PNNL

Abstract

During the past several decades, numerous reservoirs have been built across the world for a variety of purposes such as flood control, irrigation, municipal/industrial water supplies, and hydropower generation. Consequently, natural streamflow timing and magnitude have been altered significantly by reservoir operations. In addition, the hydrological cycle can be modified by land use/land cover and climate changes. To understand the fine scale feedback between hydrological processes and water management decisions, a distributed hydrological model embedded with a reservoir component is of desire. In this study, a multi-purpose reservoir module with predefined complex operational rules was integrated into the Distributed Hydrology Soil Vegetation Model (DHSVM). Conditional operating rules, which are designed to reduce flood risk and enhance water supply reliability, were adopted in this module. The performance of the integrated model was tested over the upper Brazos River Basin in Texas, where two U.S. Army Corps of Engineers reservoirs, Lake Whitney and Aquilla Lake, are located. The integrated DHSVM model was calibrated and validated using observed reservoir inflow, outflow, and storage data. The error statistics were summarized for both reservoirs on a daily, weekly, and monthly basis. Using the weekly reservoir storage for Lake Whitney as an example, the coefficients of determination (R2) and the Nash-Sutcliff Efficiency (NSE) are 0.85 and 0.75, respectively. These results suggest that this reservoir module has promise for use in sub-monthly hydrological simulations. Enabled with the new reservoir component, the DHSVM model provides a platform to support adaptive water resources management under the impacts of evolving anthropogenic activities and substantial environmental changes.