%0 Journal Article
%T A Fuzzy Inference System for the Conjunctive Use of Surface and Subsurface Water
%A Liang-Cheng Chang
%A Hone-Jay Chu
%A Yi-Wen Chen
%J Advances in Fuzzy Systems
%D 2013
%I Hindawi Publishing Corporation
%R 10.1155/2013/128393
%X This study develops the water resources management model for conjunctive use of surface and subsurface water using a fuzzy inference system (FIS). The study applies the FIS to allocate the demands of surface and subsurface water. Subsequently, water allocations in the surface water system are simulated by using linear programming techniques, and the responses of subsurface water system with respect to pumping are forecasted by using artificial neural networks. The operating rule for the water systems is that the more abundant water system supplies more water. By using the fuzzy rule, the FIS conjunctive use model easily incorporates expert knowledge and operational polices into water resources management. The result indicates that the FIS model is more effective and efficient when compared with the decoupled conjunctive use and simulation-optimization models. Furthermore, the FIS model is an alternative way to obtain the conjunctive use policies between surface and subsurface water. 1. Introduction The objective of the study is to develop a fuzzy rule-based method for the conjunctive use of surface and subsurface water systems. Zadeh [1] applied the fuzzy theory to mathematically deal with the imprecision and uncertainty. Fuzzy logic extends upon traditional Boolean logic and deals with the imprecision in human experience [2]. The fuzzy inference system (FIS) is an artificial intelligence technique that combines the fuzzy set, fuzzy logic, and fuzzy reasoning [1, 3¨C6]. The FIS utilizes linguistic variables, fuzzy rules, and fuzzy reasoning and provides a tool for knowledge representation based on degrees of membership [7]. During the past decade, the FIS application ranged from runoff forecasting to surface water supply [3¨C6, 8, 9]. Shrestha et al. [3] developed a FIS to determine a real-world reservoir operation. They constructed a fuzzy rule-based model to derive operation rules for a multipurpose reservoir. Their research used reservoir storages, estimated inflows, and demands as the premises and took reservoir releases as the consequences. The finding showed that the fuzzy-based structure was ordinary and time-saving in computation. Russell and Campbell [4] developed the FIS for a simplified hydroelectric reservoir. The results also showed that fuzzy logic seemingly offered a way to improve the existing operating practices, which was relatively easy to explain and understand when compared with the complex optimization model. Panigrahi and Mujumdar [5] used a FIS for a reservoir operation model. The study incorporated expert knowledge for framing the
%U http://www.hindawi.com/journals/afs/2013/128393/