Roller Compacted Concrete (RCC) dams are critical infrastructure, playing an important role in economic and social development. However, dam failure can cause great losses. To mitigate hazards, studies of methods to deal with the uncertainty involved in the comprehensive evaluation process of the safety state of RCC dams are hot issues. Interval number theory is applied to quantify the uncertainty in this study. A comprehensive evaluation indicator system is explored, an approach to allocating the indicator weight rationally is proposed, and a comprehensive evaluation model is established. Comprehensive evaluation standards are developed. An RCC dam in China is used to illustrate the applicability of this comprehensive evaluation method based on interval number theory. The results indicate that the method and models proposed are suitable for comprehensively evaluating the safety state of RCC dams and can be used as a new procedure to monitor the safety of an RCC dam.

This study investigates upper-reservoir dam-axis siting in pumped-storage hydropower projects, where cut–fill balance and construction cost are critical under complex terrain conditions. Existing approaches still rely heavily on manual interpretation or static GIS-based analysis and therefore do not adequately optimize dam-axis geometry or earthwork balance. To address this limitation, we propose an Improved Adaptive Variable Neighborhood Search (IAVNS) algorithm that integrates high-resolution digital elevation model (DEM) data within a two-layer adaptive framework. The inner layer performs staged planar and elevation adjustments through adaptive neighborhood operators, whereas the outer layer conducts fitness-guided subregion migration to strengthen global exploration. Experiments on the Qiannan pumped-storage project show that IAVNS obtains layouts with improved cut–fill balance. In the 30-run benchmark comparison, IAVNS achieved a mean CFR of 1.31, which is close to, although slightly above, the upper bound of the adopted earthwork-balance reference interval. In the separate 20-run case-study analysis, the average storage-volume deviation was 0.13%, with run-level deviations ranging from $-1.39\%$ to $1.16\%$. In benchmark comparisons, IAVNS improves solution quality by 22.8% relative to the Genetic Algorithm (GA) and by 16.5% relative to classical Variable Neighborhood Search (VNS), while reducing convergence time by 49.5% and 27.4%, respectively. Sensitivity analysis further suggests that the framework remains locally robust under practically reasonable parameter perturbations, and the module-level ablation study indicates that the observed performance gains arise mainly from the problem-tailored search mechanisms for dam-axis siting rather than from a generic combination of metaheuristic components. Taken together, the case-study results, repeated-run comparison, sensitivity analysis, and ablation study support the use of IAVNS as a geometry-oriented decision-support framework for preliminary dam-axis design in terrain-sensitive hydraulic engineering applications.

Against the backdrop of global climate change and rapid urbanization, island cities face increasing compound-flood risks due to their fragmented topography and limited terrestrial space, yet cross-scale modeling and high-resolution exposure assessment for archipelagic environments remain insufficient. Taking Zhoushan City, China, as a case study, this research develops an integrated compound-flood multi-receptor exposure assessment framework combining cross-scale hydrodynamic modeling with high-resolution spatialization. For hazard assessment, a one-way sequential coupling of a parametric typhoon model, FVCOM, and LISFLOOD-FP was employed to simulate storm-surge, pluvial, and compound flooding at 50-, 200-, and 1000-year design levels. Model performance was evaluated using tidal-gauge observations, historical storm-surge records, remotely sensed historical inundation, and documented urban waterlogging locations. For exposure assessment, Random Forest-based dasymetric mapping was used to generate 30 m population and secondary- and tertiary-sector GDP datasets; primary-sector GDP was spatialized using a land-cover-based approach, and 3314 critical-infrastructure facilities were compiled across eight subsystems. The results reveal the following: (1) compound-flood inundation areas were 289.95, 424.93, and 513.31 km² under the 50-, 200-, and 1000-year design scenarios, respectively; (2) under the 1000-year compound scenario, 57.5% of the population, 51.3% of GDP, and 63.3% of critical infrastructure were exposed; (3) infrastructure exposure showed strong subsystem heterogeneity, with coastal facilities having the highest exposure ratio (76%) and emergency-rescue facilities reaching 65.3%; (4) sector-disaggregated GDP exposure revealed substantial economic-geographic differences among districts/counties, highlighting the need for differentiated adaptation strategies. The proposed framework provides spatially explicit information to support differentiated coastal adaptation planning and is transferable to other archipelagos and small island cities with similar data constraints.