Estimating Future Surface Water Availability with Reservoir Evaporation and Hydrological Drought Considered under CMIP6 Scenarios

Abstract:

With rapid population growth and global warming, water demand and the risks of droughts are expected to increase and intensify, which could increase reservoir evaporative loss and adversely impact water supply reliability. Thus, it is imperative to estimate future surface water availability under climate change. In Texas, future surface water availability is evaluated using the Water Availability Model (WAM) – Run3, based on several factors, such as projected water demand and decreasing reservoir capacity due to sedimentation. However, changes of reservoir evaporation and hydrological conditions due to climate change are not incorporated into the current regional water planning process. Meanwhile, the process currently used for drought planning only considers the droughts of the 1950s and 2011. However, climate change is projected to intensify droughts risks. Thus, our objective is to assess future surface water availability by considering projected changes in reservoir evaporation and hydrological droughts under climate change. Twelve major reservoirs in the Upper Trinity River Basin are selected as our study sites, which supply water to about one quarter of Texas’ population, including the Dallas-Fort Worth Metropolitan Area. Two models are used in this study: 1) a hydrological model—the Distributed Hydrologic Soil and Vegetation Model with a Reservoir Module included (DHSVM-Res); and 2) a water availability model—WAM. Three tasks are conducted to analyze future surface water availability: 1) future naturalized streamflow, reservoir evaporation, and reservoir volume are simulated by DHSVM-Res under CMIP6 scenarios; 2) the Reservoir Storage Drought Index (RSDI)—calculated based on the outputs of DHSVM-Res simulations—is used for characterizing future hydrological droughts; and 3) the outputs from DHSVM-Res simulations are used as inputs for WAM to calculate reservoir firm yield and water supply reliability. Therefore, by using a hybrid modeling approach, our study leverages distributed hydrological modeling and water availability modeling to update information of reservoirs and hydrological droughts. This study can formulate adaptive methods to conserve the storage of individual reservoir and improve the evaluation of future surface water availability in Texas.