Rapid transitions between dry and wet phases increasingly threaten global water resources and ecosystem sustainability. However, how the terrestrial water storage (TWS)–a key determinant of water and energy budgets–modulates these dry‐wet abrupt alternation (DWAA) events remains poorly understood. Here, we leverage a recently reconstructed long‐term TWS data set to evaluate global dynamics of DWAA events, and explore their teleconnection relationships with El Niño‐Southern Oscillation (ENSO). We find that the frequency of DWAA events has increased more than three‐fold during the past 4 decades (1979–2022), driven by heightened variability of atmospheric moisture transport and circulation dynamics. ENSO plays an essential role in modulating these transitions, with the La Niña phase in particular enhancing both the coverage and intensity of these events. These findings suggest an amplified risk of hydroclimatic extremes under climate warming, highlighting the urgent need to improve monitoring and prediction of these rapid transitions.

Sustainable transboundary water governance is often challenged by conflicts between agents, which necessitates the design of cooperative and self-enforcing alternatives to facilitate equitable water distribution. The Nash bargaining approach, which originated from game theory, could offer a good mathematical framework to simulate strategic interactions among involved agents by considering individual rational benefits. Given that river-sharing problems often involve multiple self-interested agents, the asymmetric Nash bargaining solution (ANBS) could be used to describe agents’ powers, as determined by disparate social, economic, and political as well as military status, and ensure win–win strategies based on individual rationality. This paper proposed an asymmetric bargaining model by combining multi-criteria decision making, bankruptcy theory, and the ANBS for water distribution in the transboundary river context. The Euphrates River Basin (ERB) with three littoral states was used as a case study. Turkey has the highest bargaining power in ERB negotiation since it dominates in terms of economic strength, political influence, and military capacity, whereas in the two downstream countries these aspects are limited due to their internal political fragmentation and weaker military status. The water satisfaction percentages of Turkey, Syria, and Iraq under the best alternative are 96.30%, 84.23%, and 40.88%, respectively. The findings highlight the necessity for synthetically considering the agent’s disagreement utility and asymmetrical power when negotiating over water allocation.

Water scarcity is an important issue in many countries, and it is therefore necessary to improve the efficiency and equality of water resource allocation for decision makers. Based on game theory (GT), a bi-level optimization model is developed from the perspective of a leader-follower relationship among agents (stakeholders) of a river basin in this study, which consists of a single-agent GT-based optimization model of common interest and a multi-agent cooperative GT-based model. The Hanjiang River Basin is chosen as a case study, where there are conflicts among different interest agents in this basin. The results show that the proposed bi-level model could attain the same improvement of common interest by 8%, with the conventional optimal model. However, different from the conventional optimal model, since the individual interests have been considered in the bi-level optimization model, the willingness of cooperation of individuals has risen from 20% to 80%. With a slight decrease by 3% of only one agent, the increases of interest of other agents are 14%, 18%, 7%, and 14%, respectively, when using the bi-level optimization model. The conclusion could be drawn that the proposed model is superior to the conventional optimal model. Moreover, this study provides scientific support for the large spatial scale water resource allocation model.

Climate change is leading to an increase in the frequency and intensity of flooding, making it necessary to consider future changes in flood risk management. In regions where ground-based observations are significantly restricted, the implementation of conventional risk assessment methodologies is always challenging. This study proposes an integrated remote sensing and machine learning approach for flood risk assessment in data-scarce regions. We extracted the historical inundation frequency using Sentinel-1 SAR and Landsat imagery from 2001 to 2023 and predicted flood susceptibility and inundation frequency using XGBoost, Random Forest (RF), and LightGBM models. The risk assessment framework systematically integrates hazard components (flood susceptibility and inundation frequency) with vulnerability factors (population, GDP, and land use) in two SSP-RCP scenarios. The results indicate that in the SSP2-RCP4.5 and SSP5-RCP8.5 scenarios, combined high- and very-high-flood-risk areas in the Ili River Basin in China (IRBC) are projected to reach 29.1% and 29.7% of the basin by 2050, respectively. In the short term, the contribution of inundation frequency to risk is predominant, while vulnerability factors, particularly population, contribute increasingly in the long term. This study demonstrates that integrating open geospatial data with machine learning enables actionable flood risk assessment, quantitatively supporting climate-resilient planning.

The coordinated operation for hydropower generation in cascade reservoirs is critical to resolve the conflicts in hydropower needs between upstream and downstream reservoirs. Due to the individual rationality and collective rationality highlighted by game theory, we propose an integrated game-theoretical model to simulate the coordination behaviors among cascade reservoirs for hydropower generation. In the case study of a cascade-reservoir system in the Yangtze River of China, three operation models are compared and analyzed: the non-cooperative model, centralized model, and integrated game-theoretical model. The factors influencing the coordination efficiency of the integrated game-theoretical model are also explored in this study. The results indicate that the system’s hydropower generation obtained by the integrated game-theoretical model is closer to the ideal solution obtained by the centralized model compared to that obtained by the non-cooperative model. Moreover, individual hydropower generation in non-cooperation (rational individual gains) is guaranteed by the integrated game-theoretical model, which is neglected by the centralized model. Furthermore, the coordination efficiency of the integrated game-theoretical model is influenced by the water availability variation and regulation capacities of cascade reservoirs.