Comparative study on modeling approaches for water resource coupling systems based on data-driven methods and system dynamics

Abstract

[Objective] Due to unclear physical mechanisms and numerous influencing factors, modeling analysis of complex water resource coupling systems is one of the key challenges in the current research on hydrology and water resources. It is of great significance for the scientific management of water resources to clarify the practicality and accuracy of method such as data-driven method and system dynamics(SD).[Methods] Based on the previous research achievements of the research team, the water supply-power generation-environment(WPE) coupling system in the upper reaches of the Yangtze River Basin was taken as the research object. Using data from 1998 to 2020, 11 typical data-driven method were compared with the SD model to systematically evaluate their performance in the modeling of complex water resource coupling systems.[Results] The result showed that:(1) except for the SD model, all the other models exhibited different degrees of overfitting. The SD model demonstrated the best performance, with an average simulated R² of approximately 0.81 for all variables, showing strong explanatory power for system changes, and an average MAPE of approximately 11%, indicating high prediction accuracy.(2) The multiple linear regression(MLR) model performed relatively well, with an average simulated R² of approximately 0.57 for all variables and an average MAPE of about 19%.[Conclusion] The SD model can effectively solve the problems of complex water resource coupling systems, demonstrating strong stability and reliability. However, it requires modelers to have a high level of proficiency in complex system theories and method. Although the MLR model cannot comprehensively characterize the WPE system, it can meet the basic analysis requirements with simple operation and high practical applicability. The relevant research findings can provide a reference for the modeling and analysis of complex water resource systems.

Keywords

water resource coupling system / system dynamics / regression analysis / data-driven / upper reaches of Yangtze River Basin / modeling analysis / model evaluation / influencing factors