Sinokrot and Stefan,
1993, Boyd, 1996). Hence, the net heat energy flux (4)t,,t,,1) consists of summation of
these heat transfer processes. With the exception of solar radiation, which only delivers
heat energy, these processes are capable of both introducing and removing heat from a
stream. Stream shade is an important regulator of shortwave radiation heat transfer to a
stream that can create significant instream temperature increases (i.e. by loC or more)
over spatial scales ranging from a stream segment (i.e. �z1 km) to the watershed scale
(Brown 1969, Beschta and Weatherred, 1984, Boyd 1996).
6 The thermal assimilative capacity refers to the amount of heat change in a water column to cause specific temperature
response.
' Air/Water convection includes both turbulent and free surface conduction.
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The ultimate source of heat energy to a stream is solar radiation (both diffuse and direct).
Secondary sources of heat energy include longwave radiation, from the atmosphere and
near stream vegetation, streambed conduction and in some cases, groundwater exchange
at the water - substrate interface. Several processes dissipate heat energy at the air -water
interface, namely: evaporation, convection and back radiation. Heat energy is acquired
by the stream system when the flux of heat energy entering the stream is greater than the
flux of heat energy leaving. The net heat energy flux provides the rate at which energy is
gained or lost per unit area and is represented as the instantaneous summation of all heat
energy components. An example of heat transfer processes is presented in Figure below.
Figure 77. Simulated Heat Transfer Processes: Big Quilcene River at Mouth, August
Note the temporal variability in all processes, and the combined heat transfer (black line)
Mass Transfer Processes
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Net Heat Energy Continuity,
(D total — (D solar + 4D longwave + 10 evaporation + (D convection + 10 streambed
—Total Heat
SolarRad.
AirConv.
Bed Cond.
Evap.
- LW Rad.
800
700
^
}'
800
----- ;_ --------------- ._ __ ;_ __
,_ _ ____
-- ---------------
500
�
- - -
- - - - _ - - --
400
300
b-
200--
Li
100
2 0
-100
- -
j- -------- ` - - - - -- ------
-200 --
-- ------ ------- -------- -------
-- - --- ---- : - - - -
- -- r - - - -- - - -- - - - --
-300
T
�_Mr
III T M
CO CD �73 CD r r
in r- C" T CI)
r r r- Cll CU
LO r_ C" T
CU CU N M
CD CO
co CD cm CD
C4 CD CPS Cn
Mass Transfer Processes
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Mass transfer processes refer to the movement and mixing of water throughout a stream
system. The downstream transport of dissolved/suspended substances and heat
associated with flowing water is called advection. Dispersion results from turbulent
diffusion that mixes the water column. Flowing water is usually well mixed vertically,
largely a result of dispersion. Stream water mixing with inflows from surface tributaries
and subsurface (groundwater) sources moves water and heat within the stream system.
These processes (advection, dispersion and mixing of surface and subsurface waters)
redistribute the heat of a stream system via mass transfer (Boyd and Kasper, 2003).
Advection refers to the water that is transported by gravity driven river flow in the
downstream direction. In the case of water temperature, no heat energy is lost or gained
by the system during advection, assuming the heat from mechanical processes, such as
friction and compression, is negligible. Advection is simply the rate at which water and
the dissolved/suspended substances and heat are transferred downstream.
Lateral Velocity Distribution Vertical Velocity Distribution
Channel Edge (Left Bank)
V Water Surface
Flow Flow
�y
Channel Edge (Right Bank) Channel Bottom
Dispersion Defined. Dispersion is the mixing that occurs from turbulence caused by vertical and lateral
flow variations. Velocity is a function of depth, width and channel roughness (frictional forces at the
boundaries). The vertical and horizontal gradient in flow velocity causes tumbling and eddy effect mixing
Dispersion refers to the mixing caused by turbulent diffusion. Natural stream systems
flows are often vertically mixed due to turbulent diffusion of water molecules. Turbulent
flows result from a multi - dimensional variable flow velocity profile, with lower velocities
occurring near the boundaries of the channel (i.e. channel bottom and stream banks).
Higher velocities occur farthest away from channel boundaries, commonly at the top and
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center of the water column. The velocity profile results from the friction between the
flowing water and the rough surfaces of the channel. Since water is flowing at different
rates through the channel cross - section, turbulence is created, and vertical mixing results.
Dispersion mixes water molecules at a much higher rate than molecular diffusion.
Turbulent diffusion can be calculated as a function of stream dimensions, channel
roughness and average flow velocity. Dispersion occurs in both the upstream and
downstream directions.
Mixing external flows (tributaries, groundwater inflows, point sources, etc.) with
receiving waters will change the water heat when the respective temperatures are
different (as a function of stream and inflow volumes and temperatures). Remote sensing
using thermal infrared radiometry (TIR) can easily identify areas where heat change
occurs due to mixing with surface and subsurface waters. This report locates and
quantifies subsurface inflows by detecting temperature changes apparent in the TIR data.
Sources of Stream Warming and Cooling
Stream and river temperatures are dynamic over large spatial scales, regardless of
anthropogenic activities and associated human sources of heating/cooling. The temporal
variability in natural background hydrology, land cover succession and morphology
combine to create a complex and somewhat dynamic background thermal condition. The
thermal background condition is a range, instead of a static condition.
Natural sources that may increase stream
temperature include scouring effects on
morphology and floodplain vegetation,
drought, fires, insect damage to near
stream land cover, diseased near stream
land cover and windthrow and blowdown
in riparian areas. The processes in which
natural sources affect stream temperatures
include increased stream surface exposure
to heat transfer processes, altered
microclimates and flow modifications.
Legacy morphology conditions and land
cover distributions can sometimes be
caused by natural disturbances. Overall,
the extent of natural disturbances on near
stream land cover, channel morphology and hydrology is not well documented in the
literature and complicated by geologic time scales.
Factors that cool streams and rivers that are of non -human origin can be broken into mass
and heat transfer sources. Conditions that reduce radiant heat exposure will prevent or
reduce rates of stream heating, and in some cases reduce stream heating rates and
gradients. Such conditions include the persistent effects of shade produced from riparian
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vegetation, stream surface area reduction via healthy equilibrium morphology, cool near
stream microclimates that occur in well vegetated riparian corridors and mixing with the
alluvial aquifer. There are also episodic cooling effects that reduce radiant heat exposure
such as cloudiness (or any other form of vapor and particulate matter in the overlaying air
mass), cool air temperatures that reduce thermal radiation emission from the atmosphere,
vegetation and topography that is received by a stream and windy conditions that increase
evaporative cooling.
Natural mass transfers of inflow (tributaries, springs, etc.) can obviously heat and cool
the receiving water. Typically subsurface water is cooler than surface water. Cooler
subsurface waters tend to come from deeper ground water sources and snowmelt sources.
Shallow groundwater and hyporheic flows typically have warmer temperatures relative to
deep cold subsurface sources of flow (Bartolino and Niswanger, 1999).
Streams and Rivers Are Thermally Unique
Recent literature indicates that each hydrologic system (regardless of scale) is thermally
unique (Boyd and Kasper 2003, Faux et al. 2001, Torgersen et al. 2001, Torgersen et al.
1999). A definition of stream temperature uniqueness recognizes that the longitudinal
temperature profile, as well as spatial and temporal dynamics, defined at virtually any
scale, applies only to one stream, river or network. Stream temperature distributions are
highly characteristic of individual stream/river reaches and these unique temperature
patterns are expressed inter - annually ( Torgersen et al. 1995). Stream and river systems
are not only hydrologically and thermally unique, but also complex, since thermal
patterns result from complex interactions between interrelated parameters (Boyd and
Kasper 2003). These interrelated parameters can cause simultaneous thermal changes
that amplify or mask the thermal effects of other processes.
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Figure 78. Thermal Infrared Radiometer Data (July 29h, 2004 –2:00-4:00 PM)
Stream Temperature Patterns are Unique:
• Exhibits different temperature patterns across multiple scales
• Patterns result from uniquely distributed temporal thermal and hydrologic processes
• Thermal and hydrologic processes reflect the condition of the floodplain, riparian area
morphology, hydraulics, human land/water use and atmospheric conditions.
24-- —Chimacum
23- Creek
22 - —East Chimacum
f 1\ Creek
0 21-
4) —Tarboo Creek
S20-
tv
19-
Little Quilcene
18-
River
_&A1%jE 17 now Big Quilcene
6.
River
16 - AA
M 15-
14-
13--
12-
11
10
Distance From Mouth (KM)
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Data and Methods
High resolution spatial data sets serve as analytical inputs. These spatial data sets,
coupled with analytical models, can go much further than simply describing selected
processes over a reach level scale (i.e. shade heat moderation over a 1 km section of any
given stream). Instead this approach offers a comprehensive analytical framework that
does equally well at describing all heat and mass transfer processes, both localized and
cumulative effects, over large scales (over the entire basin).
Considerations for complicated and interrelated processes (i.e. hyporheic flow relations to
morphology, land cover, valley landform and land use practices) are developed to capture
recent scientific advances in our understanding, while cognizant of the limitations of data
and knowledge gaps. This methodology represents an evolution of the literature that
recognizes thermal uniqueness, explains interrelated causal factors and derives relations
to land management and the biological resources. Methodology robustness stems from
an incorporation of improvements and advancements where appropriate based upon the
input from other cooperators /researchers, the literature and resource managers.
Guiding fundamental principles of the methodology can be summarized as follows:
• Streams and rivers are thermally unique over virtually any scale. Data and
analysis address these unique thermal patterns at the landscape scale,
• The analysis captures thermal and hydrologic uniqueness with high resolution
(less than 1:5,000) spatially continuous data that complements traditional ground
level data,
• The methodology is fraught with analytical complexity. Very few simplifications,
assumptions or omissions are evident,
• Where possible, considerations for the interrelatedness between parameters are
built into the methodology,
• Analysis is performed without preconceived notions of parameter and process
sensitivity, and ultimately, model outputs, and
• Analytical resolution is scaled to match the high resolution offered from spatial
data (GIS and remote sensing).
Aside from computational speed, analytical modeling is best performed using
deterministic methods over relatively short time and distance finite difference steps.
Model operation resolution matches the dynamic nature of stream temperature that tends
to occur over small scales across a variable landscape, and sometimes in a brief period of
time.
Heat Source calculates all thermodynamic and hydraulic processes that affect both heat
and mass transfer (Boyd, 2004). Alluvial aquifer hydraulic gradients are assumed to
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Jefferson County, WA
mimic stream hydraulic gradients in the near field. Heat Source calculates a multitude of
processes for subsurface hydraulics and thermodynamics.
Important parameters in the model (as they pertain to heat and mass transfer) are:
• Bathymetry is accurately estimated,
• Flows are well characterized in the study area,
• External flows (tributaries, hyporheic flows and withdrawals) can be input into
the model,
• Flow variable processes are simulated (seasonal bar emergence, pooling, riffles,
etc.),
• Data outputs include important parameters (energy grade lines, hydraulic
dimensions, etc.),
• Simulation periods can be long.
• Surface and subsurface heat flux processes,
• Mass transfer heat flux processes,
• Longitudinal hyporheic exchanges and heat transfer,
• Surface water temperature and alluvial aquifer temperature.
• Hydraulic conductivity$ of the alluvium,
• Sediment depth9 of the alluvium underlying the stream (based on field/well
measurements and LiDAR data),
• Water balance of the system, including surface and alluvial aquifer (calculated by
model),
• Surface and alluvial aquifer flow rates /regime (calculated by model),
• External flows and withdrawals from the surface and alluvial aquifer (based on
field measurements, personal communication and water rights),
• Hydraulic head of the alluvial aquifer (calculated by model), and
• Wetted surface area over which exchange occurs (calculated by model).
For a detailed summary of Heat Source, please refer to the Heat Source User's
Manual (Boyd and Kasper, 2002).
e Hydraulic conductivity is a measure of porosity that relates velocity and hydraulic gradient in Darcy's Law.
s Sediment depth is the thickness of alluvium underlying the stream channel.
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Jefferson County, WA
5.2 Calibration Methods
General Notes:
1. It is apparent that cloudiness (measured in Port Angeles) is not correct for several
days. These data were not changed, however.
2. Data indicate that air temperatures significantly vary within the study areas,
particularly in forest canopy compared to open areas.
3. Ungaged flows are estimated (watershed area weighted average) and checked against
measured instantaneous data. This method is a crude estimate, particularly in the case
of inter- stream water transfers (diversion from Little Quilcene to Howe Creek,
transfers of from Penny Creek to the fish hatchery, diversions and agriculture returns,
ponds or reservoirs, etc.).
4. The small streams (Chimacum, East Chimacum and Tarboo) are difficult to
distinguish in the LiDAR data and may not be positioned exactly.
5.2.1 Little Quilcene River
The Little Quilcene River was a relatively easy model to calibrate, largely because it has
a large flow rate and is well characterized in the LiDAR data. Calibration followed
standard methods and produced fairly accurate RMSE values of 0.65 - 0.74 °C.
Calibration Notes:
1. Initially too hot and variable
2. Set Overhanging Vegetation Density to 95%
3. Set Sediment Depth to 0.5 m
4. Reduced Thermal Radiation (slightly) from Vegetation to 95% of Potential
5. Increased Evaporation Coefficients a and b to 0.0000000025
6. Manning's n of 0.15 is used to calibrate to measured wetted depth
5.2.2 Big Quilcene River
The Big Quilcene River was difficult to warm to the measured values. Overhanging
vegetation density was reduced in some areas to promote heating. Evaporation was also
reduced to promote heating. Calibration followed standard methods and produced fairly
accurate RMSE values of 0.56 - 0.96 °C.
Calibration Notes:
1. Initially too cold
2. Set Overhanging Vegetation Density to 25 -100%
3. Set Sediment Depth to 0.5 m and Added Constant 1 °C to Streambed
4. Thermal Radiation from Vegetation set to 100% of Potential
5. Decreased Evaporation Coefficients a and b to 0.000000001
6. Manning's n of 0.10 is used to calibrate to measured wetted depth
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5.2.3 Tarboo Creek
Tarboo Creek is a very low flow stream that proved challenging to simulate. Flow
routing initially tended to underestimate stream depth and over estimate flow velocity.
The stream is very sensitive to shading patterns and thermal radiation from the
atmosphere and vegetation. Emergent and overhanging vegetation sampled from LiDAR
provides most of the current shading in the low gradient pasture /meadows portions.
Despite these challenges, good model accuracies were achieved with RMSE of 0.77 -
0.82 °C.
Calibration Notes:
1. Initially too hot
2. Set Overhanging Vegetation Density to 90 -100%
3. Reduced Sediment Depth to 0.25 m
4. Reduced Thermal Radiation from Vegetation to 35% of Potential
5. Increased Evaporation Coefficients a and b to 0.000000002
6. A constant Manning's n of 0.35 is used to calibrate to measured wetted depth
7. Included withdrawal and accretion volumes visible in flow measurements
8. Assumed accretion flows return at same temperature as stream
5.2.4 Chimacum Creek
Chimacum Creek is a long low flow stream that traverse several pastures /meadows, and
infrequently through short distances of mixed canopy riparian areas. The model is
extremely difficult to calibrate. In particular, data indicate that areas of the stream have
virtually no diurnal profile, suggesting that accretion flows are dominate over surface
heat energy exchange. The stream resembles a wetland without a clearly defined channel
in some upper sections. In these areas, emergent vegetation is an important component of
the heat energy processes via wind attenuation. The overall calibration is poor, with
RMSE statistics in ranging from 0.87 - 1.80 °C. In particular, early season accuracies are
poor (June and early July).
Calibration Notes:
1. Initially too hot and variable
2. Set Overhanging Vegetation Density to 60 -100%
3. Set Sediment Depth to 0.5 m
4. Reduced Thermal Radiation (slightly) from Vegetation to 95% of Potential
5. Reduced Evaporation Coefficients a and b to 0.000000001
6. Manning's n of 0.25 -0.50 are used to calibrate to measured wetted depth
5.2.5 East Chimacum Creek
Calibration of East Chimacum Creek followed similar procedures as those used for
Chimacum Creek. It was difficult to maintain cool temperatures in the stream without
increasing emergent/overhanging vegetation density and reducing thermal radiation from
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Jefferson County, WA
vegetation. Hydraulics are calibrated to match measured wetted depth data. The overall
calibration is poor, with RMSE statistics in ranging from 1.10- 1.93°C. In particular, early
season accuracies are poor (June and early July).
Calibration Notes:
1. Initially too hot and variable
2. Set Overhanging Vegetation Density to 65 -95%
3. Set Sediment Depth to 0.25 m
4. Reduced Thermal Radiation from Vegetation to 25% of Potential
5. Used Default Evaporation Coefficients a and b
6. Manning's n of 0.50 is used to calibrate to measured wetted depth
5.3 Validation Statistics
Table 18. Model Validation Statistics
Root Mean Square Correlation
Error Coefficient
Drainage Site RMSE R2
Little Quilcene River
PGST LQ1.70
0.74 °C
0.89
PGST L 1.45
0.65 °C
0.86
Big Quilcene River
PGST NFH
0.65 °C
0.92
PGST B M
0.56 °C
0.91
PGST B L
0.96 °C
0.90
Tarboo Creek
JCCD TB2.45
0.85 °C
0.82
JCCD TB0.90
0.83 °C
0.77
Chimacum Creek
JCCD CH 9.0
0.90 °C
0.63
JCCD CH 7.0
0.870C
0.78
JCCD CH 6.7
1.01 °C
0.59
JCCD CH 6.5
1.07 °C
0.67
JCCD CH 6.1
1.13 °C
0.64
JCCD CH 5.3
1.85 °C
0.47
JCCD CH 3.9
1.79 °C
0.62
JCCD CH 1.1
1.22 °C
0.66
JCCD CH 0.1
1.80 °C
0.67
East Chimacum Creek
JCCD ECH 3.3
1.100C
0.70
JCCD ECH 2.8
1.18 °C
0.69
JCCD ECH 1.2
1.58 °C
0.65
JCCD ECH 1.0 1
1.79 °C
0.61
JCCD ECH 0.1 1
1.93 °C
0.70
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5.3.1 Little Quilcene River
Figure 79. Little Ouilcene Validation Statistics
29
29
27
PGST LQ1.7 RKM Z.90 —Measured
27 - -PGST
LQCR RKM 1.45
— Measured
25
— Simulated Stream
25
— Simulated Stream
623
- -- Simulated Sediment
623
Simulated Sediment
X21
X21
019
d 19
CL E 17
m 17
E 15
E 15
113
y 13
11
R2 =0.89
11
R2 =0.86
9
RMSE= 0.74 °C
9
RMSE = 0.65 °C
7
7
C
7
c c 3> 5 w rn a) cm n m a a
7 7 7 7 7 7 y m m N
c
7
c c > >> 5 a
7 3
w w w a a a a a
7 7 7 7 m d m m
N�
N N r N N M O 1� N M n N N
N N `" N N M
O N M ^ r N N
y
K
4
nj
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
21
19
617
v
(� 15
i
C13
F-
E11
v� 9
7
5�
0
r
Figure 80. Little Quilcene Longitudinal Profiles Compared to TIR Data
I I I I I I I I I
I I I I I I I I I
I I I I 1 I I I
I I I I
Pot
I I
I, .....
I I � I I• I
I I ...... I I
�I I I I I I
I I I i
1 I I 1 I I I I I
1 I I 1 I I i I I
J _ _ _ _ J _ _ _ _ _I_ _ _ _ _ L _ _ _ _ L
I I I 1 I I I I I
I I I I I I I I I
I I I I I I I I 1
1 I I I I I
I I i I I I I I I
I I I 1 IL-
O> O r- CO to CO N O
Stream km
— 7/29/04 3:00
-- 7/29/04 6:00
7/29/04 9:00
— 7/29/04 12:00
— 7/29/04 15:00
- 7/29/04 18:00
— 7/29/04 21:00
■
■
• Continuous
Data
•
. TIR - 7/29 14:30
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
5.3.2 Big Quilcene River
Prepared by Watershed Sciences Page 125
Figure
81. Big Quilcene Validation Statistics
21
R2 =0.92
21
R2 =0.91
PGST BQM RKM 4.41
PGST NFH RKM 5.08
19
RMSE = 0.65 °C
19
RMSE= 0.56 °C
t,17
v 17
m
1515
E13
E 13
�
H
E 11
Ell
I
LD
cc
H
in 9
9
— Measured
—Measured
7
Simulated Stream
7
- Simulated Stream
- - Simulated Sediment
Simulated Sediment
5
5
c
> >
w a a c
N N
> > ;
Q
� °(
N
N Cn
N N
fV
21
R2 =0.90
PGST BQL RKM 1.38
19
RMSE= 0.96 °C
17
L
15
E 13
Pr
�
9
E11
r,
6
9
�y
— Measured
7
Simulated Stream
Simulated Sediment
5
>
? ? Q
N r
N N
N
a
�� iOVI
PG"� FH
Sys
f �
° +Y
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
21
19
17
v
3 15
E13
m
E 11
9
7
5
Figure 82. Big Quilcene Longitudinal Profiles Compared to TIR Data
I I I I I I I
I I I I I I I
I I I I I I 1
I I I I I
I
- - - -- - -� - -- - -ti. - - -� -.r - --- +rte' - -�- - =-
I I I I I
I I I I I I I
I I I I I 1 I
I I I I I I I
I 1 I I I I I
I I I I I I I
I I I I I I 1
I I I I I I I
I I I I I I I
I I I I I I I
I I I I I I I
I I I I I I I
—7/29/04 0:00
—7/29/04 3:00
7/29/04 6:00
7/29/04 9:00
- - - --- 7/29/04 12:00
—7/29/04 15:00
7/29/04 18:00
—7/29/04 21:00
■
Continuous
' Data
• Sarr�leA FLIR
Co CO LO et M N O
Stream km
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Quileene and Chimacum Temperature Analysis Port Gamble SIKIallam Tribes
Jefferson County, WA
5.3.3 Tarboo Creek
Figure 83. Tarboo Creek Validation Statistics
25
25 -
—Measured
Measured
23
-
I
23 -
Simulated Stream
Simulated Stream
21
-
21 -
Simulated Sediment
Simulated Sediment
a 17
-
all 7 1 -
I
8.15
0
cL 15
E
E
913
X13
E
E
X11
j
I
9
R2=0.77
7-
JCCD TB2.4 RKM 5.75 R2=0.82
7-
JCCD TB0.9 RKM 1.60 RMSE = 0.83 °C
RMS E=2.85,0,.
5
5
,
3 -5 75 rn m > 0 M M M CL M
C
a C 3
M a CL a a
a
C�
C9
aN arn
N 6 6
N N
N N I'- Ob
C11
N 0)
CM CIJ
N C6 .L 4
- CIJ CN
pp
ii
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
23
21
— 19
v
0
17
w
L° 15
m
CL
E 13
E 11
E'
v) 9
7
5
Figure 84. Tarboo Creek Longitudinal Profiles Compared to TIR Data
I I I I I 1 I
I I I I I I I
----- +----- + - - - -- - - - -- -- - - - - - - - - - - - - - - - -
I 1 I I I I I
I I I I I I I
I I I I I I I
I I 1 I I I
I I I I I S
I I I
I I I I
1 I t I I I
I I I I I 1 I
I I I I I I I
I I I I I I I
1 I I I I I I
I
1 I I I 1 I I
1 I 1 I I I I
I I I I I I I
- - - - - - - - - - - - - - - - - '� - - - - - -- - - - - - -1 ------ 1------ I------
I I 1 I 1 I I
I I I I I I I
I I I 1 1 I I
00 1� (fl d M N r- O
Stream km
— 7/29/04 0:00
— 7/29/04 3:00
7/29/04 6:00
7/29/04 9:00
— 7/29/04 12:00
— 7/29/04 15:00
7/29/04 18:00
— 7/29/04 21:00
a
•
l Continuous
I( Data
• Sampled FUR
Prepared by Watershed Sciences ��� Page 128
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
5.3.4 Chimacum Creek
Prepared by Watershed Sciences Page 129
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 86. Chimacum Creek Validation Statistics (a
Prepared by Watershed Sciences Page 130
25
25
— Measured
— Measured
23
23
- Simulated Stream
Simulated Stream
21
21
�j
Simulated Sediment
Simulated Sediment
19
19
L
17
17
E15
15
13
13
E
E
11
11
9
R2 =0.63
co
9
R2 =0.78
RMSE= 0.90 °C
RMSE = 0.87 °C
7
7
JCCD
CH9.0
RKM 1&45
JCCD
CH7.0
RKM 1290
5
5 .............
>
>
>
> > m
C
>
>
>
> > m
m
?
7
N
Q Q G?
T
7
%
N
Q Q m
cn
N
N
N t0
N
N 00
r
N
0) N to
N
25
25
— Measured
—Measured
23
23
Simulated Stream
-- Simulated Stream
21
21
V
- -- - Simulated Sediment
v
- -- Simulated Sediment
19
19
17
L
17
15
E
15
E
1�
13
F!-
13
W
A
11
11
vi
9
R2 =0.59
0)
9
RZ =0.67
RMSE= 1.01 °C
RMSE= 1.07 °C
7
7
JCCD
CH6.7
RKM 12.60
JCCD
CH6 5
RKM 1205
5
5
7
>
>
>
3 j m CL
CL
67
7
CL
7 7 N
CL
N
N�
Q Q T
T
?
7
N
Q 4
N
r
N
t0
N
O
N
N
N
01 CO <O
N
N
Prepared by Watershed Sciences Page 130
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 87. Chimacum Creek Validation Statistics (b
Prepared by Watershed Sciences Page 131
25
25-
Measured
Measured
23 -
23 -
Simulated Stream
Simulated Stream
21 -
21 -
--- Simulated Sediment
Simulated Sediment
19 -
19-
-a
17 -
B
17 -
15-
CL
15-
E
E
0
13 -
0
1.-
13-
E
E
9 -
R2 =0.64 .6�4
U)
9-
R2=0.47
7
M _1
RMSE= 1.13 °C
7-
RMSE= 1.85 °C
5 I.JCqCq
CH6 I RK
11 .3
CH5
5 1 JC19R , 3 MR
10.3 , 11
75
5 0) C) CL
06
(D
C r-
rn 0) CL
CL
co
CD
(N
(N 0) M (0
a
Cv
co
(N
CM CD
04
0
04
25 -
25-
Measured
Measured
23 -
23 -
Simulated Stream
Simulated Stream
21
21-
imulated Sediment
Simulated Sediment
19 -
19-
17 -
17-
125
cL
15 -
I
Y
cL
15-
E
E
13 -
13 -
E
E
9 -
R2 =0.62
Go
9 -
R2=0.66
7
RMSE = 1.79 °C
7
RMSE= 1.22 °C
5 ..JM
eH,3j9 ,R"
7.78,
5 JCqQ CHI ,1 R"
-
Z 78, 1 1
.. ... .. ........
r-
75
75 05 0)
>
> 0) 0 CL
CL
C,
CD 0?
00
N
N
Q
N
N CD
('N A
N
04
25
Measured
23 -
Simulated Stream
21 -
Simulated Sediment
19-
17 -
E
S. 15 -
E
13 -
E
11
9
R2=0.67
RMSE
= 1.80 °C
7 -
JCCD CHO " 1
RKM 0.88
5 ......... ... . ..
. ........
C
75
75
0) 0) CL CL
CM
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Quilcene and Chimacum Temperature Analysis Port Gamble ,S,'Klallam Tribes
Jefferson County, WA
23
21
19
U
17
15
CL
E
13
E
� 11
9
7
Figure 88. Chimacum Creek Longitudinal Profiles Compared to TIR Data
I I , ; v-
- - - - -- - - - - - -- - - ; - - - - -r - - - - --
■
- - - - 4 - - - - - L- - - - - - - - - - -
5
00 (o cr N O Co Co d' N O
r r r r r
Stream km
—7/29/04 0:00
—7/29/04 3:00
7/29/04 6:00
7/29/04 9:00
— 7/29/0412:00
—7/29/04 15:00
7/29/0418:00
— 7/29/04 21:00
w
■ Continuous
Data
■
• Sampled FUR
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
5.3.5 East Chimacum Creek
89. East Chimacum Creek Validation Statistics (a
19
17
E16
13
F11
E
A
9
7
JCCD ECH3.3 RKM 5.68
Measured i'W
- Simulated Stream R2 =0.70
- Simulated Sediment RMSE= 1.10 °C
5
N
fb
N
5
-5 -5 N
M p f�
I � rn
M
Q
Q m � m da � a @a
CmI
N en ^ N N
An,
17
X15
ED
0
13
r11
b 9
(A
7
JCCD ECH2.8 RKM 4.00
Measured
- Simulated Stream R2 =0,69
-- Simulated Sediment RMSE= 1.18 °C
5
c c c > >>> rn rn w w rn a s c� a
C9 ab
LO
N N N N M r N N
21
19
617
15
c.13
E
m
11
y 9
7
5
N C-4 CO tr N N f� d N M ;t N N
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 90. East Chimacum Creek Validation Statistics (b
19
21
JCCD EC 0 KM 1.25
JCCD ECH 1 RKM 0.10
17
+
19
915
17
v
£ 13
I {{
15
f yy
113
j�
E
£
H9
— Measured
9
— Measured
f "
7
Simulated Stream
R2 =0.61
Simulated Stream
R2 =0.70
- Simulated Sediment
RMSE= 1.79 °C
7
- Simulated Sediment
RMSE= 1.93 °C
5
5
c c c > > >> rn
7 7 a 7
rn rn rn a a a a
> > q m
c
7
c c > >> w w
> > 7 7
a rn w a a a a
7 7 3 m 0) m 0)
N N N C4
n N
4
N� N N
M N N
N N
Figure 91. East Chimacum Creek Longitudinal Profiles Compared to TIR Data
23
%31■
19
617
9-
120
15
E
H 13
E
N01
11
9
7
L _ _ _ _
I I I I 1 I I I I ii
I I I I I I I I I
I I I I I t I I I
I I 1 1 1 I I
I i I I I I I
I I I I I I I I
I I I I I I I
I I I I I
I I • I L
I 1 I ■ I '1 If '" I.
I I I r 1 1 I
I I I I i I I I I
I I I 1 I I I I I
I I 1 1 I 1 I I I
I I I I I I I I I
I I I I I I I I I
I I I I I I I I I
_ _ _ _ _ _I _ _ _ _ _I_
I I I I I I I I 1
I I I I I I I I I
I I I I I I I I I
5
0
07 00 P. w WA "t M N P O
Stream km
— 7/29/04 0:00
— 7/29/04 3:00
7/29/04 6:00
7/29/04 9:00
— 7/29/04 12:00
— 7/29/04 15:00
7/29/04 18:00
— 7/29/04 21:00
■
i
r l Continuous
I( Data
■
• Sampled FUR
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Jefferson County, WA
5.4 WRIA 17 Stream Temperature Model Scenarios
Assumptions
Scenario 1— Development Trend
All pending water right applications and proposed rural development water
reserves are fully appropriated. The proposed rural development water
1, 2, 3, 4, 5, 6
reserves include additional withdrawals of: 0.33 cfs in Big Quilcene, 0.98
cfs in Little Quilcene, 2.36 cfs in Chimacum, and 0.06 cfs in Tarboo
subbasins.
Scenario 2 — Modified Development Trend
All proposed rural development water reserves are fully appropriated, but
no additional pending water right applications are appropriated. The
2,3
proposed rural development water reserves include additional withdrawals
of. 0.310 cfs in Big Quilcene, 0.057 cfs in Little Quilcene, 0.029 cfs in
Chimacum, and 0.019 cfs in Tarboo subbasins.
Scenario 3 — Restore 10% of withdrawal flows
No additional water withdrawal over current conditions, with restoration of
10% of current withdrawal volumes. This includes restoration of 2.83 cfs
1, 2, 3, 4, 5, 6
in Big Quilcene, 1.40 cfs in Little Quilcene, 1.16 cfs in Chimacum, and 0.37
cfs in Tarboo subbasins.
Scenario 4 — Restore 50% of withdrawal flows
No additional water withdrawal over current conditions, with restoration of
50% of current withdrawal volumes. This includes restoration of. 14.17 cfs
1, 2, 3, 4, 5, 6
in Big Quilcene, 7.01 cfs in Little Quilcene, 5.81 cfs in Chimacum, and 1.83
cfs in Tarboo subbasins.
Scenario 5 — Restore riparian vegetation
No additional water withdrawal or flow restoration over current conditions,
with extensive riparian forest cover restoration. In addition, this includes
7,8
reduction of active channel widths in the lower Big Quilcene River to levels
approaching a condition more similar to historical, circa 1870.
Scenario 6 — Reduce flows 10%
Reduce average daily flows by 10% based upon 2004 Flow Data
Scenario 7 — Reduce flows 30%
Reduce average daily flows by 30% based upon 2004 Flow Data
Scenario 8 — Increase flows 10%
Increase average daily flows by 10% based upon 2004 Flow Data
Scenario 9 — Combination of 5 and 8
7,8
Prepared by Watershed Sciences Page 135
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Scenario Assumptions
1. Information on groundwater rights, claims, and exempt wells, as well as surface
water rights and claims were derived from the WRIA 17 Stage 1 Technical
Analysis (Golder and Associates, October 2000). Information on groundwater
and surface water use applications were derived from the WRIA 17 Subbasin
Data Summary Sheets (Cascadia Consulting Group, May 2004). Ian Jablonski
(City of Port Townsend) and Bill Graham (JeffCo PUD) clarified inconsistencies
reported in the Stage 1 Technical Analysis for withdrawals in the Big Quilcene
River and Chimacum Creek subbasins, respectively.
2. All groundwater rights and claims were assumed to be in full use. Average
annual rates were used, not the higher instantaneous limits since long -term
impacts from groundwater pumping were presumed to be more important.
3. All exempt wells were assumed to be in full use at a rate of 350 gallons per day.
4. Golder and Associates (2000) reported water rights, claims, and exempt wells for
the larger Dabob - Thorndyke planning area, only a portion of which includes the
Tarboo Creek subbasin. Based on a review of GIS exhibits, we assumed that one-
third of all Dabob - Thorndyke groundwater rights, claims, and exempt wells were
in the Tarboo Creek subbasin. Similarly, we assumed that two- thirds of all
Dabob- Thorndyke surface water rights and claims were in the Tarboo Creek
subbasin.
5. We lacked detailed information on hydraulic continuity of groundwater
withdrawal for each stream. For all groundwater withdrawals (rights, claims, and
exempt wells), we used 50% of reported volumes. This assumes that either half
of withdrawn volumes were in hydraulic continuity with streams and fully
consumed with no return flow to streams. Alternatively, this assumes that half of
withdrawn volumes return to streams via septic system recharge of shallow
groundwater reserves.
6. For the Chimacum subbasin and the JeffCo PUD- operated Quimper Water
System, we did not account for out -of -basin water transfers to Indian and
Marrowstone Islands since current reported transfer volumes amount to only 0.07
cfs, or 1.6% of total groundwater withdrawal for the entire Chimacum subbasin.
7. Reductions in channel width in the Big Quilcene River to levels approaching
historical conditions, circa 1870, were performed only for channels that currently
exceed these widths.
8. Includes restoration of 15 m -wide buffers with tree heights of at least 25 m, where
current conditions are less than these thresholds. Data from historical conditions,
circa 1870, demonstrate that riparian vegetation in excess of 25 meter height were
predominant. However, the modeled vegetation scenario assumes continuous
riparian vegetation without disturbance and with uniform physical attributes,
which likely overstates the ability of vegetation to shade the stream.
Prepared by Watershed Sciences Page 136
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
5.4.1 Little Quilcene River
Table 19. Little Quilcene River - Maximum Temperatures per Model Run
STATION ID
SITE NAME
Model
Run
Tem erature C
Absolute
Max
7-Day Ave. Max
July
Aug
Sept
JCCD_LQ /1.7
Little Quilcene, RM 1.7
Measured
18.4
17.4
16.9
14.7
Simulated
18.7
17.6
17.4
15.4
Scenario 1
18.7
17.8
17.7
15.6
Scenario2
18.5
17.7
17.4
15.4
Scenario3
18.1
17.4
17.1
15.1
Scenario4
17.1
16.5
16.2
14.4
Scenario5
16.0
15.1
14.8
14.1
Scenario6
18.7
17.8
17.6
15.5
Scenario?
19.2
18.2
18.1
16.0
Scenario8
18.2
17.5
17.2
15.3
Scenario9
16.1
15.2
15.0
14.4
PGST_LQCR
Little Quilcene at
Center Rd
Measured
19.4
18.4
18.1
15.5
Simulated
19.4
17.9
17.7
15.9
Scenario 1
19.0
18.1
17.9
16.0
Scenario2
18.8
17.9
17.8
15.9
Scenario3
18.5
17.7
17.5
15.6
Scenario4
17.6
17.0
16.7
14.9
Scenario5
16.2
15.7
15.2
14.5
Scenario6
18.9
18.0
17.9
16.0
Scenario?
19.3
18.3
18.3
16.3
Scenario8
18.6
17.8
17.6
15.7
Scenario9
16.3
15.8
15.4
14.8
Scenario 1- Development Trend o
Scenario 2 - Modified Development Trend Scenario 6 - Reduce flows 10 /o
Scenario 3 - Restore 10% of withdrawal flows Scenario - Reduce flows 1 /o
8
Scenario 8
Scenario 4 - Restore 50% of withdrawal flows -Increase flows 10%
Scenario 5 - Restore riparian vegetation Scenario 9 - Combination of 5 and 8
Prepared by Watershed Sciences Page 137
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Table 20. Little Quilcene River - Temperature Changes per Model Run
Site - Scenario
Simulated Temperature Change C
Absolute
Max
7-Day Ave. Max
July
August
September
JCCD L /1.7 - Scenariol
0.0
0.2
0.2
0.2
PGST L CR - Scenariol
-0.4
0.2
0.2
0.2
JCCD L /1.7 - Scenario2
-0.2
0.0
0.0
0.0
PGST L CR - Scenario2
-0.6
0.0
0.0
0.0
JCCD L /1.7 - Scenario3
-0.6
-0.3
-0.3
-0.3
PGST L CR - Scenario3
-0.9
-0.2
-0.2
-0.2
JCCD L /1.7 - Scenario4
-1.6
-1.1
-1.2
-1.0
PGST L CR - Scenario4
-1.8
-0.9
-1.1
-0.9
JCCD L /1.7 - Scenario5
-2.7
-2.5
-2.6
-1.4
PGST L CR - Scenario5
-3.2
-2.2
-2.5
-1.3
JCCD L /1.7 - Scenario6
0.0
0.2
0.2
0.1
PGST L CR - Scenario6
-0.5
0.1
0.1
0.2
JCCD L /1.7 - Scenario7
0.5
0.5
0.7
0.5
PGST L CR - Scenario?
-0.1
0.4
0.5
0.5
JCCD L /1.7 - Scenario8
-0.5
-0.2
-0.2
-0.2
PGST L CR - Scenario8
-0.8
-0.1
-0.1
-0.1
JCCD L /1.7 - Scenario9
-2.7
-2.5
-2.6
-1.4
PGST L CR - Scenario9
-3.2
-2.2
-2.5
-1.3
Scenario 1- Development Trend Scenario 6 -Reduce flows 10%
Scenario 2 - Modified Development Trend
Scenario 3 - Restore 10% of withdrawal flows Scenario 7 - Reduce flows %
10%
Scenario 4 - Restore 50% of withdrawal flows Scenario 8 - Increase flows 5 a nd 8
a
Scenario 5 - Restore riparian vegetation Scenario 9 - Combination of 5
Prepared by Watershed Sciences Page 138
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 92. Little Quilcene, Model Scenarios — Resulting Temperature Changes
■ July ■ August a September
JCCD LQ/1.7 - Scenariol
PGST LQCR - Scenariol
JCCD LQ11.7 - Scenario2
PGST LQCR - Scenario2
JCCD LQ/1.7 - Scenario3
PGST LQCR - Scenario3
JCCD LQ11.7 - Scenario4
PGST LQCR - Scenario4
JCCD LQ/1.7 - Scenario5
PGST —LQCR - Scenario5
JCCD LQ/1.7 - Scenario6
PGST LQCR - Scenario6
JCCD LQ/1.7 - Scenario7
PGST LQCR - Seenario7
JCCD LQ11.7 - Scenario8
PGST LQCR - Scenario8
JCCD LQ/1.7 - Scenario9
PGST LQCR - Scenario9
-3 -2 -1 0 1 2 3
Resulting Change in 7 -Day Maximum Moving
Average of Daily Maximums rC)
Scenario 1— Development Trend o
Scenario 2 — Modified Development Trend Scenario 6 —Reduce flows 10/0
Scenario 3 — Restore 10% of withdrawal flows Scenario 7 — Reduce flows 30 /o
Scenario 4 — Restore 50% of withdrawal flows Scenario 8 — Increase flows 10%
Scenario 5 — Restore riparian vegetation Scenario 9 — Combination of S and 8
Prepared by Watershed Sciences Page 139
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
93. Little
Model Scenarios
Measured
— Simulated
— Scenariol
— Scenado2
— Scenario3
-- Scenario4
Scenado5
- Scenario6
— Scenario7
— Scenar1o8
— Scenario9
Thermal Limits
16 °C
Rearing, Migration &
Spawning
All Study Streams
All Year
13 °C
Summer Chum
Spawning &
Incubation
September 15 to July 1
Model Scenarios — 7
IV
18
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9
IV
18
w
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Max Moving Ave of the Daily Max
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I
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i I I I I I I I I
1 I I I I I I I I I I
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2004
Scenario 1– Development Trend Scenario 6 – Reduce flows 10%
Scenario 2 – Modified Development Trend
Scenario 3 – Restore 10% of withdrawal flows Scenario 7 – Reduce flows 30%
Scenario 4 – Restore 50% of withdrawal flows Scenario 8 – Increase flows 10%
Scenario 5 – Restore riparian vegetation Scenario 9 – Combination of 5 and 8
Prepared by Watershed Sciences � � � Page 140
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
94. Little Vuilcene Model Scenarios — Lon2itudinal Yrotiles for Model scenarios
21
V
20
a
0
0
i' 19
0
N
a; 18
N
A
7
17
w
Q
16
c
'a
15
c
0
J
14
Thermal Limits
16 °C Rearing, Migration & Spawning
All Study Streams, All Year
13 °C Summer Chum Spawning & Incubation
September 15 to July 1
a? Oq Cq OR Oq OR CR OR Cq Oq
rn ad i. W W) v ai cm o
2004
Model Scenarios
— Measured
— Simulated
— Scenariol
— Scenario2
— Scenario3
--Scenario4
- Scenario5
---- Scenado6
— Scenario7
— Scenado8
— Scenado9
Scenario 1- Development Trend o
Scenario 2 - Modified Development Trend Scenario 6 - Reduce flows 10/0
Scenario 3 - Restore 10% of withdrawal flows Scenario 7 - Reduce flows /o
1
Scenario 4 - Restore 50% of withdrawal flows Scenario 8 - Increase flows 10%
Scenario 5 - Restore riparian vegetation Scenario 9 - Combination of 5 and 8
Prepared by Watershed Sciences Page 141
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
5.4.2 Big Quilcene River
Table 21. Big Quilcene River - Maximum Temperatures per Model Run
STATION ID
SITE NAME
Model
Run
Tem erature °C
Absolute
Max
7- ay Ave. Max
July
Aug
Sept
PGST_NFH
Big Quilcene @ Hatchery
Measured
17.4
16.6
16.9
14.5
Simulated
17.5
15.7
16.7
14.6
Scenario 1
17.6
15.7
16.7
14.6
Scenario2
17.6
15.7
16.7
14.6
Scenario3
17.2
15.5
16.4
14.4
Scenario4
16.2
15.0
15.6
13.7
Scenario5
14.4
13.8
14.0
12.4
Scenario6
18.5
16.1
17.4
15.2
Scenario7
22.4
17.5
20.1
18.0
Scenario8
16.9
15.4
16.2
14.2
Scenario9
14.2
13.8
13.9
12.3
PGST_BQM
Big Quilcene, Middle
Measured
16.8
16.2
16.4
14.1
Simulated
17.6
15.6
16.6
14.7
Scenario l
17.7
15.6
16.7
14.7
Scenario2
17.7
15.6
16.7
14.7
Scenario3
17.3
15.5
16.4
14.5
Scenario4
16.4
15.2
15.8
13.9
Scenario5
14.3
13.7
13.8
12.3
Scenario6
19.4
15.9
17.4
15.9
Scenario7
18.4
16.3
17.4
15.4
Scenario8
16.8
15.3
16.1
14.2
Scenario9
14.2
13.7
13.7
12.2
PGST_BQL
Big Quilcene, Lower
Measured
18.6
17.9
18.0
15.5
Simulated
19.5
17.3
18.4
15.8
Scenario 1
19.5
17.4
18.4 1
15.9
Scenario2
19.5
17.4
18.4
15.9
Scenario3
19.1
17.2
18.1
15.6
Scenario4
18.1
16.5
17.3
15.0
Scenario5
15.0
14.3
14.3
12.8
Scenario6
20.9
17.8
19.1
16.6
Scenario7
21.4
18.6
19.9
17.0
Scenario8
18.6
16.9
17.7
15.4
Scenario9
14.8
14.2
14.2
12.7
Prepared by Watershed Sciences ��� Page 142
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Table 22. Big Quilcene River - Temperature Changes per Model Run
Site - Scenario
Simulated
Tem erature Change °C
Absolute
Max
7-Day Ave. Max
July
August
September
PGST NFH - Scenariol
0.1
0.0
0.0
0.1
PGST B M - Scenariol
0.1
0.0
0.0
0.0
PGST B L - Scenariol
0.0
0.0
0.0
0.0
PGST NFH - Scenario2
0.1
0.0
0.0
0.1
PGST B M - Scenario2
0.1
0.0
0.0
0.0
PGST B L - Scenario2
0.0
0.0
0.0
0.0
PGST NFH - Scenario3
-0.3
-0.2
-0.3
-0.2
PGST B M - Scenario3
-0.3
-0.1
-0.2
-0.2
PGST B L - Scenario3
-0.4
-0.2
-0.3
-0.2
PGST NFH - Scenario4
-1.3
-0.7
-1.1
-0.9
PGST B M - Scenario4
-1.2
-0.5
-0.8
-0.7
PGST B L - Scenario4
-1.4
-0.8
-1.1
-0.8
PGST NFH - Scenario5
-3.1
-1.8
-2.7
-2.2
PGST B M - Scenario5
-3.3
-1.9
-2.8
-2.4
PGST B L - Scenario5
-4.5
-3.0
-4.0
-3.0
PGST NFH - Scenario6
1.0
0.4
0.7
0.6
PGST B M - Scenario6
1.8
0.3
0.8
1.2
PGST B L - Scenario6
1.4
0.4
0.8
0.8
PGST NFH - Scenario7
4.9
1.8
3.4
3.4
PGST B M - Scenario7
0.8
0.7
0.7
0.7
PGST B L - Scenario7
1.9
1.3
1.5
1.2
PGST NFH - Scenario8
-0.6
-0.3
-0.5
-0.4
PGST B M - Scenario8
-0.8
-0.3
-0.6
-0.5
PGST B L - Scenario8
-0.9
-0.4
-0.6
-0.5
PGST NFH - Scenario9
-3.3
-1.9
-2.8
-2.3
PGST B M - Scenario9
-3.4
-1.9
-2.9
1 -2.4
PGST B L - Scenario9
-4.7
-3.1
-4.2
-3.2
Scenario 1- Development Trend Scenario 6 - Reduce flows 10%
Scenario 2 - Modified Development Trend o
8 1 /o
Scenario 3 - Restore 10% of withdrawal flows Scenario - Reduce flows
Scenario 4 - Restore 50% of withdrawal flows Scenario 8 - Increase flows 10%
Scenario 5 - Restore riparian vegetation Scenario 9 - Combination of 5 and 8
Prepared by Watershed Sciences Page 143
I
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 95. Big Quilcene Model Scenarios — Resulting Temperature Changes
■ July ■ August r September
PGST NFH - Scenariol
PGST BQM - Scenariol
PGST BQL - Scenariol
PGST NFH - Scenario2
PGST - BQM - Scenario2
I I 1
PGST BQL - Scenario2
PGST NFH - Scenario3
PGST BQM - ScenadO
PGST-BQL - Scenado3
I I I I I I I I
PGST _ NFH - Scenario4
I I I I I I I
PGST BQM - Scenario4
PGST _ BQL - Scenario4
I I I I I I I
PGST NFH - Scenario5
PGST BQM - Scenario5
PGST BQL - Scenario5
PGST NFH - Scenario6
PGST BQM - Scenario6
PGST BQL - Scenado6
PGST NFH - Scenario7
PGST _ BQM - Scenario7
I I I I I I I I
PGST BQL - Scenario7
PGST—NFH - Scenario8
PGST BQM - Scenario8
PGST _ BQL - Scenario8
I I I I I I I I
PGST NFH - Scenario9
PGST BQM - Scenario9
- I I I I I I
PGST-BQL - Scenario9
I 1 I I
-5 -4 -3 -2 -1 0 1 2 3 4 5
Resulting Change in 7 -Day Maximum Moving
Average of Daily Maximums ( *C)
Scenario 1— Development Trend Scenario 6 —Reduce flows 10%
Scenario 2 — Modified Development Trend o
Scenario 3 — Restore 10% of withdrawal flows Scenario 7 — Reduce flows 30 /o
Scenario 4 —Restore 50% of withdrawal flows Scenario 8— Increase flows 10%
Scenario 5 — Restore riparian vegetation Scenario 9 — Combination of 5 and 8
Prepared by Watershed Sciences Page 144
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 96. Big Quilcene Model Scenarios — 7 -Day Max Moving Ave of the Daily Max
Model Scenarios
—Measured
Simulated
Scenadol
Scenario2
Scenario3
Scenario4
Scenario5
-- - Scenario6
Scenario?
Scenario8
Scenado9
Thermal Limits
16 °C
Rearing, Migration &
Spawning
All Study Streams
All Year
13 °C
Summer Chum
Spawning &
Incubation
>tember 15 to July 1
21
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a 19
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Prepared by Watershed Sciences Page 145
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
20
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97. 13i2 Ouilcene Model Scenarios — Loni?itudim
Thermal Limits
16 °C Rearing, Migration & Spawning
All Study Streams, All Year
13 °C Summer Chum Spawning & Incubation
September 15 to July 1
Profiles for Model Scenarios
-- r - -r -- - -� - - -i -- - - -r -- r -.7 - - -r-
- - ! - - ! - -
-- - - -' --
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2004
Model Scenarios
— Measured
— Simulated
— Scenariol
— Scenario2
— ScenI
— ScenI
- ScenI
- - -- Scenario6
— Scenario7
— Scenario8
— Scenario9
Scenario 1– Development Trend Scenario 6 –Reduce flows 10%
Scenario 2 – Modified Development Trend o
Scenario 3 – Restore 10% of withdrawal flows Scenario 7 – Reduce flows 30 /o
Scenario 4 – Restore 50% of withdrawal flows Scenario 8 – Increase flows 10%
Scenario 5 – Restore riparian vegetation Scenario 9 – Combination of 5 and 8
Prepared by Watershed Sciences Page 146
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
5.4.3 Tarboo Creek
Table 23. Tarboo Creek - Maximum Temperatures per Model Run
STATION ID
SITE NAME
Model
Run
Tem erature °C
Absolute
Max
7-Day Ave. Max
July
Aug
Sept
JCCD_TB /2.6
Tarboo Creek, RM 2.6
Measured
16.2
16.2
15.8
14.6
Simulated
16.3
15.7
15.5
14.6
Scenario 1
16.3
15.7
15.5
14.7
Scenario2
16.2
15.7
15.5
14.7
Scenario3
16.0
15.5
15.3
1 14.5
Scenario4
15.5
15.0
14.8
14.0
Scenario5
16.2
15.7
15.4
14.3
Scenario6
16.3
15.7
15.5
14.7
Scenario?
16.3
15.8
15.6
14.7
Scenario8
16.2
15.7
15.5
14.6
Scenario9
16.2
15.7
15.4
14.3
JCCD_TB /0.9
Tarboo Creek, RM 0.9
Measured
17.4
16.8
16.5
15.5
Simulated
18.4
17.6
17.6
16.8
Scenario l
18.4
17.6
17.6
16.9
Scenario2
18.4
17.6
17.6
16.8
Scenario3
18.1
17.4
17.3
16.6
Scenario4
17.3
16.7
16.6
15.9
Scenario5
16.5
15.9
15.8
15.3
Scenario6
18.4
17.6
17.6
16.9
Scenario?
18.5
17.7
17.6
16.9
Scenario8
18.3
17.5
17.5
16.8
Scenario9
16.5
15.9
15.8
15.3
Scenario 1- Development Trend o
Scenario 2 - Modified Development Trend Scenario 6 - Reduce flows 10/0
Scenario 3 - Restore 10% of withdrawal flows Scenario 7 - Reduce flows /o
1
Scenario 4 - Restore 50% of withdrawal flows Scenario 8 - Increase flows 10%
Scenario 5 - Restore riparian vegetation Scenario 9 - Combination of 5 and 8
Prepared by Watershed Sciences Page 147
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Table 24. Tarboo Creek - Temperature Changes per Model Run
Site - Scenario
Simulated
Temperature Change C
Absolute
Max
7 Day Ave. Max
July
August
September
JCCD TB/2.6 - Scenariol
0.0
0.0
0.0
0.0
JCCD TB /0.9 - Scenario l.
0.0
0.0
0.0
0.0
JCCD TB /2.6 - Scenario2
-0.1
0.0
0.0
0.0
JCCD TB /0.9 - Scenario2
0.0
0.0
0.0
0.0
JCCD TB /2.6 - Scenario3
-0.3
-0.2
-0.2
-0.2
JCCD TB /0.9 - Scenario3
-0.3
-0.2
-0.2
-0.2
JCCD TB /2.6 - Scenario4
-0.8
-0.7
-0.7
-0.6
JCCD TB /0.9 - Scenario4
-1.1
-0.9
-1.0
-1.0
JCCD TB /2.6 - Scenario5
-0.1
0.0
0.0
-0.3
JCCD TB /0.9 - Scenario5
-1.9
-1.7
-1.8
-1.5
JCCD TB /2.6 - Scenario6
0.0
0.0
0.0
0.0
JCCD TB /0.9 - Scenario6
0.0
0.0
0.0
0.0
JCCD TB/2.6 - Scenario7
0.0
0.1
0.1
0.1
JCCD TB /0.9 - Scenario7
0.1
0.1
0.1
0.1
JCCD TB /2.6 - Scenario8
-0.1
0.0
0.0
0.0
JCCD TB /0.9 - Scenario8
-0.1
0.0
-0.1
-0.1
JCCD TB /2.6 - Scenario9
-0.1
0.0
-0.1
-0.4
JCCD TB /0.9 - Scenario9
-1.9
-1.7
-1.8
-1.6
Scenario 1- Development Trend Scenario 6 - Reduce flows 10%
Scenario 2 - Modified Development Trend o
Scenario 3 - Restore 10% of withdrawal flows Scenario 7 - Reduce flows 30 /o
Scenario 4 - Restore 50% of withdrawal flows Scenario 8 - Increase flows 10%
Scenario 5 - Restore riparian vegetation Scenario 9 - Combination of 5 and 8
Prepared by Watershed Sciences Page 148
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 98. Tarboo Creek Model Scenarios — Resulting Temperature Changes
■ July ■ August ■ September
JCCD TB/2.6 - Scenario1
JCCD TB /0.9 - Scenariol
JCCD TB/2.6 - Scenario2
JCCD—TB/0.9 - Scenario2
JCCD TB/2.6 - Scenario3
JCCD TB /0.9 - Scenario3
JCCD TB /2.6 - Scenario4
JCCD TB /0.9 - Scenario4
JCCD TB/2.6 - Scenario5
JCCD TB/0.9 - Scenario5
JCCD TB/2.6 - Scenario6
JCCD TB /0.9 - Scenario6
JCCD—TB/2.6 - Scenario7
JCCD TB /0.9 - Scenario7
JCCD TB /2.6 - Scenario8
JCCD TB /0.9 - Scenario8
JCCD TB/2.6 - Scenario9
JCCD TB /0.9 - Scenario9
-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0
Resulting Change in 7 -Day Maximum Moving
Average of Daily Maximums ( *C)
Scenario 1— Development Trend Scenario 6 — Reduce flows 10%
Scenario 2 — Modified Development Trend
Scenario 3 — Restore 10% of withdrawal flows Scenario 7 — Reduce flows 30 /o
Scenario 4 — Restore 50% of withdrawal flows Scenario 8 — Increase flows 10%
Scenario 5 — Restore riparian vegetation Scenario 9 — Combination of 5 and 8
Prepared by Watershed Sciences Page 149
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 99. Tarboo Creek Model Scenarios — 7 -Day Max Moving Ave of the Daily Max
Model Scenarios
Measured
—Simulated
— Scenariol
— Scenado2
— Scenario3
— Scenario4
- Scenarios
... -- _. Scenado6
— Scenado7
— Scenario8
— Scenado9
Thermal Limits
16 °C
Rearing, Migration &
Spawning
All Study Streams
All Year
13 °C
Summer Chum
Spawning &
Incubation
September 15 to July 1
18
T
w 17
0
m 16
Q 15
a
a
E 14
� E
E 1 13
2
E
12
o' 11
10
b N W CO
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i I I I I I I I I I I I I I I
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I I I I I I I I I I 1 1
I I I I I I I I I
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1 I I I I I I I I
1 I I I I I I I I
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I I I I I 1 I I I I I
I I I I I I I I I I
I I I 1 -- I - - - I - --
I I I I I I I 1 I I I I I
I I I I I I I I I I I I I I
--+--+--+--+-- -1 -------- i--- I--- I--- F-- F - - + -- -
I I I I I I I I I I I I I
t I I I I I I I I I I I I I
1 I I I I I I I I I I I I I
1 I I I I f I I I I I I 1
JGCD t2.4 KM .75
18
T
17
m 16
Q 15
E 14
M E
E1 13
E
12
11
10
M N \ M O V, N M 1' r N N
2004
I I I I I 1
I I I I I 1 I I I I I I I I I
I I I I I I I 1 I I I I 1
- -L -- -- - -� - -J - -- ----- I- - -I - -- -- L---- - - - - --
I I I 1 I I I I I I 1 1
1 I I
I I I I
41-
I - - I 1 I I I I I I I I I
I I I I I 11 1 I
I I I I I I I I I I 1 I I I
I I I I I I I I I I I I I I I
I t I I I I I I I I I I I I
�ni/n Tdr1 n dvu •ICn I I I I I I I I I I In
O N N ^ r N N ^MOS O N Ch N N
2004
Scenario 1– Development Trend o
Scenario 2 – Modified Development Trend Scenario 6 –Reduce flows 10/0
Scenario 3 – Restore 10% of withdrawal flows Scenario 7 – Reduce flows /o
Scenario 4 – Restore 50% of withdrawal flows Scenario –Increase flows 1 10%
9
Scenario 9
Scenario 5 – Restore riparian vegetation – Combination of 5 and 8
Prepared by Watershed Sciences Page 150
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 100. Tarboo Creek Model Scenarios — Longitudinal Profiles for Model Scenarios
20
V
19
CL
00
M 18
a
0
0
N
17
m 16
w
0
15
c
14
c
0
J
13
Thermal Limits
16 °C Rearing, Migration & Spawning
All Study Streams, All Year
13 °C Summer Chum Spawning & Incubation
September 15 to July 1
OR ao 0o Co aq CR OR w
I Co KO 19t M N 0
2004
Model Scenarios
— Measured
— Simulated
— Scenadol
— Scenario2
— Scenado3
— Scenado4
- - - - -- Scenario5
— Scenado6
— Scenario7
— Scenario8
— Scenado9
Scenario 1— Development Trend a
Scenario 2 — Modified Development Trend Scenario 6 —Reduce flows 10/0
Scenario 3 — Restore 10% of withdrawal flows Scenario 7 — Reduce flows /o
1
Scenario 4 — Restore 50% of withdrawal flows Scenario 8 — Increase flows 10%
Scenario 5 — Restore riparian vegetation Scenario 9 — Combination of 5 and 8
Prepared by Watershed Sciences Page 151
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
5.4.4 Chimacum Creek
Table 25. Chimacum Creek - Maximum Temperatures per Model Run
STATION ID
SITE NAME
Model
Run
Tem erature C
7 -Da Ave.
Max
Absolute
Max
July
Aug
Sept
JCCD CH/9.0
Chimacum Creek, RM 9.0
Measured
16.4
15.7
15.1
13.7
Chimacum Creek, RM 9.0
Simulated
16.6
16.2
15.6
14.5
Chimacum Creek, RM 9.0
Scenariol
16.9
16.5
15.8
14.9
Chimacum Creek, RM 9.0
Scenario2
16.7
16.2
15.6
14.5
Chimacum Creek, RM 9.0
Scenario3
16.4
15.9
15.3
14.4
Chimacum Creek, RM 9.0
Scenario4
15.7
15.3
14.7
13.9
Chimacum Creek, RM 9.0
Scenario5
16.6
16.1
15.5
14.5
Chimacum Creek, RM 9.0
Scenario6
16.7
16.2
15.6
14.6
Chimacum Creek, RM 9.0
Scenario?
16.9
16.4
15.8
14.7
Chimacum Creek, RM 9.0
Scenario8
16.6
16.1
15.5
14.5
Chimacum Creek, RM 9.0
Scenario9
16.6
16.1
15.5
14.5
JCCD CH/7.0
Chimacum Creek, RM 7.0
Measured
16.4
14.7
14.6
14.2
Chimacum Creek, RM 7.0
Simulated
16.9
16.2
16.2
15.7
Chimacum Creek, RM 7.0
Scenariol
19.1
17.4
18.1
18.1
Chimacum Creek, RM 7.0
Scenario2
16.9
16.2
16.2
15.7
Chimacum Creek, RM 7.0
Scenario3
16.3
15.7
15.7
15.3
Chimacum Creek, RM 7.0
Scenario4
15.3
14.9
14.8
14.3
Chimacum Creek, RM 7.0
Scenario5
16.4
15.9
15.8
15.1
Chimacum Creek, RM 7.0
Scenario6
17.1
16.3
16.3
15.8
Chimacum Creek, RM 7.0
Scenario?
17.9
17.1
17.1
16.5
Chimacum Creek, RM 7.0
Scenario8
16.8
16.1
16.1
15.6
Chimacum Creek, RM 7.0
Scenario9
16.3
15.8
15.7
15.0
JCCD CH/6.7
Chimacum Creek, RM 6.7
Measured
16.4
16.0
15.4
14.6
Chimacum Creek, RM 6.7
Simulated
16.4
16.0
16.1
1 15.7
Chimacum Creek, RM 6.7
Scenariol
18.5
17.4
17.8
17.9
Chimacum Creek, RM 6.7
Scenario2
16.4
16.1
16.1
15.7
Chimacum Creek, RM 6.7
Scenario3
15.8
15.6
15.6
15.2
Chimacum Creek, RM 6.7
Scenario4
15.0
14.8
14.7
14.3
Chimacum Creek, RM 6.7
Scenario5
15.9
15.6
15.5
15.0
Chimacum Creek, RM 6.7
Scenario6
16.5
16.2
16.2
15.8
Chimacum Creek, RM 6.7
Scenario?
17.2
16.9
16.9
16.5
Chimacum Creek, RM 6.7
Scenario8
16.3
15.9
16.0
15.6
Chimacum Creek, RM 6.7
Scenario9
15.8
15.5
15.4
14.9
JCCD CH /6.5
Chimacum Creek, RM 6.5
Measured
17.4
16.6
16.0
14.9
Chimacum Creek, RM 6.5
Simulated
16.8
16.6
16.6
16.0
Chimacum Creek, RM 6.5
Scenariol
18.7
17.6
17.8
17.9
Chimacum Creek, RM 6.5
Scenario2
16.9
16.6
16.7
16.0
Prepared by Watershed Sciences Page 152
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
STATION ID
SITE NAME
Model
Run
Tem
erature °C
7 -Da Ave.
Max
Absolute
Max
July
Au
Se t
Chimacum Creek, RM 6.5
Scenario3
16.4
16.2
16.2
15.6
Chimacum Creek, RM 6.5
Scenario4
15.5
1 15.3
15.1
14.5
Chimacum Creek, RM 6.5
Scenario5
16.4
16.0
15.9
15.3
Chimacum Creek, RM 6.5
Scenario6
17.0
16.7
16.7
16.1
Chimacum Creek, RM 6.5
Scenario?
17.6
17.3
17.3
16.7
Chimacum Creek, RM 6.5
Scenario8
16.7
16.5
16.6
15.9
Chimacum Creek, RM 6.5
Scenario9
16.3
15.9
15.8
15.3
JCCD CH/6.1
Chimacum Creek, RM 6.1
Measured
19.0
18.1
17.4
15.5
Chimacum Creek, RM 6.1
Simulated
17.5
17.1
17.1
16.4
Chimacum Creek, RM 6.1
Scenariol
19.2
1 18.2
18.2
18.2
Chimacum Creek, RM 6.1
Scenario2
17.6
17.2
17.2
16.5
Chimacum Creek, RM 6.1
Scenario3
17.0
16.7
16.7
16.0
Chimacum Creek, RM 6.1
Scenario4
15.9
15.7
15.6
14.9
Chimacum Creek, RM 6.1
Scenario5
16.4
16.0
15.9
15.5
Chimacum Creek, RM 6.1
Scenario6
17.7
17.2
17.3
16.5
Chimacum Creek, RM 6.1
Scenariol
18.3
17.8
17.9
17.1
Chimacum Creek, RM 6.1
Scenario8
17.4
17.0
17.0
16.4
Chimacum Creek, RM 6.1
Scenario9
16.4
16.0
15.9
15.5
JCCD CH /5.3
Chimacum Creek, RM 5.3
Measured
1 19.2
18.7
18.1
16.8
Chimacum Creek, RM 5.3
Simulated
18.4
18.0
18.0
17.1
Chimacum Creek, RM 5.3
Scenariol
20.6
19.4
19.4
19.1
Chimacum Creek, RM 5.3
Scenario2
18.5
18.0
18.0
17.1
Chimacum Creek, RM 5.3
Scenario3
17.7
17.3
17.3
16.6
Chimacum Creek, RM 5.3
Scenario4
16.1
15.9
15.9
15.3
Chimacum Creek, RM 5.3
Scenario5
16.6
16.1
16.1
15.8
Chimacum Creek, RM 5.3
Scenario6
18.6
18.1
18.2
17.2
Chimacum Creek, RM 5.3
Scenariol
19.5
18.9
19.0
17.8
Chimacum Creek, RM 5.3
Scenario8
18.3
1 17.8
17.8
17.0
Chimacum Creek, RM 5.3
Scenario9
16.5
16.1
16.0
15.7
JCCD CH /3.9
Chimacum Creek, RM 3.9
Measured
22.2
21.3
20.5
17.3
Chimacum Creek, RM 3.9
Simulated
21.3
20.6
20.3
18.1
Chimacum Creek, RM 3.9
Scenariol
22.3
21.6
21.1
18.8
Chimacum Creek, RM 3.9
Scenario2 1
21.4
20.6
20.3
18.1
Chimacum Creek, RM 3.9
Scenario3
20.4
19.7
19.5
17.7
Chimacum Creek, RM 3.9
Scenario4
18.0
17.7
17.4
16.4
Chimacum Creek, RM 3.9
Scenario5
16.4
16.0
15.8
15.6
Chimacum Creek, RM 3.9
Scenario6
21.5
1 20.7
20.4
18.2
Chimacum Creek, RM 3.9
Scenariol
22.1
21.3
20.9
18.5
Chimacum Creek, RM 3.9
Scenario8
21.1
20.4
20.1
18.0
Chimacum Creek, RM 3.9
Scenario9
16.3
16.0 1
15.7
15.6
JCCD CH /1.1
Chimacum Creek, RM 1.1
Measured
18.7
18.2 1
17.3
16.2
Prepared by Watershed Sciences Page 153
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
STATION ID
SITE NAME
Model
Run
Tem
erature C
7 -Da Ave.
Max
Absolute
Max
July
Aug
Sept
Chimacum Creek, RM 1.1
Simulated
18.8
18.3
18.4
17.1
Chimacum Creek, RM 1.1
Scenariol
18.9
18.5
18.5
17.5
Chimacum Creek, RM 1.1
Scenario2
18.8
18.3
18.4
1 17.1
Chimacum Creek, RM 1.1
Scenario3
18.6
18.2
18.2
16.9
Chimacum Creek, RM 1.1
Scenario4
18.0
17.8
17.7
16.5
Chimacum Creek, RM 1.1
Scenario5
16.0
15.2
15.1
15.2
Chimacum Creek, RM 1.1
Scenario6
18.3
17.8
17.8
17.4
Chimacum Creek, RM 1.1
Scenario?
18.5
18.0
18.0
17.6
Chimacum Creek, RM 1.1
Scenario8
18.2
17.7
17.7
17.3
Chimacum Creek, RM 1.1
Scenario9
16.0
15.1
15.1
15.2
JCCD CH /0.1
Chimacum Creek, RM 0.1
Measured
19.7
18.7
18.0
16.3
Chimacum Creek, RM 0.1
Simulated
19.0
18.5
18.5
17.4
Chimacum Creek, RM 0.1
Scenario 1
19.0
18.5
18.5
17.7
Chimacum Creek, RM 0.1
Scenario2
19.0
18.5
18.5
1 17.4
Chimacum Creek, RM 0.1
Scenario3
19.0
18.5
18.5
1 17.3
Chimacum Creek, RM 0.1
Scenario4
18.6
18.2
18.2
16.8
Chimacum Creek, RM 0.1
Scenario5
16.1
15.4
15.2
15.3
Chimacum Creek, RM 0.1
Scenario6
18.6
18.1
18.1
17.5
Chimacum Creek, RM 0.1
Scenario?
18.8
18.2
18.2
17.6
Chimacum Creek, RM 0.1
Scenario8
18.5
18.1
18.0
17.4
Chimacum Creek, RM 0.1 1
Scenario9
16.1
15.4
15.2
15.3
Scenario 1- Development Trend °
Scenario 2 - Modified Development Trend Scenario 6 -Reduce flows 10 /o
Scenario 3 - Restore 10% of withdrawal flows Scenario 7 - Reduce flows 30%
Scenario 4 - Restore 50% of withdrawal flows Scenario 8 - Increase flows 10%
Scenario 5 - Restore riparian vegetation Scenario 9 - Combination of 5 and 8
Prepared by Watershed Sciences Page 154
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Table 26. Chimacum Creek - Temperature Changes per Model Run
Simulated Temperature Change (°C)
Absolute 7 -Day Ave. Max
Site - Scenario Max July August September
JCCD_CH/9.0 - Scenariol
0.3
0.3
0.2
0.4
JCCD_CH/7.0 - Scenariol
2.2
1.2
2.0
2.4
JCCD_CH/6.7 - Scenariol
2.1
1.3
1.8
2.2
JCCD_CH/6.5 - Scenariol
1.9
1.0
1.2
1.9
JCCD_CH/6.1 - Scenariol
1.7
1.1
1.1
1.8
JCCD_CH/5.3 - Scenariol
2.2
1.4
1.4
2.0
JCCD_CH/3.9 - Scenariol
1.0
1.0
0.8
0.7
JCCD CH/1.1- Scenariol
0.1
0.1
0.1
0.4
JCCD_CH/0.1 - Scenariol
0.0
0.0
0.0
0.3
JCCD_CH/9.0 - Scenario2
0.1
0.0
0.0
0.0
JCCD_CH/7.0 - Scenario2
0.0
0.0
0.0
0.0
JCCD_CH/6.7 - Scenario2
0.0
0.0
0.0
0.0
JCCD_CH/6.5 - Scenario2
0.1
0.0
0.0
0.0
JCCD_CH/6.1 - Scenario2
0.1
0.0
0.0
0.0
JCCD_CH/5.3 - Scenario2
0.1
0.0
0.0
0.0
JCCD_CH/3.9 - Scenario2
0.1
0.0
0.0
0.0
JCCD_CH/1.1 - Scenario2
0.0
0.0
0.0
0.0
JCCD_CH/0.1 - Scenario2
0.0
0.0
0.0
0.0
JCCD_CH/9.0 - Scenario3
-0.2
-0.2
-0.2
-0.2
JCCD_CH/7.0 - Scenario3
-0.6
-0.5
-0.4
-0.4
JCCD_CH/6.7 - Scenario3
-0.6
-0.4
-0.5
-0.4
JCCD_CH/6.5 - Scenario3
-0.4
-0.4
-0.5
-0.4
JCCD_CH/6.1 - Scenario3
-0.5
-0.4
-0.5
-0.4
JCCD_CH/5.3 - Scenario3
-0.7
-0.7
-0.7
-0.5
JCCD_CH/3.9 - Scenario3
-0.9
-0.8
-0.8
-0.4
JCCD_CH/1.1 - Scenario3
-0.2
-0.1
-0.1
-0.2
JCCD_CH/0.1 - Scenario3
0.0
0.0
0.0
-0.2
JCCD_CH/9.0 - Scenario4
-0.9
-0.9
-0.9
-0.6
JCCD_CH/7.0 - Scenario4
-1.6
-1.2
-1.4
-1.4
JCCD_CH/6.7 - Scenario4
-1.4
-1.2
-1.4
-1.4
JCCD_CH/6.5 - Scenario4
-1.3
-1.3
-1.5
-1.5
JCCD_CH/6.1 - Scenario4
-1.6
-1.4
-1.5
-1.6
JCCD_CH/5.3 - Scenario4
-2.3
-2.0
-2.1
-1.8
JCCD_CH/3.9 - Scenario4
-3.3
-2.9
-2.8
-1.7
JCCD_CH/l.I - Scenario4
-0.8
-0.6
-0.6
-0.6
JCCD_CH/0.1 - Scenario4
-0.4
-0.3
-0.3
-0.6
JCCD_CH/9.0 - Scenario5
0.0
0.0
0.0
0.0
JCCD_CH/7.0 - Scenario5
-0.5
-0.3
-0.4
-0.6
JCCD_CH/6.7 - Scenario5
-0.5
-0.5
-0.5
-0.7
JCCD_CH/6.5 - Scenario5
-0.4
-0.6
-0.7
-0.7
JCCD_CH/6.1 - Scenario5
-1.1
-1.2
-1.3
-0.9
JCCD_CH/5.3 - Scenario5
-1.8
-1.9
-1.9
-1.3
JCCD CH/3.9 - Scenario5
-4.9
4.5
-4.5
-2.5
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Scenario 1- Development Trend Scenario 6 - Reduce flows 10%
Scenario 2 - Modified Development Trend
Scenario 3 - Restore 10% of withdrawal flows Scenario 7 - Reduce flows %
1
Scenario 4 - Restore 50% of withdrawal flows Scenario 8 - Increase flows 10%
Scenario 5 - Restore riparian vegetation Scenario 9 - Combination of 5 and 8
Prepared by Watershed Sciences Page 156
Simulated Temperature Change CC)
Absolute
7 -Day Ave. Max
Site - Scenario
Max
July
August
September
JCCD_CH/1.1 - Scenario5
-2.8
-3.2
-3.3
-1.9
JCCD_CH/0.1 - Scenario5
-2.9
-3.1
-3.3
-2.1
JCCD_CH/9.0 - Scenario6
0.1
0.1
0.0
0.1
JCCD_CH/7.0 - Scenario6
0.2
0.1
0.1
0.1
JCCD_CH/6.7 - Scenario6
0.1
0.1
0.1
0.1
JCCD_CH/6.5 - Scenario6
0.2
0.1
0.1
0.1
JCCD_CH/6.1 - Scenario6
0.2
0.1
0.1
0.1
JCCD_CH/5.3 - Scenario6
0.2
0.2
0.2
0.1
JCCD_CH/3.9 - Scenario6
0.2
0.2
0.2
0.1
JCCD_CHJ1.1 - Scenario6
-0.5
-0.5
-0.6
0.3
JCCD_CH/0.1 - Scenario6
-0.4
-0.3
-0.4
0.1
JCCD_CH/9.0 - Scenario7
0.3
0.3
0.2
0.2
JCCD_CH/7.0 - Scenario7
1.0
0.9
0.9
0.8
JCCD_CH/6.7 - Scenario7
0.8
0.8
0.8
0.8
JCCD_CH/6.5 - Scenario7
0.8
0.7
0.6
0.7
JCCD_CH/6.1 - Scenario7
0.8
0.7
0.7
0.7
JCCD_CH/5.3 - Scenario7
1.1
1.0
1.0
0.8
JCCD_CW3.9 - Scenario7
0.8
0.7
0.6
0.3
JCCD_CH/1.1 - Scenario7
-0.3
-0.3
-0.4
0.5
JCCD_CH/0.1 - Scenario7
-0.2
-0.2
-0.3
0.2
JCCD_CH/9.0 - Scenario8
0.0
0.0
0.0
0.0
JCCD_CH17.0 - Scenario8
-0.1
-0.1
-0.1
-0.1
JCCD_CH/6.7 - Scenario8
-0.1
-0.1
-0.1
-0.1
JCCD_CH/6.5 - Scenario8
-0.1
-0.1
-0.1
-0.1
JCCD_CH/6.1 - Scenario8
-0.1
-0.1
-0.1
-0.1
JCCD_CHJ5.3 - Scenario8
-0.1
-0.2
-0.2
-0.1
JCCD_CW3.9 - Scenario8
-0.2
-0.2
-0.2
-0.1
JCCD_CH/1.1 - Scenario8
-0.6
-0.7
-0.7
0.2
JCCD_CH/0.1 - Scenario8
-0.5
-0.4
-0.5
0.0
JCCD_CH/9.0 - Scenario9
0.0
-0.1
-0.1
-0.1
JCCD_CH/7.0 - Scenario9
-0.6
-0.4
-0.5
-0.7
JCCD_CH/6.7 - Scenario9
-0.6
-0.6
-0.6
-0.8
JCCD_CH/6.5 - Scenario9
-0.5
-0.7
-0.8
-0.7
JCCD_CH/6.1 - Scenario9
-1.1
-1.2
-1.3
-1.0
JCCD_CH/5.3 - Scenario9
-1.9
-1.9
-2.0
-1.3
JCCD_CH/3.9 - Scenario9
-5.0
4.6
-4.6
-2.5
JCCD_CH/1.1 - Scenario9
-2.8
-3.2
-3.3
-1.9
JCCD CH/0.1 - Scenario9
-2.9
-3.1
-3.3
-2.2
Scenario 1- Development Trend Scenario 6 - Reduce flows 10%
Scenario 2 - Modified Development Trend
Scenario 3 - Restore 10% of withdrawal flows Scenario 7 - Reduce flows %
1
Scenario 4 - Restore 50% of withdrawal flows Scenario 8 - Increase flows 10%
Scenario 5 - Restore riparian vegetation Scenario 9 - Combination of 5 and 8
Prepared by Watershed Sciences Page 156
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
l U l . C;h;imacum Creek Model Scenarios - Kesultmg Temperature Changes (a
■ July ■ August a September
JCCD_CH/9.0 - Scenariol
JCCD_CHR.0 - Scenariol
JCCD_CH /6.7 - Scenariol
JCCD_CH /6.5 - Scenariol
JCCD_CH/6.1 - Scenariol
JCCD_CH/5.3-Scenariol
JCCD_CH/3.9 - Scenariol
JCCD_CH /1.1 - Scenariol
JCCD_CH /0.1 - Scenariol
JCCD_CH/9.0-Scenario2
JCCD_CH17.0 - Scenario2
JCCD_CH /6.7 - Scenario2
JCCD_CH/6.5 - Scenario2
JCCD_CH /6.1 - Scenario2
JCCD_CH /5.3 - Scenario2
JCCD_CH /3.9 - Scenario2
JCCD_CH /1.1 - Scenario2
JCCD_CH /0.1 - Scenario2
JCCD_CH/9.0 - Scenario3
JCCD_CH17.0 - Scenario3
JCCD_CH /6.7 - Scenario3
JCCD_CH/6.5 - Scenario3
JCCD_CH /6.1 - Scenario3
JCCD_CH /5.3 - Scenario3
JCCD_CH /3.9 - Scenario3
JCCD_CH /1.1 - Scenario3
JCCD_CH /0.1 - Scenario3
JCCD_CH/9.0 - Scenario4
JCCD_CH17.0 - Scenario4
JCCD_CH /6.7 - Scenario4
JCCD_CH /6.5 - Scenario4
JCCD_CH /6.1 - Scenario4
JCCD_CH/5.3-Scenario4
JCCD_CH /3.9 - Scenario4
JCCD_CH /1.1 - Scenario4
JCCD_CH /0.1 - Scenario4
JCCD_CH/9.0 - Scenario5
JCCD_CH/7.0 - Scenario5
JCCD_CH/6.7 - Scenario5
JCCD_CH /6.5 - Scenario5
JCCD_CH /6.1 - Scenario5
JCCD_CH /5.3 - Scenario5
JCCD- CH /3.9 - Scenario5
JCCD_CH /1.1 - Scenario5
JCCD CH /0.1 - Scenario5
-5 -4 -3 -2 -1 0 1 2 3 4 5
Resulting Change in 7 -Day Maximum Moving
Average of Daily Maximums (*C)
Scenario 1- Development Trend o
Scenario 2 - Modified Development Trend Scenario 6 -Reduce flows 10/0
Scenario 3 - Restore 10% of withdrawal flows Scenario 7 - Reduce flows /o
1
Scenario 4 - Restore 50% of withdrawal flows Scenario 8 - Increase flows 10%
Scenario 5 - Restore riparian vegetation Scenario 9 - Combination of 5 and 8
Prepared by Watershed Sciences Page 157
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 1 U2. Chimacum Creek Model Scenarios - Resulting Temperature Changes (t
■ July ■ August a September
JCCD-CH/9.0 - Scenario6 ;
JCCD-CH/7.0 - Scenario6
JCCD-CH/6.7 - Scenario6
JCCD CH /6.5 - Scenario6
JCCD-CH/6.1 - Scenario6
JCCD-CH/5.3 - Scenario6
JCCD-CH/3.9 - Scenario6
JCCD_CH /1.1 - Scenario6
JCCD CH /0.1 - Scenario6
JCCD-CH/9.0 - Scenario7
JCCD CH/7.0 - Scenario7
_ I I I I I I I I
JCCD-CH/6.7 - Scenario7
JCCD CH /6.5 - Scenario7
JCCD CH/6.1 -Scenario7
JCCD-CH/5.3 - Scenario7
1 I I I I I I
JCCD CH/3.9 - Scenario7
- I I I I I I I
JCCD-CH/1.1 - Scenario7
JCCD-CH/0.1 - Scenario7
JCCD CH /9.0 - Scenario8
JCCD CH17.0 - Scenario8
JCCD-CH/6.7 - Scenario8
I I I I I I I I
JCCD-CH/6.5 - Scenario8
JCCD-CH/6.1 - Scenario8
JCCD-CH/5.3 - Scenario8
JCCD CH/3.9 - Scenario8
JCCD-CH/1.1 - Scenario8
I I I I I I I I
JCCD_CH /0.1 - Scenario8
JCCD-CH/9.0 - Scenario9
JCCD_CH17.0 - Scenari09
JCCD_CH/6.7 - Scenario9
JCCD CH/6.5 - Scenario9
JCCD_CH /6.1 - Scenario9
JCCD-CH/5.3 - Scenario9
JCCD CH/3.9-Scenario9
JCCD-CH/1.1 - Scenario9
JCCD CH /0.1 - Scenario9
-5 -4 -3 -2 -1 0 1 2 3 4 5
Resulting Change in 7 -Day Maximum Moving
Average of Daily Maximums (*C)
Scenario 1- Development Trend Scenario 6 - Reduce flows 10%
Scenario 2 - Modified Development Trend
Scenario 3 - Restore 10% of withdrawal flows Scenario 7 - Reduce flows 30%
Scenario 4 - Restore 50% of withdrawal flows Scenario 8 - Increase flows 10%
Scenario 5 - Restore riparian vegetation Scenario 9 - Combination of 5 and 8
Prepared by Watershed Sciences � �� �� Page 158
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 103a. Chimacum Model Scenarios - 7-Day Max Moving Ave of the Daily Max
JCCD CH6.5 RKM 1Z05
T 19
I I I I I I I I I I I I I I I
Model Scenarios
-
A18
1
Measured
o
-- -- 1-- - - -� -- -- 1-- f-- +-- * - -� -- ------- -I - -�-
Simulated
I I I I I I I I I I I
ci 16
Scenado1
--
14
--'-- -- - - - -! - ---- - - -' -- - ' - - -' -- '-
Scenado2
o E
I
Z' 'j� 13
l0
-- - - - -- -- - - = - -' -- - -I - --
Scenado3
E 12----
-------- ,-- -I - - -- i -- T ------- - - - -,- - -, - -j
E
A
Scenano4
10
I I I
_- T- _r__r_- r__I___I___1__,_
----- -- Scenado5
I I 1 1 1 1
A
-- Scenado6
8
I I I I I I I I I I I I I I I
p�
N N ti v N ` N M N N
Scenario?
n n C
JCCD CH5.3 RKM 10.30 20"
Scenado8
20
-- r---- r---- r--° r— I--°-- r— r-- r-- -- r--- r--- -r- ---- r- -- r- -�--'�
Scenado9
_T ,s
1 I I
-- -- - - -1 -- - -�- - -- t-- Y - -I -- ---- 1 - - -I -- -
I I I I I I I I I I I I I I
a 16
-- -- - - -I -- -- -+ - -- -- ---- I-- - - -� -�
I I
Thermal Limits
16
p..
> L
I I I
160C
T - 14
I - - 1 - - -1-
Rearing, Migration &
-- -I -- -- -- - -- -- - - -' --
- -1 - 1 1 1
awnm
Spawning
0 s
2 .- 13
----- - - - - -- ; -- ------ - - - - -, -
,z
- - -- -- -- -- - -; - -; - -; - -; - - - -,
--- - - -1 --
All Study Streams
e
I ; r ,
All Year
-- r-- I--- I___ I__,-- ,-- T__T-- r-- r-- r-- I - - -I -- I --
19
I I I 1 I I
13 °C
�
-- Y--_____- 1-- y__- 1_ _Y__t__Y__r__t.._- I___I___I__y_
I I I I 1 I E
Summer Chum
8
LO R; M o�: N M N N
Spawning &
Incubation
JCCD CH1.1 RKM 2.78 2004
zo
September 15 to July l j
1 I I I
,s
-- I--- 1--- I-- �-- �-- ,-- �-- T-- Y-- �-- Y-- I--- 1-- -I - -,-
I
I I I I I I I I I I I
ro 17
16
-- - - - -1 -- -- - -- +- - ------ - - -� -�
I I I I
v
I
C 7 14
.O
- - 1 -- 1 - - -1 -- 1 -- - -- -- -' -- - -I -- �-
2 9 13
I I I
7 12
1 1 I I
I
10
I I I I
r - - r - - --- I - - -I- �-
I
I I I 1
8
'n
N N N M P N M e N N
N
2004
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 104. Chimacum Model Scenarios — Longitudinal Profiles for Model Scenarios
24
«� 23
a 22
°o
M 21
20
N 19
18
c 17
CL
16
C
15
0 14
J
13
Thermal Limits
16 °C Rearing, Migration & Spawning
All Study Streams, All Year
1300 Summer Chum Spawning & Incubation
September 15 to July 1
i
f �
i
r
1 _ ,
r'- w to V CM N e C CA Co r- CC LO qtmN —0
2004
Model Scenarios
Measured
— Simulated
— Scenariol
— Scenario2
— Scenario3
Scenario4
- -- Scenario5
--- Scenaro6
— Scenado7
— Scenario8
— Scenario9
Scenario 1— Development Trend Scenario 6 — Reduce flows 10%
Scenario 2 — Modified Development Trend
Scenario 3 — Restore 10% of withdrawal flows Scenario 7 — Reduce flows 30%
Scenario 4 — Restore 50% of withdrawal flows Scenario 8 — Increase flows 10%
Scenario 5 — Restore riparian vegetation Scenario 9 — Combination of 5 and 8
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
5.4.5 East Chimacum Creek
Table 27. East Chimacum Creek - Maximum Temperatures per Model Run
STATION ID
SITE NAME
Model
Run
Tem erature °C
Absolute
Max
7 -Da y Ave. Max
July
Aug
Sept
JCCD_ECH/3.3
East Chimacum, RM 3.3
Measured
16.1
15.7
15.2
13.9
Simulated
16.5
15.4
15.3
14.6
Scenario5
15.9
14.9
14.9
14.2
Scenario6
16.6
15.5
15.5
14.7
Scenario?
17.1
15.9
15.9
14.9
Scenario8
16.4
15.2
15.2
14.5
Scenario9
15.8
14.9
14.8
14.1
JCCD_ECH/2.8
East Chimacum, RM 2.8
Measured
16.6
16.0
15.4
14.0
Simulated
16.9
15.9
16.0
15.5
Scenario5
16.0
15.0
15.0
14.7
Scenario6
17.0
16.0
16.1
15.6
Scenario?
17.5
16.4
16.5
15.9
Scenario8
16.8
15.8
15.9
15.4
Scenario9
15.9
14.9
14.9
14.6
JCCD_ECH/1.2
East Chimacum, RM 1.2
Measured
18.8
18.2
17.1
15.7
Simulated
17.8
17.2
17.4
16.6
Scenario5
16.1
15.2
15.2
15.0
Scenario6
18.0
17.4
17.5
16.8
Scenario?
18.4
17.7
17.9
17.1
Scenario8
17.7
17.1
17.2
16.5
Scenario9
16.1
15.1
15.1
15.0
JCCD_ECH/1.1
East Chimacum, RM 1.1
Measured
18.2
17.8
16.9
15.6
Simulated
18.0
17.2
17.2
16.6
Scenario5
16.2
15.4
15.3
15.0
Scenario6
18.2
17.3
17.4
16.7
Scenario?
18.7
17.7
17.7
17.0
Scenario8
17.8
17.0
17.0
16.5
Scenario9
16.1
15.3
15.2
1 15.0
JCCD_ECH/0.1
East Chimacum, RM 0.1
Measured
20.2
19.4
18.6
16.4
Simulated
18.8
17.7
17.7
17.3
Scenario5
16.5
15.2
15.2
15.2
Scenario6
18.9
17.8
17.8
17.4
Scenario?
19.2
17.9
18.0
17.6
Scenario8
18.7
17.7
17.7
17.2
Scenario9
16.4
15.2
15.1
15.1
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Table 28. East Chimacum Creek - Temperature Changes per Model Run
Site - Scenario
Simulated
Temperature Change C
Absolute
Max
7 Day Ave. Max
July
August
Septembe
r
JCCD ECH/3.3 - Scenario5
-0.6
-0.4
-0.5
-0.4
JCCD ECH/2.8 - Scenario5
-0.9
-0.9
-1.0
-0.8
JCCD ECH/1.2 - Scenario5
-1.7
-2.1
-2.2
-1.6
JCCD ECH /1.1 - Scenario5
-1.8
-1.8
-1.9
-1.6
JCCD ECH/0.1 - Scenario5
-2.3
-2.5
-2.5
-2.1
JCCD ECH/3.3 - Scenario6
0.1
0.1
0.1
0.1
JCCD ECH/2.8 - Scenario6
0.1
0.1
0.1
0.1
JCCD ECH/1.2 - Scenario6
0.2
0.1
0.1
0.1
JCCD ECH /1.1 - Scenario6
0.2
0.2
0.2
0.1
JCCD ECH/0.1 - Scenario6
0.1
0.1
0.1
0.1
JCCD ECH/3.3 - Scenario7
0.6
0.5
0.5
0.3
JCCD ECH /2.8 - Scenario7
0.6
0.5
0.5
0.4
JCCD ECH/1.2 - Scenario7
0.6
0.5
0.5
0.4
JCCD ECH/1.1 - Scenario7
0.7
0.5
0.5
0.4
JCCD ECH/0.1 - Scenario7
0.4
0.2
0.2
0.3
JCCD ECH/3.3 - Scenario8
-0.1
-0.1
-0.1
-0.1
JCCD ECH/1.2 - Scenario8
-0.1
-0.1
-0.1
-0.1
JCCD ECH/2.8 - Scenario8
-0.1
-0.1
-0.1
-0.1
JCCD ECH /1.1 - Scenario8
-0.2
-0.2
-0.2
-0.1
JCCD ECH/0.1 - Scenario8
-0.1
0.0
0.0
-0.1
JCCD ECH/3.3 - Scenario9
-0.7
-0.5
-0.6
-0.5
JCCD ECH/2.8 - Scenario9
-1.0
-1.0
-1.0
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JCCD ECH/1.2 - Scenario9
-1.7
-2.2
-2.3
-1.6
JCCD ECH/1.1 - Scenario9
-1.9
-1.9
-2.0
-1.6
JCCD ECH/0.1 - Scenario9
-2.4
-2.5
-2.6
-2.2
Scenario 1- Development Trend Scenario 6 -Reduce flows 10%
Scenario 2 - Modified Development Trend
Scenario 3 - Restore 10% of withdrawal flows Scenario 7 - Reduce flows 30%
Scenario 4 - Restore 50% of withdrawal flows Scenario 8 - Increase flows 10%
Scenario 5 - Restore riparian vegetation Scenario 9 - Combination of 5 and 8
Prepared by Watershed Sciences Page 162
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 105. East Chimacum Creek Model Scenarios — Resulting Temperature Changes
JCCD ECH /3.3 - Scenario5
JCCD ECH /2.8 - Scenario5
JCCD_ECH /1.2 - Scenario5
JCCD ECH /1.1 - Scenario5
JCCD ECH /0.1 - Scenario5
JCCD_ECH/3.3 - Scenario6
JCCD ECH /2.8 - Scenario6
JCCD ECH /1.2 - Scenario6
JCCD_ECH /1.1 - Scenario6
JCCD ECH /0.1 - Scenario6
JCCD ECH /3.3 - Scenario7
JCCD ECH /2.8 - Scenario7
JCCD_ECH /1.2 - Scenario7
JCCD ECH /1.1 - Scenario7
JCCD ECH /0.1 - Scenario7
JCCD ECH /3.3 - Scenario8
JCCD ECH /1.2 - Scenario8
JCCD ECH /2.8 - Scenario8
JCCD ECH /1.1 - Scenario8
JCCD ECH /0.1 - Scenario8
JCCD ECH/3.3 - Scenario9
JCCD ECH /2.8 - Scenario9
JCCD ECH /1.2 - Scenario9
JCCD ECH /1.1 - Scenario9
JCCD ECH /0.1 - Scenario9
-3
■ July ■ August a September
3
-2 -1 0 1 2
Resulting Change in 7 -Day Maximum Moving
Average of Daily Maximums ( *C)
Scenario 1— Development Trend o
Scenario 2 — Modified Development Trend Scenario —Reduce flows 1000
Scenario 3 — Restore 10% of withdrawal flows Scenario 7 7 — Reduce flows /o
1 0%
Scenario 4 — Restore 50% of withdrawal flows Scenario 8 — Increase flows 1
Scenario 5 — Restore riparian vegetation Scenario 9 — Combination of 5 and 8
Prepared by Watershed Sciences Page 163
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 106. East Chimacum Model Scenarios — 7 -Day Max Moving Ave of the Daily
Max (a)
Prepared by Watershed Sciences Page 164
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Prepared by Watershed Sciences Page 164
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 107. East Chimacum Model Scenarios - 7 -Day Max Moving Ave of the Daily
Max (b)
Model Scenarios
Measured
Simulated
Scenario1
Scenario2
Scenario3
Scenario4
Scenario5
- Scenario6
Scenario?
Scenario8
Scenario9
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16 °C
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Scenario 1— Development Trend o
Scenario 2 — Modified Development Trend Scenario 6 —Reduce flows 10%
Scenario 3 — Restore 10% of withdrawal flows Scenario 7 — Reduce flows
1 /o
Scenario 4 — Restore 50% of withdrawal flows Scenario 8 — Increase flows 10%
Scenario 5 — Restore riparian vegetation Scenario 9 — Combination of 5 and 8
Prepared by Watershed Sciences Page 165
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
Figure 108. East Chimacum Model Scenarios — Longitudinal Profiles for Model
Scenarios
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— ScenarioB
— Scenario9
Scenario 1— Development Trend o
Scenario 2 — Modified Development Trend Scenario 6 —Reduce flows 1000
Scenario 3 — Restore 10% of withdrawal flows Scenario 7 — Reduce flows
1 /o
Scenario 4 — Restore 50% of withdrawal flows Scenario 8 — Increase flows 10%
Scenario 5 — Restore riparian vegetation Scenario 9 — Combination of 5 and 8
Prepared by Watershed Sciences Page 166
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
6. Discussion
What are the seasonal patterns and spatial distributions of stream
temperatures?
July was the warmest stream temperature period, with August also producing fairly warm
stream temperatures. Some reaches of Chimacum Creek also experienced a warm period
in June, a phenomenon that the models could not simulate. Stream temperature spatial
distributions are fairly variable, but generally follow a classic heating pattern in the
downstream direction.
How do existing land and water uses affect stream temperatures
spatially and temporally?
Results demonstrate that land uses that reduce flows will typically warm the study
streams in July, August and September. It follows that land and water uses that promote
increases in instream fows have a moderating effect and reduce stream temperatures
during this period. Increases in riparian vegetation had large cooling effects in all cases.
What are the seasonal and spatial distributions of physical and thermal
habitat?
This report considers thermal habitat as follows:
Salmon & Trout Thermal Needs Summer Chum Salmon Thermal Needs
16DC Rearing & Mgration 16oC Rearing & Mgrabon
All Study Streams All Study Streams
All Year July 1St to September 15th
13oC Spawning & Incubation
All Study Streams, Excluding East Chimacum
September 15th to July 15t
Under these thermal limits, very few reaches of the study streams offer optimal thermal
habitats to salmonids, for rearing, migration, spawning and egg incubation. Exceptions
include the upper Big Quilcene River, upper Little Quilcene River, upper Tarboo Creek
(above RM 4.0), upper Chimacum Creek (above RM 7.0) and East Chimacum Creek
(above RM 5.4). The model simulation results per flow and riparian scenario indicate
that combinations of flow increases and riparian vegetation enhancements will create a
significant improvement in thermal habitat (see models scenarios for results).
How does irrigation and flow management affect physical and thermal
habitat?
Flow management that reduces stream flow decreases physical habitat (by reducing the
wetted extent of the channel) and decreases thermal habitat by allowing increased stream
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Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
warming. Management that increases stream flows creates the opposite effects,
increasing both physical and wetted habitat.
Some scenarios create only a small temperature increase. Does that
mean that it doesn't affect fisheries?
It is important to consider why some flow decreases create only small temperature
increases. In the case of the Big and Little Quilcene Rivers for scenario 2 (modified
development trend), small flow reductions are not significant enough for the model to
create a large temperature response. In short, these streams do not respond to very
small flow decreases because they have large flows, relative to the modeled
withdrawal rates (i.e., as a percentage of instream flow).
In the case of Chimacum and East Chimacum Creek, along with Tarboo Creek, the
extreme low flows and slow travel times over many miles allows for these streams to
reach a thermal equilibrium with the surrounding environment. Therefore, decreases in
flows offer little increased warming because they simply cannot warm anymore. The
thermal environment governs maximum temperatures, and these streams are likely near
or at these temperatures in their contemporary condition. In short, these streams do not
warm much because they are already warm.
In either case, does this mean that these flow reductions and small temperature responses
are not likely to affect fisheries? Results in this report indicate that all of the study
streams are in an artificially warmed contemporary condition during critical periods of
the summer chum life history. Management that fails to promote improvements in
physical and thermal habitats, will maintain these stressful contemporary conditions. An
easy way to answer this question is to acknowledge that flow decreases already are
adversely affecting fisheries, any additional increases in temperature exacerbate the
problem, and failure to cool stream temperature maintains the problem.
What are primary and secondary influences of land cover upon surface
water thermal habitat, as simulated by the model?
Riparian land cover provides shade as a function of vegetation height and density, as well
as proximity to the stream. Solar radiation is the largest potential heat source to a stream,
and therefore stream shading is important in reducing the rate of heating during the
daytime. The primary influence of vegetation on thermal habitats is reducing the
rate of heating of a stream, resulting in cooler daily maximum temperatures (Boyd,
19996, Boyd and Kasper, 2002, Beschta et al. 1987, Beschta and Weatherred,1984).
Riparian vegetation also emits thermal radiation that can be received by the stream. This
may serve to insulate the stream and provide warming, especially during nighttime. The
result is that a stream often has less diurnal (daily) variation in temperatures. Increased
riparian vegetation will buffer temperature, reducing daytime temperatures, and
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Quilcene and Chimacum Temperature Analysis Port Gamble SX/allam Tribes
Jefferson County, WA
potentially slightly increasing nighttime temperatures temperatures (Boyd, 19996,
Boyd and Kasper, 2002, Beschta et al. 1987, Beschta and Weatherred,1984).
Under what conditions can restoration efforts recreate pre- settlement
physical and thermal habitats?
It is extremely difficult to reproduce a theoretical and defensible understanding of
historical conditions that is robust. In this effort, the investigators do not claim to have
done so. Instead, the elements that are quantified and changed to match a condition
closer to pre - settlement are flow and riparian vegetation. By minimizing water
withdrawals from streams and promoting late -seral riparian vegetation, these elements
will begin to trend toward a historical condition that promotes consistently cooler stream
temperatures.
Morphology and floodplain function are also an important elements that have undergone
extensive modifications in the post - settlement period. Little effort has been made in this
study to quantify the morphologic changes, including: wetland functions, floodplain
connection/condition, channel condition and sediment regimes. These stream parameters
are important, and a certainly understated in this study by their omission.
Prepared by Watershed Sciences � �,. � ✓ ' ��� � Page 169
Quilcene and Chimacum Temperature Analysis Port Gamble S'Klallam Tribes
Jefferson County, WA
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