[Objective] River basins with complex terrain and sparse ground-based rainfall observations often fail to fully capture the spatial heterogeneity of rainfall. This introduces substantial uncertainties into hydrological runoff modeling, flood disaster risk management, and related applications. The Nujiang River Basin upstream of the Gongshan station in southwestern China exemplifies this challenge: while it covers a vast area with highly rugged topography, it is plagued by a scarcity of rainfall gauges and their uneven distribution. This study aims to address the challenge of design storm estimation in such data-sparse river basins by exploring the use of high-resolution reanalysis rainfall data. [Methods] A systematic performance assessment was first conducted for three precipitation datasets: the China Meteorological Forcing Dataset (CMFD), the Multi-Source Weighted-Ensemble Precipitation product (MSWEP), and ERA5. Daily rainfall values from each dataset were compared with available gauge observations using four statistical indicators: Pearson correlation coefficient (R), relative bias (BIAS), root mean square error (RMSE), and mean absolute error (MAE) to identify the dataset with the best overall performance. Subsequently, for the assessed optimal dataset, the L-moment method was applied in a basin-wide, grid-scale batch processing approach to compute design storms. The specific steps included: (1) determining the most appropriate probability distribution type for each grid point through goodness-of-fit tests; (2) validating the reliability of the method using leave-one-out cross-validation based on observed data. In contrast to conventional analyses typically conducted separately at individual stations, this grid-scale batch processing approach enabled consistent treatment across the entire spatial domain of the river basin, thereby providing a more intuitive reflection of the spatial distribution characteristics of rainfall. Then, annual maximum rainfall series for 1-day, 3-day, and 7-day durations were extracted for each grid cell to compute grid-based design storm values for specified return periods according to the locally optimal probability distribution type and parameters. Finally, spatial analysis was conducted on the design storm values to reveal their spatial distribution patterns. [Results] The evaluation of daily areal average rainfall revealed substantial performance differences among the three reanalysis datasets. ERA5 tended to significantly overestimate rainfall in the Nujiang River Basin, with a BIAS of up to 56%, indicating substantial deviation from ground observations. MSWEP performed better than ERA5. CMFD showed the best performance, displaying a strong correlation with observed station data (R=0.82), an exceptionally low BIAS (1%), and the smallest RMSE (1.38 mm) and MAE (0.78 mm) among the three datasets. The accuracy assessment results at each station further confirmed the superiority of CMFD. Nevertheless, all three datasets exhibited their largest significant errors at Gongshan station—an outcome consistent with previous studies indicating that both reanalysis and merged products struggled to maintain accuracy in areas of steep relief and high spatial rainfall variability. The derivation of design storms using the grid-scale L-moment method driven by CMFD exhibited significant reliability, specifically manifested in the following aspects.At the station scale,the design storm values under the 5% design frequency,estimated by the L-moment method based on CMFD grid data,were highly consistent with results obtained by the Pearson Type Ⅲ distribution’s visual curve-fitting method. At the areal scale, for the 1-day, 3-day, and 7-day annual maximum design storms in the river basin, under the four return periods of 0.1%, 1%, 2%, and 5%, the relative errors between the calculation results of the CMFD-based grid method and the areal design storm values of the river basin derived by the traditional visual curve-fitting method were within 10%. Spatial analysis of the CMFD-derived design storm maps revealed three distinct high-value zones of design storms across the river basin. The high-value zone surrounding Gongshan station was corroborated by observed data, confirming its reliability. The other two potential high-intensity zones were located in areas lacking adequate ground observations and thus required further verification through targeted field campaigns. [Conclusion] The grid-based high-resolution design storm estimation framework in this study overcomes the limitations of traditional station-based methods in data-scarce basins. By integrating optimally evaluated reanalysis precipitation data with the L-moment method applied in a spatially explicit manner, the approach yields detailed precipitation extreme maps that preserve local variation. Compared with the conventional approach that relies solely on limited station data to produce basin-average or single-station design storm estimates, the generated design storm maps deliver substantially enhanced spatial detail and accuracy.

[Objective] To meet the demands of constructing a modern reservoir operation and management matrix and to further enhance the flood forecasting and early warning capabilities of the Danjiangkou Reservoir, this study simulates the over-standard flood discharge scenario of the Danjiangkou Reservoir, and analyzes the evolution and inundated conditions of the downstream flood, aiming to improve the accuracy of the flood forecasting visualization and emergency planning. In doing so, the study seeks to provide stronger support for ensuring the safety of the Danjiangkou Reservoir Project and the security of water supply. [Methods] Based on the principles of the continuity equation and the momentum equation, the MIKE series model software was used to establish a two-dimensional hydrodynamic model of the downstream river channel and floodplain. Fully considering the impact of flood evolution on key cities downstream, a computational grid was constructed based on DEM and measured terrain to simulate the flood evolution of the downstream areas during over-standard discharge from the Danjiangkou Reservoir under seven scenarios. The arrival time of flood and peak flood in downstream areas under different scenarios was analyzed. The relationships between peak flood water level, peak flood discharge, design water level, and maximum allowable flow at typical cross-sections were compared. Based on GIS software, the inundation range and inundation depth in the downstream areas under different scenarios were analyzed. [Results] Under the regulation and storage effect of the project, the flood reached Xiangyang and its upstream areas within 2 to 10 hours, the Yicheng-Shayang cross-section within 10 to 24 hours, and the Xiantao area approximately two days later. The arrival time of the flood peak at each typical cross-section exceeded 68 hours. Under the condition of concrete dam failure, the flood spread pattern in the mountainous areas near the dam was similar to that under the regulation and storage scenario, while the flood evolution speed in the plain areas was generally more than 3 hours slower than that under the engineering regulation and control scenario. In the case of sudden over-standard water inflow and earth dam failure, the flood and flood peak in the areas upstream of Zhongxiang arrived within 12 and 18 hours, respectively, while in the areas downstream of Zhongxiang, they arrived after 13 and 31 hours, respectively. There were high risks of embankment overflow in the section from Danjiang to Yicheng. Under the conditions of verification flood, design flood, dead water level failure of the concrete dam, and failure of the elevated part of the concrete dam, the inundation depth of most areas from the dam site to Fancheng, Xiangyang was 16-20 meters, while that downstream of Tianmen was less than 3 meters. In the case of a severe flood in which all soil and rocks collapsed, the inundation depth from the dam site to Fancheng, Xiangyang was approximately 35 meters, while that of the Danjiangkou section exceeded 50 meters. The flood in Shayang County caused the inundation of over 70% of the area in Qianjiang City, with the overall inundation depth below 2 meters. [Conclusion] Based on the above results, this study provides strong support for the emergency preparedness for the safety management of the Danjiangkou Reservoir Dam, the development of a visualized flood rehearsal, and the construction of a modern reservoir operation management matrix.

[Objective] This study aims to quantitatively evaluate the effects of the emergency regulation of the Three Gorges Reservoir in response to the Tuanzhou polder breach emergency, thereby improving the understanding of flood control regulation of the Three Gorges Reservoir and laying a foundation for further optimization of its operation in the future. [Methods] A one-dimensional and two-dimensional coupled hydrodynamic model for the Jingjiang River reach and east Dongting Lake was established and validated with field-measured data. Hydrological conditions of the river-lake system under different regulation scenarios of the Three Gorges Reservoir were designed and simulated, and the effects of reservoir regulation on river-lake discharge and water levels were quantitatively analyzed. The development of emergencies in the Dongting Lake area (including Tuanzhou polder) before and after the breach, as well as the variation of water level at Qilishan, were analyzed. The effects of the Three Gorges Reservoir regulation on alleviating the flood-control pressure in the Dongting Lake area were discussed. [Results] Compared with the original regulation plan before the Tuanzhou polder emergency, the actual regulation of the Three Gorges Reservoir reduced the water level in east Dongting Lake by up to approximately 0.34 m, and advanced the time for the water level at Qilishan station to fall below the warning level by 18 hours. Flood-control emergencies in the Dongting Lake area mainly occurred during the high-water period after the water level exceeded the warning level and during the water recession period, and the regulation of the Three Gorges Reservoir reduced the probability of emergencies in the Dongting Lake area. [Conclusion] The emergency regulation of the Three Gorges Reservoir shortens the duration of the Qilishan water level exceeding the warning level and alleviates flood-control pressure in the Dongting Lake area. This study provides a scientific and quantitative evaluation of the regulation effects of the Three Gorges Reservoir, which provides a basis for further optimization of its operation.

[Objective] To evaluate the potential chain disaster effects such as debris flows under ultra-standard extreme hydrological conditions, this study aims to establish a comprehensive catastrophe evolution analysis system and propose optimized design solutions to enhance safety control capabilities from the source, transforming the safety control of tailing dams from passive response to proactive defense. [Methods] A combination of numerical simulation and engineering analysis was adopted. Focusing on a typical tailing dam, we constructed an integrated 3D catastrophe evolution analysis model covering the reservoir area and downstream regions. The finite element strength reduction method was used for numerical stability analysis of the tailing dam, accurately identifying potential sliding surfaces and instability failure zones through plastic strain cloud maps. Furthermore, multi-phase flow coupling simulation technology was introduced to combine the process of dam failure and subsequent debris flow progression. Within a digital elevation model, the entire evolution process of post-failure debris flow in downstream valleys was dynamically simulated, quantitatively acquiring critical disaster-causing parameters such as flow velocity, inundation extent, and depth. [Results] (1) Regarding dam stability, under the action of extreme flood levels, the maximum deformation zone identified by the finite element strength reduction method is not located at the dam body but correlates with the reservoir shape and topography. This area represents the most likely initial instability zone, highly susceptible to triggering local or overall landslides, thus inducing dam breaches.(2) Concerning the debris flow evolution process, simulations accurately depicted the descent paths and dynamic evolution characteristics of breached debris flow. Specifically, in terms of flow velocity, maximum flow velocities were observed in the immediate downstream area of the breach, indicating strong erosive capabilities; however, velocities gradually decreased with distance and widening terrain while still posing significant threats to key residential areas and infrastructure. In terms of inundation extent and depth, significant inundation areas formed in downstream valleys, with simulation results clearly delineating risk boundaries corresponding to different flood magnitudes. Maximum inundation depths reached several meters in downstream low-lying areas, directly threatening roads, buildings, and farmlands. Through coupled analysis, the full-chain disaster evolution characteristics from dam breach, debris flow formation to final deposition were identified. [Conclusion] This study proposes optimizing the existing drainage system of tailing dams with a stepped energy dissipation structure which significantly reduces the velocity and kinetic energy of descending floods, effectively controlling overflow erosion on the dam slope, fundamentally weakening the dynamic basis for overtopping destruction. It elevates the safety control system from traditional passive reinforcement and post-disaster rescue to a new phase of proactive intervention in water flow energy, preventing damage before it occurs, thereby markedly enhancing the ability of tailing dams to cope with sudden excessive floods. The research findings provide important theoretical support and technical references for risk assessment, emergency planning, and engineering renovation and expansion of similar tailing dams.

[Objective] Drought-flood abrupt alternation (DFAA), characterized by high suddenness, strong complexity, and great destructive power, has emerged as a significant risk source threatening regional ecological security and social sustainable development. This study aims to systematically review the progress of DFAA research, clarify its development trajectory, research hotspots, and knowledge structure, identify existing research gaps, and provide scientific guidance for future research directions. [Methods] Based on Web of Science (WOS) Core Collection and China National Knowledge Infrastructure (CNKI) database, Chinese and English publications related to drought-flood abrupt alternation (DFAA) between 2005 and 2024 are systematically retrieved. The bibliometric analysis tool CiteSpace software is utilized to visually analyze annual publication trends, keyword co-occurrences, and keyword bursts. On this basis, existing research is summarized and compared from three dimensions—identification methods, causal mechanisms, and disaster impacts—and, accordingly, optimization pathways for future research are proposed. [Results] (1) From 2005 to 2024, a total of 322 DFAA-related publications were issued globally, with China accounting for 53.2%. The development of CNKI literature went through three stages: preliminary exploration (2005-2010), rapid development (2011-2018), and stable development (2019-2024). Publications in the WOS have accelerated since 2018 and reached a peak in 2023, reflecting a rapid increase in international attention. (2) Domestic research focuses on the spatiotemporal evolution patterns and atmospheric circulation mechanisms of DFAA, with keyword bursts concentrated in trend analysis, spatiotemporal characteristics, and low-frequency oscillations. International research places greater emphasis on the long-term changes of DFAA and its ecological impacts in the context of climate change, with hotspot keywords including the Yangtze River, vegetation, and climate change. (3) First, there is a lack of a unified, multi-scale coupled DFAA identification system, as existing indices are mostly limited to a single temporal scale and consider limited factors in index construction. Second, causal analysis relies excessively on meteorological factors, with insufficient consideration of underlying surface changes and human activities. Third, impact assessment focuses on agricultural yield reduction and vegetation response, while research on the long-term impacts on urban resilience, water resource security, socio-economic systems, and ecosystem service functions remains inadequate. [Conclusion] Research on DFAA is currently at a critical stage of transitioning from phenomenon description to mechanism analysis and comprehensive impact assessment. Future research should focus on constructing a comprehensive identification indicator system that integrates multiple temporal scales and considers regional heterogeneity, while integrating multi-source data such as precipitation, soil moisture, temperature, topography, and vegetation to improve the accuracy and applicability of event identification. Future efforts are needed to deepen investigations into the formation mechanisms of DFAA and to strengthen regional comparisons and global-scale correlation analysis. In addition, the dimensions of impact research should be expanded to systematically assess the compound effects of DFAA on urban infrastructure, water resource allocation, ecological service functions, and socio-economic resilience, and to establish long-term monitoring networks that can provide scientific support for disaster risk management and climate adaptation policy formulation.

[Objective] During the impact of Typhoon Kong-Rey on Shanghai in the autumn of 2024, the Suzhou River reached a new historical high water level. To deeply analyze the causes of this high water level event, assess the response capacity of the existing flood control and drainage system, and explore optimized scheduling and engineering measures, this study systematically reviews the hydrological process of the high water level in the Suzhou River during Typhoon Kong-Rey and proposes practical countermeasures. It aims to provide insights and a scientific basis for optimizing flood control scheduling and urban flood control and drainage system in Shanghai, while also serving as a reference for other cities facing similar challenges. [Methods] A method combining field investigation and numerical simulation was adopted, and data on rainfall, water level, tidal level, and hydraulic facility scheduling during Typhoon Kong-Rey were collected. Considering factors such as rainfall-runoff, river network hydrodynamics, and pump-gate scheduling, a hydrodynamic model for the tidal river network was constructed to simulate the flow dynamics and water level changes in the Suzhou River and its adjacent river network. The average coefficient of determination for water level simulations reached 0.96. On this basis, a knowledge graph was utilized to identify the causes of the high water level in the Suzhou River. Three types of countermeasures were proposed: emergency discharge restriction on both banks, emergency diversion in the river network, and optimized planning for increased drainage. Different scheduling schemes were set up for simulation and comparison to quantitatively evaluate their effectiveness in reducing high water levels and their risk impacts. [Results] Simulations showed that the high water level in the Suzhou River during Typhoon Kong-Rey was primarily caused by the combined effects of concentrated rainfall in the middle and lower reaches, substantial inflow of floodwater from both banks, and the backwater effect from the high tidal level of the Huangpu River. Simulations of different countermeasures revealed the following results. (1) Emergency discharge restriction on both banks: Short-term discharge restriction in the Jiabaobei and Dianbei areas could reduce the highest water levels along the Suzhou River by 0.16-0.29 m, lowering the highest water level at Beixinjing to below 4.25 m. (2) Emergency diversion in the river network: Combining discharge restriction in Jiabaobei and Dianbei areas with emergency diversion via the Xinchapu River could maintain the highest water level along the entire Suzhou River below 4.20 m, diverting approximately 1.02 million m³ of floodwater, with minimal impact on flood control on both banks. (3) Optimized planning for increased drainage: After the implementation of the planned Suzhou River estuary pump station and Wenzaobang east pump station, the reduction in the highest water level along the Suzhou River could reach 0.40-0.64 m, while also enhancing the drainage capacity of the Jiabaobei area and significantly improving regional flood control resilience. [Conclusion] Existing engineering system for the Suzhou River has shortcomings under extreme events. Scientific scheduling and engineering optimization can effectively reduce the risk of high water levels. It is recommended to prioritize the “Jiabaobei + Dianbei discharge restriction + Xinchapu diversion” as the emergency scheduling scheme, and to accelerate the construction of the Suzhou River estuary pump station and the Wenzaobang east pump station, thereby establishing a multi-level flood control and drainage system of “restriction-diversion-expansion”. This study provides replicable and scalable scheduling experience and engineering approaches for Shanghai to cope with similar extreme typhoon events, and also offers important references for other plain cities with tidal river networks.

[Objective] This study focuses on the coordinated flood control scheduling of the Three Gorges and Qingjiang cascade reservoirs under complex flood regional compositions. By selecting combinations of different flood areas in the Three Gorges and Qingjiang river basins as model inputs, this study aims to establish a multi-objective joint flood control optimal scheduling model, with innovative optimization of the activation timing and utilization methods for the reservoir group’s flood control capacity. The objectives are to fully exploit the potential of joint flood control scheduling of reservoir groups and leverage their synergistic effects in flood mitigation and disaster reduction while ensuring upstream and downstream flood control safety. [Methods] The study integrated the characteristics of flood events and regional compositions, using the frequency and intensity of extreme flood events to select combinations of flood areas as model inputs. A multi-objective joint scheduling model for the Three Gorges and Qingjiang cascade reservoirs was established, with the objective of ensuring upstream and downstream flood control safety. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) was employed to solve the model, enabling the exploration of optimal activation strategies for flood control capacity under different flood regional compositions. The model was validated using floods from typical years (1969, 1981, 1998, and 2020). The results were compared with actual scheduling schemes to highlight the benefits of coordinated scheduling. [Results] The coordinated flood control optimal scheduling model provided a broad and evenly distributed Pareto frontier, revealing a significant trade-off between the objectives of minimizing excess flood volume at control points and lowering the peak water level for flood regulation at the Three Gorges. For the typical years, the optimal peak water levels for flood regulation and excess flood volumes were as follows: 156.2-168.8 m and 13.97-25.15 billion m³ (1969), 163.3-171.0 m and 21.56-31.47 billion m³ (1981), and 161.8-171.0 m and 25.01-32.91 billion m³ (1998). The activation timing of Qingjiang flood control capacity advanced with increasing river basin flood volume, emphasizing the importance of early activation during extreme floods. Compared to the actual operation scheme, the coordinated operation scheme for the 2020 typical year reduced the maximum flood regulation water level at the Three Gorges by 5.0 m, decreased the excess flood volume by 56.2 billion m³, increased the peak flood discharges at Zhicheng and Chenglingji by 2 603 m³/s and 1 035 m³/s, respectively, and lowered the final water level of the Three Gorges Reservoir by 4.2 m. The coordinated scheduling scheme ensured that Qingjiang reservoir reached its highest water level before mid-July and maintained high-water-level operation until the flood season ended in the Yangtze River Basin, thereby fully achieving its flood peak shaving and detention functions. [Conclusion] This study proposes innovative strategies for activating flood control capacity in the Three Gorges and Qingjiang cascade reservoirs, specifically tailored to different regional flood compositions, thereby providing decision-makers with diversified scheduling schemes. The findings demonstrate that optimal scheduling schemes significantly enhance flood mitigation benefits, as evidenced by substantial reductions in excess flood volume and peak discharge. However, constrained by the limited flood control capacity of the reservoir group, the joint scheduling of Qingjiang and Three Gorges reservoirs cannot maximize flood control benefits across the river basin. Future efforts should incorporate additional water projects, such as flood detention areas, into the joint scheduling framework to further strengthen flood control capabilities across the river basin. This study provides theoretical foundations and technical support for exploring the coordinated scheduling potential of large-scale river basin reservoir groups and facilitating science-based decision-making.

[Objective] Flood disaster risk assessment for coastal cities is crucial for improving the resilience of new urban planning and disaster emergency management capabilities. This study focuses on the issues in existing research on flood risk assessment in coastal new towns, such as incomplete indicator systems and insufficient spatial analysis accuracy. Taking Lingang New City in Shanghai as the study area, this study conducted a detailed comprehensive flood disaster risk assessment to provide a scientific basis and decision support for disaster risk management, emergency response, and urban planning. [Methods] Following the principles of scientific rigor and operability, a three-dimensional assessment model was established integrating the hazard of disaster-inducing factors, the exposure of disaster-prone environments, and the vulnerability of disaster-bearing bodies. A high-resolution grid unit of 30m × 30m was innovatively adopted, and a combined subjective-objective weighting approach was used by integrating the Analytic Hierarchy Process (AHP) and the entropy weight method. Through spatial overlay analysis, a refined flood disaster risk assessment was achieved. [Results] (1) Hazard distribution: Due to the limited and relatively uniform distribution of rainfall sampling points, rainfall indicators in the study area were regarded as homogeneously distributed. Therefore, the spatial variation in the hazard of disaster-inducing factors was mainly determined by river network density. (2) Exposure distribution: High and relatively high exposure areas were mainly located near towns and streets, where the proportion of impervious surfaces was high, and both vegetation coverage and terrain elevation were relatively low. Low and relatively low exposure areas were widely distributed in suburban and rural areas. (3) Vulnerability distribution: High and relatively high vulnerability areas were concentrated in Pudong New Area, especially around Nicheng Town and Dishui Lake, where GDP per unit area and population density were relatively high. Fengxian District showed comparatively lower vulnerability. (4) Comprehensive risk distribution: The spatial distribution of comprehensive flood risk levels in Lingang New Area was relatively balanced, with high-risk areas accounting for 10.34%, relatively high-risk areas 17.97%, medium-risk areas 27.59%, relatively low-risk areas 27.03%, and low-risk areas 17.07%. Spatially, there were significant regional disparities. The southeastern coastal region (e.g., Nanhui New Town and its surroundings) had the highest risk, followed by central town areas (e.g., Nicheng Town, Shuyuan Town), while the central-western rural areas had the lowest risk. [Conclusion] The proposed “three-dimensional nine-indicator” assessment framework overcomes the limitation of separating subjective and objective weights in traditional risk assessments. The constructed flood risk indicator system can provide a replicable risk governance paradigm for China and other rapidly developing coastal cities.

[Objectives] This study aims to improve the accuracy and efficiency of flash flood forecasting in the Guanshan River Basin and other similar small mountainous watersheds frequently affected by flood disasters by analyzing the runoff generation mechanisms of flash floods. By comparing the performance of saturation-excess, infiltration-excess, and hybrid runoff generation modes in simulating flash floods of different magnitudes, we also seek to overcome the limitations of single-mode simulation under complex terrain and different rainfall intensities. [Methods] The runoff generation module of the Xin’anjiang model was modified to simulate 38 flood events in the Guanshan River Basin (24 for calibration, 14 for validation) using saturation-excess, infiltration-excess, and hybrid runoff generation modes. Flood magnitudes were classified into small, medium, large, and extra-large according to the Specifications for Hydrological Information and Forecasting. Simulation results were evaluated using Nash-Sutcliffe efficiency coefficient (NSE), peak discharge error, and runoff depth error to compare the applicability and advantages of different runoff generation mechanisms. [Results] The vertical hybrid runoff generation mode demonstrated higher accuracy and stability across different flood magnitudes. It outperformed the other two modes in terms of NSE during both calibration and validation periods, with particularly strong performance in simulating extra-large floods. The saturation-excess mode performed better for small floods but was less stable for large and extra-large events. The infiltration-excess mode achieved the highest accuracy in simulating peak discharges of large floods, but performed relatively poorly in small and extra-large events. Further analysis of the runoff generation mechanisms indicated that runoff generation processes were closely related to rainfall characteristics, soil infiltration rates, and underlying surface conditions. Under intense and short-duration rainfall, infiltration-excess was the dominant mechanism, while under low-intensity and long-duration rainfall, saturation-excess prevailed. The vertical hybrid mode comprehensively integrates both mechanisms, dynamically adjusting the runoff generation approach based on varying rainfall conditions. It enabled effective simulation of flash flood processes under different rainfall scenarios. Additionally, this mode showed higher precision in simulating the recession processes, as it better reflected river basin storage states and the dynamics of interflow and groundwater runoff. [Conclusions] The vertical hybrid runoff generation mode demonstrates significant advantages in simulating flash floods in the Guanshan River Basin, providing robust support for improving the accuracy and efficiency of flash flood forecasting in this area. These findings not only provide a theoretical basis for flood prevention and disaster mitigation in the Guanshan River Basin but also offer innovative approaches for flash flood forecasting in complex mountainous watersheds. The innovation of this study lies in its comprehensive consideration of multiple runoff generation mechanisms and its validation of the hybrid mode’s adaptability under different rainfall conditions through comparative analyses. Future research will further refine the runoff generation module by incorporating more detailed physical processes and parameterization methods, while exploring the coupled applications of hydrological and hydrodynamic models to enhance the model’s capability in simulating complex hydrological processes and provide deeper insights into flood evolution in small mountainous watersheds.

[Objectives] The parameter calibration of the CASC2D hydrological model is mainly based on manual trial-and-error methods. It lacks a global sensitivity analysis of model parameters and the identification of relationships between parameters and simulation indices based on such analysis. Therefore, there remains considerable room for further exploration and discussion regarding parameter calibration methods and practices for the CASC2D hydrological model. [Methods] The CASC2D model is relatively suitable for flood forecasting in small semi-arid watersheds. This study selected the region upstream of the Suyukou hydrological station in the eastern foothills of the Helan Mountains as the study area. The Sobol index method, a representative global sensitivity analysis approach, was employed. Independent and global sensitivity analyses were conducted for eight key parameters of the CASC2D hydrological model, based on three performance indicators derived from simulation results: peak flow timing, peak discharge, and coefficient of determination. These analyses identified the correlations between model sensitive parameters and model-simulated peak discharge, peak flow timing difference, and coefficient of determination, providing references for model parameter calibration. [Results] The three parameters with the greatest global influence on the peak flow timing were saturated hydraulic conductivity (K_s), channel roughness coefficient (n_c), and soil water deficit (M_d). The peak flow timing of flood was mainly related to the infiltration calculation in the model. During the flow concentration process, channel routing played a controlling role, while overland flow routing played a supporting role. Additionally, the peak flow timing of flood was negatively correlated with river width (L) and vegetation interception (I), and positively correlated with n_c, overland flow roughness coefficient (n_s), K_s, capillary pressure head (H_c), and M_d. The parameters that had the greatest global influence on peak discharge and coefficient of determination were K_s, H_c, and n_c. Flood peak discharge was jointly influenced by infiltration characteristic parameters, overland flow routing parameters, and channel routing parameters. Among them, infiltration characteristics played the dominant role, while in the routing process, overland flow routing was relatively more influential. Coefficient of determination was mainly related to infiltration characteristics and channel routing parameters, with the former being dominant. Additionally, peak discharge showed positive correlations only with n_c, n_s, K_s, H_c, and M_d. Coefficient of determination was negatively correlated with I and K_s, but positively correlated with L, n_s, H_c, and M_d. [Conclusions] This study further explores and supplements research on global sensitivity analysis of CASC2D hydrological model parameters. It proposes the types and sequence for adjusting eight key parameters in response to errors in peak discharge, peak flow timing, and coefficient of determination during initial calibration. The study also suggests reasonable increase or decrease ranges for each parameter based on their sensitivity to different indicators. These findings provide references for properly selecting the directions and ranges of parameter adjustments during calibration. Due to the interactions among parameters, the selection of adjustment directions and ranges during calibration should be based on each parameter’s independent sensitivity and degree of interaction obtained from the first-order and total effect indices. The research findings can provide references for manual calibration efforts and improve the efficiency of parameter calibration. Furthermore, given the current lack of research on automated calibration for this model, the findings offer strategic guidance for the development of automated calibration algorithms.

The accuracy of predicting the peak flood flow at the breach of earth-rock dam is crucial for dam break analysis. To improve the prediction accuracy of the post-breach peak flood flow, this paper presents a prediction model based on the General Regression Neural Network (GRNN), optimized by the Fennec Fox Optimization (FFA) algorithm for hyperparameters, to forecast the peak flood flow caused by dam breaches. Using a database of domestic and international dam failure cases, the model selects three factors as input variables: the reservoir capacity above the breach bottom, the water depth above the breach bottom, and the breach depth, to build the FFA-GRNN prediction model. To evaluate the model’s precision and fitting accuracy in predicting peak flood discharge at dam break, we compared it with four other intelligent algorithms. Results show that the proposed FFA-GRNN model has a lower Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and a higher coefficient of determination (R²) than other models, indicating superior computational precision and fitting performance.

To optimize the drainage engineering layout in the Lixia River water network area, it is essential to consider the interaction between the internal lowland and the incidence of heavy rainfall in adjacent waterlog-prone areas. Using the Copula function, we constructed a joint distribution of rainfall frequencies for these waterlogged areas to calculate the heavy rainfall probability. Pearson Type-III marginal distributions for the rainfall frequencies in the Fubu and Doubei areas, together with Frank Copula function for the fitting of their two-dimensional joint distribution, facilitates the calculation of the probabilities of heavy rainfall for specified durations and return periods. By integrating observed rainfall time series with frequency analysis, we found that the risk of both waterlog-prone areas (namely the Fubu and Doubei areas) experiencing heavy rainfall beyond design standards is minimal. Specifically, when heavy rainfall in the Fubu area exceeds design drainage criteria, the likelihood of heavy rainfall in the Doubei area surpassing design flood control thresholds remains low. These findings support the feasibility of the proposed drainage channel scheme in the Doubei area.

To elucidate the near-field propagation characteristics of waves generated by subaerial landslides, we developed a three-dimensional numerical model of subaerial landslide impulse waves using FLOW-3D. We simulated the landslide body’s entry into water and subsequent wave propagation, and analyzed the 3D impulse wave’s temporal-frequency evolution via wavelet transform. Our findings reveal that the energy of the 3D landslide impulse wave primarily shifts from the main radial direction to the sides. Beyond a distance of two times the water depth from the plunging point, the energy spectrum’s evolution in other radial directions closely resembles that in the main radial direction. Additionally, the decay rate of local energy across all radial directions becomes consistent, and the energy transmission velocity of wave components near the dominant frequency does not vary with the radial angle. We further introduce the concepts and estimation formulas for the near-field characteristic wave energy peak and its transmission velocity, which are valuable for assessing landslide surge disasters.

Based on the FVCOM hydrodynamic model and the FVCOM-SWAVE wave model, we developed a wave-current coupled storm surge model for the Bohai sea, Yellow sea, and East China Sea during Typhoon “Chan-hom”. Following rigorous validation of surge elevations and significant wave heights, we quantified the impact of wave-current interaction on storm surge and identified key dynamic factors. Findings indicate that wave-current interaction significantly influences surge elevations in near-shore shallow waters, contributing approximately 14% to peak surge water levels. During high tide periods, wave-current interaction tends to reduce surge elevations, but increases surge levels during low tide periods. Accounting for wave-current interaction, the simulated significant wave heights show better agreement with observations. Additionally, the study compares the contributions of tide-surge interaction, wind field, and pressure to surge elevation. The wind field primarily drives surge elevations, with its effects most pronounced in the coastal waters of Zhejiang Province and Hangzhou Bay, where maximum surge elevations reach up to 2 m. In open sea areas, air pressure dominates surge elevations within the typhoon center’s radius. However, in coastal waters, particularly at the head of Hangzhou Bay, nonlinear tide-surge interaction and wave-current interaction significantly impact surge elevations, with respective maxima of 1.2 m and 0.5 m. These findings offer critical insights for enhancing coastal disaster prevention and mitigation strategies.

To cope with the severe flood challenges caused by extreme meteorological events in the western part of Shanghai, an effective water level control strategy was proposed. The Qingsong region of Shanghai during the “Fireworks” typhoon was selected as the research object. The actual rainfall and working condition data were comprehensively analyzed, including rainfall, water level of the river outside the polder, water level of the secondary polder, and water level process of the river outside the polder. Two strategies were proposed, namely, over-storage of rivers and lakes in the secondary polder area and controlling of drainage after the rain peak in the polder area. The effectiveness of alleviating the high water level was evaluated by using digital topographic analysis and numerical simulation of flood control. It is found that the implementation of the above strategies can greatly enhance the storage capacity, and the theoretical estimate is to increase the capacity by about 11.7 million m³ and 2.46 million m³, respectively, which can reduce the water level of the river channel in the area by about 30 cm, and effectively alleviate the high water level. This study not only verifies the effectiveness of the strategy, but also adds new controlling methods to the existing flood control and drainage system, which provides a scientific basis for the city’s scheduling decision-making when facing major water challenges, and has important practical value and theoretical contribution to building a more resilient water management system and ensuring the safe operation of the city.

This paper aims to investigate key issues related to simulating floods from hilly to plain areas due to human activities and propose corresponding solutions and models. These issues encompass the uneven spatial distribution of rainfall within the basin, substantial differences in runoff generation and convergence between hilly and plain areas, and complex boundary conditions influenced by water conservancy engineering construction and scheduling. To address these issues, the Hanbei River basin is divided into 11 units as a case study. The uneven spatial distribution of rainfall is tackled by analyzing the spatial distribution of extreme rainfall events in each unit. Calibration of each unit’s hydrological model parameters is conducted based on its underlying surface conditions using the API model, thereby improving the model’s fit to the actual conditions and addressing the significant differences in runoff generation and convergence between hilly and plain areas. The model incorporates the impacts of human activities such as river diversion, reservoirs, flood storage areas, sluices, pump stations construction, and scheduling, as well as land use, into the physical model and runoff simulation. This integration enables the construction of a runoff system that accurately reflects actual scheduling scenarios. The NSE values of simulated peak flows for all scenarios exceed 0.85, indicating strong agreement between simulated and measured values for peak flow, water level, and peak time.

Flood disasters are highly frequent and strongly destructive. Risk assessment reveals high-risk hotspots and their driving factors, aiding in the establishment of a scientific and efficient flood control and disaster reduction system. This study focuses on the Xunjiang Flood Control Protection Area in the Pearl River Basin. Initially,the HEC-RAS hydrodynamic model was constructed to extract maximum flow velocity and water depth for flood risk evaluation. Subsequently, the exposure and vulnerability of affected populations were assessed by using the AHP and entropy weight methods in consideration of factors including population density, GDP, and land use. Finally, flood risk was quantified, and spatial-temporal changes were analyzed. Results indicate that the hydrodynamic model achieves an average accuracy exceeding 0.80, with a false positive rate below 0.28. Medium to high-risk zones in the Xunjiang Flood Control Protection Area exceed 5.20%. From 1997 to 2017, risks of various levels displayed an increasing trend. Notably, nearly 46.69% of medium to high-risk zones exhibited significant upward trends. These findings support informed decision-making in flood risk management practices.

To address the challenge of estimating the return level of hydrological drought events due to the limited sample size of drought events that can be obtained from measured streamflow data, we applied three commonly utilized annual runoff probability distribution functions,namely, Log-normal, Gamma, and Normal,to measured runoff data obtained from the Waizhou station on the Ganjiang River. Theoretical probability distribution functions (PDFs) for drought characteristics, including duration and severity, were derived using statistical properties of annual runoff. The return period, defined as the mean interarrival time of drought events surpassing a certain severity threshold, was computed and validated through Monte Carlo simulation. Results demonstrate that deriving return periods of hydrological drought events using PDFs of drought duration and severity establishes a robust statistical basis with credible accuracy. The proposed method partially mitigates sample bias in estimating drought return periods based on limited observed hydrological series, offering a novel approach to assessing future drought risk.

The Three Gorges Interval (TGI) accounts for 5.6% of the upper Yangtze River basin area. However, floods originating from this region constitute over 10% of the floods in the Three Gorges Reservoir (TGR). Hence, heavy rainfall-induced flood is an important factor that must be taken into consideration in ensuring reservoir flood control safety. Based on TGR inflow data during 2007-2011 and flow data from upstream Cuntan and Wulong stations, we developed a HEC-HMS flood simulation model to examine the correlation between rainstorm floods in the TGI and inflow floods into the reservoir. We proposed an interval flood modeling scheme based on classified parameter adjustment and staged testing according to flood sources: for floods primarily driven by upstream inflows, the flood confluence parameters were calibrated; for floods predominantly influenced by regional precipitation,the flow yield parameters were calibrated. To validate the model, we compared simulated flood processes post-2012 with operational records of the TGR, demonstrating model accuracy with the relative errors of peak flow rate in calibration and verification periods within ±20% and peak time errors below 3 hours. Comparisons with Three Gorges Project (TGP) operation records confirmed the model’s suitability for simulating post-2012 TGR flood processes. Examining the flood event on June 26, 2016, as a representative case, we observed a significant 27.2% contribution rate of flood peak within the reservoir, with a peak time advance of 16 hours. These findings facilitate understanding TGR flood impacts and serve as a technical reference for flood modeling schemes within the basin region.

A high-resolution storm surge model encompassing the Bohai Sea, Yellow Sea, and East China Sea is developed based on the Finite Volume Community Ocean Model (FVCOM) to simulate and hindcast the storm surges induced by Typhoon Chan-hom. The model’s surge predictions align closely with observed tidal gauge data. Based on the International Best Track Archive for Climate Stewardship (IBTrACS) datasets, a linear regression is established between typhoons’ maximum wind speeds and their minimum central pressures along China’s coast, achieving a correlation coefficient of 0.96. On this basis, a variety of hypothetical typhoon paths are constructed based on the maximum wind intensity model to calculate the possible maximum storm surges (PMSS) in the Hangzhou Bay and Zhoushan Archipelago. Our findings indicate that typhoons landing perpendicular to the coastline yield the highest surge elevations, peaking at 8.76 m in Hangzhou Bay and 2.62 m in the Zhoushan Archipelago. This research offers valuable insights for the risk assessment and disaster prevention and mitigation for marine engineering projects in the Hangzhou Bay and Zhoushan Archipelago areas.