Reducing risk of shortages due to drought in water supply systems using genetic algorithms

Abstract

AbstractThe evaluation of risk of shortages due to drought in water supply systems is a necessary step both in the planning and in the operation stage. A methodology for unconditional (planning) and conditional (operation) risk evaluation is presented in this study. The risk evaluation is carried out by means of an optimisation model based on genetic algorithms aimed to define thresholds for the implementation of mitigation measures tested through Monte Carlo simulation that makes use of a stochastic generation of streamflows. The GA enables the optimisation of reservoir storages which identify monthly thresholds for shifting three states of the system (normal, alert and alarm) to which correspond different mitigation measures such as water demand rationing, additional supplies from alternative sources or reduction of release for ecological use. For unconditional risk evaluation a long time horizon has been considered (40 years), while the conditional risk evaluation is performed on a short time horizon (2–3 months). Results of simulations have been studied by means of consolidated indices of performance and frequency analysis of shortages of a given entity corresponding to different planning/management policies. A multi‐use water system has been used as a case study including competing irrigation and industrial demands. Copyright © 2008 John Wiley & Sons, Ltd.