Decision support system in watershed management under uncertainty.

Abstract

Watershed ecosystems consist of numerous resources which have important environmental, social, cultural, and economic values. The mutual existence and interaction among different resources within the watershed ecosystem calls for a multiobjective watershed resources management analysis. These objectives are often uncertain since they are based on estimation and/or measurement data. Probabilistic methods or fuzzification are usually the methods used in modeling these uncertainties. Selection of the best decision alternative is based on using some Multiple Criterion Decision Making (MCDM) technique. Through simulation in this dissertation, we examine the probabilistic model to address the watershed management problem. In particular, the distance-based methods, which are the most frequently used MCDM techniques, are employed in the problem analysis. In most cases, several interest groups with conflicting preferences are willing to influence the final decision. In our study, a new method is suggested to incorporate their preference orders into the DM's final preference. The application of MCDM techniques combined with stochastic simulation and conflicting preference orders is new in the watershed management literature. Detailed analysis and comparison of the numerical results will help to decide on the suitability of the MCDM technique in watershed resources management. In particular, our numerical results indicate that in practical applications the best alternative selection is significantly influenced by the uncertainties in the payoff values. Hence, in situations where suitable data are available, our methodology is highly recommended.