Quantifying the spatiotemporal variations of basin-scale surface water (SW)–groundwater (GW) interactions is vital for the conjunctive management of water resources in the basin. In this study, an integrated hydrological model (SWAT-MODFLOW) is used to simulate the SW–GW system in the Huashan Basin. The numerical model was calibrated and validated using the streamflow observations of the watershed outlet and the groundwater levels of the long-term monitoring wells from 2016 to 2020 in the study area. The model results show that the SWAT–MODFLOW can achieve a better fit for the streamflow discharge, compared with the results in the single SWAT model, with R² (coefficient of correlation) and NSE (Nash-Sutcliffe efficiency coefficient) of 0.85 and 0.83, respectively. The water table fitting results indicate that R² and RMSE can reach 0.95 and 0.88, respectively. The water budgets analysis demonstrates that the average rate (0.5281 m³/s) of GW abstraction to SW is larger than the rate (0.1289 m³/s) of SW recharge to GW. Moreover, the exchange rate of SW and GW gradually reaches a peak value from June to August, and the lowest value is shown in April, for each hydrological year. Based on the IPPC6 CanESM5 dataset supplied by the Canadian Climate Centre, the regional precipitation scenario subject to climate change was predicted by the ASD (Auto Statistical Downscaling Model) a statistical downscaling method, under the climate scenarios of SSP2_4.5 and SSP5_8.5. The SW–GW interaction pattern was modeled under the future scenarios in the study area. The current (2016–2020) average annual rate of the SW–GW interaction is considered as the base value. Subject to the SSP2_4.5 scenario, the average exchange rate of the SW recharge to GW is 0.1583 m³/s, which is an increase of 22.8%. The average exchange rate of the GW discharge to SW is 0.5189 m³/s which is a reduction of 0.017%. Subject to the SSP5_8.5 scenario, the average exchange rate of SW recharge to GW is 0.1469 m³/s, which is an increase of 14.7%. The average exchange rate of the GW discharge to SW is 0.5953 m³/s, which is an increases of 12.7%. The results can assist in water resource management in the basin, by identifying potential locations of nutrient transport from the aquifer to the river, as well as changes in spatial variability under future climatic conditions.

The rapid development of urban underground space utilization, coupled with the increasing frequency of extreme precipitation events, has heightened the vulnerability of underground spaces to flood disasters, rendering flood prevention a critical challenge in underground infrastructure planning. While existing research predominantly focuses on pre-disaster early warning systems, in-disaster evacuation protocols, and post-disaster recovery strategies for underground flooding, systematic investigations into the disaster-bearing characteristics of underground spaces and the interrelationships among storage capacity, water depth, and disaster mechanisms remain notably deficient. To address these gaps, this study consolidates methods for identifying flood disaster-bearing characteristics in urban three-dimensional spatial contexts and establishes a comprehensive indicator system encompassing external flooding, underground waterlogging, and disaster-specific attributes. By defining the safe evacuation water depth at ground-level exits as a critical control threshold, we derive site-specific safe evacuation times and propose a methodology for constructing capacity-depth-disaster (C-D-D) curves to quantify flood resilience. These contributions provide a scientific foundation for abstracting representative underground space models, analyzing volume-dependent flood response mechanisms, and guiding integrated surface-underground disaster prevention planning at regional scales, thereby bridging theoretical research and practical decision-making in urban flood risk management.

Accurate and reliable measurement and prediction of the spatial and temporal distribution of rain field over a wide range of scales are important top

Rapid urbanization and frequent extreme events have made urban flooding a growing threat to residents. This issue is acute in old urban districts, where extremely limited land resources, outdated standards and poor infrastructure have led to inadequate drainage and uneven pipe settlement, heightening flood risk. This study applies InfoWorks ICM Ultimate (version 21.0.284) to simulate flooding in a typical old urban district for six return periods. A risk assessment was carried out, flood causes were analyzed, and mitigation strategies were evaluated to reduce inundation and cost. Results show that all combined schemes outperform single-measure solutions. Among them, the green roof combined with pipe optimization scheme eliminated high-risk and medium-risk areas, while reducing low-risk areas by over 78.23%. It also lowered the ponding depth at key waterlogging points by 70%, significantly improving the flood risk profile. The permeable pavement combined with pipe optimization scheme achieved similar results, reducing low-risk areas by 77.42% and completely eliminating ponding at key locations, although at a 50.8% higher cost. This study underscores the unique contribution of cost-considered gray-green infrastructure retrofitting in old urban areas characterized by land scarcity and aging pipeline networks. It provides a quantitative basis and optimization strategies for refined modeling and multi-strategy management of urban waterlogging in such regions, offering valuable references for other cities facing similar challenges. The findings hold significant implications for urban flood control planning and hydrological research, serving as an important resource for urban planners engaged in flood risk management and researchers in urban hydrology and stormwater management.

A significant part of Hong Kong has hilly terrain with relatively short flow concentration time and, hence, is susceptible to the threat of flash floods and landslides during intense convective thunderstorms and tropical cyclones. For places like Hong Kong, a rainfall model that could adequately capture small-scale temporal and spatial variations would be highly desirable. The main challenge in rain-field modeling is to capture and describe the dynamic time-space evolution of the rainfall during rainstorm events. In this study, radar data with a high spatial (1 km²) and temporal (6 min) resolution of four rainstorm events in Hong Kong are analyzed. A geostatistical approach based on indicator variograms of rain-fields is used. The spatial structure of a rain-field is found to be highly anisotropic and should be adequately considered in the model. Variability of the spatial structure of a rain-field was described well by the main features of the variograms. Moreover, it is possible to identify whether multiple rainstorm centers exist by comparing the mean length and range. In order to establish reliable statistics on the spatial and temporal structure of rain-fields in Hong Kong, this approach could be applied to a large set of rainstorm events in this same region in the future.