Optimizing Reservoir Operation Policy Using Chance Constraint Nonlinear Programming for Koga Irrigation Dam, Ethiopia

One of typical problems in water resources system modeling is derivation of optimal operating policy for reservoir to ensure water is used more efficiently. This paper introduces optimization analysis to determine monthly reservoir operating policies for five scenarios of predetermined cropping patterns for Koga irrigation scheme, Ethiopia. The objective function of the model was set to minimize the sum of squared deviation (SSD) from the desired targeted supply. Reservoir operation under different water availability and thresholds of irrigation demands has been analyzed by running a chance constraint nonlinear programming model based on uncertain inflow data. The model was optimized using Microsoft Excel Solver. The lowest SSD and vulnerability, and the highest volumetric reliability were gained at irrigation deficit thresholds of 20% under scenario I, 30% under scenario II, III and V, and at 40% under scenario IV when compensation release is permitted for downstream environment. These thresholds of deficits could be reduced by 10 % for all scenarios if compensation release is not permitted. In conclusion the reservoir water is not sufficient enough to meet 100% irrigation demand for design command areas of 7,000 ha. The developed model could be used for real time reservoir operation decision making for similar reservoir irrigation systems. In this specific case study system, attempt should be made to evaluate the technical performance of the scheme and introduce a regulated deficit irrigation application.