Inexact Fuzzy Chance-Constrained Nonlinear Programming Approach for Crop Water Allocation under Precipitation Variation and Sustainable Development

Abstract

In this study, an inexact fuzzy chance-constrained nonlinear programming (IFCCNP) method was developed for agriculture water resources management under multiple uncertainties. It improved upon the previous stochastic programming methods, and could reflect uncertainties expressed as probability distributions, fuzzy sets, intervals, and their combinations. By using the integration of above programming to represent the multiple uncertain parameters, the IFCCNP can generate results that are more reliable reflecting practical problem than the previous methods. The developed model is then applied to a case study of agriculture water resources management system where many crops and their planting stages are considered under different precipitation years for demonstrating its applicability. The results indicate that comprehensive solutions have been obtained. Through analysis under different precipitation levels, it provides bases for identifying desired agriculture water resources management plans with reasonable benefit and irrigation schedules under crops and their planting stages. IFCCNP is applicable to practical problems to address the crop water allocation under the precipitation variation and sustainable development with multiple uncertainties. Decision alternatives can be generated for decision makers through the proposed approach under typical years.