Ice Formation on Brownlee Reservoir and Potential Effects on Big Game Populations

R. Ryel Ryel and Associates North Logan, UT

N. Mesner Dept. of Geography & Earth Resources Utah State University

S. Jensen White Horse Associates Smithfield, UT

Technical Report Appendix E.3.2-35 December 2001 Revised July 2003 (Minor Typographical Changes) Hells Canyon Complex FERC No. 1971 Copyright © 2003 by Idaho Power Company

Ice Formation on Brownlee Reservoir and Potential Effects on Big Game Populations

Technical Report Appendix E.3.2-35

Final Draft December 2001

Prepared for:

Idaho Power Company Boise, Idaho

Prepared by:

R. Ryel Ryel and Associates North Logan, Utah

N. Mesner Department of Geography and Earth Resources Utah State University Logan, Utah

S. Jensen White Horse Associates Smithfield, Utah

Brownlee Reservoir Ice—Effects on Big Game

Table of Contents

Table of Contents...... i List of Tables...... ii List of Figures...... ii ABSTRACT...... 1 1.0 INTRODUCTION...... 2 1.1. Background ...... 2 1.2. Justification...... 2 1.3. Objectives...... 3 2.0 METHODS ...... 3 2.1. Study Area...... 3 2.2. Big Game Surveys...... 4 2.3. Reservoir Ice Model...... 4 2.3.1. Basic Model Structure and Calibration ...... 5 2.3.2. Embayments ...... 5 2.3.3. Modeling Ice...... 6 2.3.4. Simulations ...... 6 2.3.5. Sensitivity Analysis...... 8 2.3.6. Model Validation...... 8 2.3.7. Assessing timing of ice formation and thawing ...... 8 3.0 RESULTS...... 9 3.1. Big Game Surveys...... 9 3.1.1. Mule Deer ...... 9 3.1.2. Elk...... 10 3.1.3. Bighorn Sheep ...... 10 3.2. Embayments...... 10 3.3. Simulations ...... 11 3.3.1. Embayments ...... 11 3.3.2. Comparison between Operational Scenarios...... 11 3.3.3. Effect of Rising and Falling Water Levels on Ice Formation...... 13 3.3.4. Ice Formation and Big Game Distribution ...... 13 3.4. Sensitivity Analyses...... 13 3.5. Model Validation ...... 14 3.6. Periods of Ice Formation and Thawing ...... 15 4.0 DISCUSSION...... 16 4.1. Ice Formation...... 16 4.2. Effects on Big Game...... 18 5.0 Literature Cited...... 21

i Brownlee Reservoir Ice—Effects on Big Game

List of Tables

Table 1. Variables in ice formation submodel of CE-QUAL-W2 assessed in sensitivity analysis. Middle values (bold) shown were used in simulations and are default values from CE- QUAL-W2, while low and high values were used in sensitivity analyses...... 25 Table 2. Result of k-means cluster analysis for embayments in Brownlee Reservoir. Embayment characteristics were measured at 15 water surface elevations separated by 3 m. Both cluster means and standard deviation of area and thalweg length are shown for members of each cluster...... 25 Table 3. Results of sensitivity analysis of coefficients used in ice submodel of CE-QUAL-W2. Shown are maximum and minimum differences between simulation run with variable changed to low or high parameter values (Table 1) and original simulation run. Differences in days with ice formation are expressed as absolute differences in days. Differences in maximum ice thickness are expressed as percent differences. Simulation shown is for Brownlee Reservoir in January 1995 (medium flow year) for “cold” freeze cycle under proposed operations. Similar results were also found for the run-of-river scenario for the same period (results not shown)...... 26

List of Figures

Figure 1. Brownlee Reservoir on Snake River between Oregon and Idaho...... 27 Figure 2a. Lower Brownlee Reservoir showing model segments used in CE-QUAL-W2, embayments and wildlife survey units...... 29 Figure 2b. Upper Brownlee Reservoir showing model segments used in CE-QUAL-W2, embayments and wildlife survey units...... 31 Figure 3. (upper) Inflow from Snake River to Brownlee Reservoir during low (1992), medium (1995) and high (1997) flow years. Twenty-day simulation periods are shown as horizontal bars. (lower) Detail of flows during months used in simulations. Twenty-day simulation periods are shown as horizontal bars...... 33 Figure 4. Water surface elevations of Brownlee Reservoir for low flow, 1992 (upper), medium flow, 1995 (middle) and high flow, 1995 (lower) years for proposed operations and run-of-river operational scenarios. 20-day simulation periods are shown as horizontal bars...... 34 Figure 5. Air temperatures used in “cold” (upper) and “warm” (lower) freeze period simulations...... 35

ii Brownlee Reservoir Ice—Effects on Big Game

Figure 6. Sites on Brownlee Reservoir where water temperatures and ice formation were measured in January−March, 2001 for model validation. ‘Main’ refers to measurements made in main reservoir body, ‘Emb’ within embayments, and ‘PR’ within the Powder River arm...... 37 Figure 7. Average densities of mule deer adjacent to Brownlee Reservoir measured during March of 1998, 2000 and 2001. Numbers of embayments within reservoir segments are also indicated...... 39 Figure 8. Average densities of elk adjacent to Brownlee Reservoir measured during March of 1998, 2000 and 2001. Numbers of embayments within reservoir segments are also indicated...... 41 Figure 9. Average densities of bighorn sheep adjacent to Brownlee Reservoir measured during March of 1998, 2000 and 2001. Numbers of embayments within reservoir segments are also indicated...... 43 Figure 10. Number and area of embayments in Brownlee Reservoir as a function of water surface elevation...... 45 Figure 11. (upper) Simulated days of ice persisting in Brownlee Reservoir within embayments of four different sizes (see Table 2) during “cold” freeze period (see text). Horizontal labels indicate the main reservoir segments containing the embayment. Broad bars indicate the period in days when reservoir ice is < 10 cm thick, while the narrow black bars indicate the total days when ice is present. (lower) Simulated maximum ice thickness for the same simulations...... 46 Figure 12a. Simulated days of ice persisting in Brownlee Reservoir within embayments during “cold” freeze period (see text) for low flow year (1992) in December (upper), January (middle) and February (lower). Horizontal labels indicate the main reservoir segments containing the embayment. Broad bars indicate the period in days when reservoir ice is < 10 cm thick, while the narrow black bars indicate the total days when ice is present...... 47 Figure 12b. Same as Figure 12a, except for medium flow year (1995)...... 48 Figure 12c. Same as Figure 12a, except for high flow year (1997)...... 49 Figure 13. Simulated maximum ice thickness for simulations in Figure 12a,b,c. PO is proposed operations and RR is run-of-river operational scenario...... 50 Figure 14a. Simulated days of ice persisting in Brownlee Reservoir within embayments during “warm” freeze period (see text) for low flow year (1992) in December (upper), January (middle) and February (lower). Horizontal labels indicate the main reservoir segments containing the embayment. Broad bars indicate the period in days when reservoir ice is < 10 cm thick, while the narrow black bars indicate the total days when ice is present...... 51 Figure 14b. Same as Figure 14a, except for medium flow year (1995)...... 52

iii Brownlee Reservoir Ice—Effects on Big Game

Figure 14c. Same as Figure 14a, except for high flow year (1997)...... 53 Figure 15. Simulated maximum ice thickness for simulations in Figure 14a,b,c. PO is proposed operations and RR is run-of-river operational scenario...... 54 Figure 16a. Simulated days of ice persisting in the Powder River arm of Brownlee Reservoir during “cold” freeze period (see text) for low flow year (1992) in December (upper), January (middle) and February (lower). Horizontal labels indicate the main reservoir segments containing the embayment. Broad bars indicate the period in days when reservoir ice is < 10 cm thick, while the narrow black bars indicate the total days when ice is present...... 55 Figure 16b. Same as Figure 16a, except for medium flow year (1995)...... 56 Figure 16c. Same as Figure 16a, except for high flow year (1997)...... 57 Figure 17. Simulated maximum ice thickness for simulations in Figure 16a,b,c. PO is proposed operations and RR is run-of-river operational scenario...... 58 Figure 18a. Simulated days of ice persisting in the Powder River arm of Brownlee Reservoir during “warm” freeze period (see text) for low flow year (1992) in December (upper), January (middle) and February (lower). Horizontal labels indicate the main reservoir segments containing the embayment. Broad bars indicate the period in days when reservoir ice is < 10 cm thick, while the narrow black bars indicate the total days when ice is present...... 59 Figure 18b. Same as Figure 18a, except for medium flow year (1995)...... 60 Figure 18c. Same as Figure 18a, except for high flow year (1997)...... 61 Figure 19. Simulated maximum ice thickness for simulations in Figure 18a,b,c. PO is proposed operations and RR is run-of-river operational scenario...... 62 Figure 20a. Simulated days of ice persisting in main body of Brownlee Reservoir during “cold” freeze period (see text) for low flow year (1992) in December (upper), January (middle) and February (lower). Horizontal labels indicate the main reservoir segments containing the embayment. Broad bars indicate the period in days when reservoir ice is < 10 cm thick, while the narrow black bars indicate the total days when ice is present...... 63 Figure 20b. Same as Figure 12a, except for medium flow year (1995)...... 64 Figure 20c. Same as Figure 12a, except for high flow year (1997)...... 65 Figure 21. Simulated maximum ice thickness for simulations in Figure 20a,b,c. PO is proposed operations and RR is run-of-river operational scenario...... 66 Figure 22. Maximum and minimum air temperatures measured at Brownlee Reservoir dam during the period December 2000 through March 2001. ‘S’ refers to the time ice was first observed in main reservoir embayments and in the iv Brownlee Reservoir Ice—Effects on Big Game

Powder River arm, ‘T’ refers to the time thick ice (> 10 cm) was observed in the Powder River arm, and ‘M’ refers to the time when ice had melted from the Powder River arm...... 67 Figure 23. (upper) Period when minimum daily air temperatures at Brownlee Reservoir dam first were below the indicated temperature for four consecutive nights for the period 1966−2001. The black box represents the median date for this occurrence. Percentages refer to the number of years during 1966−2001 when minimum temperatures were at or below the threshold temperatures for four consecutive nights. (lower) Number years when minimum nighttime temperatures were above 0 C for seven consecutive nights by time of first occurrence. Indicated dates represent ending date of seven day string...... 68

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ABSTRACT

The effects of ice formation on Brownlee Reservoir big game populations were assessed. In particular, potential mortality due to animals falling through ice and predation while traversing ice were primary concerns of the study. The focus was on populations of mule deer (Odocoileus hemionus), elk (Cervus elaphus) and Rocky Mountain bighorn sheep (Ovis canadensis) that frequent areas adjacent to the reservoir during the winter months. Patterns of ice formation with two operational scenarios for Brownlee Reservoir were considered: proposed operations and run-of-river. Aerial surveys were conducted in March 1998, 2000 and 2001 to count numbers of animals using land areas around the reservoir. Counts of mule deer adjacent to Brownlee Reservoir increased during the three years from 9,262 to 12,097 within the survey area largely due to greater numbers of fawns. Total numbers of elk fluctuated from 980 to 1,261, while numbers of bighorn sheep declined from 75 to 57. The decline in bighorn sheep was primarily related to a decline in adult rams. Mule deer in particular were concentrated in uplands along the lower two-thirds of the reservoir, while some areas of high elk density were located in uplands adjacent to the lower reservoir. The two-dimensional laterally averaged, hydrodynamic and water quality simulation model, CE-QUAL-W2, was used to simulate ice formation within the reservoir. Simulations of ice formation were conducted for embayments, the Powder River arm (a large, narrow bay) and the main reservoir for 20-day periods during December, January, and February. The two operational scenarios for Brownlee Reservoir were simulated for a low, medium and high flow year. Simulations indicated that there was little difference in ice formation and persistence between the two operational scenarios. Ice formation was more likely in the lower two-thirds of the reservoir than the upper third, and was more likely in embayments and in the Powder River arm. The period of time that ice was too thin to be safe for crossing (< 10 cm) was also similar between the two operational scenarios. Assessment of the period of ice formation in the reservoir indicated that initial ice formation was likely to occur after the first of December with the median date in late December. This analysis also indicated that breakup and thawing of ice sheets was likely to occur from late February to early April. This period of expected ice formation was during the periods when deer were observed to cross the reservoir. The highest concentrations of big game animals, particularly mule deer, and mule deer migration routes were largely associated with portions of the reservoir that had the most embayments and potential for ice formation. Despite this, little evidence could be found that mortality occurred from individuals falling through the ice. However, there was some evidence of increased potential for predation by individuals crossing the ice. Severe winters would be expected to be periods when ice formation would have the greatest effect on mortality of mule deer. Overall, however, no information suggested that the viability of these populations of big game animals was adversely affected by ice formation under proposed operations. Results of simulations indicated that there should be no increased potential for mortality due to ice formation under the run-of-river operational scenario.

1 Brownlee Reservoir Ice—Effects on Big Game

1.0 INTRODUCTION

1.1. Background The uplands adjacent to Brownlee Reservoir are important wintering areas for several big game species. Most numerous of these are mule deer (Odocoileus hemionus), elk (Cervus elaphus) and Rocky Mountain bighorn sheep (Ovis canadensis). All are ecologically and economically important species in this region. Winter habitat is often critical in the persistence of populations of North American ungulates. Both forage availability (Austin and Urness 1983, Wickstrom et al. 1984, Austin et al. 1994) and microclimate affect (Garrott et al. 1987) the quality and importance of lands used during the winter months. Within the vicinity of Brownlee Reservoir, elevation, climate and vegetation composition combine to make this a critical wintering area for big game species (Edelmann et al. 2001). Elevations along the reservoir are typically much lower than the surrounding mountainsides, and winters are relatively mild. In addition, the variable topography allows animals to access south- and west- facing slopes where snow accumulation and persistence is further reduced. These warmer slopes also result in significant fall, winter and early spring regrowth of annual grasses, which may constitute the bulk of forage, at least for mule deer (Edelmann 2002). While the low elevation areas along sections of Brownlee Reservoir are important wintering areas, the proximity of animals to the reservoir makes movement across embayments and narrow sections of the reservoir probable. While such movements in open water are unlikely problematic (Simpson 1987, Boroski and Barrett 1999), movements when ice has formed can result in mortality of individuals that break through the ice (Kelsall 1960, Skoog 1968, Bos 1973, Skogland and Molmen 1980, Bedrossian et al. 1984, USDI 1985, IDFG 1986, Miller and Gunn 1986). Additionally, animals weakened or injured by struggling in the water after breaking through ice may become more vulnerable to predation (Banfield 1954, Miller and Gunn 1986). Ice is typically considered safe for human foot travel when greater than 10 cm (4 in) in thickness (various state and province recommendations). Little information exists on ice thickness that is safe for big game animals, but ice as thin as 2.5 cm (1 in) has been reported to permit passage of caribou (Kelsall 1960). Since adult big game animals typically weigh as much or more than a human, safe ice for passage by large wildlife is probably similar to that recommended for humans. Also deer traveling on “safe” ice may become predisposed to predation (especially coyotes). Incidental observations at Brownlee Reservoir (F. B. Edelmann, personal communication) suggest that coyotes may pursue deer onto ice where deer are easily captured after loosing footing. This may especially be the case during severe winters when the deer and coyotes are concentrated close to the reservoir and extensive icing is probable. Expanses of ice may also entice deer travel when concentrated at low elevations.

1.2. Justification The Hells Canyon hydroelectric project (FERC License No. 197) occurs in the midst of very important winter range for mule deer, elk and bighorn sheep. Natural resource agencies in Idaho and Oregon have expressed concern that operation and

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maintenance of the Hells Canyon Complex of reservoirs (Brownlee, Oxbow and Hells Canyon) may have negative influence on big game populations wintering in Hells Canyon. One voiced concern suggested that the proximity of big game mammals to the reservoirs in winter might result in a negative impact due to ice formation. Conditions that produce thin ice or sunken ice could have negative effects on wildlife by entrapping individuals. This study was conducted in response to this concern, and focused on the differences in ice formation with different reservoir management alternatives. Because field investigations indicate that ice formation apparently does not occur on Oxbow and Hells Canyon reservoirs, only ice formation on Brownlee Reservoir was considered as potentially affecting big game wildlife. This study of the ice formation on Brownlee Reservoir was proposed as part of a comprehensive investigation of wildlife resources in Hells Canyon.

1.3. Objectives The overall objective of this study is to assess the potential effect of ice formation on Brownlee Reservoir on big game populations. Specific objectives were:

1) Determine the distribution of mule deer, elk and bighorn sheep during winter months within the vicinity of Brownlee Reservoir; 2) Assess and compare the potential for ice formation on Brownlee Reservoir under two management scenarios: proposed operations and run-of-river; 3) Assess the period when ice formation is most likely on Brownlee Reservoir, and the frequency of years that ice formation may occur; 4) Assess the distribution of mule deer, elk and bighorn sheep relative to areas of ice formation on Brownlee Reservoir;

Two research efforts were conducted to meet these objectives. The first was a comprehensive field survey of wintering mule deer, and opportunistic surveys for elk and bighorn sheep, in the vicinity of Brownlee Reservoir (see Edelmann et al. 2001). The second effort was to assess ice formation on the reservoir. This effort was conducted using a detailed water quality reservoir simulation model that predicted ice formation as affected by flow, air temperature, reservoir water temperatures and absorbed solar radiation.

2.0 METHODS 2.1. Study Area The Hells Canyon Complex of reservoirs on the Snake River lies along the border between Oregon and Idaho within the southern portion of Hells Canyon. Brownlee Reservoir is the most upstream of the three reservoirs and has the largest surface area. This narrow reservoir extends for approximately 89 km (55 mi) with the dam located at the north end (Figure 1). Brownlee Reservoir is steep sided and has a maximum depth approaching 90 m (300 ft) near the dam.

3 Brownlee Reservoir Ice—Effects on Big Game

The steep terrain above the reservoir has many small canyons that reach the reservoir. These small canyons form embayments along the edges of the reservoir of various sizes and shapes. Because the embayments are somewhat more sheltered from winds, they are much more likely to form ice than the main reservoir body (Shulyakovskii 1966). There are also areas where wildlife are more apt to cross when covered with ice as they move between adjacent hillsides. In addition to the numerous embayments, the Powder River creates a large arm of the reservoir. This arm is approximately 15 km (9.3 mi) long. The upper end of the arm (approximately 3.5 km) is in an open valley, while much of the rest is a narrow canyon. The upper end is protected from strong canyon winds and often forms ice during the winter months. Additional information on the study area is contained in Edelmann et al. (2001) and Harrison et al. (1999).

2.2. Big Game Surveys Edelmann et al. (2001) conducted aerial surveys of mule deer, elk and bighorn sheep in March of 1998, 2000 and 2001 and counted numbers of animals within 54 survey areas adjacent to Brownlee Reservoir (Figure 2). The surveys were conducted 20−26 March 1998, 10−17 March 2000 and 5−15 March 2001. Surveys were not conducted in 1999 because a helicopter was not available. These surveys were not censuses, but rather used as indicators of relative distributions of big game species and populations wintering near Brownlee Reservoir. Survey data were assumed to represent populations expected to be exposed to reservoir icing. The surveys were conducted using a Hiller 12E helicopter with two observers and a pilot. Helicopter elevation was maintained approximately 60−90 m (200−300 ft) above ground level, but adjusted when necessary for safety. Search paths began at the reservoir shoreline within a survey area and were flown at 150 m (500 ft) contours until the top of the survey area was reached or deep snow was encountered. Numbers of 1) adult and fawn deer; 2) bull, cow, and calf elk; and 3) ram, ewe, and lamb bighorn sheep were recorded in each survey area. Details on survey methods are contained in Edelmann et al. (2001) and Edelmann (2002).

2.3. Reservoir Ice Model Simulations of reservoir ice formation were conducted using the two-dimensional laterally averaged, hydrodynamic and water quality model, CE-QUAL-W2 (Cole and Buchak 1995). This model is used to simulate water movement within and through a reservoir, and reservoir temperature and water quality profiles. It also has routines to predict ice formation, thickness, persistence, and melt. The model structure represents a reservoir as longitudinal bands of defined length and width, and layers of defined depth. The longitudinal segments and stacked layers results in the two-dimensional characteristic of this reservoir model. CE-QUAL-W2 is well suited for long, narrow water bodies like Brownlee Reservoir. Version 3.00 of this model was used as supplied by IPC. CE-QUAL-W2 was developed to simulate water surface elevations, water velocity, temperature, and chemical and biological constituents for reservoirs. It permits multiple inflows and outflows, and can effectively be structured to account for multiple

4 Brownlee Reservoir Ice—Effects on Big Game

branches. This model was selected for this work because it had appropriate provisions for modeling ice formation, and the model has been used and calibrated for use on Brownlee Reservoir by IPC.

2.3.1. Basic Model Structure and Calibration The implementation of CE-QUAL-W2 is a multi-step process which includes defining reservoir geometry and various model coefficients, and developing driving parameters. Much of this development was conducted by IPC and is detailed in Harrison et al. (1999). The following is a summary of the model implementation (parameterization and calibration) conducted by IPC. The implementation of CE-QUAL-W2 for Brownlee reservoir included the portion of the Snake River from the dam (RM 284.6) to the head of the reservoir (RM 335). The geometry for the reservoir included two branches, the main reservoir and the Powder River arm (Figures 2a,b). The main reservoir branch was divided into 26 longitudinal segments (Figures 2a,b, Nos. 2−27) that were 3.2 km (2 mi) in length except for the first and last segments, which were shorter. The Powder River arm was divided into eight longitudinal segments (Figure 2a, Nos. 30−37) varying in length from 1.0 to 2.7 km (1 to 1.7 mi). The thickness of horizontal layers was constant throughout the reservoir at 2.0 m (6.5 ft). This reservoir bathymetry was developed from topographic maps and bathymetric data in Harrison et al. (1999). Input data for calibrations and simulations were obtained from a variety of sources. Water inflows to Brownlee Reservoir from the Snake, Powder, and Burnt rivers were obtained from measurements by USGS. Outflows from three structures on Brownlee Dam (5 penstocks, 3 gates opening into spillway, 4 gates at top of spillway) were obtained from IPC operations at the dam. Meteorological data (air temperature, dewpoint temperature, wind speed, wind direction, cloud cover) was obtained from a weather station at the dam (after mid 1996), Parma, Idaho and Prairie City, Oregon. Biological and water quality parameters were collected from various samplings within the reservoir and inflow rivers. Calibration is essential to ensure that the predictions by CE-QUAL-W2 are similar to what occurs in the reservoir. Calibrations were conducted by IPC to ensure both that physical and biological/chemical predictions of the model matched measured data (see Harrison et al. 1999 for complete details). Model calibration initially focused on parameters that directly affect reservoir hydrodynamics. This initially entailed matching measured and predicted water surface elevations by fine-tuning inflow and outflow values. The next step was to ensure suitable water temperature predictions. This involved assessing coefficients of bottom friction and eddy viscosity, coefficients that affect the heat budget, and effective outlet flow. The final step was a calibration of water quality parameters. This calibration involved assessing organic matter partitioning and various first-order kinetic, rate and temperature coefficients. Dissolved oxygen was used as the primary indicator of suitable model coefficients.

2.3.2. Embayments Embayments along the reservoir edge were considered to be primary places for ice formation within the reservoir. These sheltered bays are subjected to less wind and are

5 Brownlee Reservoir Ice—Effects on Big Game

likely somewhat thermally isolated from the main reservoir body. Embayments occur most commonly where the reservoir flooded small canyons in steep terrain. Embayments were identified from topographic maps of the reservoir bathymetry. The length, maximum width, and surface area were measured for each embayment at full pool and for reservoir elevations at 3 m increments. A cluster analysis was performed to create categories of embayments based on geometric features of surface area and thalweg length. The analysis included all embayments measured at each 3 m depth increment as the size, shape and absolute position of embayments typically changed with water depth. The K-means cluster procedure (Everitt 1980) was used in this analysis. This procedure is most useful for forming a small number of clusters from a large number of observations. To include embayments in the bathymetric structure for CE-QUAL-W2, small branches were added to the main reservoir branch. The model structure allows only one branch to join within a reservoir segment, so only one embayment could be considered per reservoir segment per simulation run. These embayments were constructed as two segments, each one-half the measured thalweg length, and width appropriate to match the measured total embayment surface area.

2.3.3. Modeling Ice The model CE-QUAL-W2 has a detailed routine for calculating ice formation and melting on the surface of reservoirs. The ice cover submodel is based on heat exchange at the ice-air interface and ice-water interface, and heat fluxes through the ice. Ice formation requires that the surface water temperature has been lowered below the freezing point by water-air heat exchange processes. Negative surface water temperatures are then converted to an equivalent ice thickness. Once ice is formed, its thickness is based on 1) heat exchanges from the air through the ice to the underlying water, 2) the ice melt at the ice-air interface, and 3) ice melt and formation at the ice-water interface. While wind is considered in the heat exchange between air and surface water and affects surface water temperature, there is no provision for delaying or preventing ice formation due to wind-induced wave action. Details of the ice submodel in CE-QUAL-W2 are contained in Cole and Buchak (1995) The ice routine requires 6 coefficients which help regulate the rates of various physical processes (Table 1). These parameters are difficult to measure directly, and the default values provided with CE-QUAL-W2 were used. To assess the importance of these values on ice formation, a sensitivity analysis was performed (see Section 2.3.5).

2.3.4. Simulations Two reservoir operation scenarios were assessed in this report: proposed operations and run-of-river. Inflows, outflows and water surface elevations of both scenarios were defined by IPC. The proposed operations scenario simulated reservoir conditions under operational rules proposed by IPC to regulate flows out of Brownlee Dam during the next licensing period. The run-of-river scenario was designed to simulate full pool conditions (2,077 ft above mean sea level) where outflows from Brownlee Dam equaled inflows to the reservoir within the operational constraints of Brownlee Dam (Parkinson 2001). Simulations were conducted for years with three inflow levels from the Snake River as identified by IPC: low (1992), medium (1995) and high (1997). Snake River

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inflows in these years (Figure 3, upper) resulted in different hydrodynamics within the reservoir for the two flow scenarios, most obviously different patterns of reservoir water surface elevation (Figure 4). For the proposed operations scenario, water surface elevation had the greatest fluctuation in the high flow year and least in the low flow year. Run-of-river operations with full pool had minimal water surface elevation fluctuations in the three years. The model simulations with CE-QUAL-W2 to assess ice formation were conducted to specifically address the following questions:

1) Do ice formation, persistence, and melting patterns differ between operational scenarios (i.e., proposed and full pool run-of-river) and among inflow years (i.e., High = 1997, Medium = 1995, and Low = 1992)? 2) Does the period of unsafe ice (< 10 cm thickness) differ in length between operational scenarios? 3) Do ice formation, persistence, and melting patterns differ with the physical characteristics of embayments? 4) Does rising or falling water surface affect ice formation? 5) Do spatial patterns of ice formation differ between operational scenarios?

The simulations were conducted primarily to assess differences in ice formation, thickness and persistence between the two operational scenarios. The intent was not to predict exactly when ice would form or to determine with high accuracy ice thickness. Instead the intent of this work was to determine the important differences in icing characteristics of the two reservoir operation scenarios. Ice forms when air temperatures are sufficient to cool surface waters to below the freezing point since temperatures of inflow waters to the reservoir are above the freezing point. From the accumulated weather data (1992−2001), periods, when air temperatures were below freezing for most of the day and night, occur primarily in the period December through February. Thus, these months were considered to be the period when ice formation was most likely to occur, and simulations were conducted for reservoir conditions during these months only. During December through February, temperatures fluctuate greatly both within a month and among years. This suggests that there are periods of ice formation, with variable persistence followed by periods of melting, a pattern supported by anecdotal observations. Initial model simulations using measured meteorological data produced similar patterns of ice formation and melting as cold air temperatures would initiate freezing and subsequent warmer temperatures would result in ice melt. Because of the variability in weather among the three study years (and among all years of accumulated weather data), it was decided that creating a fixed freezing and thawing cycle would permit the best evaluation of ice formation under different inflow and dam operational scenarios. Two 20-day freeze/thaw cycles were developed with a seven day freezing cycle: a “warm” cycle where the daily air temperatures varied between –6.1 and 1.3 °C, and a “cold” cycle where the daily air temperatures varied between –20.4 and –8.7 °C (Figure 5). The meteorological data used for these cycles were measured, but the middle seven days were a repetition of the coldest day of the cycle. Both of these cycles resulted in ice formation, persistence and melting for most of

7 Brownlee Reservoir Ice—Effects on Big Game

the reservoir embayments. These freeze/thaw cycles were then used as meteorological inputs to the model for 20-day periods in December, January and February for each of the three flow years and two operational scenarios (Figure 3). With the exception of the meteorological input data, all other model input variables for simulations were those developed by IPC for the simulated periods during the years 1992, 1995 and 1997 (see Harrison et al. 1999). Starting reservoir temperature profiles for all three simulation months were assumed to be the same and were the values discussed in Harrison et al. (1999). Embayments were added to the model structure as needed as described in Section 2.3.2. Because reservoir water surface elevations under proposed operations changed during the simulations periods (Figure 4), the effect of rising or falling water levels on ice formation could be assessed. For both the January and February simulation periods, the reservoir water surface elevation declined during the medium and high flow years. In the December periods for all simulations, the reservoir water surface elevations increased. Differences in ice formation between the proposed operations and run-of-river (where water surface elevations did not change) were used to assess the effect of rising or falling reservoir water surface elevations on ice formation and persistence.

2.3.5. Sensitivity Analysis Sensitivity analyses are typically conducted to determine the effect of coefficients that were difficult to measure on simulation outputs. In the ice submodel, six parameters are defined by the user, none of which are easily measured. A sensitivity analysis was conducted to assess the effects of these coefficients on the development of ice and on the differences between the two flow scenarios. Coefficient values were changed by ± 30−100% for each of the six parameters listed in Table 1.

2.3.6. Model Validation Model validation is used to determine whether the simulation results match measured values. Validation was used to assess:

1) whether surface water temperatures corresponded appropriately to ice formation, 2) simulated and measured differences between main channel and embayment surface water temperatures, and 3) whether simulated temperature profiles where ice formed were realistic.

Water temperatures were measured at 12 locations (3 in main reservoir body, 8 embayments, 1 in upper Powder River arm) on 12 days in the period January through March, 2001 (Figure 6). Temperature was measured at the water surface, 5m depth, and 10 m depth with a Hydrolab. Ice formation was noted at the time of measurement. These measurements were compared to simulated ice and temperature patterns for the proposed operations scenario.

2.3.7. Assessing timing of ice formation and thawing Wildlife is most vulnerable to ice-related mortality when they cross the reservoir during periods with thin ice and periods when sheet ice breaks up in spring. An analysis was conducted to assess whether these periods of vulnerability coincided with periods of

8 Brownlee Reservoir Ice—Effects on Big Game

big game migration and reservoir crossing patterns. This analysis included an assessment of winter temperature patterns, observed periods of ice formation and thawing, and simulations of ice formation. Records of ice formation on the main body of Brownlee Reservoir and in the Powder River arm have not been kept through time. Only during the period January to March 2001 (see Section 2.3.6), were such records maintained. This period fell during an unusually mild period of winters (Edelmann et al. 2001, Edelmann 2002), and is not likely representative of the timing of ice formation in the reservoir in many years. However, the reservoir characteristics when ice formation occurred should reflect the conditions when ice is likely to form. Air temperature patterns at Brownlee Dam coinciding with ice formation in embayments and within the Powder River arm were assessed. These were compared with simulations using CE-QUAL-W2 to determine when ice formation and ice sheet thawing was most likely using the “warm” cycle air temperature data adjusted upward or downward by a uniform temperature (range −5 to 5 °C from the original “warm” cycle temperatures). These temperature patterns were then assessed in air temperature data collected from the Brownlee Dam during the period December 1−April 15 for the years 1966−2001. Dates in which thin or thawing ice were most probable were then identified and compared to periods of mule deer migration and observed reservoir crossing (Edelmann 2002).

3.0 RESULTS

3.1. Big Game Surveys

3.1.1. Mule Deer Mule deer were observed in March surveys in all 54 survey areas along Brownlee Reservoir (Figure 7). Total number of deer observed ranged from 9,262 in 1998 to 12,097 in 2001, and the density increased from 7.8 to 10.1 deer/km2. The 30% increase was predominately due to greater numbers of fawns each year. Approximately 71−75% of the deer observed were classified as adult deer each year for a fawn to 100 adult ratio of 31−39 (see Edelmann et al. 2001). Densities of deer varied among survey areas, ranging from 1.6 to 20.1 deer/km2 averaged for the three survey years (Figure 7). Densities of deer adjacent to the reservoir tended to increase in survey areas near the north end of the reservoir. Studies of mule deer movements using radio collars (see Edelmann 2002) indicated that about 75% of mule deer that winter in the vicinity of Brownlee Reservoir were migratory with the rest maintaining year-round residency near the reservoir. Spring migration from the wintering areas adjacent to the reservoir to higher elevations tended to occur in April, while in the fall, return migrations occurred into late December. One distinct migration corridor involving Brownlee Reservoir was identified; animals summering in the Wallowa Mountains were found to migrate from winter-activity areas adjacent to Brownlee Reservoir and the Powder River arm. Mule deer were found to cross the reservoir primarily during three of the four seasons: spring, fall and winter (see Edelmann 2002). These crossings occurred primarily

9 Brownlee Reservoir Ice—Effects on Big Game

across the Powder River arm and the downstream half of the reservoir. Many deer were observed to make multiple crossings. Some of these crossings occurred when the Powder River arm was covered with ice. Migrant deer made about two-thirds of the reservoir crossings. No direct mortalities of deer were observed due to animal falling through the ice (see Edelmann 2002), although ice was primarily confined to the Powder River arm during the three years of study. One radio-tagged doe was killed by coyotes while trying to cross the Powder River arm while it was frozen. Two radio-tagged fawns drowned while trying to cross Brownlee and Oxbow reservoirs. Four other radio-tagged deer were killed by predators within a day of crossing the reservoir. Additional predation of deer while crossing the ice was observed on Brownlee Reservoir, and this predation appeared to be enhanced by the inability of deer to elude predators on the slippery ice surface (F. B. Edelmann, personal communication). These observations suggest that deer may be more susceptible to predation when crossing reservoir ice.

3.1.2. Elk Elk were observed in 25 of the 54 survey areas (Figure 8). Total elk observed ranged from 980 in 1988 to 1,261 in 2000, but declined to 1,003 in 2001. This decline was largely due to few elk calves being observed in 2001 versus 2000. Densities ranged from 0.02 to 8.2 elk/km2 in survey areas where elk were observed when averaged for the three survey years. Survey areas with high densities of elk were distributed sporadically along the entire length of Brownlee Reservoir (Figure 8). Higher density areas were more prevalent on the Idaho side of the reservoir near Brownlee Dam.

3.1.3. Bighorn Sheep Rocky Mountain bighorn sheep were observed in only 7 of the 54 survey units (Figure 9). Total sheep observed declined from 75 to 57 from 1998 to 2001. The decline was largely in the number of adult rams. Numbers of lambs ranged from 3 to 11, while numbers of ewes remained relatively constant. Within survey units where bighorn sheep were observed, densities ranged from 0.01 to 1.2 animals/km2 (Figure 9). Most bighorn sheep were found in survey areas just north of Brownlee Dam. While few survey areas contained sheep, they were consistently found in the same areas each year. This suggests a high fidelity to suitable habitat.

3.2. Embayments Eighty embayments were identified when the reservoir was at full reservoir pool (Figure 2). Over half (47) of these embayments were located within the 16 km (10 mi) of the reservoir closest to Brownlee Dam (2.9 embayments/km). Few embayments (3) were located within upper 32 km (20 mi) of the reservoir (0.1 embayments/km). Moderate numbers of embayments occurred within the rest of the reservoir (0.8 embayments/km). The total area of these embayments at full pool was approximately 150 hectares (370 acres). The largest of these embayments covered an area of approximately 8.4 hectares (20.8 acres). The number and area of embayments declined with the water surface elevation of the reservoir (Figure 10). Area declined much faster and at a water surface elevation of 600 m above mean sea level, little area of embayments existed.

10 Brownlee Reservoir Ice—Effects on Big Game

A cluster analysis was conducted to categorize embayments for simulating ice formation. Clustering embayments into four groups resulted in explaining over 87% of the variation in the cluster variables, and was selected as a suitable number of clusters. More clusters explained little of the remaining variability. Although four groups were defined, the cluster analysis indicated that there was a relatively continuous distribution of embayments from ones with relatively small area (mean = 0.2 hectares) and short thalweg length, to large embayments (mean = 54 hectares) with longer thalweg length. As expected from this cluster analysis, the embayment area and thalweg length were highly correlated (r = 0.90, p < 0.0001).

3.3. Simulations

3.3.1. Embayments Simulations were conducted for embayments that contained thalweg and total area characteristics of the means of the four embayment groups identified by cluster analysis (Table 2). Simulated ice duration and thickness indicates that the pattern of ice formation was relatively insensitive to the size of embayment (Figure 11). This suggests that the hydrological linkage of the main reservoir to the embayment may be less important than the air-water, air-ice and ice-water heat exchange at the surface of the embayment. Local air temperature likely is most important in affecting ice formation. Wave action from the main reservoir, however, likely affects ice formation in the embayments, and protected embayments might have greater potential for ice formation. Size of embayment would likely be less of an issue than location relative to wave patterns. The model CE-QUAL-W2 has no provision for wave action affecting ice formation.

3.3.2. Comparison between Operational Scenarios Simulations were conducted to evaluate ice formation in 1) embayments, 2) the Powder River arm, and 3) the main reservoir under the two operational scenarios: proposed operations and run-of-river. Simulations were conducted using both the “warm” freeze and “cold” freeze weather periods for 20-day periods in December, January and February. Low, medium and high inflow years from the Snake River were considered.

Embayments Simulations for embayments were done for a single embayment placed into segments 3, 6, 10, 16, 20, 24 and 27 (Figures 2a,b). These segments were representative of the longitudinal distribution of segments, and all contained embayments. Because of the very similar ice formation patterns for the four clusters of embayments (Figure 11), a single embayment type was used, having thalweg and area characteristics of Cluster 2 (Table 2). The simulations for the “cold” freeze period for the three inflow years (low, medium and high) showed differences in ice formation patterns by river segment, but little difference by reservoir operational scenario (Figures 12a,b,c). Ice formation did not occur in the embayment in the most upstream reservoir segment (3) in any of these simulations, and the duration of ice on the reservoir generally decreased with distance from Brownlee Dam. This was due to the inflow temperatures of water from the Snake River, which cooled as it flowed through the reservoir. Higher inflows (Figure 12c) reduced the number of segments where ice formed (due to warming of reservoir waters

11 Brownlee Reservoir Ice—Effects on Big Game

with less residence time), but ice still formed in the segments with the most embayments located close to Brownlee Dam. The number of days when ice thickness was not safe for human foot travel (< 10 cm) was also similar between the two operational scenarios (Figures 12a,b,c) for all three flow years. The maximum thickness of ice during the freeze period was very similar between operational scenarios (Figure 13). When differences in ice thickness did occur, slightly thinner maximum ice thickness and one more day of ice less than 10 cm were typically exhibited by the proposed operations scenario. In addition, the proposed operations scenario for some of the simulated embayments had an extra day of ice persistence. Very similar results were found for simulations using the “warm” freeze period (Figures 14a,b,c). However, the maximum ice thickness was much less, with the thickness never reaching the “safe” 10 cm in any of the simulations (Figure 15). The number of days was also less in the “warm” freeze period as would be expected. Ice did not form in segments 3, 6, and 10 closest to the Snake River inflow. Again, relatively warm inflow temperatures reduced ice formation.

Powder River The Powder River arm of Brownlee Reservoir showed ice formation patterns for both operational scenarios that were quite similar to patterns for the embayments in reservoir segments 20, 24 and 27. This was true for both the “cold” (Figures 16a,b,c; Figure 17) and “warm” freeze simulation periods (Figures 18a,b,c; Figure 19). The only exception to this was the minimal ice formation during December in the low flow period where relatively warm temperatures from the main reservoir may have helped keep temperatures above those necessary for freezing (Figures 16a, 18a). In addition during the “warm” freeze period, the Powder River inflows may have also helped maintain temperatures above freezing in the upper Powder River arm (Figure 18a). During the warm freeze period, ice thickness was always less than the desired thickness for safe passage (< 10 cm). For the “cold” freeze period, ice thickness was greater than the 10 cm for much of the ice period. The largest differences in ice patterns between the two flow scenarios were from February of the high flow year (Figure 18c, bottom). The proposed operations scenario had greater ice duration for the middle segments of the Powder River arm. This was possibly due to less exchange with the main reservoir with lower and falling reservoir levels (Figure 4). Reduced exchange may have permitted greater cooling of these segments. The lack of ice formation in the uppermost segment at this time was likely due to relatively warm inflow waters from the Powder River warming the upper segment which has lower total volume with reduced water surface elevation.

Main Reservoir Simulations with CE-QUAL-W2 also indicated ice formation within the main reservoir. As discussed earlier, CE-QUAL-W2 does not have provisions to reduce ice formation with wind. Wind in the model only affects the mixing of reservoir waters. Because the main reservoir is subjected to greater winds and is more exposed, it was felt that ice formation under the “warm” freeze period was not likely. However, if winds were minimal, the “cold” freeze period might produce ice formation. As with simulated ice formation in embayments and the Powder River arm, there was little difference between the two operational scenarios (Figures 20a,b,c; Figure 21). Little or no ice formed during

12 Brownlee Reservoir Ice—Effects on Big Game

the December months in any of the years due to warmer inflow temperatures from the Snake River. Ice also did not form in the upstream reservoir segments for any of the simulations due to relatively warm inflow temperatures from the Snake River. Maximum predicted ice thickness was similar to that predicted for the embayments and the Powder River arm for the “cold” freeze period.

3.3.3. Effect of Rising and Falling Water Levels on Ice Formation Simulations to specifically assess the effect of rising and falling reservoir water surface elevations were not conducted. However, the proposed operations scenarios in the medium (1995) and high (1997) flow years had rising and falling reservoir levels during winter inherent to the simulations. Comparing ice formation patterns for these periods with patterns for the run-of-river simulations for the same time period gave a good indication of the effects of rising and falling water surface elevations.

During January and February, reservoir water surface levels declined while in December they increased for the proposed operations scenario (Figure 4). Rates of decrease in reservoir water surface elevation were 0.15 m/d in January and February in the medium flow year 1995, and 0.15 m/d in the high flow year 1997. In December, water surface elevations increased 0.15 m/d in the medium flow year 1995 and 0.15 m/d in the high flow year 1997. As discussed above, simulation results were quite similar between the two operational scenarios for both medium and high flow years for embayments, the Powder River arm and the main reservoir. This suggests that increasing and decreasing water surface elevations have similar ice formation patterns to the situation when water surface elevations are stable, at least for the measured rates of change in water surface elevation.

3.3.4. Ice Formation and Big Game Distribution The pattern of ice formation in embayments and the Powder River arm was found to be similar between the two operations scenarios. For embayments, simulations indicated that ice formation was most likely to occur in the downstream two-thirds of the reservoir. Ice formation in the Powder River occurred under similar conditions to these embayments. As outlined above, most of the embayments are found in the downstream third of the reservoir (Figure 2a,b). This region of the reservoir and the Powder River arm are adjacent to areas where mule deer are concentrated in late winter (Figure 7), and are areas where deer have been observed to cross the reservoir (see Section 3.1.1). Several of the higher concentration areas for elk are also located in areas adjacent to this portion of the reservoir (Figure 8), but elk do not tend to concentrate near the shore (F. B. Edelmann, personal communication). Bighorn sheep are even less closely associated with the lower reservoir or the Powder River arm (Figure 9) than elk.

3.4. Sensitivity Analyses The sensitivity of coefficients of the ice submodel of CE-QUAL-W2 to the simulated ice patterns was conducted. The duration of ice formation and ice thickness were compared for 14 main reservoir segments, 8 Powder River arm segments and embayments located in 7 main reservoir segments. This analysis indicates that the simulated duration and thickness of ice was minimally affected by the selection of

13 Brownlee Reservoir Ice—Effects on Big Game

coefficient values (Table 3). While coefficient values were changed 30−100%, the maximum change in simulated ice thickness was only 6%. The number of days necessary for ice formation, or periods with ice thickness less than 10 cm, changed maximally by one day. The only exception was one segment of one embayment where ice formed with a 33% increase in BETAI (fraction of solar radiation absorbed by ice) while in the original simulation, ice did not form. Interactions among coefficients might result in greater differences. However, there was no indication of this. Simulations were also conducted where all coefficient values were changed to the low or high values (Table 1). Maximum differences in duration and ice thickness were the same or less for changes in individual parameters (Table 3).

3.5. Model Validation Model validation was used to compare measured system responses to model simulations. Measurements of reservoir temperatures and ice formation were conducted in January−March, 2001. Unfortunately, this winter period, as well as the other winters during the study, was relatively mild, and ice formation was minimal except in the Powder River arm. However, several important characteristics of the measured data corresponded to simulated responses. Simulations indicated that ice formed when surface water temperatures were below freezing, and ice could persist when surface waters reached at least 1.3 °C after having formed. These results were consistent with measured values where ice was found with surface temperatures below freezing and thin ice persisting with surface water temperatures up to 1.9 °C. Water temperature profiles of the measured data to 10 m depth were relatively constant, varying less than 1 °C except where ice was formed. When ice was formed, the surface water temperature often differed from temperatures at 5 and 10 m by 2−4 °C. This was consistent with simulated results where these temperature differences were up to 2.6 °C. Relatively uniform temperature profiles are consistent with significant mixing of waters, likely enhanced by winds. However, when conditions were suitable for ice formation, air-water heat exchange cooled only the surface of the water resulting in ice formation. Measured temperature profiles were similar between main river and nearby embayments, although embayments were often a few tenths of a degree cooler than the nearby main channel measurements. This was consistent with simulated results. When ice was formed in the embayments, surface water temperatures in the embayments were often 1−2 °C cooler than the main reservoir. Surface temperatures in the measured profiles for main reservoir sites never deviated from the 5−10 m temperatures by 1 °C, strongly suggesting the effects of wind induced mixing. Thus, ice formation in embayments as measured was most likely due to less wave action as hypothesized above, and not differences in temperatures (except at the surface). One significant difference between measured data and model simulations was the greater duration and thickness of ice in the Powder River arm than observed in embayments along the main reservoir. Simulations suggested similar ice formation patterns between the Powder River and embayments in the lower half of the reservoir. It is likely, however, the greater ice persistence measured for the Powder River was due to two factors. First, there were likely lower nighttime air temperatures in the confined

14 Brownlee Reservoir Ice—Effects on Big Game

valley containing the Powder River arm. Snow cover likely enhanced this temperature difference. In contrast, the main Brownlee Reservoir when not frozen likely warms the air within its immediate vicinity. Second, the Powder River arm may be more sheltered from strong winds. This would reduce mixing of water and permit more cooling of the surface water. Also, less wind may reduce the wave action that can break and dissolve thin ice.

3.6. Periods of Ice Formation and Thawing Ice was observed to form in both the Powder River arm and at least one embayment following three nights when minimum air temperatures at Brownlee Dam reached about −5 °C (Figure 22). This temperature pattern coincided closely with CE-QUAL-W2 simulation results which indicated that about four nights with −5 °C would be sufficient to form the thin ice that was observed. These simulations also suggested that warmer temperatures (−3 °C or warmer nighttime minimum) would produce minimal ice, and that colder temperature (−7 °C or colder nighttime minimum) would form ice that exceeded 10 cm in thickness. Thick ice (> 10 cm) was observed in the Powder River arm after four nights with minimums around −7 °C (Figure 22), consistent with model simulations. Based on these results, thin ice could be expected to form when nighttime temperatures were at least −5 °C for four consecutive nights, and thick ice would form when temperatures were at least −7 °C for a similar period. An analysis of the nighttime minimum temperature data collected at Brownlee Dam was conducted to determine when these two temperature criteria were met, and the frequency of years such criteria occurred. Similar analyses were conducted for the minimum temperatures ranging from −3 °C to −22 °C (Figure 23, upper). These results indicate that the range of dates and median date over which these temperature patterns first occurred were similar for minimum temperatures ranging from −5 °C to −17 °C. The predicted date of initial ice formation ranged from early December to early February, with the median date at the end of December. The frequency of years (35 years total) these temperature criteria were met declined with temperature, ranging from 89% for −5 °C to 14% for −17 °C (Figure 23, upper). This indicates that the potential for thin ice formation (< 10 cm) occurs most years and thick ice formation (> 10 cm) could occur over 70% of the years. The period of spring thawing and break up of ice was also assessed. Open water was found in the Powder River arm after 5 days of minimum air temperatures at Brownlee Dam exceeding 0 °C (Figure 22). Simulations with CE-QUAL-W2 indicate that thawing of ice would occur within seven days with minimum temperatures exceeding 0 °C. Seven-day periods occurring after 15-February were assessed for the air temperature data for Brownlee Dam for the 35-year period of record. Such periods were found to end as early as the third week of February to as late as the first week of April, with a relatively uniform distribution of occurrence during the 35-year period (Figure 23, lower). It is important to note that these predicted periods of ice formation and thawing reflect ideal conditions of ice formation, and that air temperature at Brownlee Dam would reflect conditions across much of the reservoir and in the Powder River arm. These assumptions, however, are likely not fully met, but the estimated time window of initial thin ice formation and thawing are probably representative. As discussed above, wind

15 Brownlee Reservoir Ice—Effects on Big Game

conditions within the main reservoir have a sizable influence on the ice formation process. Thus, while air temperature conditions for ice formation may occur, ice may not form within the main reservoir, even in relatively protected embayments. But as the minimum air temperature drops, the potential for ice formation in the main reservoir will increase even with wind movement. However, these conditions would still occur within the same time period as predicted for ice formation with warmer temperatures, just at a lower frequency (Figure 23, upper). Within the Powder River arm, minimum nighttime air temperatures may be lower than measured at Brownlee Dam due to the confined nature of the basin surrounding this arm of water and the presence of much less temperature-moderating surface water than at the dam site. This would mean ice could form within the Powder River arm when minimum air temperatures at Brownlee Dam appear too warm for ice formation. The similarity of the timing of the initial 4-day periods with minimums of −3 °C and colder temperatures suggest that this confined portion of the reservoir may have similar time periods of initial ice formation to the rest of the reservoir (Figure 23, upper). In addition, in early December, water temperatures would often be sufficiently warm to reduce ice formation, delaying the date of initial thin ice formation. The frequency of thin or thick ice formation on the Powder River arm, however, may be greater than predicted in Figure 23 (upper) due to temperatures somewhat colder than measured at Brownlee Dam. Anecdotal data suggests the upper Powder River arm freezes nearly every year. The window estimate for initial thin ice formation and thawing is likely conservative. Because of relatively warm reservoir water temperatures in December, initial ice formation is likely delayed some until cold air temperatures reduce the water temperature sufficiently. Thawing may also occur earlier than suggested. Measured data indicated thawing with only five consecutive days of minimum air temperatures above 0 °C, while simulations were conducted using seven consecutive days. In addition, several days with nighttime minimums above 0 °C with one or two nights where temperatures dipped just below freezing could also be sequences which could result in ice break up, but these periods would not meet the seven-consecutive-day criteria used in this analysis. Colder air temperatures in the Powder River arm could delay ice thawing and cause the actual date of ice thawing to be later than predicted by this analysis. However, in the spring period, temperature inversions which significantly decrease air temperatures in the Powder River arm would be rare, especially when regional nighttime air temperatures are above freezing.

4.0 DISCUSSION

4.1. Ice Formation Accurately predicting ice formation and patterns on reservoirs is a difficult task. Thermal conditions necessary for ice formation are determined by absorption of radiant energy from the sun, heat exchange with the atmosphere and reservoir bottom, and the redistribution of heat in the water via transport by currents and turbulent mixing (Pivovarov 1973). These factors are complicated by intermittent cloud cover, small-scale climatic differences, water depth, inflow volume and temperature, and wind which affect

16 Brownlee Reservoir Ice—Effects on Big Game

both turbulent mixing and molecular alignment necessary for ice formation (Shulyakovskii 1966, Pivovarov 1973). On reservoirs, ice forms first in shallow areas and embayments that are protected from wind. Stable ice forms in the main reservoir body only when conditions throughout much of the open water become simultaneously suitable for ice formation (Shulyakovskii 1966). Portions of the reservoir affected by river inflows act more like rivers than lakes, while areas buffered from these inputs have thermal dynamics characteristic of lakes. The timing of ice formation and persistence can thus vary greatly depending on location within the reservoir. Winds which become funneled within narrow canyons can greatly increase the wind speed (Harrison et al. 1999) and reduce the potential for ice formation, or rapidly break up thin ice which has formed (Shulyakovskii 1966). The results of simulations conducted in this study are consistent with the perspective that ice formation patterns can vary within a reservoir. Ice was much more likely to form in the downstream two-thirds of the reservoir than in the upstream third, both in the main channel (Figures 20a,b,c) and the associated embayments (Figures 12a,b,c; Figures 14a,b,c). The inflow of the Snake River affects the upper third much more than the lower portions both in terms of having relatively warmer temperatures and having a significant effect on the heat exchange processes by affecting turbulent mixing. In addition, the shallower and protected Powder River arm exhibited ice formation patterns that would be expected for a lake or protected embayment (Figures 16a,b,c; Figures 18a,b,c). The greater ice thickness and persistence measured in the Powder River during winter 2001 (model validation data) as compared to main reservoir embayments strongly suggests that the Powder River arm is subjected to less wind and likely lower nighttime temperatures. The large reservoir body likely ameliorates nighttime temperatures unless it is completely frozen over (which is rare for Brownlee Reservoir), while snow cover in the Powder River valley likely enhances nighttime cooling. Describing such differences in wind and temperatures between the Powder River arm and the main reservoir was beyond the scope of this project. The sensitivity analyses for coefficients used in the ice submodel suggests that factors not incorporated into the model (e.g., wave action, local air temperature differences) likely have greater influence on local ice formation patterns than the coefficient values selected. Although ice prediction may be imprecise, there was a high degree of similarity in duration and thickness of ice formation between the two operational scenarios. The reason for the similarity may be that ice formation is largely influenced by the local interaction of air temperature and surface water temperature. It appears that for these two operational scenarios, differences in lateral and vertical mixing of waters within the reservoir is not sufficient to greatly alter the pattern of ice formation. Other operational scenarios, however, may have different effects on mixing of waters within the reservoir and could have greater effect on ice formation. This would be most likely for scenarios when the inflow waters were a greater portion of the stored water and where water elevations fluctuated greatly. Both of these situations would result in greater lateral and vertical mixing of water within the reservoir and likely reduce ice formation. The proposed operations during the winter months include periods of rising and falling reservoir water surface elevations. These are due to inflows not equaling outflows, to store water or create storage volume for projected inflows. For these periods in all flow years (low, medium and high), the change in elevation of the water surface was not

17 Brownlee Reservoir Ice—Effects on Big Game

sufficient to significantly change ice formation or the duration of icing. While ice formed similarly to the situation with stable water surface elevations, increasing or decreasing water surface elevations could affect ice patterns. Increasing water surface elevations may result in ice breakup or in ice floating away from areas of formation (Shulyakovskii 1966), and reduce the effective stability of ice in embayments. Falling water surface elevations may also cause the ice to break up or the surface to sag, the latter having implications for wildlife to become stranded on the sagging ice. The analysis for the time when ice first forms and when ice sheets would thaw in the spring indicated that the window ice may be present stretches from early December to early April. However, the analysis of temperature patterns suggests that the time of initial ice formation and spring thawing are highly variable among years. At least for the Powder River arm where ice forming conditions are most optimal on Brownlee Reservoir, ice would be expected to form most winters, and would be expected to be of sufficient thickness to support the weight of wildlife. For the main body of the reservoir, ice formation is likely to be much less regular. During January−March 2001, ice formed only intermittently on some embayments within the main reservoir, and not at all in the main reservoir body. In contrast, the Powder River arm eventually formed ice > 10 cm thickness. This suggests that temperatures would have to be quite a bit colder during the winter before embayments or the main reservoir body would freeze and maintain ice. Also, periods of minimal wind would likely be needed to enhance ice formation. Given that four consecutive days at −7 °C were not sufficient for significant ice formation in embayments or the main reservoir body, periods of colder temperatures would be needed. Analyses suggest that these colder periods would occur less than half the years (Figure 23, upper). This is consistent with anecdotal observations of ice formation on Brownlee Reservoir (F. B. Edelmann, personal communication).

4.2. Effects on Big Game Ice on reservoirs can have two effects on wildlife: direct mortalities resulting from animals breaking through the ice, and increased predation risk. There is ample documentation that populations of big game mammals can suffer mortalities by breaking through ice on lakes and reservoirs (Banfield 1954, Kelsall 1960, Skoog 1968, Bos 1973, Skogland and Molmen 1980, Bedrossian et al. 1984, USDI 1985, IDFG 1986, Miller and Gunn 1986). Death is caused by exposure to the icy water, and possibly drowning (Skoog, 1968, Bos 1973, Miller and Gunn 1986). In addition, there are reports of animals breaking through ice and surviving (Banfield 1954, Wilk 1958, Miller and Gunn 1986). Miller and Gunn (1986) suggest that breaking through ice by barren-ground caribou (Rangifer tarandus groenlandicus) is not an uncommon or frightening experience. However, subsequent death of animals weakened or injured through extended struggling has been hypothesized. Banfield (1954) and Miller and Gunn (1986) suggest that such animals have an increased risk of predation. In addition, animals slipping on the ice may be at additional risk to predation when crossing the reservoir even though they do not break through the ice (Edelmann 2002). There are no written accounts, but a few anecdotal accounts (e.g., D. Humphrys, ODFW retired biologist) of big game animals dying in Brownlee Reservoir due to breaking through the ice. At Palisades Reservoir on the Snake River in Idaho, about ten

18 Brownlee Reservoir Ice—Effects on Big Game

elk die each year by breaking through the ice (IDFG 1986). Similarly, about six mule deer die breaking through ice at Anderson Ranch Reservoir in Idaho (IDFG 1986). This suggests that the potential for such mortalities at Brownlee Reservoir certainly exists. Several deer carcasses were observed floating in the reservoir each winter during this deer study (F. B. Edelmann, personal communication), but whether ice contributed to these mortalities is unknown. Certainly areas where mule deer regularly cross the reservoir and occur in high concentrations adjacent to the reservoir would be locations where mortality would be the greatest. These coincide with areas of the reservoir (Powder River arm and downstream half of the reservoir) where ice formation is most likely. Evidence from study at Brownlee Reservoir (Edelmann 2002) indicates that mule deer may suffer increased risk of predation with ice cover on the reservoir. Mule deer were observed being killed while crossing ice on the Powder River; loss of traction on the slippery surface was cited as a contributing factor. In addition, mule deer were killed within a day following swimming across the reservoir. This suggests that individuals that break through the ice might suffer similar increases in predation when fatigue becomes a factor. Quantifying this increased mortality is difficult. Animals killed by predators in these situations may already be weak from other factors and thus more susceptible to predation anyway. The significance of mortality of animals caused by breaking through reservoir ice or being additionally susceptible to predation is best assessed in terms of the effects on the whole population viability, stability and exploitable surplus. Such mortality is a major concern if it is sufficient to cause the population to suffer major declines in numbers, reduce hunting surpluses, or worse reach levels which make local extinction likely. However, if only a few animals die each year or every few years, there is little negative effect on the populations. Within Brownlee Reservoir, there appears to be relatively little mortality of deer, elk, or bighorn sheep due to reservoir ice formation as evidenced by the minimum of documented mortalities. Considering there are roughly 10,000 mule deer, and 1,000 elk, even a very low mortality rate of 1% would mean that 100 mule deer and 10 elk would die each winter. Certainly numbers of this magnitude would mean that mule deer would be regularly observed breaking through the ice and carcasses would be observed each year. Higher rates of mortality would mean an even greater potential for such observations. Small numbers of deer were found floating in the reservoir during the winter, but it is unknown if these animals simply drowned or additionally fell through the ice (F. B. Edelmann, personal communication). The apparent low mortality of mule deer found for Brownlee Reservoir is in spite of the fact that the areas of the reservoir with the greatest potential for ice formation (embayments and the Powder River arm) are located adjacent to uplands where mule deer are concentrated. The biggest potential for ice related mortality of wildlife would occur during severe winters, especially for mule deer. Severe winters would be periods when ice formation is most prevalent, certainly in the Powder River arm and main reservoir embayments. Deep snow cover would likely force animals closer to the reservoir and increase their likelihood for encounters with ice, and this would occur at a time when animals would be weakened by limited winter forage and movements through deep snow (Edelmann 2002). Shorelines form abrupt boundaries in the lower extents of the winter range, which interrupt escape terrain for the deer. Furthermore, the steep and broken

19 Brownlee Reservoir Ice—Effects on Big Game

shorelines (often due to shoreline slumping) appeared to increase predator capture efficiencies by allowing predators to trap deer against shoreline cliffs and on steep rocky shorelines where escape was nearly impossible (Edelmann 2002). Ice formation would likely add to the susceptibility of mule deer to predators in these situations. Edelmann et al. (2001) indicate that mule deer populations fluctuate in response to winter weather. Their evaluation indicates that declines in the populations corresponded with extreme low temperatures and high snowfall. Increased energy requirements with the extreme cold and forage buried by snow were listed as the primary causes of increased mortality. Observed declines were conservatively in the 10−20% range, but apparently can reach 40% in the most severe winters (Edelmann et al. 2001). Populations recovered rapidly from modest declines when subsequent winters had moderate conditions. Causes of deer mortality have not been monitored during a severe winter at Brownlee Reservoir, and it is difficult to ascertain how much additional mortality could result to the population. Certainly the persistence of the mule deer and elk populations in the vicinity of Brownlee Reservoir during the period of >40 years the reservoir has been in existence strongly suggests that ice induced mortality is not sufficient to greatly reduce population viability. However, a 10% additional icing mortality during a severe winter might be significant relative to exploitable surpluses of these game animals, reducing the hunting opportunities for a few years until the population rebounds. Evidence does not exist that mortality due to animals breaking through ice on Brownlee Reservoir would be significant under proposed operations at least for most winters. The infrequent severe winters at the reservoir would be the most likely for ice to affect mortality. Simulations conducted here suggest that the run-of-river operations scenario would have similar ice formation patterns to the proposed operations. This suggests that implementation of the run-of-river operational scenario would not change mortality of animals in the reservoir. Characteristics of the operation of Brownlee Reservoir, however, could increase or decrease the potential for mortality of big game mammals. Falling reservoir water levels under ice could create situations where there is an air gap between the ice and water surface, or sagging ice which slopes upward from a hole. Both situations would make escaping from a hole in the ice more difficult. Miller and Gunn (1986) discuss the importance of stable flat ice surface for barren-ground caribou to extract themselves from a hole in the ice. Also, falling reservoir levels could increase the potential for ice to crack and form weak spots. This would increase the potential for animals to break through ice. Similarly, rising water levels coinciding with ice formation could weaken ice and create weak spots where animals would be more likely to fall through. Lower reservoir levels reduce the area of embayments and the area where ice may form. In addition, lower reservoir water surface levels and volume increase the effect of warmer inflow water, also reducing the potential for ice formation. However, proportionally higher riverine flows can make ice thinner with more weak areas (Shulyakovskii 1966). The proximity of big game animals and areas of the reservoir susceptible to ice formation certainly creates the opportunity for animals to cross ice and be pursued onto ice by predators (especially coyotes). Excluding severe winters, it appears that current movements do not rely consistently on moving across areas of ice, and animals falling through the ice do not appear to be a common occurrence. An exception might be the fall

20 Brownlee Reservoir Ice—Effects on Big Game

migration route crossing the Powder River arm (Edelmann 2002) where ice can form in December, a period during which animals may still be crossing this arm of the reservoir. However, increased human disturbance or changes in movement patterns due to recreational or other development could increase the potential for animals to move across ice. Such development should ensure land passage for deer to minimize the need for animals crossing iced regions of the reservoir.

5.0 Literature Cited

Austin, D. D., and P. J. Urness. 1983. Overwinter forage selection by mule deer on seeded big sagebrush-grass range. Journal of Wildlife Management 47:1203-1206.

Austin, D. D., R. Stevens, K. R. Jorgensen, and P. J. Urness. 1994. Preferences of mule deer for 16 grasses found on Intermountain winter ranges. Journal of Range Management 47:308-311.

Banfield, A. W. F. 1954. Preliminary investigations of the barren-ground caribou. Part 2: Life history, ecology and utilization. Canadian Wildlife Service, Wildlife Management Bulletin, Series 1, No. 10B. 112 pp.

Bedrossian, K. L., R. D. Carleson, J. H. Noyes, and W. S. Potter. 1984. Status review of wildlife mitigation at Columbia Basin hydroelectric projects, Oregon facilities: final report. Oregon Dept. of Fish and Wildlife, Portland, OR. Environmental Management Section U.S. Dept. of Energy, BPA Div. of Fish and Wildl. Agreement No. DE-AI79-83BP12913.

Boroski, B. B., and R. H. Barrett. 1999. Movement patterns and survivorship of black- tailed deer migrating across Trinity Reservoir, California. California Fish and Game 85:63-69.

Bos, G. N. 1973. Nelchina caribou report. Alaska Department of Fish and Game Projects W-17-4, W-17-5, Progress Report, Juneau, Alaska. 23 pp.

Cole, T. M. and E. M. Buchak. 1995. CE-QUAL-W2: a two-dimensional, laterally averaged, hydrodynamic and water quality model, Version 2.0: User manual. Instruction Report EL-95-1, U.S. Army Engineer Waterways Experiment Station, Vicksburg, MS.

Edelmann, F. B., editor. 2002. Wintering mule deer ecology in the reservoir reach of the Hells Canyon Hydroelectric Complex. Technical Report Appendix E.3.2-32, in License Application for the Hells Canyon Complex. Idaho Power Company, Boise, ID, USA.

21 Brownlee Reservoir Ice—Effects on Big Game

Edelmann, F. B., V. R. Pope, and A. M. Rocklage. 2001. Mule deer population survey in Hells Canyon. Technical Report Appendix E.3.2-30, in License Application for the Hells Canyon Complex. Idaho Power Company, Boise, ID, USA.

Everitt, B. S. 1980. Cluster analysis. Heineman Educational Books, Ltd., London.

Garrott, R. A., G. C. White, R. M. Bartmann, L. H. Carpenter, and A. W. Alldredge. 1987. Movements of female mule deer in northwest Colorado. Journal of Wildlife Management 51:634-643.

Harrison, J., S. Wells, R. Meyers, S. Parkinson, and M. Kasch. 1999. 1999 status report on Brownlee Reservoir water quality and model development. Draft technical report, Idaho Power Corp., Boise, ID. 70 pp.

Idaho Department of Fish and Game (IDFG). 1986. Wildlife impact assessment – Anderson Ranch, Black Canyon, and Boise Diversion Projects, Idaho. Final report prepared to USDOE BPA, Div. of Fish and Wildl. Idaho Dept. Fish and Game Contract No. DE-AI-85BP23578.

Kelsall, J. P. 1960. Cooperative studies of barren-ground caribou, 1957-58. Canadian Wildlife Service, Wildlife Management Bulletin, Series No. 15. 145 pp.

Miller, F. L., and A. Gunn. 1986. Observations of barren-ground caribou travelling on thin ice during autumn migration. Arctic 39:85-88.

Parkinson, S. K. editor. 2001. Project hydrology and hydrologic models applied to the Hells Canyon Reach of the Snake River. In: Technical appendices for Hells Canyon Complex Hydroelectric Project. Idaho Power Company, Boise, ID. Technical Report E.1-4.

Pivovarov, A. A. 1973. Thermal conditions in freezing lakes and rivers. Wiley, New York, NY. 136 pp.

Shulyakovskii, L. G. 1966. Manual of ice-formation forecasting for rivers and inland lakes. Jerusalem, Israel Program for Scientific Translations (available from the U.S. Dept. of Commerce Clearinghouse for Federal Scientific and Technical Information, Springfield, VA.) 215 pp.

Simpson, K. 1987. Impacts of a hydro-electric reservoir on populations of caribou and grizzly bear in southern British Columbia. Report prepared by Keystone Bio- Research, Surrey, British Columbia for Ministry of Environment and Parks, Wildl. Branch, Nelson, B.C. 37 pp.

22 Brownlee Reservoir Ice—Effects on Big Game

Skogland, T., and O. Molmen. 1980. Prehistoric and present habitat distribution of wild mountain reindeer at Sevrefjell. Pages 130-141 in Reimers, E, E. Gaare, and S. Skjenneberg, eds. Proceedings of the Second International Reindeer/caribou Symposium. Roros, Norway.

Skoog, R. O. 1968. Ecology of the caribou (Rangifer tarandus granti) in Alaska. Ph.D. Thesis, University of California, Berkeley, 720 pp.

U.S. Department of Interior (USDI) 1985. Wildlife impact assessment, Palisades Project, Idaho. Final Report. U.S. Dept. Inter., U.S. Fish and Wildl. Serv.

Wickstrom, M. L., C. T. Robbins, T. A. Hanley, D. E. Spalinger, and S. M. Parish. 1984. Food intake and foraging energetics of elk and mule deer. Journal of Wildlife Management 39:192-199.

Wilk, A. L. 1958. Report on caribou studies September 22 to December 15, 1958. Canadian Wildlife Service unpublished report, 29 pp.

23 Brownlee Reservoir Ice—Effects on Big Game

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24 Brownlee Reservoir Ice—Effects on Big Game

Table 1. Variables in ice formation submodel of CE-QUAL-W2 assessed in sensitivity analysis. Middle values (bold) shown were used in simulations and are default values from CE-QUAL-W2, while low and high values were used in sensitivity analyses.

Variable Description Value Units Ratio of reflection to incident radiation (ALBEDO) 0.20 0.25 00.30 -- Coefficient of water-ice heat exchange (HWI) 7.00 10.0 13.00 -- Fraction of solar radiation absorbed by ice (BETAI) 0.40 0.60 00.80 -- Solar radiation extinction coefficient (GAMMAI) 0.05 0.07 00.10 -- Minimum ice thickness before ice formation (ICEMIN) 0.01 .025 00.05 m Temperature above which ice formation not allowed 1.00 3.00 05.00 C (ICET2)

Table 2. Result of k-means cluster analysis for embayments in Brownlee Reservoir. Embayment characteristics were measured at 15 water surface elevations separated by 3 m. Both cluster means and standard deviation of area and thalweg length are shown for members of each cluster.

Variables Cluster 1 Cluster 2 Cluster 3 Cluster 4 Area (m2) 2,225 9,536 24,048 51,493 Thalweg (m) 42 127 234 460

Standard Deviations Cluster 1 Cluster 2 Cluster 3 Cluster 4 Area (m2) 1,721 3,359 6,955 14,777 Thalweg (m) 25 31 63 90

No. of Embayments 317 175 66 21

25 Brownlee Reservoir Ice—Effects on Big Game

Table 3. Results of sensitivity analysis of coefficients used in ice submodel of CE-QUAL-W2. Shown are maximum and minimum differences between simulation run with variable changed to low or high parameter values (Table 1) and original simulation run. Differences in days with ice formation are expressed as absolute differences in days. Differences in maximum ice thickness are expressed as percent differences. Simulation shown is for Brownlee Reservoir in January 1995 (medium flow year) for “cold” freeze cycle under proposed operations. Similar results were also found for the run-of-river scenario for the same period (results not shown).

Low Parameter Value High Parameter Value Days Days Max. ice Days Days Max. ice < 10 cm ice total thickness < 10 cm ice total thickness Variable Extremes (no. days) (no. days) (%) (no. days) (no. days) (%) ALBEDO maximum 0 0 0.07 1 1 0.43 ALBEDO minimum -1 -1 -0.27 0 0 0.00

HWI maximum 1 1 1.13 1 1 0.00 HWI minimum -1 -1 0.00 0 0 -0.95

BETAI maximum 1 0 0.00 4 6 5.91 BETAI minimum -1 -1 -1.85 0 0 0.00

GAMMAI maximum 0 0 0.00 0 0 0.26 GAMMAI minimum 0 0 -0.03 0 0 0.00

ICEMIN maximum 0 0 0.00 0 0 0.00 ICEMIN minimum 0 0 0.00 0 0 0.00

ICET2 maximum 0 0 0.00 0 0 0.00 ICET3 minimum 0 0 0.00 0 0 0.00

All maximum 1 1 0.87 4 6 5.51 All minimum -1 -1 -0.88 0 0 -0.64

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32 Brownlee Reservoir Ice—Effects on Big Game

2500

2000

1997 (high flow) )

-1 1500 s 3

1000 Flow (m

1995 (medium flow) 500 1992 (low flow)

0 JanFeb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

2500

2000

1997 (high flow) )

-1 1500 s 3 1995 (medium flow)

1000

Flow (m 1992 (low flow)

500

0 November December January February

Figure 3. (upper) Inflow from Snake River to Brownlee Reservoir during low (1992), medium (1995) and high (1997) flow years. Twenty-day simulation periods are shown as horizontal bars. (lower) Detail of flows during months used in simulations. Twenty-day simulation periods are shown as horizontal bars.

33 Brownlee Reservoir Ice—Effects on Big Game

640 1992 (low flow) 635

630

625

620

615 WSE (m)

610

605

600 R un of R iver Proposed operation 595 JanFeb M ar A pr M ay Jun J ul A u g Sep Oct Nov Dec

1 9 9 5 (m e d iu m flo w ) 635

630

625

620

615 WSE (m)

610

605

600 R un of river Proposed operation 595 JanFeb M ar AprMay Jun J ul A u g Sep Oct Nov Dec

1997 (high flow) 635

630

625

620

615 WSE (m)

610

605

600 R un of river Proposed operation 595 JanFeb Mar A pr M ay Jun J ul Aug Sep Oct Nov Dec

Figure 4. Water surface elevations of Brownlee Reservoir for low flow, 1992 (upper), medium flow, 1995 (middle) and high flow, 1995 (lower) years for proposed operations and run-of-river operational scenarios. 20-day simulation periods are shown as horizontal bars.

34 Brownlee Reservoir Ice—Effects on Big Game

15 Cold freeze cycle 10

5

0

-5

-10 Air temperature(C) -15

-20

-25 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Time (d)

15 Warm freeze cycle 10

5

0

-5

-10 Air temperature(C) -15

-20

-25 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Time (d)

Figure 5. Air temperatures used in “cold” (upper) and “warm” (lower) freeze period simulations.

35 Brownlee Reservoir Ice—Effects on Big Game

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44 Brownlee Reservoir Ice—Effects on Big Game

90 160 Number 80 Area 140 70 120 60 100 50 80 40 60 30 40 Number of embayments 20 Area of embayments(hectares) 10 20

0 0 580 590 600 610 620 630 640 WSE (m)

Figure 10. Number and area of embayments in Brownlee Reservoir as a function of water surface elevation.

45 Brownlee Reservoir Ice—Effects on Big Game

14 January 1995 (medium flow year)

Cluster 1 12 Cluster 2 Cluster 3 10 Cluster 4

8

6 Days withDays ice

4

2

0 00 0 3 6 10 16 20 24 27 Segment containing embayment January 1995 (medium flow year) 0.35 Cluster 1 Cluster 2 0.30 Cluster 3 Cluster 4 0.25

0.20

0.15

0.10 Maximum ice thickness (m) 0.05 000 0.00 3 6 10 16 20 24 27 Segment containing embayment

Figure 11. (upper) Simulated days of ice persisting in Brownlee Reservoir within embayments of four different sizes (see Table 2) during “cold” freeze period (see text). Horizontal labels indicate the main reservoir segments containing the embayment. Broad bars indicate the period in days when reservoir ice is < 10 cm thick, while the narrow black bars indicate the total days when ice is present. (lower) Simulated maximum ice thickness for the same simulations.

46 Brownlee Reservoir Ice—Effects on Big Game

Cold freeze period 14 December 1992 (low flow year) Run of river 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 00 0 3 6 10 16 20 24 27 14 January 1992 (low flow year) Run of river Segment containing embayment 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 0 3 6 10 16 20 24 27 14 February 1992 (low flow year) Run of river Segment containing embayment 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 0 3 6 10 16 20 24 27 Segment containing embayment

Figure 12a. Simulated days of ice persisting in Brownlee Reservoir within embayments during “cold” freeze period (see text) for low flow year (1992) in December (upper), January (middle) and February (lower). Horizontal labels indicate the main reservoir segments containing the embayment. Broad bars indicate the period in days when reservoir ice is < 10 cm thick, while the narrow black bars indicate the total days when ice is present.

47 Brownlee Reservoir Ice—Effects on Big Game

Cold freeze period 14 December 1995 (medium flow year) Run of river 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 0 3 6 10 16 20 24 27 14 January 1995 (medium flow year) Run of river Segment containing embayment 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 0 3 6 10 16 20 24 27 14 February 1995 (medium flow year) Segment containing embayment Run of river 12 Proposed operations

10

8

6 Days with ice with Days 4

2 00 0 3 6 10 16 20 24 27 Segment containing embayment

Figure 12b. Same as Figure 12a, except for medium flow year (1995).

48 Brownlee Reservoir Ice—Effects on Big Game

Cold freeze period 14 December 1997 (high flow year) Run of river 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 0 3 6 10 16 20 24 27 14 January 1997 (high flow year) Run of river Segment containing embayment 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 0 3 6 10 16 20 24 27 14 February 1997 (high flow year) Run of river Segment containing embayment 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 00 0 3 6 10 16 20 24 27 Segment containing embayment

Figure 12c. Same as Figure 12a, except for high flow year (1997).

49 Brownlee Reservoir Ice—Effects on Big Game

Cold freeze period 0.40 1992 (low flow year) 0.35

0.30 RR-Dec PO-Dec 0.25 RR-Jan PO-Jan 0.20 RR-Feb PO-Feb 0.15

0.10 Maximum ice thickness (m) thickness ice Maximum 0.05 00000000 00 0.00 3 6 10 16 20 24 27 1995 (medium flow year) 0.35 Segment containing embayment

0.30 RR-Dec PO-Dec 0.25 RR-Jan PO-Jan 0.20 RR-Feb PO-Feb 0.15

0.10 Maximum ice thickness (m) thickness ice Maximum 0.05 000000 00 0.00 3 6 10 16 20 24 27 1997 (high flow year) 0.35 Segment containing embayment

0.30 RR-Dec PO-Dec 0.25 RR-Jan PO-Jan 0.20 RR-Feb PO-Feb 0.15

0.10 Maximum ice thickness (m) thickness ice Maximum 0.05 000000000000 00 0.00 3 6 10 16 20 24 27 Segment containing embayment

Figure 13. Simulated maximum ice thickness for simulations in Figure 12a,b,c. PO is proposed operations and RR is run-of-river operational scenario.

50 Brownlee Reservoir Ice—Effects on Big Game

Warm freeze period 14 December 1992 (low flow year) Run of river 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 00 0 3 6 10 16 20 24 27 14 January 1992 (low flow year) Run of river Segment containing embayment 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 00 0 3 6 10 16 20 24 27 14 February 1992 (low flow year) Run of river Segment containing embayment 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 00 0 3 6 10 16 20 24 27 Segment containing embayment

Figure 14a. Simulated days of ice persisting in Brownlee Reservoir within embayments during “warm” freeze period (see text) for low flow year (1992) in December (upper), January (middle) and February (lower). Horizontal labels indicate the main reservoir segments containing the embayment. Broad bars indicate the period in days when reservoir ice is < 10 cm thick, while the narrow black bars indicate the total days when ice is present.

51 Brownlee Reservoir Ice—Effects on Big Game

Warm freeze period 14 December 1995 (medium flow year) Run of river 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 00 0 3 6 10 16 20 24 27 14 January 1995 (medium flow year) Run of river Segment containing embayment 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 0 0 3 6 10 16 20 24 27 14 February 1995 (medium flow year) Run of river Segment containing embayment 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 00 00 0 3 6 10 16 20 24 27 Segment containing embayment

Figure 14b. Same as Figure 14a, except for medium flow year (1995).

52 Brownlee Reservoir Ice—Effects on Big Game

Warm freeze period 14 December 1997 (high flow year) Run of river 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 00 0 3 6 10 16 20 24 27 14 January 1997 (high flow year) Run of river Segment containing embayment 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 00 0 3 6 10 16 20 24 27 14 February 1997 (high flow year) Run of river Segment containing embayment 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 00 0 0 3 6 10 16 20 24 27 Segment containing embayment

Figure 14c. Same as Figure 14a, except for high flow year (1997).

53 Brownlee Reservoir Ice—Effects on Big Game

Warm freeze period 1992 (low flow year) 0.35

0.30 RR-Dec PO-Dec 0.25 RR-Jan PO-Jan 0.20 RR-Feb PO-Feb 0.15

0.10 Maximum ice thickness (m) thickness ice Maximum 0.05 000000 000000 000000 0.00 3 6 10 16 20 24 27 1995 (medium flow year) 0.35 Segment containing embayment

0.30 RR-Dec PO-Dec 0.25 RR-Jan PO-Jan 0.20 RR-Feb PO-Feb 0.15

0.10 Maximum ice thickness (m) thickness ice Maximum 0.05 000000000000 000 00 0.00 3 6 10 16 20 24 27 1997 (high flow year) 0.35 Segment containing embayment

0.30 RR-Dec PO-Dec 0.25 RR-Jan PO-Jan 0.20 RR-Feb PO-Feb 0.15

0.10 Maximum ice thickness (m) thickness ice Maximum 0.05 000000 000000000000 0 0.00 3 6 10 16 20 24 27 Segment containing embayment

Figure 15. Simulated maximum ice thickness for simulations in Figure 14a,b,c. PO is proposed operations and RR is run-of-river operational scenario.

54 Brownlee Reservoir Ice—Effects on Big Game

Cold freeze period 14 December 1992 (low flow year) Run of river 12 Proposed operations

10

8

6 Days with ice

4

2 0 00 00 0 30 31 32 33 34 35 36 37 14 January 1992 (low flow year) Run of river Powder River arm segment 12 Proposed operations

10

8

6 Days with ice with Days

4

2

0 30 31 32 33 34 35 36 37 14 February 1992 (low flow year) Run of river Powder River arm segment 12 Proposed operations

10

8

6 Days with ice with Days

4

2

0 30 31 32 33 34 35 36 37 Powder River arm segment

Figure 16a. Simulated days of ice persisting in the Powder River arm of Brownlee Reservoir during “cold” freeze period (see text) for low flow year (1992) in December (upper), January (middle) and February (lower). Horizontal labels indicate the main reservoir segments containing the embayment. Broad bars indicate the period in days when reservoir ice is < 10 cm thick, while the narrow black bars indicate the total days when ice is present.

55 Brownlee Reservoir Ice—Effects on Big Game

Cold freeze period December 1995 (medium flow year) 14 Run of river 12 Proposed operations

10

8

6 Days with ice with Days

4

2 0 00 0 30 31 32 33 34 35 36 37 14 January 1995 (medium flow year) Powder River arm segment Run of river 12 Proposed operations

10

8

6 Days with ice with Days

4

2

0 30 31 32 33 34 35 36 37 14 February 1995 (medium flow year) Run of river Powder River arm segment 12 Proposed operations

10

8

6 Days with ice with Days 4

2

0 30 31 32 33 34 35 36 37 Powder River arm segment

Figure 16b. Same as Figure 16a, except for medium flow year (1995).

56 Brownlee Reservoir Ice—Effects on Big Game

Cold freeze period 14 December 1997 (high flow year) Run of river 12 Proposed operations

10

8

6 Days with ice with Days 4

2 00 0 30 31 32 33 34 35 36 37 14 January 1997 (high flow year) Powder River arm segmentRun of river Proposed operations 12

10

8

6 Days with ice with Days

4

2

0 30 31 32 33 34 35 36 37 14 February 1997 (high flow year) Run of river Powder River arm segment Proposed operations 12

10

8

6 Days with ice with Days

4

2

0 30 31 32 33 34 35 36 37 Powder River arm segment

Figure 16c. Same as Figure 16a, except for high flow year (1997).

57 Brownlee Reservoir Ice—Effects on Big Game

Cold freeze period 1992 (low flow year) 0.35

0.30

0.25 RR-Dec PO-Dec 0.20 RR-Jan PO-Jan 0.15 RR-Feb PO-Feb 0.10 Maximum ice thickness (m) thickness ice Maximum 0.05 00 00 0.00 30 31 32 33 34 35 36 37 1995 (medium flow year) 0.35 Powder River arm segment

0.30

0.25 RR-Dec 0.20 PO-Dec RR-Jan 0.15 PO-Jan RR-Feb 0.10 PO-Feb Maximum ice thickness (m) thickness ice Maximum 0.05 0 00 0.00 30 31 32 33 34 35 36 37 1997 (high flow year) 0.35 Powder River arm segment

0.30

0.25

0.20 RR-Dec PO-Dec 0.15 RR-Jan PO-Jan 0.10 RR-Feb

Maximum ice thickness (m) PO-Feb 0.05 00 0.00 30 31 32 33 34 35 36 37 Powder River arm segment

Figure 17. Simulated maximum ice thickness for simulations in Figure 16a,b,c. PO is proposed operations and RR is run-of-river operational scenario.

58 Brownlee Reservoir Ice—Effects on Big Game

Warm freeze period 14 December 1992 (low flow year) Run of river 12 Proposed operations

10

8

6 Days with ice

4

2 00 00 0 00 00 0 30 31 32 33 34 35 36 37 14 January 1992 (low flow year) Run of river Powder River arm segment 12 Proposed operations

10

8

6 Days with ice with Days

4

2

0 30 31 32 33 34 35 36 37 14 February 1992 (low flow year) Run of river Powder River arm segment 12 Proposed operations

10

8

6 Days with ice with Days

4

2

0 30 31 32 33 34 35 36 37 Powder River arm segment

Figure 18a. Simulated days of ice persisting in the Powder River arm of Brownlee Reservoir during “warm” freeze period (see text) for low flow year (1992) in December (upper), January (middle) and February (lower). Horizontal labels indicate the main reservoir segments containing the embayment. Broad bars indicate the period in days when reservoir ice is < 10 cm thick, while the narrow black bars indicate the total days when ice is present.

59 Brownlee Reservoir Ice—Effects on Big Game

Warm freeze period 14 December 1995 (medium flow year) Run of river 12 Proposed operations

10

8

6 Days with ice with Days 4

2 0 00 0 30 31 32 33 34 35 36 37 14 January 1995 (medium flow year) Run of river Powder River arm segment 12 Proposed operations

10

8

6 Days with ice with Days

4

2

0 30 31 32 33 34 35 36 37 14 February 1995 (medium flow year) Run of river Powder River arm segment 12 Proposed operations

10

8

6 Days with ice with Days

4

2

0 30 31 32 33 34 35 36 37 Powder River arm segment

Figure 18b. Same as Figure 18a, except for medium flow year (1995).

60 Brownlee Reservoir Ice—Effects on Big Game

Warm freeze period 14 December 1997 (high flow year) Run of river 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 0 30 31 32 33 34 35 36 37 14 January 1997 (high flow year) Run of river Powder River arm segment 12 Proposed operations

10

8

6 Days with ice with Days

4

2

0 30 31 32 33 34 35 36 37 14 February 1997 (high flow year) Run of river Powder River arm segment 12 Proposed operations

10

8

6 Days with ice with Days 4

2 0 0 30 31 32 33 34 35 36 37 Powder River arm segment

Figure 18c. Same as Figure 18a, except for high flow year (1997).

61 Brownlee Reservoir Ice—Effects on Big Game

Warm freeze period 1992 (low flow year) 0.35

0.30 RR-Dec PO-Dec 0.25 RR-Jan PO-Jan 0.20 RR-Feb PO-Feb 0.15

0.10 Maximum ice thickness (m) thickness ice Maximum 0.05 00 000 00 00 0.00 30 31 32 33 34 35 36 37 1995 (medium flow year) 0.35 Powder River arm segment

0.30 RR-Dec PO-Dec 0.25 RR-Jan PO-Jan 0.20 RR-Feb PO-Feb 0.15

0.10 Maximum ice thickness (m) thickness ice Maximum 0.05 0 00 0.00 30 31 32 33 34 35 36 37 1997 (high flow year) 0.35 Powder River arm segment

0.30 RR-Dec PO-Dec 0.25 RR-Jan PO-Jan 0.20 RR-Feb PO-Feb 0.15

0.10 Maximum ice thickness (m) 0.05 0 00 0.00 30 31 32 33 34 35 36 37 Powder River arm segment

Figure 19. Simulated maximum ice thickness for simulations in Figure 18a,b,c. PO is proposed operations and RR is run-of-river operational scenario.

62 Brownlee Reservoir Ice—Effects on Big Game

Cold freeze period 14 December 1992 (low flow year) Run of river 12 Proposed operations

10

8

6 Days with ice

4

2 00 00 00 00 00 00 00 00 00 00 00 00 00 00 0 2 3 6 8 10 12 14 16 18 20 22 24 26 27 14 January 1992 (low flow year) Run of river Reservoir segment 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 0 2 3 6 8 10 12 14 16 18 20 22 24 26 27 14 February 1992 (low flow year) Run of river Reservoir segment 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 0 2 3 6 8 10 12 14 16 18 20 22 24 26 27 Reservoir segment

Figure 20a. Simulated days of ice persisting in main body of Brownlee Reservoir during “cold” freeze period (see text) for low flow year (1992) in December (upper), January (middle) and February (lower). Horizontal labels indicate the main reservoir segments containing the embayment. Broad bars indicate the period in days when reservoir ice is < 10 cm thick, while the narrow black bars indicate the total days when ice is present.

63 Brownlee Reservoir Ice—Effects on Big Game

Cold freeze period December 1995 (medium flow year) 14 Run of river 12 Proposed operations

10

8

6 Days with ice with Days 4

2 00 00 00 0 00 00 00 00 00 00 00 0 2 3 6 8 10 12 14 16 18 20 22 24 26 27 14 January 1995 (medium flow year) Reservoir segment Run of river 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 0 2 3 6 8 10 12 14 16 18 20 22 24 26 27 14 February 1995 (medium flow year) Run of river Reservoir segment 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 00 0 2 3 6 8 10 12 14 16 18 20 22 24 26 27 Reservoir segment

Figure 20b. Same as Figure 12a, except for medium flow year (1995).

64 Brownlee Reservoir Ice—Effects on Big Game

Cold freeze period 14 December 1997 (high flow year) Run of river 12 Proposed operations

10

8

6 Days with ice with Days 4

2 00 00 00 0 0 0 00 00 00 00 00 00 00 0 2 3 6 8 10121416182022242627 14 January 1997 (high flow year) Run of river Reservoir segment 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 00 0 0 2 3 6 8 10121416182022242627 14 February 1997 (high flow year) Reservoir segment Run of river 12 Proposed operations

10

8

6 Days with ice with Days

4

2 00 00 00 00 00 0 0 0 2 3 6 8 10121416182022242627 Reservoir segment

Figure 20c. Same as Figure 12a, except for high flow year (1997).

65 Brownlee Reservoir Ice—Effects on Big Game

Cold freeze period 1992 (low flow year) 0.35 RR-Dec PO-Dec 0.30 RR-Jan PO-Jan 0.25 RR-Feb PO-Feb 0.20

0.15

0.10 Maximum ice thickness (m) thickness ice Maximum 0.05

00000 000000 00 00 00 00 00 00 00 00 00 00 00 00 0.00 0 2 3 6 8 10 12 14 16 18 20 22 24 26 27 1995 (medium flow year) 0.35 Reservoir segment RR-Dec PO-Dec 0.30 RR-Jan PO-Jan 0.25 RR-Feb PO-Feb 0.20

0.15

0.10 Maximum ice thickness (m) thickness ice Maximum 0.05

000000000000 00 0 00 00 00 00 00 00 00 0.00 2 3 6 8 10 12 14 16 18 20 22 24 26 27 1997 (high flow year) Reservoir segment 0.35 RR-Dec PO-Dec 0.30 RR-Jan PO-Jan 0.25 RR-Feb PO-Feb 0.20

0.15

0.10 Maximum ice thickness (m) thickness ice Maximum 0.05

000000000000 000000 00 00 00 0 00 00 00 00 00 00 00 0.00 2 3 6 8 10 12 14 16 18 20 22 24 26 27 Reservoir segment

Figure 21. Simulated maximum ice thickness for simulations in Figure 20a,b,c. PO is proposed operations and RR is run-of-river operational scenario.

66 Brownlee Reservoir Ice—Effects on Big Game

25

20

15

10

5

Air temperature (C) temperature Air 0

-5

ST M -10 December 2000 January 2001 February 2001 March 2001

Figure 22. Maximum and minimum air temperatures measured at Brownlee Reservoir dam during the period December 2000 through March 2001. ‘S’ refers to the time ice was first observed in main reservoir embayments and in the Powder River arm, ‘T’ refers to the time thick ice (> 10 cm) was observed in the Powder River arm, and ‘M’ refers to the time when ice had melted from the Powder River arm.

67 Brownlee Reservoir Ice—Effects on Big Game

0

100 % -5 89 % 71 %

-10 54 % 31 %

-15 20 %

Temperature (C) Temperature 14 %

-20 6 % 3 %

-25 December January February

7

6

5

4

3 Frequency

2

1

0 b r r r e a a a pr Mar M M M A 5 -4 10 r -28 Feb 1- - -20 Mar 5-9 Apr 0-24 F 5 6 1-15 6 Ma 2 2 1 1 21-25 26-30 Mar 1 3

Figure 23. (upper) Period when minimum daily air temperatures at Brownlee Reservoir dam first were below the indicated temperature for four consecutive nights for the period 1966−2001. The black box represents the median date for this occurrence. Percentages refer to the number of years during 1966−2001 when minimum temperatures were at or below the threshold temperatures for four consecutive nights. (lower) Number years when minimum nighttime temperatures were above 0 °C for seven consecutive nights by time of first occurrence. Indicated dates represent ending date of seven-day string.

68