Global climate change is presenting a variety of challenges to hydrology and water resources because it strongly affects the hydrologic cycle, runoff, and water supply and demand. In this study, we assessed the effects of climate change scenarios on hydrological variables (i.e., evapotranspiration and runoff) by linking the outputs from the global climate model (GCM) with the Soil and Water Assessment Tool (SWAT) for a case study in the Lijiang River Basin, China. We selected a variety of bias correction methods and their combinations to correct the lower resolution GCM outputs of both precipitation and temperature. Then, the SWAT model was calibrated and validated using the observed flow data and corrected historical GCM with the optimal correction method selected. Hydrological variables were simulated using the SWAT model under emission scenarios RCP2.6, RCP4.5, and RCP8.5. The results demonstrated that correcting methods have a positive effect on both daily precipitation and temperature, and a hybrid method of bias correction contributes to increased performance in most cases and scenarios. Based on the bias corrected scenarios, precipitation annual average, temperature, and evapotranspiration will increase. In the case of precipitation and runoff, projection scenarios show an increase compared with the historical trends, and the monthly distribution of precipitation, evapotranspiration, and runoff shows an uneven distribution compared with baseline. This study provides an insight on how to choose a proper GCM and bias correction method and a helpful guide for local water resources management.

Water resources are very important to support the socio-economic development and maintain environmental health, which is a typical issue in water resources management. In this study, we developed an optimal allocation model for a large complex system of water resources by considering both water supply and river ecological benefits. The water supply benefit is defined as the minimum water deficit for different water users, while the ecological benefit involves making the reservoir release as close as possible to the natural streamflow. To solve this problem, the combination of decomposition-coordination (DC) and discrete differential dynamic programming (DDDP) methods were proposed. The proposed methods first decomposed a large system with multi-objective programming into subsystems, and the optimal solution of each subsystem was accomplished by the DDDP method to solve the system efficiently. Then the subsystems’ solutions were coordinated to figure out the near global optimal solution. The proposed models were tested in the Lingui and Yongfu County, Guilin City in China. Results show that the optimal reservoir release is close to the natural flow regime and there is a slight water deficit ratio in both level years. The water supply objective is more sensitive to the system model compared with the ecological objective, and the result of water allocation is optimized when the reservoir release is as close as possible to the natural flow based on the minimum water deficit. The proposed system model could facilitate sustainable water use and provide technical support for water resources management in economic development.

Sustainable development in water resources is becoming a hot topic in recent years. The world is facing the disequilibrium between the availability of resources and the increase in population with fast-growing economies and social development. This study proposes a new methodological framework of sustainable development of water resources based on the response linkages and feedback loops of economy-ecology-food (EEF) nexus. It provides a new way to identify the interconnection and coevolution process between these EEF. The multi-objective model and system dynamic (SD) model were coupled to characterize the interconnections between processes and their dynamic responses to a set of scenarios. The combination of decomposition-coordination method (DC) and dynamic programming was used to find the optimal scenario based on each component of the EEF nexus. The Upper reach of Guijiang River Basin (UGRB) was presented as a case study. Results showed that the coupled multi-objective model and SD model presented in this study are able to characterize the interactions and feedback between EEF systems adequately. Most importantly, the rapid growth rate of socio-economic indexes will drive the awareness of river ecology and showed a higher sensitivity under different decision preferences. The results provided in this study can provide baseline information for stakeholders and policymakers in the field of water management for a better understanding of the interactions across systems.

The accelerated consumption of water resources caused by the rapid increase of population and urbanization is intensifying the negative interactions of water uses across socioeconomic development, ecological protection, and food productivity (SEF), which causes an imbalance between water supply & demand, ecological and food vulnerability, and further water unsustainability. To solve this problem, this study developed an integrated modeling framework to better identify the dynamic interaction and coevolution process of the nexus across SEF systems in the context of sustainable water uses by coupling two models: system dynamic model (SD) and multi-objective optimization model. First, the SD model is used to simulate both the dynamic interaction of each agent and the coevolution process of the whole system under external changes. Next, the multi-objective optimal model is used to generate the optimal scheme by iteration process with the initial scheme of SD, further identifying the dynamic interaction and coevolution process in terms of sustainable water use. Finally, the model uncertainty considering different weighting factors is analyzed. The framework is applied to the Upper Reaches of Guijiang River Basin, China. Results show that: (i) the rapid economic growth intensifies the ecological awareness and cannot support such rapid development because it rises the conflict between environment and economic water uses, resulting in more water shortages of socio-economy and food agent. (ii) Once the economic growth rate decreased, water resources are able to support economic development with decreased overload index and stable crop yield, which further contributes to water sustainability. (iii) The river ecological agent is the critical factor that affects the robustness of the model. (iv) The equal consideration of each water usage is the most beneficial to sustainable development. These results highlight the importance of water resources management considering the tradeoffs across multiple stakeholders and give a strong reference to policymakers for comprehensive urban planning.