Research On Water Resource Allocation Management Based Upon Uncertainty Theory For High-tech District,Binzhou City

Due to the influence of the industrial and society activities, regional water resource problems are being more and more serious, seriously hindered the coordination of economic, social and environmental sustainable development. Therefore, to carry out the regional water resources planning plays an important role for modern regional social and economic development. However, the uncertainty inherent in the system of water resources as well as a variety of complex interactions between uncertain parameters, were a test of traditional deterministic planning models and methods. Therefore, it is the target of the research in the article to deal with the complexity of water resource system planning under the uncertainty optimization method. In this article, in view of the shortage of water resource and water environment pollution problem we have to face in the process of development of high-tech zone of Binzhou city. Fistly, on the basis of MonteCarlo simulation technique, uncertain interval-chance-constrained linear programming model (ICCP) and were constructed based on water environmental capacity. Results show that the ICCP can well reflect the complexity and uncertainty in the system. Decision scheme is obtained under different water environment risk, which can help policymakers make trade-offs between the risk of water environment and the regional economic benefits, and provide theoretical and technical support for related departments to formulate reasonable economic, environmental and social sustainable development scheme. The management agency needs to promise an allocation target, which can help the farmers make their culture plans. If the promised water is not delivered, the benefit will be reduced due to the penalty imposed. Since the available water quantity of sources is randomly varied, this problem can be formulated as a two-stage stochastic programming (TSP) model. So, Inexact chanced-constrained two-stage stochastic programming model (ICCTSP) was formulated based on the analysis of the ICCP model. In the two-stage model, the first stage:make a target plan before the random events occurre; the second:After the random events occure, consider the cause of punishment, correct empirical decisions, and look for optimization decision-making for the system. ICCTSP is effective for stochastic problems, it combines more uncertain theory, can handle multiple uncertainty problem. The combination of a variety of uncertainty theory is the development direction of future uncertainty optimization.