Stochastic Simulation of Natural Water Supply and Demand in Irrigation District and Risk Evaluation

Abstract

Reliable water shortage evaluation in irrigation districts is based on more accurate water supply and demand data series. The objective of this paper is to propose a stochastic simulation model to more accurately simulate a water supply-demand time series (WSDTS). This stochastic simulation model is a two-dimensional contemporaneous-temporal dependence model (C-TDM) of natural WSDTS based on a time series of annual rainfall and reference crop evapotranspiration (ET0) from 1970 to 2013 in the Luhun irrigation district in Henan Province, China. The results reveal that the statistical properties as well as the contemporaneous dependence relationship (CDR) and temporal dependence relationship (TDR) of the WSDTS are well-maintained in the simulated data. All correlation coefficients exceed 0.95. The root-mean square error (RMSE) of the C-TDM indicates that the model performs better than either a contemporaneous dependence model (CDM) or a temporal dependence model (TDM). Furthermore, the copula-based stochastic simulation model is used to evaluate the water shortage risk in the Luhun irrigation district. The joint probability distribution (JPD) of a rainfall-poor, rich-ET0 scenario is 0.24, suggesting that a serious water resources shortage is unlikely to occur. In addition, the results indicate that considering both the TDR and CDR in stochastic simulation models can provide more conservative and reliable forecasts for water shortage risk evaluations in irrigation districts.