Flooding poses a significant threat as a prevalent natural disaster. To mitigate its impact, identifying flood-prone areas through susceptibility mapping is essential for effective flood risk management. This study conducted flood susceptibility mapping (FSM) in Chandrapur district, Maharashtra, India, using geographic information system (GIS)-based frequency ratio (FR) and Shannon’s entropy index (SEI) models. Seven flood-contributing factors were considered, and historical flood data were utilized for model training and testing. Model performance was evaluated using the area under the curve (AUC) metric. The AUC values of 0.982 for the SEI model and 0.966 for the FR model in the test dataset underscore the robust performance of both models. The results revealed that 5.4% and 8.1% (FR model) and 3.8% and 7.6% (SEI model) of the study area face very high and high risks of flooding, respectively. Comparative analysis indicated the superiority of the SEI model. The key limitations of the models are discussed. This study attempted to simplify the process for the easy and straightforward implementation of FR and SEI statistical flood susceptibility models along with key insights into the flood vulnerability of the study region.

This study aimed to evaluate the suitability of literature parameter values for the Green–Ampt infiltration model to be used in hydrodynamic rainfall–runoff simulations. The outcome of this study supports to decide which literature values should be taken if observed data for model calibration is not available. Different laboratory experiments, a plot-scale experiment in the Thiès catchment in Senegal, and a flash flood in the region of El Gouna in Egypt, have been simulated with the 2D shallow water model Hydroinformatics Modeling System (hms) incorporating the Green–Ampt model. For four test cases with available runoff data, the results of the calibrated models were compared to those obtained from average values after Rawls et al. (Journal of Hydraulic Engineering 1:62–70, 1) and Innovyze (Help documentation of XPSWMM and XPStorm, 2). The results showed a clear underestimation of infiltration in two of three considered laboratory experiments, while for a field experiment in Senegal, average values after Rawls et al. (Journal of Hydraulic Engineering 1:62–70, 1) led to a strong overestimation and the ones after Innovyze (Help documentation of XPSWMM and XPStorm, 2) to an underestimation of infiltration. In a case study on flash floods in an ungauged region in Egypt, the values of both sources led to a strong overestimation of infiltration, when the simulation results are compared to observed flooding areas. It can be concluded, that the values after Innovyze (Help documentation of XPSWMM and XPStorm, 2) lead to overall better results than the ones after Rawls et al. (Journal of Hydraulic Engineering 1:62–70, 1). According to the results, the hydraulic conductivity in ungauged areas with bare sandy soil should be reduced by about 90–100 % compared to the value after Rawls et al. (Journal of Hydraulic Engineering 1:62–70, 1).

This paper aims to quantify potential changes in extreme precipitation under climate change scenarios in the city of Berlin, Germany, and their resulting impacts on urban flooding in a selected flood-prone area of the city. Furthermore, it investigates the effectiveness of the existing drainage system, infiltration from unsealed surfaces, and retention roofs during extreme rainfall events under both current and future climate conditions. Finally, uncertainties in infiltration are addressed by varying soil hydraulic conductivity and the degree of surface sealing. The effect of climate change on the statistical distribution of extreme precipitation in Berlin is assessed by analyzing a single-model set of climate scenario simulations at convection permitting resolution (COSMO-CLM). Three 30-year periods are simulated: The historical period under observed greenhouse gas concentrations from 1971 to 2000 and two RCP8.5 scenario periods from 2031 to 2060 and from 2071 to 2100. For the historical period, the estimated 1 h rainfall sum for a 100-year return level (referred to as “Historical 100a”) agrees well with the statistical values from station observations. For the period 2031–2060 under RCP8.5 conditions the respective rainfall sum of the 1 h 100-year event (referred to as “Future 100a”) increases by 46 % and the strongest hourly intensity in all three simulated 30-year periods (referred to as “Strongest”) is increased by 123 % compared to the Historical 100a event. The impacts of these increases in extreme precipitation on flooding characteristics in a Central-Berlin region around the Gleimtunnel, which is known for frequent pluvial flooding, are studied by conducting simulations with the 2D surface flow model hms${}^{++}$ coupled to a 1D drainage model. The Future 100a event results in a 51 % increase in the simulated maximum water depth, a 43 % increase in maximum surface runoff at the local flooding hotspot Gleimtunnel, and a 33 % increase in the volume of combined sewer overflow at one selected outfall. For the Strongest event, the respective increases are 137 % (maximum water depth), 296 % (maximum surface runoff), and 74 % (combined sewer overflow). The effects of the existing drainage system and infiltration under different rainfall scenarios are highlighted by comparing simulation results with and without their consideration. Neglecting the drainage system results in a 170 % increase in the maximum water depth at the Gleimtunnel for the Historical 100a event and a 110 % increase for the Strongest event, compared to the reference simulations. While the drainage system strongly reduces flooding, especially at hotspots, it cannot fully prevent severe flooding, and its effectiveness decreases with higher rainfall intensity. Studying infiltration reflects potential impacts of surface sealing or, conversely, desealing as a climate adaptation strategy. Neglecting infiltration increases the maximum water depth at the Gleimtunnel by 33 % for the Historical 100a event and 18 % for the Strongest event compared to the reference simulations. The volume of combined sewer overflow increased by 19 %–30 % if infiltration was neglected. Infiltration significantly reduces flooding, though its effectiveness decreases with higher rainfall intensity. As a potential adaptation strategy, the impact of replacing all roofs with retention roofs is examined. For this best-case adaptation scenario, the maximum water depth at the local hotspot is reduced by 22 %–24 %, and the volume of combined sewer overflow by 15 %–20 % in the different scenarios. Since full retention on all roof surfaces is considered for all rainfall scenarios, the effects are almost the same. Remarkably, the retention roofs significantly reduced the maximum surface runoff in the Gleimtunnel during the Strongest event to below the stability threshold for pedestrians, which was clearly exceeded in the simulation without retention roofs. The results of this study highlight the potential local impacts of ongoing global warming in terms of heavy rainfall and urban flooding in the city of Berlin and emphasize the need to combine grey infrastructure, retention roofs, surface desealing, and other blue-green measures.

Within this work, the impact of mitigation measures and infiltration on flash floods is investigated by using a 2D robust shallow water model including infiltration with the Green-Ampt model. The results show the combined effects of infiltration and mitigation measures as well as the effectiveness of bypass channels in addition to retention basins. Retention basins at appropriate locations could reduce the maximum water depth at critical locations by 23%, while the additional implementation of drainage channels lead to a reduction of 75%, considering also infiltration lead to a further reduction of 97%. If infiltration was considered without mitigation measures, the peak water depth was reduced by 67%. For an exceptional extreme event the measures lead to a reduction of 73% at some locations, while at other locations the overflow from retention basins due to overstraining generated even higher inundations with an increase of 58%.