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System dynamics (SD) have been used in water resources management for many years. However, water resources management using SD is usually in one direction, up to down or down to up, and doesn't consider internal and external system feedbacks, which may mislead managers and reduce the adaptability of water resources systems. Therefore, dynamic management of a water resources-socioeconomic-environmental (WSE) system based on feedbacks was established in this paper using SD, and a feedback function considering different intensities of feedbacks was proposed. The Beijing-Tianjin-Hebei region (BTHR), China, was chosen as the study area. Three subsystems were included in the WSE system: socioeconomic subsystem, water resource subsystem, and environmental subsystem. We established and compared different dynamic management scenarios with various intensities of feedbacks. The results show that shortage of water resources and pollution in the BTHR will continue to deteriorate from 2015 to 2030 if no management measures are taken, and the government should direct more attention to reducing the water demand of primary industry and population growth. In addition, we found that the three subsystems in the WSE system influence each other and evolve mutually. In particular, the influence of the water resources subsystem on the environmental subsystem is remarkable and cannot be ignored. This paper may act as a guide for adaptive and multi-objective management of WSE systems. [ABSTRACT FROM AUTHOR]

Human activities and climate change are two key factors influencing the variation of the total amount of available surface and groundwater, hereafter termed water resources. Quantitatively separating their impacts remains a challenge. To this end, we used time-varying Budyko-type equations and a hierarchical Bayesian model in this paper to separate their impacts in 31 provincial-level divisions of China. The time-varying Budyko-type equations treat the Budyko equation parameter w as a variable, which depends on human activities (represented by per capita gross regional production) and climate change (represented by temperature and precipitation). The hierarchical model quantifies the uncertainty of parameters and the interrelation between covariates across regions in China. The results show that the time-varying Budyko-type equation can improve the fitting capability for water resources in China. The hierarchical Bayesian model, which considered spatial dependence, reduced the uncertainty of the parameters compared to spatially independent counterparts. For most regions of China, human activities reduce water resources while climate change increases them. Southeastern China is the most influenced area, and its water resources decreased approximately 50 mm because of human activities. This study can provide a basis for water resource management under climate change and human activity constraints in China. [ABSTRACT FROM AUTHOR]