Abstract:

Bayesian network is applied in water resource management to deal with the uncertainty of multi-object decision-making problem. The relationship between variables is analyzed, and then Bayesian network model is constructed, including directed acyclic graph which describes the dependent relationship of variables and conditional probability tables which express the specific level of the dependency. On the premise that all the six objective variables achieve the intended goals, the probabilistic inference of Bayesian network is taken. Results of the case study show that the compensation amount increase to 500 yuan (RMB) per Mu（Mu≈666.666 7 m²）, all of the objective variables could achieve optimization.  So the reasonable water resources decision scheme that the government should give the compensation of 500 yuan (RMB) per Mu to the farmers was proposed. Bayesian network can intuitively express the uncertain relationship between variables in the case study. The probabilistic inference result takes into the environmental benefit as well as the farmer’s benefit, so the multi-objective variables could achieve optimization. It is an effective method to deal with the multi-objective decision-making problem with uncertainty of water resource management.

Key words: Bayesian networks, water resource management, uncertainty