A Multi-Period Simulation-Optimization Model for Conjunctive Management of Ground and Surface Water for a Semi-Arid Coastal Region: Corpus Christi, Texas

The city of Corpus Christi, TX currently relies on surface water supplies to meet its water demands.  Being in a semi-arid region, rainfall is erratic and water is stored in two interconnected reservoirs - Choke Canyon Reservoir on the Frio River and Lake Corpus Christi on the Nueces River.  The Nueces River is a major source of freshwater inflow into the Nueces delta and the Corpus Christi bay.  The reservoir systems have to be operated in such a way that freshwater inflow requirements prescribed for the Corpus Christi estuary system are met.  Given the increased water demands and climatic variability, the city of Corpus Christi is currently contemplating on developing an aquifer storage and recovery (ASR) system wherein surplus available surface water can be routed and stored to meet the requirements during high demand periods.  The goal of the present study is to develop a multi-period simulation-optimization model for the combined reservoir systems and the proposed ASR facility.  The model objective is to maximize the storage in the interconnected surface and subsurface storage units while meeting the freshwater inflow requirements to the Nueces delta and the Corpus Christi Bay.  Other constraints include meeting the water demands of the city and its service area as well as other junior water right holders on the river.  The simulation model uses monthly mass-balances for the three storage units and the surplus surface water available is taken as the maximum limit available for storage in the ASR system.  The drawdown constraints are placed along the Corpus Christi ASR district jurisdictional area to ensure that the storage and drawdown from the ASR has no deleterious impacts on the adjoining area.  The model is used to evaluate the performance characteristics of conjunctive water management strategies for the city that meets economic demands while providing for ecological needs.