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1. Climate change impacts on water supply and irrigation water demand in the Columbia River Basin Jennifer Adam1, Kiran Chinnayakanahalli1, Claudio Stockle2, and Michael Barber1 1Civil and Environmental Engineering, Washington State University, PO Box 642910,Pullman, WA 99164-2910. 2Biological Systems Engineering, Washington State University, PO Box 646120, Pullman, WA 99164-6120. T IP T, IP I Q Q01 updated Soil moisture 1. Introduction 3. Modeling Q12 • Rising temperature and changes in the frequency and magnitude of precipitation due to climate change (IPCC-AR4 report) events are anticipated to affect crop production, water availability and quality, and flood risk in the PNW (Stockle et al 2009, Elsner et al 2009, Hamlet and Lettenmaier 2007). • Agriculture is a vital part of the economy in the Pacific Northwest (PNW). In 2008, wheat production accounted for $1.7 billion, the third largest value in the United States (NASS, 2009) . • The eastern side of the Cascade Mountains, which receives only 5-25” of rain annually, is particularly vulnerable to drought. In the last decade, there have been 10-20% yield losses during severe drought years, with an average of $90 million/year (NASS, 2009). • The challenge is to anticipate the probable effects of climate change on the hydrological cycle and make sound land use, water use, and agricultural management decisions that will best serve the needs of agricultural production while protecting our freshwater resources. • A system of models (see Boxes 2 and 3) are applied to assess the impacts of projected climate change on hydrology, water resources, and agricultural productivity. Here we describe the preliminary model integration work. OBJECTIVE: To apply a coupled hydrology and cropping systems model to project and compare future water supply and irrigation water demand over the Washington State portion of the Columbia River Basin for improved water resources management. Redistribute I, Q01 and Q12 to CropSyst layers Qb ET0 ,I, Q01, Q12 CropSyst VIC LAND COVER USA- USDA crop land data layer Canada – derived from National Ecological Framework for Canada *Not all land cover types shown in the legend* VIC-CropSyst Integration Strategy VIC-CropSyst Integration Variables: T – Transpiration, IP – Interception capacity, I – Infiltration, Q – Runoff, Qb– Baseflow, Q01– Drainage from 0 to 1, Q02 – Drainage from 0 to 2, ET0 – Penman Monteith Pot. Evap. 2. Methods and Tools Four groups of socio-economic scenarios allow a range of future greenhouse gas emissions. • We are applying a system of linked models, including VIC hydrology model (Liang et al. 1994), a dynamic crop systems model (CropSyst: Stockle et al. 2003), and ColSim • Funding for this project is being provided by the Washington State Department of Ecology Physical System of Dams and Reservoirs Impact models and other tools are used to explore the impacts of climate and hydrologic change on agriculture and water resources management. crop The downscaled climate data are used to drive land surface hydrology models to simulate the hydrologic cycle in an altered climate. The greenhouse gas scenarios are used to drive coupled Atmosphere-Ocean General Circulation Models (AOGCMs) to simulate future climate. Output from 17 AOGCMs are archived with the IPCC. UW/Princeton Variable Infiltration Capacity (VIC) Model Columbia River Basin reservoir operations model –ColSim (Hamlet et al. 1999) 4. Conclusions The future climate data from the AOGCMs need to be bias-corrected and spatially and temporally downscaled before they can be applied to regional basins. One method is called Bias Correction Statistical Downscaling (BCSD; Wood et al. 2004). • Application of down-scaled and bias-corrected AOGCM climate data to drive hydrologic models has the potential to improve our understanding of the impacts of climate and hydrologic change on agriculture and water resources management. For example, the framework developed here can be used to study the impact of climate change on crop dynamics. • The major challenge to both of this project is the simplistic treatment of crops and agricultural practices in the hydrologic models. Therefore, we are expanding the capabilities of the modeling framework by coupling VIC to a dynamic crop growth model, CropSyst. The expanded capabilities of the coupled models will enable further investigations into the linkages and feedbacks between climate, hydrology, and agriculture.