Estimating contribution of upstream watersheds in mountainous river system during low flow conditions under climate change scenarios

Contributions of upstream mountainous watersheds, also known as headwater systems, on river flows will be affected both spatially and temporally due to the impacts of climate change on different hydrological processes. Changes in patterns of winter and summer precipitation, as well as increases in summer evaporation rates as a result of increases in temperatures, will have severe impacts on low flows of the mountainous watersheds affecting downstream water availability. The primary objective of this study is to estimate future contributions from upstream mountainous watersheds during low flow periods for both near term (2035 to 2044) and distant future (2081 to 2090) periods taking climate change scenarios RCP 4.5 and 8.5 into consideration. Secondary objectives are to determine the frequencies and variability of low flows and to find the changes in low flow patterns as a result of the different scenarios. Multivariate Adaptive Constructed Analogs Multivariate Adaptive Constructed Analogs (MACA) statistically downscaled climate data for the conterminous US at 4km spatial and daily temporal resolution for the two periods mentioned above have been used as inputs to the Distributed Hydrologic Soil Vegetation Model (DHSVM) to estimate future low flows compared with the 2000-2009 baseline period. The models were calibrated using the observed meteorological data of six-year (1998 - 2004) period from the nearby SNOTEL sites and weather stations and the results show a very good fit in terms of Nash Sutcliffe Efficiency (NSE), percent volume error and coefficient of determination. Predictions of future low flows are now being processed. Predicted low flows and the contribution of headwater system to the river under climate change scenario would be very crucial to water resource management planners and policymakers as river ecosystem and the downstream uses are dependent on the low flows. The results of this study will be used to estimate the drought frequency of this region under both climate change scenarios.