Abstract

Coastal zones are the primary interface for the exchange of natural and man-made materials between terrestrial and coastal ecosystems. While continuous industrial development and population growth in the coastal region promote unprecedented economic prosperity, water resource management in bay and estuary areas turns out to be a crucial challenge. Therefore, local, state, and federal water planning groups are attempting to manage the supply of freshwater inflow based on sustainability goals, especially for semi-arid coastal regions like South Texas. Surface and ground water management practices in this semi-arid coastal region are implemented to ensure an ever-lasting water supply on one hand and to maintain ecosystem integrity in the bay and estuary system on the other hand. The aim of this study is to apply a stochastic compromise programming model to identify a compromise solution under uncertainty in terms of two competing objectives: minimizing freshwater release from a coastal reservoir and maximizing fishery harvest in its associated bay—Corpus Christi Bay, South Texas. The global criterion method used in the solution procedure seeks to select a compromise solution that possesses the shortest distance from a positive ideal solution (PIS) and the farthest distance from a negative ideal solution (NIS). Solutions were found using three distance-based functions in conjunction with stochastic constraints reflecting the risk levels involved in decision-making. Results indicate that current flows in the mouth of the Nueces River are not sufficient to maintain the salinity level and to satisfy harvest requirements in the Corpus Christi Bay if water supply goal in the city has higher priority. Therefore, a sustainable management plan of exploring the structure of demand and supply is highly desirable in this fast growing urban region.

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