Nonlinear Programming Optimization and Quantification of Evaporation Losses in Dry Region Reservoir System.

摘要

eservoirs are an important water resource that play an important role in the water distribution economy especially in dry regions. It is essential to meet the demand for goods and services by storing and managing water proficiently. Controlling the water flow efficiently is critical to deliver the desired amount of water at the right time. Climate change makes it more important to control and manage the reservoir professionally to reduce even minor water losses like evaporation.;This study investigates the operation of a dry area multi-reservoir system to minimize losses. Elephant Butte and Caballo Reservoir in New Mexico is selected as a case-study example, but the study is extendable to other similar reservoirs systems. The objectives are: (1) to reduce total evaporation losses by minimizing the total surface area; (2) to reduce evaporation losses from single reservoir by minimizing the related surface area; and (3) apply constraints sensitivity analysis to make the study applicable from other similar systems. A nonlinear programming optimization method is used after mass balance calculation is performed though the collected historical data. The linear-interpolation functions is used improve data accuracy in MATLAB. The nonlinear programming optimization performs a differential numerical simulation of the system. The model is used with different objective functions to quantify and minimize the evaporation from related reservoir. The differential analysis compares the historical data to determine the gain in the storage monthly and yearly and validates with evaporation saving. The sensitivity analysis focuses on Caballo reservoir minimum operational storage level.;The study shows an average storage gain of 6.19 KAF/year (%5.4 more water saving) when the optimization is performed for total evaporation losses. The total annual savings are approximately