Currently, the implementation of water resource spatial equilibrium strategy is a fundamental policy of water resource integrated management in China; it is also a considerable challenge to explore the relationship structure features of water resources, society, economy and ecological environment (WSEE) complex system. For this purpose, firstly, we applied information entropy, ordered degree and connection number coupling method to reveal the membership characteristics between different evaluation indicators and grade criterion. Secondly, the system dynamics approach was introduced to describe the relationship features among different equilibrium subsystems. Finally, the ordered degree, connection number, information entropy and system dynamics integrated model was established to conduct relationship structure simulation and evolution trend evaluation of the WSEE system. The application results in Hefei city, Anhui Province, China, demonstrated that: (1) the variation of overall equilibrium conditions of WSEE system in Hefei city, 2020–2029 was higher compared to that of 2010–2019, though the increasing rate of ordered degree and connection number entropy (ODCNE) became slower after 2019; and (2) the annual ODCNE value from 2020 to 2029 of WSEE system under dry year scenarios increased about 0.0812, which indicated that the construction of Yangtze-Huaihe Diversion (YHD) project could play significant positive role in mitigating the equilibrium situation of WSEE system in Hefei city in the future. On the whole, this study is capable of providing the guidance basis for constructing a theoretical framework of structure simulation and equilibrium evaluation analysis of WSEE complex system.

As a critical intervention for enhancing inland navigation efficiency, waterway regulation projects profoundly modify riverine hydrodynamic conditions while optimizing navigability. This study employs the MIKE21 hydrodynamic model to establish a two-dimensional numerical framework for assessing hydrological alterations induced by channel regulation in the Hui River, China. Through comparative simulations of pre- and post-project scenarios across dry, normal, and wet hydrological years, the research quantifies impacts on water levels, flow velocity distribution, and geomorphic stability. Results reveal that channel dredging and realignment reduced upstream water levels by up to 0.26 m during drought conditions, while concentrating flow velocities in the main channel by 0.5 m/s. However, localized hydrodynamic restructuring triggered bank erosion risks at cut-off bends and sedimentation in anchorage basins. The integrated analysis demonstrates that although regulation measures enhance flood conveyance and navigation capacity, they disrupt sediment transport equilibrium, destabilize riparian ecosystems, and compromise hydrological monitoring consistency. To mitigate these trade-offs, the study proposes design optimizations—including ecological revetments and adaptive dredging strategies—coupled with enhanced hydrodynamic monitoring and riparian habitat restoration. These findings provide a scientific foundation for balancing navigation improvements with the sustainable management of fluvial systems.

Construction of an integrated drought index is a fundamental task to conducting drought disaster risk management and developing drought resistance planning strategies. Given the evident non-consistent features during the drought evolution process, firstly, the GAMLSS approach was utilized to construct multiple combination scenarios of time-variant parameters and corresponding probability distribution functions. Then, the time-variant comprehensive drought index integrating the variable characteristics of precipitation and soil moisture was established by means of the copula function. Finally, the reliability of the time-variant comprehensive drought index was verified through its application in frequency analysis and return period determination of drought hazard system in Huaibei Plain, China. The application results demonstrated that: (1) The variation of the time-variant integrated drought indicator presented strong consistency with both soil moisture and precipitation during historical years in Huaibei Plain. (2) The overall variation of the drought hazard system characterized by drought duration and severity presented a gradual mitigation trend from west to east and north to south in Huaibei Plain, which agrees with the geographic differences and water resources availability distribution features. (3) Drought recognition results, including the frequency of drought events and typical drought processes with extreme grades, are in agreement with the practical statistics and observed data series. On the whole, the proposed time-variant integrated drought indicator is capable of extracting complex variation characteristics within the drought hazard evolution process, and can be further applied in drought monitoring, recognition and assessment research fields.

There is an increasing trend in the use of multi-objective evolutionary algorithms (MOEAs) to solve multi-objective optimization problems of the allocation of water resources. However, typically the outcome is a set of Pareto optimal solutions which make up a trade-off surface between the objective functions. For decision makers to choose a satisfactory alternative from a set of Pareto-optimal solutions, this paper suggests a new method based on least squares support vector machine (LSSVM) and k-means clustering for ranking the optimal solutions for the multi-objective allocation of water resources. First, the k-means clustering method was adopted to reduce the large set of solutions to a few representative solutions. Then, to capture and represent the decision maker's preferences as well as to select the most desirable alternative, the LSSVM method was applied to obtain the utility value for each representative solution. According to the magnitude of the utility values, the final priority orders of the representative solutions were determined. Finally, this methodology was applied to rank the Pareto optimal solution set obtained from the multi-objective optimization problems of water resources allocation for the water-receiving areas of the South-to-North Water Transfer Project in Hebei Province, China. Moreover, the comparisons of the proposed method with the information entropy method and the artificial neural network (ANN) model were given. The results of the comparison indicate that the proposed method has the ability to rank the non-dominated solutions of the multi-objective operation optimization model and that it can be employed for decision-making on water allocation and management in a river basin.