A methodology is presented for predicting impacts and risks to water resources, at the watershed scale, from somewhat unknown future climate. It is then applied to estimate impacts to a semi-arid watershed in Texas. Because all models of water movement and storage in watersheds provide estimates (and best guesses), rather than absolute answers, and because the specifics of future weather are unknown, this approach uses likelihoods (or probabilities) for relative change in magnitude, ∆, between future and historical precipitation, evapotranspiration, storm runoff, and aquifer recharge to evaluate future risk to water availability. Projected (future) climate trends for the study site from climate models are a 3 ˚C increase in average temperature, which means that the potential for evapotranspiration will increase, no significant change in average annual precipitation, which means that there generally will not be more water available for evaporation, and a semi-arid classification from 2011–2100. Future precipitation is projected as unchanged for typical conditions. Consequently, no significant change is estimated for evapotranspiration, runoff, or recharge for average conditions. With expectations for significant temperature increase, an increase in the amount of rainfall is needed to increase evapotranspiration, runoff, and recharge. Increases in rainfall during infrequent large storms are included in the analysis for future conditions, which produces increased water availability during infrequent extreme events but does not change expectations for average conditions.

Abstract: A framework for the assessment of relative risk to watershed-scale water resources from systemic changes is presented. It is composed of two experiments, or pathways, within a Monte Carlo structure and provides quantification of prediction uncertainty. One simulation pathway is the no change, or null hypothesis, experiment, and the other provides simulation of the hypothesized system change. Each pathway uses a stochastic weather generator and a deterministic water balance model. For climate change impact analysis, the framework is calibrated so that the differences between thirty-year average precipitation and temperature pathway values reproduce climate trends. Simulated weather provides forcing for identical water balance models. Probabilistic time histories of differences in actual evapotranspiration, runoff, and recharge provide likelihood per magnitude change to water resources availability. The framework is applied to a semi-arid watershed in Texas. Projected climate trends for the site are a 3 ˚C increase in average temperature and corresponding increase in potential evapotranspiration, no significant change in average annual precipitation, and a semi-arid classification from 2011–2100. Two types of water balance model are used in separate applications: (1) monthly water balance and (2) daily distributed parameter. Both implementations predict no significant change, on average, to actual evapotranspiration, runoff, or recharge from 2011–2100 because precipitation is unchanged on average. Increases in extreme event intensity are represented for future conditions producing increased water availability during infrequent events.