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To avoid the nuisance of frequent flooding during rainy season, designing an efficient stormwater drainage system has become the need of the hour for present world engineers and urban planners. The present case study deals with providing a solution to stormwater management problem in an urbanized area. Mann–Kendall and Sen’s slope tests are used to perform the trend analysis of rainfall events using daily rainfall data (1956–2012), while the L-moments-based frequency analysis method is employed to estimate the design storm for a small urbanized area in West Bengal, India, using daily annual maximum rainfall (1975–2013). SWMM (Storm Water Management Model) and MIKE URBAN models are used to design an efficient drainage system for the study area. Two-dimensional (2D) MIKE URBAN model is primarily used to overcome the limitation of one-dimensional (1D) SWMM in simulating flood extent and flood inundation. Model simulation results from MIKE URBAN are shown for an extreme rainfall event of July 29, 2013. A multi-purpose detention pond is also designed for groundwater recharge and attenuating the peak of outflow hydrograph at the downstream end during high-intensity rainfall. This study provides an insight into the importance of 2D model to deal with location-specific flooding problems.

Managing stormwater under climate uncertainty is a concern in both built-out communities and those continuing to undergo land use change. In this study, a suite of climate change scenarios were developed to represent a probable range of change in the 10-year recurrence interval design storm. The Environmental Protection Agency’s Stormwater Management Model was used to predict flooding due to undersized drainage components within watersheds representing a traditional, built-out urban area and a developing suburban area with intact green infrastructure corridors. Despite undersized infrastructure and flooding in both study watersheds, the risk of property damage in the suburban watershed was negligible across the range of scenarios even at projected build-out, due in part to flood storage capacity of the green infrastructure network. Adaptation approaches – including pipe upsizing, underground storage, and bioinfiltration – and costs were also modeled in both watersheds. In the built-out site, bioinfiltration practices were predicted to moderate both flooding and total adaptation costs even when implemented over a relatively modest (10 %) portion of the watershed; however, a substantial upgrade to gray stormwater infrastructure (pipes and storage chambers) was also needed to mitigate impacts. In the urbanizing community, maintaining an intact green infrastructure network was surmised to be the most cost-effective approach for enhancing the resilience of urban stormwater systems to climate uncertainties and urbanization.

Flood frequency analysis and hydrological modelling are crucial for water resource management and flood mitigation, especially in regions vulnerable to extreme weather. This study utilises the HEC-HMS hydrological model to simulate rainfall-runoff processes and generate design storms for various return periods across 24 sub-watersheds of the Jhelum Basin, Kashmir. The model setup includes rainfall transformation using the ModClark method, baseflow estimation through the Linear Reservoir Method, and flood routing via the Muskingum approach. Satellite-based gridded rainfall data and sub-basin-specific hyetographs were used as meteorological inputs to ensure spatially distributed precipitation representation. Calibration and validation were performed using discharge data from Sangam, Ram Munshibagh, and Asham gauging stations (2020–2023), covering five high-flow events. This research marks the first application of event-based design storms at the sub-watershed scale in the Kashmir Valley using HEC-HMS, providing high-resolution insights into flood risk patterns. The model showed strong agreement with observed hydrographs (R² > 0.78, NSE > 0.56, RSR < 0.6, PBIAS within ± 25%). Sensitivity analysis identified curve number, time of concentration, and infiltration rates as key parameters influencing performance. Results indicated varied hydrological responses, with watersheds like Lower Jhelum, Sindh, Lidder, and Pohru showing higher peak discharges due to steep slopes, while low-lying areas such as Wular-II and Anchar exhibited prolonged flood retention. Urbanised watersheds like Dal and Wular-I showed moderate to high peaks, highlighting infrastructure vulnerability. Design storms for 2–500-year return periods identified critical flood-prone zones, offering insights for infrastructure planning and risk management. This research highlights the effectiveness of HEC-HMS model as an important non-structural flood mitigation measure in a mountainous region of Kashmir.

There is an urgent need to assess the uncertainties in stormwater pipe design owing to the increasing occurrence of urban floods triggered by urbanisation and climate change. The design storm concept involves determining the event duration and corresponding depth. Various design hyetograph methods are available to partition the design storm depth into segments, which raises questions about their impact on stormwater system design. This study analysed an ensemble of eight widely used hyetograph methods, including triangular, linear/exponential, Chicago and alternating block, in industrial and residential urban catchments using the stormwater management model. The modelling results revealed clear disparities between hyetograph methods in terms of catchment hydrological response. Depending on the method used, the simulated outlet peak flow varied by ±30% in both catchments. As a result, outlet pipe sizes varied by one and two increments in the residential and industrial catchments, respectively. Almost no flooding was evident in the manholes using simple single‐point hyetographs, whereas a quarter of the manholes showed flooding with more complex multipoint methods. Results underline the presence of high uncertainty in design flow estimates. Multipoint hyetograph methods should be used for designing critical infrastructure to minimise flooding risk if no local or regional data are available.

Design storms are key components for planning drainage networks and flood risk management. Due to atmospheric processes, precipitation accumulations across multiple temporal intervals are often correlated and can combine to shape flood intensities. However, current design storm guidance overlook the observed correlations between return periods of different duration intervals within storms and may thereby lead to under‐ or over‐estimation of the flood risk. We present a new approach for generating plausible design storms that accounts for joint return periods. Focusing on short‐duration extreme precipitation events, potentially leading to urban pluvial flooding, we analyze the dependencies between critical precipitation intensities over the 10‐min, 30‐min, 1‐hr, 3‐hr, and 6‐hr intervals, for data from Zurich (Switzerland). We then propose a method based on a canonical vine copula model for sampling precipitation intensities that reflect the observations' dependencies. Using this model, we then generate realistic design storms with a constrained micro‐canonical cascade model. Our results shows that the common block methods (e.g., the Chicago and Euler design storms) tend to overestimate total precipitation volumes on average, by up to 56%. Furthermore, we highlight the variability in possible duration‐frequency profiles, leading to both higher and lower total precipitation volumes compared to standard approaches. This underscores the need to switch from traditional block methods to a more realistic sampling of design storms, incorporating multiple design storm scenarios for robust risk assessment. The model is applicable to any time series of precipitation, regardless of its location or climate. The code is freely available.

Intensity-duration-frequency (IDF) curves, commonly used in stormwater infrastructure design to represent characteristics of extreme rainfall, are gradually being updated to reflect expected changes in rainfall under climate change. The modeling choices used for updating lead to large uncertainties; however, it is unclear how much these uncertainties affect the design and cost of stormwater systems. This study investigates how the choice of spatial resolution of the regional climate model (RCM) ensemble and the spatial adjustment technique affect climate-corrected IDF curves and resulting stormwater infrastructure designs in 34 US cities for the period 2020 to 2099. In most cities, IDF values are significantly different between three spatial adjustment techniques and two RCM spatial resolutions. These differences have the potential to alter the size of stormwater systems designed using these choices and affect the results of climate impact modeling more broadly. The largest change in the engineering decision results when the design storm is selected from the upper bounds of the uncertainty distribution of the IDF curve, which changes the stormwater pipe design size by five increments in some cases, nearly doubling the cost. State and local agencies can help reduce some of this variability by setting guidelines, such as avoiding the use of the upper bound of the future uncertainty range as a design storm and instead accounting for uncertainty by tracking infrastructure performance over time and preparing for adaptation using a resilience plan.

It is undeniable that coastal regions worldwide are facing unprecedented damages from catastrophic floods attributable to storm-tide (tidal) and extreme rainfall (pluvial). For flood-risk assessment, although recognizing compound impact of these drivers is a conventional practice, the marginal/individual impacts cannot be overlooked. In this letter, we propose a new measure, Tide-Rainfall Flood Quotient (TRFQ), to quantify the driver-specific flood potential of a coastal region arising from storm-tide or rainfall. A set of inundation and hazard maps are derived through a series of numerical and hydrodynamic flood model simulations comprising of design rainfall and design storm-tide. These experiments are demonstrated on three different geographically diverse flood-affected coastal regions in India. The new measure throws light on existing knowledge gaps on the propensity of coastal flooding induced by the marginal/individual contribution of storm-tide and rainfall. It shall prove useful in rationalizing long-term flood management strategies customizable for storm-tide and pluvial dominated global coastal regions.

Climate change, driven by human activities and increasing greenhouse gas emissions, is pushing Earth’s climate toward a warmer state, as evidenced by long-term observations. The frequency and intensity of unprecedented rainfall events have increased in recent years, underscoring the urgent need to revise design storms and depth-duration frequency (DDF) curves to better adapt to and mitigate the impacts of climate change. This study used a serial type of stochastic rainfall generator (SRG) that is capable of simulating daily rainfall series by embedding unprecedented events to study extreme precipitation scenarios under the changing climate. By perturbing values of power law tuning parameters in the SRG model, we developed thirty-six precipitation scenarios, some of which directly correlate with the current climate change scenario, while others represent very extreme conditions. High-performance computing is employed to run the computationally intensive SRG for simulating thirty-six scenarios across the entire Indian region. These simulated scenarios were analyzed to prepare rainfall return level maps and DDF curves. The findings reveal substantial increases in rainfall return levels across all frequencies when unprecedented events are considered, with pronounced impacts in coastal, northeastern, and Himalayan regions. The spatial pattern of simulated extreme precipitation was consistent across all generated scenarios from SRG irrespective of the return periods. Minimal spatial uncertainty in return level estimates across climate zones is observed which confirms the robustness of the SRG model and spatial clusters of extreme rainfall are identified irrespective of SRG being a point model. The analysis in this study based on SRG simulated climate change scenarios offers crucial insights for revising design storms and for devising climate resilience and flood management strategies.

Estimation of urban runoff peak and volume is a fundamental step in determining the transferring capacity of urban drainage systems. The main aim of this study was to present an application of the Storm Water Management Model (SWMM) in order to estimate urban flooding of a semi-arid area (Zanjan city in the northwest of Iran). The performance of an urban drainage system in the study area was also investigated. According to the results, SWMM is an effective tool for urban flood estimation in a semi-arid area. In this study, urban peak flow was simulated via a calibrated model with acceptable accuracy. Based on the results of the model simulation, the capacity of the main canals in the study area is sufficient for peak runoff transferring for a design storm with 50 year return periods, without retrofitting. Whereas, based on local observation and model results, localized and surface flooding can be observed in some urban areas.

The design flood for a coastal basin based on model simulations can be impacted by various conditions other than design storm, such as tide level. However, the design storm and tide level are usually investigated separately, and the relation between them has not been sufficiently studied, which may have unexpected impacts on model simulations. This paper presents a bivariate assessment framework that aims to evaluate the coordination between design storm and tide level using a copula-based joint distribution to derive the conditional probability of coincidences between design storm and tide level intervals. We apply this framework to the Tai Lake Basin (TLB) in the eastern coast of China and investigate what tide level along its coastline is appropriate for guiding flood control planning. Our findings reveal that the currently-used tide level along the southern coast of TLB is too low and should be raised by approximately 0.35 m and 0.12 m under maximum 1-day and 3-day storms, respectively. Meanwhile, the tide levels for the north and east coasts are appropriate. This paper provides a comprehensive understanding of the interplay between design storm and tide level in a large coastal basin, offering insights into the design of flood protection systems.