Evaluating impacts of climate change on future water scarcity in an intensively managed semi-arid region using a coupled model of biophysical processes and water rights

Author:

Han BangshuaiORCID,Benner Shawn G.,Flores Alejandro N.ORCID

Abstract

Abstract. In semiarid and arid regions with intensively managed water supplies, water scarcity is a product of interactions between complex biophysical processes and human activities. Evaluating water scarcity under climate change necessitates modeling how these coupled processes interact and redistribute waters in the system under alternative climate conditions. A particular challenge on the climate input lies in adequately capturing the plausible range of variability of future climate change along with central tendencies. This study generates a large ensemble of daily climate realizations by combining a stochastic weather generator, historical climate observations, and statistically downscaled General Circulation Model projections. Three climate change scenario groups, reflecting the historical, RCP4.5, and RCP8.5 conditions, are developed. A modeling framework is built using the Envision alternative futures modeling platform to 1) explicitly capture the spatiotemporally varying irrigation activities as constrained by local water rights; and 2) project water scarcity patterns under climate change. The study area is the Treasure Valley, an irrigation-intensive semi-arid human-environment system. Climate projections for the region show future increases in both precipitation and temperature. The projected increase in temperature has a significant influence on the increase of the allocated and unsatisfied irrigation amount. Projected changes in precipitation produce more modest responses. The scenarios identify spatially distinct areas more sensitive to water scarcity, highlight the importance of climate change as a driver of scarcity, and identify potential shortcomings of the current water management. The approach of creating climate ensembles overcomes deficiencies of using a few or mean values of individual GCM realizations.

Publisher

Copernicus GmbH

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