Under the circumstances of global warming and rapid urbanization, damage caused by urban inundation are becoming increasingly severe, attracting the attention of both researchers and governors. The accurate simulation of urban inundation is essential for the prevention of inundation hazards. In this study, a 1D pipe network and a 2D urban inundation coupling model constructed by InfoWorks ICM was used to simulate the inundation conditions in the typical urbanized area in the north of Lin’an. Two historical rainfall events in 2020 were utilized to verify the modeling results. The spatial–temporal variation and the causes of urban inundation under different designed rainfalls were studied. The results were as follows: (1) The constructed model had a good simulation accuracy, the Nash–Sutcliffe efficiency coefficient was higher than 0.82, R² was higher than 0.87, and the relative error was ±20%. (2) The simulation results of different designed rainfall scenarios indicated that the maximum inundation depth and inundation extent increased with the increase in the return period, rainfall peak position coefficient, and rainfall duration. According to the analysis results, the urban inundation in Lin’an is mainly affected by topography, drainage network (spatial distribution and pipe diameter), and rainfall patterns. The results are supposed to provide technical support and a decision-making reference for the urban management department of Lin’an to design inundation prevention measures.

Urban flooding, driven by extreme rainfall events and urbanization, poses substantial risks to urban safety and infrastructure. This study employed a neighborhood-scale InfoWorks ICM model to analyze the full-process impacts of urban flooding under six rainfall return periods in Haining, China. The results reveal distinct non-linear responses from the 3-year to 50-year rainfall return period: (1) the surface runoff volume increases by 64.3%, with peak timing advancing by about one minute; (2) the overflow nodes rise from 37.35% to 63.24%, with durations over 30 min increasing by 78.6%; (3) the inundation areas expand by 164.9%, with maximum depths increasing by 0.31 m, showing significant regional disparities; and (4) high-risk zones, such as Haining People’s Square and Railway Station, require targeted interventions due to severe surface overflow and inundation. This comprehensive analysis emphasizes the need for tailored and phased flood prevention measures that address each stage of urban flooding. It provides a strong framework to guide urban planning and enhance resilience against rainfall-induced urban flooding.

Precipitation data in urban hydrological models are derived from an ideal stormwater model, which has some uncertainties and limited prediction times. Therefore, to reliably forecast urban flooding, prolong prediction time periods, and better support associated research in urban flood forecasting, a combination of weather forecasts and urban hydrology is necessary. By applying comprehensive cloud microphysical schemes in the Weather Research and Forecasting (WRF) model to the predecessor torrential rainfall associated with Typhoon Khanun (2017), this study evaluated different configurations of atmospheric-hydrological simulations based on the WRF model and InfoWorks ICM. Results showed that the microphysics scheme could significantly affect spatial and temporal distributions of the simulated torrential rainfall. Generally, the combination of WRF and NSSL schemes produced better performance. Applying the NSSL scheme to the WRF model and combining it with the InfoWorks ICM system can reproduce torrential rainfall and urban flood formations.

Due to the rapid acceleration of urbanisation and the increasing occurrence of extreme rainfall events, underpasses have become critical hotspots of urban flooding vulnerability. In this study, we investigated 36 underpasses in Hangzhou using the Urban Flood Inundation Model (UFIM) to systematically evaluate their drainage performance. A high-resolution hydraulic simulation framework was developed by integrating terrain data, drainage pipe networks, pumping stations, and land-use information. Based on the maximum tolerable hourly rainfall derived from multi-scenario simulations, the facilities were divided into high-, medium-, and low-vulnerability groups. Our quantitative and spatial analyses reveal a pronounced core–periphery disparity: 41.7% of the underpasses were highly vulnerable (drainage threshold ≈ 61.3 mm/h), exhibiting significant spatial agglomeration in the older urban core. In contrast, facilities in newly developed peripheral areas demonstrated better drainage performance (threshold up to 75.6 mm/h). Furthermore, the backwater effect from downstream rivers at flood stages significantly constrains pump efficiency by increasing the static head requirement. Based on these spatial vulnerabilities and thresholds, targeted infrastructure optimisation and spatial planning strategies are proposed, shifting the focus from uniform engineering upgrades to vulnerability-based drainage capacity enhancements.