Abstract. The potential effects of climate change on the hydrology and water resources of the Colorado River basin are assessed by comparing simulated hydrologic and water resources scenarios derived from downscaled climate simulations of the U.S. Department of Energy/National Center for Atmospheric Research Parallel Climate Model (PCM) to scenarios driven by observed historical climate. PCM climate scenarios include an ensemble of three 105-year future climate simulations based on projected 'business-as-usual' (BAU) greenhouse gas emissions and a control climate simulation based on static 1995 greenhouse gas concentrations. Downscaled transient temperature and precipitation sequences were extracted from PCM simulations, and were used to drive the Variable Infiltration Capacity (VIC) macroscale hydrology model to produce corresponding streamflow sequences. Results for the BAU scenarios were summarized into Periods 1, 2, and 3 (2010-2039, 2040-2069, 2070-2098). Average annual temperature changes for the Colorado River basin were 0.5 • C warmer for control climate, and 1.0, 1.7, and 2.4 • C warmer for Periods 1-3, respectively, relative to the historical climate. Basin-average annual precipitation for the control climate was slightly (1%) less than for observed historical climate, and 3, 6, and 3% less for future Periods 1-3, respectively. Annual runoff in the control run was about 10% lower than for simulated historical conditions, and 14, 18, and 17% less for Periods 1-3, respectively. Analysis of water management operations using a water management model driven by simulated streamflows showed that streamflows associated with control and future BAU climates would significantly degrade the performance of the water resources system relative to historical conditions, with average total basin storage reduced by 7% for the control climate and 36, 32 and 40% for Periods 1-3, respectively. Releases from Glen Canyon Dam to the Lower Basin (mandated by the Colorado River Compact) were met in 80% of years for the control climate simulation (versus 92% in the historical climate simulation), and only in 59-75% of years for the future climate runs. Annual hydropower output was also significantly reduced for the control and future climate simulations. The high sensitivity of reservoir system performance for future climate is a reflection of the fragile equilibrium that now exists in operation of the system, with system demands only slightly less than long-term mean annual inflow.

T he hydrology of the Pacific Northwest (PNW) is particularly sensitive to changes in climate because seasonal runoff is dominated by snowmelt from cool season mountain snowpack, and temperature changes impact the balance of precipitation falling as rain and snow. Based on results from 39 global simulations performed for the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4), PNW temperatures are projected to increase an average of approximately 0.3°C per decade over the 21 st century, while changes in annual mean precipitation are projected to be modest, with a projected increase of 1% by the 2020s and 2% by the 2040s. Based on IPCC AR4 projections, we updated previous studies of implications of climate change on the hydrology of the PNW. In particular, we used results from 20 global climate models (GCMs) and two emissions scenarios from the Special Report on Emissions Scenarios (SRES): A1B and B1. PNW 21 st century hydrology was simulated using the full suite of GCMs and 2 SRES emissions scenarios over Washington, as well as focus regions of the Columbia River basin, the Yakima River basin, and those Puget Sound river basins that supply much of the basin's municipal water supply. Using two hydrological models, we evaluated projected changes in snow water equivalent, seasonal soil moisture and runoff for the entire state and case study watersheds for A1B and B1 SRES emissions scenarios for the 2020s, 2040s, and 2080s. We then evaluated future projected changes in seasonal streamflow in Washington. April 1 snow water equivalent (SWE) is projected to decrease by an average of approximately 27-29% across the State by the 2020s, 37-44% by the 2040s and 53-65% by the 2080s, based on the composite scenarios of B1 and A1B, respectively, which represent average effects of all climate models. In three relatively warm transient watersheds west of the Cascade crest, April 1 SWE is projected to almost completely disappear by the 2080s. By the 2080s, seasonal streamflow timing will shift significantly in both snowmelt dominant and transient, rain-snow mixed watersheds. Annual runoff across the State is projected to increase by 0-2% by the 2020s, 2-3% by the 2040s, and 4-6% by the 2080s; these changes are mainly driven by projected increases in winter precipitation.

(2016). Value of long-term streamflow forecasts to reservoir operations for water supply in snow-dominated river catchments. Water Resources Research, 52(6) , University of Bristol -Explore Bristol Research General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms RESEARCH ARTICLE 10.1002/2015WR017864Value of long-term streamflow forecasts to reservoir operations for water supply in snow-dominated river catchments Abstract We present a forecast-based adaptive management framework for water supply reservoirs and evaluate the contribution of long-term inflow forecasts to reservoir operations. Our framework is developed for snow-dominated river basins that demonstrate large gaps in forecast skill between seasonal and inter-annual time horizons. We quantify and bound the contribution of seasonal and inter-annual forecast components to optimal, adaptive reservoir operation. The framework uses an Ensemble Streamflow Prediction (ESP) approach to generate retrospective, one-year-long streamflow forecasts based on the Variable Infiltration Capacity (VIC) hydrology model. We determine the optimal sequence of daily release decisions using the Model Predictive Control (MPC) optimization scheme. We then assess the forecast value by comparing system performance based on the ESP forecasts with the performances based on climatology and perfect forecasts. We distinguish among the relative contributions of the seasonal component of the forecast versus the inter-annual component by evaluating system performance based on hybrid forecasts, which are designed to isolate the two contributions. As an illustration, we first apply the forecast-based adaptive management framework to a specific case study, i.e., Oroville Reservoir in California, and we then modify the characteristics of the reservoir and the demand to demonstrate the transferability of the findings to other reservoir systems. Results from numerical experiments show that, on average, the overall ESP value in informing reservoir operation is 35% less than the perfect forecast value and the inter-annual component of the ESP forecast contributes 20-60% of the total forecast value.