Analysis and Forecasting of Wetness-Dryness Encountering of a Multi-Water System Based on a Vine Copula Function-Bayesian Network

Abstract

The analysis and forecasting of wetness-dryness encountering is the basis of joint operation of a multi-water system, which is important for water management of intake areas of water transfer projects. On the basis of a vine copula function-Bayesian network, this study developed an analysis and forecasting of a wetness-dryness encountering model. The model consists of two modules: firstly, the joint distribution among multi-inflows is established based on the vine copula function, and the obtained historical laws of wetness-dryness encountering; then, a Bayesian network is established in order to forecast wetness-dryness encountering in the future, using the forecasting information of some water systems. The model was applied to the water receiving areas inside Jiangsu Province of the South-to-North Water Transfer East Route Project in China. The results revealed the following: (1) Compared with conventional copulas, the probability values of wetness-dryness encountering obtained by the vine copula function were closer to the observed values. (2) The wetness-dryness encountering in 2017–2019 was forecasted, and the results were consistent with reality. These results demonstrate that the proposed model improves the accuracy of the obtained historical laws of wetness-dryness encountering, and that it can forecast wetness-dryness encountering in the future.