Search Results (637)

Indian metropolitan cities such as Mumbai grapple with rapid urbanisation, extreme urban density, high built-up areas, loss of green cover, and shrinking open spaces, resulting in increased impermeable surfaces, urban heat island effects, and frequent flooding occurrences. Modern stormwater management has increasingly been characterised by integrated grey-green approaches; however, cities in the Global North benefit from established policies, technical expertise, and financial resources that enable the systematic and large-scale integration of Blue-Green Infrastructure (BGI) through district-wide geospatial assessment frameworks, unlike many cities in the Global South. Despite growing interest in nature-based stormwater solutions, there remains a dearth of geospatial empirical research from India examining the placement, distribution, performance, and functionality of BGI integrated with existing stormwater management systems in cities such as Mumbai. Furthermore, hydrological modelling using tools such as the Storm Water Management Model (SWMM) for the design, planning, and implementation of BGI in Indian cities remains largely unexplored. This study explores the role of BGI strategies in improving urban stormwater management within high-density Indian cities under a 25-year return period extreme rainfall scenario. Using an integrated approach that combines QGIS-based spatial analysis with EPA-SWMM hydrologic-hydraulic modelling, the research examines runoff behaviour, identifies flooding hotspots, and evaluates the effectiveness of Low Impact Development (LID)-based BGI measures such as permeable pavements, infiltration trenches, and green roofs applied at the ward level in Mumbai’s F/North and G/North Wards. Detailed land use classification, spatial mapping, and rainfall simulation corresponding specifically to a 25-year return period rainfall event was used to assess pre- and post-intervention conditions. The findings indicate that the applied BGI measures led to a 12.6% reduction in peak runoff (137.6 m³/s to 120.2 m³/s) and a 5.5% decrease in total runoff volume (783,510 m³ to 740,410 m³). More importantly, the peak flooding flow rate decreased by 45% (94.1 m³/s to 51.7 m³/s), demonstrating that BGI measures can efficiently reduce peak flooding flows by extending runoff hydrographs during extreme rainfall events. These findings are specifically applicable to the simulated 25-year return period extreme rainfall scenario and may vary under different rainfall intensities or return periods. Less extreme events could potentially experience even greater relative reductions or prevent flooding altogether, while also easing downstream hydraulic loads. Overall, strategically placed BGI interventions can significantly reduce surface runoff and peak flow, thereby enhancing stormwater resilience within spatially constrained urban environments. This study provides a replicable, data-driven framework for catchment-scale stormwater planning in dense Indian cities under extreme rainfall conditions, offering practical insights into methods, local contextual considerations, and spatial planning strategies for policymakers and urban planners seeking to retrofit and adapt existing infrastructure under increasing hydrologic stress and climate variability. Full article

Environmental risk management in urban areas has become increasingly important in recent decades, mainly due to climate change and the anticipated rise in the frequency and severity of extreme rainfall events. In highly urbanized environments, these conditions can intensify hydraulic stress on drainage systems, leading to flooding and surcharge within combined sewer networks. Continuous simulations (2008–2018) were performed using coupled hydrological–hydraulic modeling. Discharge outputs and rainfall series were aggregated at hourly resolution and segmented into independent events. Results show marked seasonality: ~86 events/year and ~118 events/year were identified, with higher occurrence in autumn and winter and fewer events in summer. Event duration tends to be longer from late autumn to spring, whereas summer events are generally shorter. Conversely, peak rainfall and peak discharge exhibit higher median values and variability during summer and early autumn, consistent with intense convective Mediterranean storms. Full article

To address frequent street-level flooding, inadequate targeted management, and unbalanced cost-effectiveness in the old urban area, this study takes Yong’an Subdistrict in Quanshan District, Xuzhou, as a typical case, regards the street-level as its fundamental analytical unit and constructs a systematic “simulation–assessment–strategy” framework, focusing on evaluating and enhancing flood resilience in old urban districts. First, numerical simulation quantifies water depth under extreme rainfall to identify the flood risk spatial distribution. Second, a flood resilience assessment system is established based on the “exposure–vulnerability–adaptive capacity” framework, using the TOPSIS method to measure and grade street resilience. Finally, differentiated flood management strategies are proposed by integrating assessment results with regional characteristics. This study shows that high-risk flooding zones are clustered, with resilience results significantly correlated with the flood risk distribution. Low-resilience areas highly overlap with high-risk zones, mainly due to deficiencies in engineering, ecological, and social resilience. Accordingly, differentiated strategies—”pipe network upgrades + permeable paving”, “retention facilities + smart drainage”, and “micro-topography modifications”—are applied to old residential areas, core commercial districts, and new development peripheries. This approach balances management costs and effectiveness, providing theoretical and practical support for precise street-level flood management and spatial optimization in old urban districts. Full article

Deep stormwater drainage tunnels are increasingly being used to mitigate urban flooding, but in-tunnel sediment deposition reduces their discharge capacity and complicates their maintenance. With direct field observation constrained, numerical simulation is essential, and river-based total sediment load formulas require reassessment for use in deep tunnels. The three-phase (air–water–sediment) CFD solver SedInterFoam is first validated against a benchmark open-channel suspended sediment experiment, and is then applied to a horseshoe tunnel under a fixed design discharge for multiple inlet sediment concentrations spanning urban stormwater conditions. Four classical formulas (Yang, Shen–Hung, Ackers–White, Engelund–Hansen) are evaluated at the CFD-resolved hydraulic state; Toffaleti is omitted because its zone-based formulation is incompatible with the partially filled horseshoe geometry. The CFD consistently shows persistent retention of a substantial fraction of the inlet sediment load, whereas the transport capacity-limited interpretation of the classical formulas predicts near-complete sediment throughput—indicating structural inadequacy for the dilute, supply-limited regime typical of urban stormwater. A Universal Soil Loss Equation (USLE)-style dimensionless deposition formula is therefore proposed, with inlet sediment loading as the explicit independent variable and a tunnel correction factor $K_{tunnel}$ absorbing the geometric, hydraulic, and sediment variations. Its regression yields an almost linear scaling and a nearly constant deposition ratio, while analysis of the internal flow and concentration fields shows that the retained sediment is strongly concentrated near the bed and that near-bed turbulent mixing weakens moderately with a rising inlet concentration. While calibrated for a single non-cohesive settleable sand fraction, the framework provides a transferable basis for inlet-loading-dependent deposition prediction in deep stormwater drainage tunnels, and subsequent extension of $K_{tunnel}$ to broader sediment conditions with field-based validation is expected to enable maintenance planning, dredging volume estimation, and sediment retention risk assessment. Full article

Quantifying the impact of land use changes on the threat of flash-floods is a critical consideration in flood hazard planning and risk reduction, and is an area of active research. Here, a coupled Weather Research and Forecasting model hydrological extension package (i.e., WRF-Hydro) modeling approach is applied to simulate flash-flooding processes for short-duration, localized, intense precipitation events. To better understand the effect of urbanization on flash floods, a series of numerical experiments is performed surrounding Ellicott City, Maryland, a location which has experienced both significant heavy rainfall events and suburban development over the past several decades. Two intense rainfall events occurring on 30 July 2016 and 27 May 2018 are investigated, respectively, to first calibrate the hydrologic model performance and then quantify the sensitivity of flash flooding to varying degrees of urbanization. Performing the same experiments using observed historical land use states is of more limited insight, as the thrust of suburban development in the Ellicott City region significantly predates satellite-derived land use datasets. Results confirm that urbanization produces larger river streamflow, higher water stages, faster hydrologic responses to achieve peak flow discharge, and shorter recession limbs, even for very intense, short-duration events. The collective findings suggest that WRF-Hydro is applicable for both watershed flash flood prediction and hypothesis testing, and demonstrates potential utility to urban development decision-makers in locations such as Ellicott City, which could face future increases in catastrophic flooding. Full article

Efficient operation of rainwater pumping stations is essential for mitigating urban flooding under climate change. This study focuses on the Samcheok Osipcheon watershed, located in Gangwon-do, South Korea, and proposes a deep learning-based inflow prediction framework for the Samcheok-si drainage system using SWMM-simulated datasets. A total of 900 rainfall scenarios were generated and used to train three models: ANN, CNN, and LSTM. All models reproduced inflow hydrographs with high accuracy, but the CNN model showed overfitting with oscillations in the recession limb. The LSTM model demonstrated the best performance, achieving an NSE of 0.97 and a PPE of 3.45%. Based on the predicted inflow, two pump operation strategies were evaluated. The proactive operation considering upstream surcharge conditions, combined with second-level control, reduced peak water levels from 2.585 m to 2.439 m (approximately 5.6%) compared to the conventional operation. In addition, second-level pump operation reduced excessive discharge and stabilized detention basin water levels. The results indicate that the proposed framework can support real-time pump operation, enhance the resilience and sustainability of urban drainage systems, and contribute to sustainable urban flood mitigation. Full article

Urban pluvial flood risk in industrial zones is intensifying under climate change, yet the joint influence of digital elevation model (DEM) resolution, surface roughness heterogeneity, and infiltration capacity on simulation accuracy remains insufficiently characterized. This study presents a comprehensive sensitivity analysis combining five DEM resolutions (0.5, 1, 2, 5, and 10 m), six rainfall scenarios (10- to 200-year return periods plus the observed event of 10 July 2024), and three infiltration rates (5, 10, and 20 mm h⁻¹), yielding 90 simulation cases executed with the open-source GPU solver SynxFlow on an NVIDIA A100 80GB GPU. A spatially distributed Manning’s roughness field (n_M = 0.013–0.100 s m^−1/3) was derived from the Ministry of Environment land cover product, replacing the conventional uniform-roughness assumption. Model performance was assessed against seven validation gauges (five flooded, two no-flood controls) compiled from contemporaneous news reports, using the 25 m × 25 m patch-maximum simulated depth at each gauge and probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI). The 0.5 m baseline achieved POD = 0.80, FAR = 0.20, and CSI = 0.67 at the 5 cm depth threshold. Coarsening the grid reduced peak depth by up to 37% and flooded area by 5%, with the most rapid degradation occurring between 2 m and 5 m. A 2 m grid retained area error within 2% and volume error within 1% while delivering an approximately 33-fold runtime reduction relative to the 0.5 m baseline; the 10 m grid achieved up to ~1400× speedup, spanning three orders of magnitude across the resolution range. Resolution sensitivity intensified under higher rainfall and lower infiltration, confirming that “adequate” resolution is conditional on event severity. A tiered resolution selection matrix linking application scale, target accuracy, and computational cost is proposed to support evidence-based flood adaptation planning for industrial zones. Full article

This study introduces a modelling framework for representing surface runoff along urban streets during intense rainfall events. The approach incorporates a dynamic assessment of sewer system capacity, obtained through dedicated simulations that capture its temporal variability during flooding. A one-dimensional sewer model is first used to quantify the volume of rainfall effectively conveyed by the drainage network; these results are then used to construct a reduced hyetograph, which serves as input for a one-dimensional street-flow model. The methodology was applied to a flood-prone urban catchment in southern Italy and calibrated and validated using field observations, including direct measurements and video-derived flow estimates. Full article

Urban areas are increasingly vulnerable to climate-related stresses such as heatwaves, flooding, and resource inefficiencies, requiring integrated, data-driven strategies to enhance resilience and sustainability. This study presents a modular assessment and planning framework that combines Geographic Information Systems (GIS), Building Information Modeling (BIM), City Information Modeling (CIM), microclimate simulations (ENVI-met, SWMM), Life Cycle Assessment (LCA), and remote sensing within a unified decision support interface (DSI). The framework operates across multiple spatial scales—from individual buildings to entire cities—to assess climate vulnerability, support evidence-based urban regeneration, and inform sustainable renovation strategies. It enables the identification of multifunctional interventions that reduce climate risks while improving energy efficiency, resource management, and environmental quality. Urban areas are classified based on their exposure and sensitivity to climate stressors, providing a systematic basis for prioritizing adaptation and mitigation measures. The approach is validated through a case study in Daegu, Republic of Korea, a city facing an aging building stock and increasing climatic pressures. The framework is presented as a conceptual design operating at Technology Readiness Level (TRL) 3–4, indicating that it has passed its proof-of-concept, with key components including ENVI-met microclimate simulations and Sentinel-2/Landsat remote sensing processing demonstrably operational for the Daegu context. Illustrative performance benchmarks drawn from the peer-reviewed literature demonstrate that framework-guided interventions can achieve urban heat island reductions of 1.5–4.0 °C via green roof and reflective surface combinations; stormwater runoff reductions of 30–60% through sustainable urban drainage systems; and building energy savings of 25–45 kWh/m²/yr from deep façade renovation. Its modular and transferable design ensures applicability across diverse urban contexts with similar climatic and infrastructural challenges. Full article

This study presents a practical application of a subgrid approach for urban pluvial flooding that implicitly accounts for the secondary drainage network. Parameters required by the subgrid model (e.g., pipe diameter, spacing) can be easily estimated, reducing the data requirements and modelling efforts compared to classical 1D/2D simulations. Applied to simulate the 2009 flooding of a Padova district, the model improves accuracy in flood extent and water levels compared to models that ignore the secondary network, without the need for surveys of smaller-scale pipes. This data-efficient approach proves to be a practical tool for simulating urban pluvial floods, particularly in data-scarce urban areas. Full article

One of the consequences of urbanization is the impermeabilization of the landscape, which increases the stormwater runoff and the risk of pluvial flooding. To address this challenge, this study proposes a methodology to quantify the impact of reducing impermeable areas in the design of pluvial drainage systems. This methodology is applied in the Lake Ganzirri Area, located in Messina, Italy, where accelerated expansion of residential projects and the closure of drainage outlets due to environmental restrictions have enhanced the risk of pluvial flooding. The relationship between impermeable areas and the impact on risk of failure is assessed using rainfall events derived from regional depth-duration-frequency curves, a pluvial drainage network, and InfoWorks ICM simulations for different impermeable scenarios. Full article

Coastal cities are prone to flooding due to extreme rainfall, rising sea levels, and urbanization. This study develops a non-stationary flood risk prediction framework for a coastal city to assess the combined effects of rainfall, tide, and land surface change on future flood inundation and socioeconomic risk. Future rainfall was predicted by integrating the time-varying parameter distribution (TVPD) model with CMIP6 data through a genetic algorithm; future tides were estimated using the TVPD model; and land use in 2035 was simulated using the Markov–PLUS model. Flood inundation and the associated socioeconomic risks were then evaluated. The results showed that the integrated rainfall prediction approach reduced RMSE by 13.4% compared with the individual models. The land use simulation also showed acceptable performance, with a Kappa coefficient of 0.79 and an FOM value of 0.15. Under the combined effects of rainfall, tide, and land use change, the future peak inundation volume increased by 19.97% on average relative to the baseline period, while the affected population and economic losses increased by 72,603 people and US$12.61 billion, respectively. These results indicate that flood risk in coastal cities may be substantially exacerbated under a non-stationary environment, and the proposed framework can provide support for future flood risk assessment and adaptation planning. Full article

Urban flood modelling in heavily engineered catchments requires model structures that capture not only surface runoff processes but also hydraulic infrastructure and operational controls. This study applies a TELEMAC-2D rain-on-grid framework to two urban sub-catchments of the Emscher River (North Rhine-Westphalia, Germany) to quantify the relative effects of surface calibration, explicit infrastructure representation, and operational rules on the simulated flood response. A stepwise model development workflow was implemented, including land use-based calibration of Manning’s n and SCS Curve Numbers, explicit integration of culverts and bridges, and rule-based representation of retention basins and pumping stations. Model performance was evaluated using hydrograph shape, peak discharge, peak timing, event volume, and inundation behaviour across different antecedent moisture conditions (AMC). The results show that surface calibration alone was insufficient to consistently reproduce observed hydrographs. In the Rossbach sub-catchment area, integrating retention basins, pumping stations, and operational rules improved model performance from NSE = −0.129 under AMC I to NSE = 0.773 under AMC III. RMSE decreased from 3.380 to 1.515 m³ s⁻¹, peak discharge error from −6.198 to −0.492 m³ s⁻¹, and volume bias from −0.664 to +0.038. A targeted, routing-focused calibration further improved timing behaviour but increased volume bias, indicating residual deficiencies in the representation of rapid urban conveyance pathways. The findings show that reliable urban flood simulation in infrastructure-rich catchments depends not only on calibrating surface parameters but also on explicitly representing hydraulic structures, operational controls, and antecedent wetness conditions. Full article

Driven by sea-level rise and frequent compound coastal flooding, accurate inundation simulation is essential for disaster mitigation and urban planning. To address the topologically disconnected overestimation errors inherent in the traditional bathtub model, this study proposes a dynamic coastal inundation simulation framework based on an 8-neighbor seed-spread algorithm. Within this framework, a digital elevation model (DEM) is resampled to a 10 m spatial resolution, and a high frequency tidal sequence with a 5-min temporal resolution is reconstructed from typical spring tides. The vertical datums of both the topography and tidal water levels are strictly unified to the Mean Sea Level (MSL) to maintain physical consistency. Comparative experiments across multiple water level scenarios reveal a distinct threshold effect and non-linear expansion characteristics in inundation responses under complex geomorphological conditions. Because the traditional bathtub model fails to account for the blocking effects of inland physical barriers, its overestimation increases significantly once the water level exceeds critical flood protection thresholds. By generating high resolution Time of Arrival (ToA) maps, the proposed framework provides a robust spatial–temporal basis for precise coastal risk assessment, evacuation planning, and defense resource allocation. Full article

Digital Elevation Model (DEM) resolution plays a critical role in hydraulic flood modelling by influencing inundation accuracy, spatial precision and computational efficiency. However, limited studies have simultaneously evaluated both inundation accuracy and computational performance across multiple DEM resolutions in event-based urban flood modelling. This study aims to evaluate the impact of DEM spatial resolution on the performance of HEC-RAS 1D and 2D models in simulating an event-based urban flood that occurred on 3 March 2025. A 1 m LiDAR-derived DEM was resampled to 2 m, 5 m, 8 m, 10 m, 20 m, 25 m, and 30 m resolutions to assess the effects of terrain generalization on hydraulic response. Simulated inundation extents were validated against observed flood areas derived from aerial imagery, and computation time was recorded for each scenario. Results reveal a clear trade-off between spatial accuracy and computational demand. In the 1D simulations, deviation from observed inundation increased from 0.76 ha at 1 m to 2.50 ha at 30 m, while computation time remained relatively stable. The 2D simulations were more sensitive to DEM resolution, with deviation increasing from 0.33 ha to 3.12 ha and longer runtimes at finer resolutions. Among the evaluated scenarios, the 10 m DEM provided the most balanced performance in both 1D and 2D models. For rapid assessment and operational flood management, where computational efficiency and timely decision-making are critical, a 1D modelling approach combined with a 10 × 10 m DEM is recommended as a practical and efficient solution. Full article