Climate Change, Fish, Agriculture, and Power: Impacts and Implications for Future Snake River Water Resources Management N. T. VanRheenen1, R. N. Palmer2, A. F. Hamlet2, and D. P. Lettenmaier2 1
Department of Civil and Environmental Engineering, University of Washington, Box 352700, Seattle, WA 98195-2700; Ph (206)616-1775; Fax (206) 685-9185; email:
[email protected] 2
Department of Civil and Environmental Engineering, University of Washington, Box 352700, Seattle, WA 98195-2700
Abstract This paper describes the approach taken in a study exploring water resources impacts associated with climate change scenarios in the Snake River basin in the Pacific Northwest. The Snake River is an extremely important river within the Columbia River basin that supports significant agricultural activity. Recently, a series of dams on this river have been targeted for removal because of their impact on salmon. Transient climate ensembles are used as inputs to the Variable Infiltration Capacity (VIC) macroscale hydrologic model to predict daily transient streamflow scenarios throughout the basin to 2050. Water resource simulation models are used to predict, on a monthly time-step, the implications of the altered climates on changes in streamflow timing and volume in approximately 91.5% of the basin’s 17.9 BCM of total storage. Preliminary results from these models indicate that both short and longterm climate change will have important implications for future policy and operational decisions in the region. Of particular interest are the effects of increasingly stringent river outflow regulation on irrigation deliveries, fish endangerment, hydropower generation, and flood control. Early analysis indicates that the predicted changes in magnitude and timing of future streamflows under climate change conditions will impact reliability in these areas. To address these concerns, a series of operational alternatives and optimizations are developed that mitigate future agricultural, economic, hydropower, and environmental impacts on the system. Introduction In a review of over 1000 relevant peer-reviewed studies, Gleick et al. (2000) concluded that “in many cases and in many locations, there is compelling scientific evidence that climate changes will pose serious challenges to our water systems.” The impacts of climate change on water resources, vis-à-vis global warming scenarios, on U.S. hydrology and water resources is expected to be most profound in the west, where the runoff cycle is largely determined by snowmelt (Cohen et al., 2000). Many previous studies indicate that the effects of warmer climates on the seasonality of runoff in such regions will likely shift a portion of spring and summer
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melt runoff earlier in the year (Smith and Tirpac, 1989; Piechota and Dracup, 1997; Lettenmaier et al., 1999; IPCC, 2001). Water supply systems in the western U.S. are negatively impacted from such shifts in runoff seasonality, because, although streamflows are heavily regulated, snowpack represents significant water storage that helps to augment low streamflows during relatively dry summers (Hamlet and Lettenmaier, 1999; VanRheenen et al., 2003, in review). The Columbia River basin (CRB) covers portions of seven western states and the Canadian province of British Columbia, with a total area about the size of the state of Texas. The water resources of the CRB have been extensively developed over the past 60-years for flood control, hydropower production, irrigation, and navigation. The hydrology of the CRB is dominated by snow accumulation and melt, a cycle that is highly sensitive to changes in temperature (Leung and Ghan, 1999). Many previous studies (Gleick and Chaleki, 1999; McCabe and Wolock, 1999; Hamlet and Lettenmaier, 1999; Lettenmaier and Gan, 1990) indicate that even relatively small increases in temperature would result in a significant shift in runoff patterns. This shift in the seasonality of runoff is characterized by lower snow accumulation, earlier peak snowmelt, higher winter runoff, higher evapotranspiration, and thus, lower summer and autumn streamflows. The consequences of seasonality shifts for managed water resources could be substantial because snowmelt influences summer and autumn inflows, when a relatively small proportion of annual precipitation falls in most of the western U.S. (e.g. Lettenmaier and Sheer, 1991). Thus, the CRB’s climate sensitivity is likely to add stress to the already complicated and conflicting objectives faced by CRB water resources management (Miles et al, 2000). Measuring 1,000 miles long and draining 103,200 square miles, the Snake River is the largest tributary of the Columbia River (Figure 1). The Snake River basin drains 87% of the State of Idaho. The reservoir system has total storage of approximately 17.9 billion cubic meters (BCM) (14.5 million acre-feet [MAF]) and is managed and operated by State, Federal, and private agencies to provide water for agricultural crops, flood control, and power generation. Underlying the eastern and central areas of the basin is the 308 BCM (250 MAF) Snake River Plain aquifer (Figure 2). This highly productive aquifer has been declared a sole source aquifer by the U.S. Environmental Protection Agency, due to the nearly complete reliance on the aquifer for drinking water supplies in the area. Collective discharge from the aquifer totals about 221 cubic meters/second (cms) (7800 cubic feet/second [cfs]). Operation of the system, which is dictated by numerous legal mandates, water rights, storage contracts, interagency agreements, flood control rules, and other guidelines, will likely be under intense pressure if current climate predictions are correct.
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Figure 1. Snake River and major tributaries. Note that river reaches above Brownlee Reservoir are not shown. (SR3 Report, 2000)
Figure 2. Snake River Plain aquifer. Note that river reaches above Brownlee Reservoir are not shown. (SR3 Report, 2000) 3
The climate change projections for this study are provided by a state-of-the-art coupled land-atmosphere-ocean General Circulation Model (GCM) (Washington et al., 2000). This study, like similar studies in the Columbia River basin (Payne et al., 2003) and the Sacramento-San Juaquin River basins (VanRheenen et al., 2003) utilizes a statistical downscaling approach for translating climate model outputs into hydrologic model inputs. A hydrology model translates the climate scenarios into daily runoff and streamflow at selected locations within the study domains. A water resources management model, jointly with a groundwater model, operating at monthly timesteps, calculate the potential impacts of the global warming scenarios on system operations in the Sanke River basin. To help to further understand and mitigate the potential impacts of these predicted climates on water resources management practices, a robust joint optimization-simulation model of surface and groundwater supplies is developed. Climate Prediction and Assessment Approach Over the past decade, numerous analyses of the potential effects of climate change on water resources have been conducted. The most sophisticated of these have employed suites of computer simulations (see, e.g., Lettenmaier et al., 1999). These typically begin with a coupled ocean-atmospheric general circulation model (GCM) that generates future climate scenarios. The future climate scenarios include estimates of future changes in precipitation and temperature that are used to force a rainfall-runoff (hydrologic) model, which produces future streamflow scenarios. The streamflow scenarios serve as input data for a water resources system model that calculates the performance of the water resources system for a given region. The climate prediction and assessment approach adopted for this study generally follows the method of the earlier studies in assembling an offline, one-way linkage between three computer models. The GCM provides global surface and atmospheric fields, including monthly total precipitation and monthly average temperature, for model integrations of length 20 to 300 years. The GCM output is adjusted statistically to remove regional bias, and the climate scenario anomalies are downscaled for use as forcings at the finer resolution of the Variable Infiltration Capacity (VIC) macroscale physical hydrology model. The resulting streamflow time series produced by the hydrologic model is used as inflow to the water resources system, Snake River Water Model (SWAT). SWAT is a monthly timestep reservoir model developed by the University of Washington that incorporates the major projects and operational features of the Snake River and major tributaries and evaluates the performance of each hydrologic scenario with respect to a comprehensive set of system objectives. The analysis of transient climate change effects on land surface hydrology, hence water resources management, is complicated by the confounding of natural variability (which would occur in the absence of climate change) with the long-term climate change signal. Although most climate change impact assessments to date have been based on transient GCM output that produces a single future climate scenario, such deterministic approaches could well lead to misleading results. To 4
address this issue, we use ensembles of GCM scenarios, each giving rise to a different statistical realization of the surface hydrologic forcings and system performance corresponding to a given emissions scenario. Bias-Correction and Downscaling of Climate Model Scenarios Regional biases in GCM simulations of the observed climate are well documented (Watson et al., 1996; Wilby and Wigley, 1997; Wilby et al., 1999; Maurer et al., 2001). Implementation of an approach to address such biases requires several preliminary steps. First, the bias-correction of GCM outputs is based on a comparison of GCM model climatology (taken from one or more control runs) with observed regional climatology (taken from historical observations). Second, downscaling of multi-decadal climate forecasts from the spatially coarse resolution (~2.5 degrees latitude by longitude), often archived at a monthly timestep, to the resolution of the VIC macroscale hydrology model (daily, 0.125 degree), will downscaled directly via interpolation and temporal disaggregation of output from the GCM. These steps create ensembles of VIC daily forcings that can be run from the current date over the forecast horizon. Water Resources Models Snake River Water Resources Model The Snake River Water Model (SWAT) is a monthly timestep surface and groundwater resource simulation model that incorporates the major projects and operational features of the Snake River basin and simulates the movement and storage of water within the basin given current operational policies. 91.5 % (16.4 BCM) of the total storage in the basin is modeled in SWAT. Modeled river reaches and reservoirs are listed in Table 1. The primary hydrologic input to SWAT is monthly streamflow, either from observed natural or unregulated flows (for studies of past climate) or from the VICgenerated hydrology. The groundwater component of SWAT operates jointly with surface water resources. Recharge rates for calibration runs and predicted climates are calculated and input prior to running the joint model. SWAT is used to explore system performance and reliability given various operating policies and alternative climate and operating scenarios. The model’s outputs are reservoir levels and releases, from which the predicted performance of the system with respect to such operating criteria as water quality, flood control, hydropower production, agricultural and municipal diversions, navigation, and instream flows for fish is calculated. As is customary in planning studies, perfect forecasting techniques are used for purposes of determining reservoir releases; future inflows are assumed to be known.
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Table 1. Snake River simulation and optimization model components: major river reaches and reservoirs Major Reach
Extent of Coverage
Reservoir (Cap. - TAF)
1
Snake River: Jackson to Henry’s Fork
Jackson Lake to Henry’s Fork
Jackson Lake (847)
2
Henry’s Fork
Island Park to Snake River
Island Park (128)
3
Willow Creek
Ririe Reservoir to Snake River
Ririe (101)
4
Blackfoot River
Blackfoot Reservoir to Snake River
Blackfoot (413)
5
Snake River: Henry’s Fork to Milner
Henry’s Fork Confluence to Milner Dam
American Falls (1673)
Palisades (1401)
Lake Walcott (210) Milner (50)
6
7
8
Snake River: Milner Dam to Brownlee
Milner Dam to Brownlee Dam
Boise River
South Fork and Main Stem Boise River – Anderson Ranch Reservoir to Snake River
Anderson Ranch (493)
North Fork/Main Stem Payette and Deadwood Rivers – Cascade and Deadwood Reservoirs to Snake River
Cascade (703)
Payette River
C.J. Strike (259) Brownlee (1420)
Arrowrock (287) Lucky Peak (293)
Deadwood (162)
9
Owyhee River
Owyhee Reservoir to Snake River
Owyhee (1120)
10
Clearwater River
Dworshak Reservoir to Snake River
Dworshak (3560)
11
Snake River: Brownlee to Lower Monumental
Brownlee Dam to Lower Monumental Dam
Hell’s Canyon (168)
11 Total Reaches, 18 Total Reservoirs
Total Storage
Other reaches included in predicted runoff, but not explicitly modeled: Little Wood River, Salmon River, Malheur River, Burnt River, Powder River
1329 TAF 91.5% of Basin Tot.
Snake River Water Allocation Optimization Model The Snake River Water Allocation Optimization Model (SWOP) is a monthly timestep surface water resource optimization model that is used to develop new 6
operating rules for use by SWAT. SWOP is alternatively incorporates either current flood storage rules or current flow targets as constraints and determines optimal release volumes or storages, respectively, needed to meet demands in each month. The optimization model may be further expanded to include optimization of future crop planting and irrigation practices based on water available and crop price forecasts. Conclusion Research for this project is well underway. As of February 2003, the surface water resources component of the modeling effort (SWAT) is being verified and calibration. The groundwater component of SWAT will be incorporated by mid April. Furthermore, we expect preliminary climate change runs to be completed by the end of March, with water resources impacts to be measured shortly thereafter. While the optimization model (SWOP) will not be completed by June 2003, we do expect to have made some progress. Our goal in this effort is to evaluate the sensitivity of a complex water resources system, given climate change, in a way that is more useful than what is used currently. In any system, operations will adapt as climatic and demand pressures dictate. By incorporating an optimization model a priori, in the development of possible future targets, we hope to be able to use simulation to investigate areas of future weakness in the system. References Cohen, S. J., Miller, K. A., Hamlet, A. F., and Avis, W. (2000). “Climate change and resource management in the Columbia River basin.” Water International, 25(2), 253-272. Gleick, P. H. (2000). “Water: The potential consequences of climate variability and change for the water resources of the United States”, Report of the Water Sector Assessment Team of the National Assessment of the Potential Consequences of Climate Variability and Change, Pacific Institute, Berkeley, CA. Gleick, P.H. and Chaleki, E. L. (1999). “The impacts of climatic changes for water resources of the Colorado and Sacramento-San Joaquin River basins.” J. Amer. W. Res. Assn., 35 (6), 1429-1441. Hamlet, A. F, and Lettenmaier, D. P. (1999). “Columbia River streamflow forecasting based on ENSO and PDO climate signals.” J. Water Resc. Plan. & Mgmt., 125(6), 333-341. IPCC (Intergovernmental Panel on Climate Change). (2001). Climate Change 2001: The Scientific Basis: Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. http://www.ipcc.ch/pub/spm22-01.pdf. Lettenmaier, D. P., Wood, A. W., Palmer, R. N., Wood, E. F., and Stakhiv, E. Z. (1999). “Water resources implications of global warming; a U.S. regional perspective.” Climatic Change, 43, 537-579.
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Lettenmaier, D. P. and Sheer, D. P. (1991). “Climatic sensitivity of California water resources.” J. Water Resc. Plan. & Mgmt., 117(1), 108-125 Lettenmaier, D. P. and Gan, T-Y. (1990). “Hydrologic sensitivities of the Sacramento-San Joaquin River basin, California, to climate change.” Wat. Resc. Resrch., 26, 69-86 Leung, L. R. and Ghan, S. J. (1999). “Pacific Northwest climate sensitivity simulated by a regional climate model driven by a GCM. Part II: 2xCO(2) simulations.” J. Climate, 12 (7), 2031-2053. McCabe, G. J. and Wolock, D. M. (1999). “General-circulation-model simulations of future snowpack in the western United States.” J. Amer. Water Resc. Assn., 35 (6), 1473-1484 Miles, E. L., Snover, A. K., Hamlet, A. F., Callahan, B. and Fluharty, D. (2000). “Pacific Northwest regional assessment: The impacts of climate variability and climate change on the water resources of the Columbia River basin.” J. Amer. Water Resc. Assn., 36 (2), 399-420 Payne, J. T., Wood, A. W., Hamlet, A. F., Palmer, R. N., and Lettenmaier, D. P. (2003). “Mitigating the effects of climate change on the water resources of the Columbia River basin.” Climatic Change, in review. Piechota, T. and Dracup, J. A. (1997). “Western US streamflow and atmospheric circulation patterns during El Nino/Southern Oscillation.” J. Hydrology, 201(14), 249-271. Smith, J. B. and Tirpak, D. A. (eds.). (1989) The Potential Effects of Global Climate Change on the United States: Appendix A – Water Resources, Office of Policy, Planning, and Evaluation, U.S. Environmental Protection Agency. VanRheenen, N. T., Wood, A. W., Palmer, R. N., and Lettenmaier, D. P. (2003). “Potential implications of PCM climate change scenarios for Sacramento San Joaquin River basin hydrology and water resources.” Climatic Change, in review. Washington, W. M., Weatherly, J. W., Meehl, G. A., Semtner, A. J., Bettge, T. W., Craig, A. P., Strand, W. G., Arblaster, J., Wayland, V. B., James, R., and Zhang, Y. (2000). “Parallel climate model (PCM) control and transient simulations.” Climate Dynamics, 16 (10-11), 755-774 Watson, R. T., Zinyowera, M. C., and Moss. R. H. (1996). Climate Change: Impacts, adaptations, and mitigation of climate change, 1995, Cambridge University Press, New York. Wilby, R. L. and Wigley, T. M. L. (1997). “Downscaling general circulation model output: a review of methods and limitations.” Prog. Phys. Geog., 21, 530548. Wilby, R. L., Hay, L. E., and Leavesley, G. H. (1999). “A comparison of downscaled and raw GCM output: implications for climate change scenarios in the San Juan River basin, Colorado.” J. Hydrol., 225, 67-91.
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