Journal of Water Resource and Protection, 2013, 5, 816-822 http://dx.doi.org/10.4236/jwarp.2013.58082 Published Online August 2013 (http://www.scirp.org/journal/jwarp) Irrigation Planning with Conjunctive Use of Surface and Groundwater Using Fuzzy Resources D. G. Regulwar, V. S. Pradhan Department of Civil Engineering, Government College of Engineering, Aurangabad, India Email: regulwar@geca.ac.in, vizpradhan@gmail.com Received June 3, 2013; revised July 4, 2013; accepted August 7, 2013 Copyright © 2013 D. G. Regulwar, V. S. Pradhan. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ABSTRACT Surface and groundwater are related systems. They can be used conjunctively to maximize the efficient use of available resources. Groundwater may be used to supplement surface water to cope with the irrigation demands to meet the defi- cits in low rainfall periods. The parameters involved in the present study are groundwater availability, surface water availability, water requirement of crops and crop area. The inclusion of such uncertain parameters leads to accept the decision making process beyond the consideration of economic benefits. In the present study, an irrigation planning model is formulated by considering the conjunctive use of surface and groundwater. The resources in the present model, i.e. the area, surface water and groundwater availability are represented by fuzzy set. The linear membership function is used to fuzzify the objective function and resources. The model is applied to a case study of Jayakwadi project and solved for maximization of the degree of satisfaction () which is 0.546. Keywords: Conjunctive Use; Irrigation Planning; Fuzzy Linear Programming (FLP); Uncertainties; Optimization 1. Introduction In water management practices conjunctive use is con- sidered important as surface and groundwater are related systems. Uncertainty in the parameters involved makes it difficult for the decision maker to derive the water use policy and estimate the returns from the system. Such uncertainties are efficiently tackled through fuzzy logic. Kashyap and Chandra [1] have developed a mathematical model for achieving an optimal conjunctive use policy incorporating spatially and temporally distributed groundwater withdrawals and spatially distributed crop- ping patterns. The groundwater withdrawals were con- strained to keep the water table elevations within an ap- propriate range. Murthy [2] illustrated with a hypotheti- cal example the case of conjunctive use of surface and groundwater to replace surface water. Onta et al. [3] have developed a stochastic dynamic programming model to derive the optimal operating policy and also a lumped simulation model is used to evaluate the alternative poli- cies for each alternative and a multiple criteria decision making is used to select the most satisfactory alternative plan. Mohan and Jyothiprakash [4] have formulated a FLP model to derive optimal crop plans for an irrigation system for conjunctive use of surface and groundwater. The results of FLP model were compared with classical linear programming model which showed that the fuzzy linear programming model maximized the degree of sat- isfaction. Vedula et al. [5] have developed a mathemati- cal model to obtain an optimal conjunctive use policy for irrigation with the objective of maximizing the sum of relative yields of crops in a reservoir-canal-aquifer sys- tem. The crop water allocations are achieved by integra- tion of the reservoir operation for canal release along with groundwater pumping. Srinivasulu and Satyanara- yana [6] addressed the problem of a canal irrigated in saline groundwater areas by developing a linear pro- gramming model for allocation of land and water re- sources to different crops. A genetic algorithm model was developed by Nagesh Kumar et al. [7] to obtain an optimal operating policy and optimal crop water alloca- tions with the objective of maximizing the relative yields from the crops in the study area. Manuel et al. [8] have presented an integrated non linear hydrologic economic modeling framework for optimizing conjunctive use of surface and groundwater for a river basin through capac- ity expansion. Khare et al. [9] have presented an eco- nomic optimization problem to explore the potential use of surface and groundwater resources using linear pro- gramming to arrive an optimal cropping pattern for maximization of net benefits. Kentel and Aral [10] have Copyright © 2013 SciRes. JWARP