Forecast-based analysis for regional water supply and demand relationship by hybrid Markov chain models: a case study of Urumqi, China

Abstract

A clear understanding of regional water supply and demand trend is crucial for proper water resources planning and management in water-deficient areas, especially for Northwest China. In this study, three hybrid stochastic models (Markov chain model, unbiased Grey-Markov model and Markov model based on quadratic programming) were developed separately for predicating the available water resources, water demand, and water utilization structure in Urumqi. The novelty of this study arises from the following aspects: (1) compared with other models, the developed models would provide ideal forecasting results with small samples and poor information; (2) this study synthetically took into account water supply and demand, water utilization structure trend; (3) the prediction results were expressed as interval values for reducing the forecasting risk when carrying out water resources system planning and operational decisions. Analysis of water supply and demand in Urumqi under different reuse ratios was also conducted based on the forecasting results. The results would help managers and policy-makers to have a clear understanding of regional water supply and demand trend as well as the water utilization structure in the future.