Adaptive management of water resources based on an advanced entropy method to quantify agent information

Abstract

Abstract Adaptive management is currently an important method to optimize the management of complex water resources systems. Regional water resources adaptive management was conducted based on the advanced theory of a complex system multi-agent model; the state of an agent was tracked and modified by information entropy theory, which was improved by using individual standard deviations. With the goal of optimizing the adaptation of each agent of the region, water resources in the major grain production area of China were managed under the constraints of the total annual available water resources and water use efficiency requirements for 2015 and 2030. By introducing the adaptive water resources management in 2015, the domestic benefits and economic benefits increased by 2.90% and 14.81%, respectively, with respect to observed values. The ecological benefits declined by 3.63%, but ecological water demand was fully satisfied, and the ecological water environment was improved. Given the water use efficiency targets in 2030, applying adaptive management resulted in an increase of domestic, economic, and ecological benefits of 34.29%, 21.14%, and 1.78%, respectively. The results show that the adaptive management method presented can help managers to balance the benefits of various agents to determine the direction of water resources management decisions.