Fuzzy Goal Programming Approach to Estimate Groundwater Availability

One of the important steps in aquifer management is to determine the amount of groundwater that is available for use. This available groundwater is a function of both aquifer hydrogeologic characteristics as well as the risk preferences of the decision makers involved. Simulation-Optimization approaches can be used to develop tools capable of incorporating both aquifer hydrogeological characteristics and the preferences of the stakeholders while estimating groundwater availability.

In Texas, assessment of groundwater availability is a decentralized, stakeholder driven process. Therefore, different values and preferences of stakeholders must be effectively reconciled to obtain sustainable water availability estimates. Multiple objectives such as maximizing pumping for economic gains and minimizing pumping for conservation can be simultaneously considered using techniques such as goal programming. Goal programming is a tool not for optimizing but rather to identify/achieve “satisfactory” outcome. The satisfying solution may be inferior to the best possible solution for any single objective considered.

It is important to note that in considering a complex and emotional issue like groundwater management, the knowledge, judgments and management goals of the stakeholders tend to be imprecise and ill-defined. The vagueness resulting from subjective preferences of stakeholders and decision-makers needs to be considered for successful implementation of consensus based availability estimates. Fuzzy set-theoretic approaches provide useful tools to capture the varying degrees of preferences of decision-makers.

In this study, fuzzy goal programming is used in conjunction with the Groundwater-Availability-Models (GAM) developed by Texas Water Development Board to evaluate the impacts of policy choices on estimated groundwater availability. The application of fuzzy-goal-programming as a decision support tool is demonstrated using information from Refugio County, Texas as an illustrative case study