An optimization model for water resources allocation risk analysis under uncertainty Free

In order to deal with the risk of low system stability and unbalanced allocation during water resources management under uncertainties, a risk-averse inexact two-stage stochastic programming model is developed for supporting regional water resources management. Methods of interval-parameter programming and conditional value-at-risk model are introduced into a two-stage stochastic programming framework, thus the developed model can tackle uncertainties described in terms of interval values and probability distributions. In addition, the risk-aversion method was incorporated into the objective function of the water allocation model to reflect the preference of decision makers, such that the trade-off between system economy and extreme expected loss under different water inflows could be analyzed. The proposed model was applied to handle a water resources allocation problem. Several scenarios corresponding to different river inflows and risk levels were examined. The results demonstrated that the model could effectively communicate the interval-format and random uncertainties, and risk aversion into optimization process, and generate inexact solutions that contain a spectrum of water resources allocation options. They could be helpful for seeking cost-effective management strategies under uncertainties. Moreover, it could reflect the decision maker's attitude toward risk aversion, and generate potential options for decision analysis in different system-reliability levels.