Flooding In Urban Areas Research Articles

STORMWATER MANAGEMENT DIRECTIVES AND STRATEGIES IN TEH EUROPEAN UNION

The paper provides an overview of legal regulations, that is, directives and strategies related to new approaches to stormwater management. The goals, recommendations and guidelines for the implementation/application of new approaches are also listed in order to reduce and mitigate the negative consequences of increasingly frequent urban floods. The development of green infrastructure and solutions related to it are emphasized with the aim of reducing rainfall floods in urban areas and mitigating their consequences. Previous examples from practice in the European Union have shown that for the implementation of green infrastructure in urban areas, it is necessary to have appropriate legal regulations as a basis. In the Canton of Sarajevo and the state of Bosnia and Herzegovina, in order to establish new approaches to stormwater management, it is necessary to monitor and harmonize laws and regulations with the Directives and Strategies of the European Union with the ultimate goal of protecting the environment and improving the quality of life and living conditions. This presupposes a contribution to sustainable social economic and environmental improvement.

Enhancing transparency in data-driven urban pluvial flood prediction using an explainable CNN model

Mitigating severe losses caused by pluvial floods in urban areas with dense population and property requires effective flood prediction for emergency measures. Physics-based models face issues with low computational efficiency for real‐time flood prediction. An alternative approach for rapid prediction instead of physics-based models is to predict from a data-driven perspective. However, data-driven approaches for urban flood prediction are often perceived as “black box” and might raise concerns. In this study, we propose an explainable deep learning (DL) approach for rapid urban pluvial flood prediction with enhanced transparency using a convolutional neural network (CNN) and the explainable artificial intelligence (AI) framework Shapley additive explanation (SHAP). We process a systematic stepwise feature selection process and establish a CNN model considering topography, drainage networks and rainfall to predict maximum inundation depths. Then, SHAP is applied to provide trustworthy explanations for the decision making in model results. The results show that: 1) Forward selection can offer insights into selecting effective input variables for improved predictions and promote understanding of DL modelling. The spatial pattern of inundation depths predicted by the proposed CNN model shows good agreement with those predicted by the physics-based model, demonstrated by average correlation coefficient (CC) and mean absolute error (MAE) values of 0.982 and 0.021 m, respectively. 2) The CNN model substantially outperforms the physics-based model in computational speed when using the same hardware, achieving speedups of 210 times on GPU and 51 times on CPU in the case study (575167 grid cells, 14.38 km2). Particularly, it can still achieve good performance on a CPU-only standard laptop without high-performance hardware, with only a modest increase in computational time. 3) The SHAP explainable analysis confirms that the CNN model correctly captures the relationships between input variables and water depth, revealing a reasonable decision-making process, enhancing its transparency. The explainable DL approach incorporating SHAP for rapid urban pluvial flood prediction is promising to build trust among stakeholders and provide a trustworthy reference for prompt measures aiming at saving lives and protecting assets during flood emergencies. Additionally, the proposed DL approach can potentially be further expanded to analyze the causes of urban flooding events and serve as a foundation for exploring the transferability of data-driven urban flood prediction, providing benefits for better urban flood risk management.

Hydrological and hydrodynamic modelling for flood management: A case study of the Yamuna River Basin in Delhi

Study regionYamuna River (Delhi), India. Study focusThe anthropogenic activities within the vicinity of the floodplain reduce the river's margin and subsequently alter the magnitude of the river's flow. The encroachment of riverbeds leads to waterlogging and flooding in urban areas, thereby causing damage to property, human life, etc. It necessitates a comprehensive study of the floodplain and changes in its proximity such as encroachment of floodplains to carry out any further activities with certainty. This study employs a two-dimensional model to simulate the Yamuna River's (YR) hydrodynamic characteristics, focusing on India's Delhi region. New hydrological insightsSimulated flood flows are employed to evaluate floods of once in 10, 20, 25, and 30-year return periods using the flood frequency analysis for 1951–2013. The model validation results indicated that the model could mimic the flood depth in YR. Simulation results revealed that the floodplain's encroachment had increased the severity of the floods. The increase in the extremeness of flooding events, i.e., from once in a 10-year return period to a 30-year return period event, is expected to increase the areas at risk of floods by 12 %. The model also offers a potential platform for evaluating other alternatives, such as further encroachment, for a business-as-usual scenario or for restoring the Yamuna floodplains. With such a comprehensive perspective, floodplains' role enhances river basin resilience to climate and anthropogenic changes and increases flood safety.

Urban Drainage Network Structure Optimization Using Emperor Penguin Optimization Algorithm

Urban drainage systems are an essential component of urban infrastructure that plays a critical role in managing stormwater and preventing flooding in urban areas. With the changing climate and urbanization, the challenges faced by urban drainage systems are becoming increasingly complex. Additionally, aging infrastructure further exacerbates the problem, creating anurban sewage line that must be made more resilient. Redundancy is just a fundamental characteristic of such a robust urban drainage network. Redundancy in urban drainage systems can help to ensure that the system continues to function during extreme weather events or emergencies, reducing the likelihood of flooding and damage. However, the exact locations where redundancy should be increased and its contribution to resilience are not well understood. In recent years, several studies have focused on developing frameworks for optimising urban drainage structures which account pipeline redundancy.One similar research presented a paradigm for constructing the ideal network layout for urban drainage infrastructure, which considers pipeline redundancy under consideration. The original architecture and structure of the urban drainage network was developed using emperor penguin optimizer algorithms and graph theory in the research. Complicated system modelling was done to find extra water pathways or redundancy which might well be implemented to boost resistance. The suggested approach has been utilised to the test region in Dongying City, Shandong Province, China, and its findings revealed even under rainfall above the design specification, the entire overflow capacity of such urban drainage network including pipeline redundancy significantly decreased about 20-30%, compared to the network without pipeline redundancies. The interest in creating optimization algorithms had also increased recently that can be used to design and manage urban infrastructure systems. One such algorithm is the Emperor Penguin Optimization (EPO) algorithm. EPO was a recently developed swarm-based optimization An algorithm which simulates Emperor penguins behaviour in their search for food in Antarctica. The algorithm has shown promising results in solving complex optimization problems in different fields, including engineering, computer science, and management. The EPO algorithm's key features include an emperor search strategy, local search, and randomization, enabling that to efficiently and successfully examine the search process. The algorithm's emperor penguin search strategy enables it to dynamically adjust the search parameters based on the problem's characteristics and progress. The local search feature allows it to escape local optima and explore the search space further. Finally, the randomization feature adds stochasticity to the search process, helping to ensure that the algorithm can avoid getting stuck in a sub-optimal solution. In this article, we aim to explore the potential of EPO as a tool for optimizing Urban drainage solutions which take into account pipeline redundancy. We will start by reviewing the existing Literature upon that optimization in urban drainage facilities, particularly the application of particle swarm optimization, genetic algorithms, and ant colony enhancement. The EPO algorithm will next be described in full including its working principle, key features, and the steps involved in applying it to an optimization problem. Finally, we will present a case study that applies the EPO technique was developed to optimise the network model of such an urban drainage infrastructure taking into account pipeline redundancies, and compare the results with other optimization algorithms. Through this, we aim to demonstrate the potential of EPO as a powerful tool for designing and managing urban infrastructure systems, particularly for enhancing the resilience of urban drainage systems. The study will provide valuable insights into the optimal design of urban drainage technologies which take into account pipeline redundancy, helping policymakers and urban planners make informed decisions about improvingthe adaptability of urban drainage networks. The findings can contribute to the development of sustainable and resilient urban infrastructure systems, which are essential for ensuring the well-being and prosperity of urban residents.

Water Infiltration Policy for Urban Flood Management

This research was conducted to determine the implementation of water absorption policies for flood management in urban areas, especially in the city of Cirebon at the Cirebon City Public Works and Spatial Planning (DPUPR) department. The research approach used is normative juridical, conceptualizing law as written norms so that this research emphasizes studies in the form of legislative products, namely those that regulate water absorption such as regional regulation number 38 of 2019 concerning the implementation of groundwater conservation through infiltration wells and infiltration holes. biopore. Policy implementation in flood management by the Cirebon City PUPR Service has included handling floods and puddles as a priority in the Regional Government Work Plan (RKPD) for 2025. For handling urban drainage, the PUPR Service's work target is to reach up to 83% by 2024, and 86% for 2025, and 89% for 2026. One of the strategies taken includes the creation of retention ponds, absorption wells and eco-drainage. However, there are still several obstacles in implementing this policy, such as limited resources and lack of community participation. To overcome these obstacles, efforts need to be made such as increasing the budget, providing adequate human resources, and educating the public about the importance of water absorption. Overall, the implementation of the water absorption policy for flood management in Cirebon City has shown a positive direction. With continued efforts and collaboration from various parties, it is hoped that this policy can be more effective in minimizing the risk of flooding in urban areas.

Cumulative sedimentation hazard map of urban areas subject to hyperconcentrated flash flood: A case study of Suide County in the Wuding River basin, China

AbstractFlash floods can carry substantial sediment, posing significant sedimentation hazards in hilly cities. The sedimentation hazard map can reproduce the sediment thickness and extent of an extreme events scenario, playing an important role in sediment risk management. However, current research primarily focuses on modeling the inundation area and depth of floods, while studying sedimentation hazard caused by flash floods in urban areas remains insufficient. This paper aims to address this gap by utilizing a numerical model that simulates hyperconcentrated flow in hilly urban areas using the two‐dimensional hydro‐sediment‐morphological model to compile the cumulative sedimentation hazard map. The model, built upon the open‐source TELEMAC‐MASCARET framework, incorporates Zhang Hongwu's formula to simulate sediment‐carrying capacity, particularly suitable for hyper‐sediment concentration near the riverbed. This paper uses the data of extreme flash flood events in the Wuding River basin in 2017 to simulate and compile the cumulative sedimentation hazard map. The hazard map delineates the sedimentation hazard extent and level attributable to overbank floodplain sedimentation. Notably, the sediment thickness is highest in areas near the levees on both sides of the Dali River. Moreover, the map illustrates the extent of channel erosion resulting from hyperconcentrated floods, which could jeopardize bank stability.

A parallel porosity model for large-scale modelling of river floods in urban areas

With the purpose of modelling at a large-scale river floods affecting urban areas, this work presents a numerical model solving the two-dimensional Shallow Water Equations with porosity. The distribution of buildings within urban fabrics is accounted for by means of a spatially-distributed field of the storage porosity parameter. The finite volume scheme conserves mass and it ensures the well-balancing property over complex topography. A structured multi-resolution grid is adopted for the domain discretization and the parallelization on Graphic Processing Units (GPUs) enables the reduction of the computational costs. Model testing is performed against experimental data and applications over real domains as well. The results provided by the proposed model agree with those obtained by resolving building footprints on a high-resolution mesh, meanwhile reducing the runtimes up to 6 times.

Simulations of low impact development designs using the storm water management model

This study assessed the U.S. Environmental Protection Agency's Storm Water Management Model (SWMM) for urban water management challenges. This study conducted a sensitivity analysis to identify the most influential factors in the SWMM. Moreover, the performance of SWMM was evaluated with the HYDRUS-1D module in simulating infiltration rates. The sensitivity results showed field capacity as the most significant factor, highlighting the need for advanced modeling techniques to consider factors like field capacity. The SWMM was evaluated by the HYDRUS-1D that SWMM consistently underestimated peak infiltration rates and commenced infiltration calculations only when soil moisture exceeded field capacity. It reveals its limitations in handling unsaturated soil conditions and highlights the consideration of the matric head of the soil during the infiltration calculation in soil media. Moreover, the evaluation of bioretention areas showed larger areas resulting in more substantial flow reductions but with significant variability under different rainfall conditions. Accordingly, this result emphasizes the importance of careful consideration for environmental factors in bioretention design. This study contributes by enhancing understanding of SWMM's limitations in simulating urban water management challenges. Thus, this research will offer technical assistance to stakeholders focused on challenges such as runoff, hydrologic cycle, and urban flooding in urban areas.

Evaluating the effect of geocell with vegetation and gravel on changes in the effective parameters of runoff using a rainfall simulator (case study: Iran)

Permeable pavements can reduce the negative effects of flooding in urban areas. This research seeks to study and compare the performance of the impervious surface as a control (O), sandy loam (SL), gravel (G), gravel with geocell layer (GGE), rosemary (R), rosemary with geocell layer (RRE), turf (T), and turf with geocell layer (TGE) in reducing runoff volume (RV), time to start runoff (TR), runoff coefficient (C), time to end runoff (TER), peak flowrate (PF), time to peak (TP), and time base (TB) under six different rainfall intensities (i) and two different slopes (s) using a rainfall simulator. For this purpose, 96 physical models were considered at the laboratory level. For the dependent variables TR, TER, PF, TP, and TB, there was a significant difference between the data at the level of 5% in all cases. Based on the results, changes in rainfall intensity, slope, and type of treatment could make a significant difference in the results of the C parameter. All treatments were able to reduce runoff volume in all test conditions. Rosemary had a better performance in controlling runoff and parameters affecting it compared to turf. The maximum and minimum cumulative runoff volumes observed for treatment GGE are 85.4 and 2 L, respectively. Finally, the results revealed that GGE could perform better in reducing runoff and cumulative volume in all cases compared to the rest of the test groups. The highest percentage of runoff volume reduction in GGE treatment was 96.5%.

Urban pluvial flood modelling in the absence of sewer drainage network data: A physics-based approach

1D/2D dual drainage models have become one of the most useful tools in the study of urban pluvial floods. However, such models require information about the sewer network that is not always readily available. In this study we present a physics-based approach for assessing urban pluvial floods, with the aim of overcoming the common situation of having limited information on the sewer system. The method proposed involves the use of available open-access information within a virtual sewer network generation tool. This realistic approach allows for the implementation of 1D/2D dual drainage models, such as the recently developed Iber-SWMM model. Results obtained from four storm events using a virtual sewer network in Iber-SWMM were compared with those derived using data from the actual sewer network in a coastal town located in NW Spain. These results revealed that the proposed approach can reasonably represent the sewer network's drainage capacity during pluvial floods, especially compared to other simplified approaches, like the rainfall reduction method. The proposed approach also accounts for the sewer network transport capacity and the impact of overflows when a sewer’s capacity is exceeded. Hence the study confirms the significant effect of these processes on the magnitude of pluvial flooding in urban areas. The methodology is shown to be robust, and can be applied to any urban settlement in which no proper record of the sewer network is available.

Potential of Decentral Nature-Based Solutions for Mitigation of Pluvial Floods in Urban Areas—A Simulation Study Based on 1D/2D Coupled Modeling

Urban drainage systems are generally designed to handle rainfall events only up to a certain intensity or volume. With climate change, extreme events that exceed the design storms and consequently result in flooding are occurring more frequently. Nature-based solutions (NBSs) have the potential to reduce the pressure on urban drainage systems and to increase their resilience. This study presents an approach to compare and evaluate the effectiveness of NBSs for flood mitigation using a coupled 1D/2D model of surface and sewer flow. The study analyzes the effect of infiltration systems (dimensioned to return periods of T = 5 and 100 years), various green roofs, and tree pits considering the different degrees of implementation. The NBSs are represented as LID elements according to SWMM. As expected, the mitigation effect of NBSs declines with increasing rainfall intensities. However, infiltration systems dimensioned to T = 100 years achieve almost three times the flood reduction compared to systems dimensioned to T = 5 years, even during extremely heavy rainfall events (100 mm), resulting in a reduced total flood volume of 15.1% to 25.8%. Overall, green roofs (excluding extensive green roofs) provide the most significant flood reduction (33.5%), while tree locations have the least effect.

Nature-Based Disaster Risk Reduction of Floods in Urban Areas

Nature-Based Disaster Risk Reduction of Floods in Urban Areas

Multi-tier scheduling algorithm of dispatching systems for urban water logging

Due to global warming, considerable amounts of storm rain have occurred, causing urban water logging and flooding. The efficient scheduling of drainage systems among pumping stations is crucial to mitigating flash flooding in urban areas. This study introduces a Multi-Level Dynamic Priority and Importance Scheduling (MDPIS) algorithm as a proactive solution for addressing urban flooding through the optimization of drainage system discharge capacities. The algorithm's robustness is guaranteed through the integration of a multi-tier drainage system and dependency relationships. Additionally, the incorporation of an importance parameter is considered for facilitating the practical exploration of flooding risk evaluation. The proposed model was applied to simulate a drainage system in Haining City, and the results indicate that its accuracy, flexibility and reliability outperform that of existing algorithms such as fixed-priority scheduling. Moreover, the proposed approach enabled a considerable reduction in overflow loss and improved the efficiency of the sewage system. This method can improve the responses of cities to the rising problem of urban water logging.

Flood-Resilient Smart Cities: A Data-Driven Risk Assessment Approach Based on Geographical Risks and Emergency Response Infrastructure

Flooding in urban areas is expected to become even more common due to climatic changes, putting pressure on cities to implement effective response measures. Practical mechanisms for assessing flood risk have become highly desired, but existing solutions have been devoted to evaluating only specific cities and consider only limited risk perspectives, constraining their general applicability. This article presents an innovative approach for assessing the flood risk of delimited urban areas by exploiting geospatial information from publicly available databases, providing a method that is applicable to any city in the world and requiring minimum configurations. A set of mathematical equations is defined for numerically assessing risk levels based on elevation, slope, and proximity to rivers, while the existence of emergency-related urban infrastructure is considered as a risk reduction factor. Then, computed risk levels are used to classify areas, allowing easy visualisation of flood risk for a city. This smart city approach not only serves as a valuable tool for assessing the expected flood risk based on different parameters but also facilitates the implementation of cutting-edge strategies to effectively mitigate critical situations, ultimately enhancing urban resilience to flood-related disaster.

Sensitivity Analysis of Start Point of Extreme Daily Rainfall Using CRHUDA and Stochastic Models

Forecasting extreme precipitation is one of the basic actions of warning systems in Latin America and the Caribbean (LAC). With thousands of economic losses and severe damage caused by floods in urban areas, hydrometeorological monitoring is a priority in most countries in the LAC region. The monitoring of convective precipitation, cold fronts, and hurricane tracks are the most demanded technological developments for early warning systems in the region. However, predicting and forecasting the onset time of extreme precipitation is a subject of life-saving scientific research. Developed in 2019, the CRHUDA (Crossing HUmidity, Dew point, and Atmospheric pressure) model provides insight into the onset of precipitation from the Clausius–Clapeyron relationship. With access to a historical database of more than 600 storms, the CRHUDA model provides a prediction with a precision of six to eight hours in advance of storm onset. However, the calibration is complex given the addition of ARMA(p,q)-type models for real-time forecasting. This paper presents the calibration of the joint CRHUDA+ARMA(p,q) model. It is concluded that CRHUDA is significantly more suitable and relevant for the forecast of precipitation and a possible future development for an early warning system (EWS).

Investigation of Runoff and Flooding in Urban Areas based on Hydrology Models: A Literature Review

Investigation of Runoff and Flooding in Urban Areas based on Hydrology Models: A Literature Review

Hydrological reduction and control effect evaluation of sponge city construction based on one-way coupling model of SWMM-FVCOM: A case in university campus

The exacerbation of global warming, the frequent incidence of extreme weather events, and the rapid urbanization have collectively contributed to the heightened prevalence of flooding in urban areas. As a result of this challenge, sponge city (SPC) has been adopted in China as an efficient means of preventing and controlling urban floods. To evaluate the hydrological reduction and control effect of sponge city construction (SPCC) within a university campus, a one-way coupled model integrating one-dimensional sewer hydrodynamic model (SWMM) and two-dimensional surface flow model (FVCOM), namely SWMM-FVCOM model, was established. The Nash-Sutcliffe efficiency (NSE) of the SWMM were greater than 0.75 under there rainfalls with different intensity, indicating the good reliability and stability of this model could be used in the subsequent simulation. An analysis of drainage capacity and the risk of urban flooding was conducted using this model before and after the implementation of SPCC, considering six rainfall scenarios. Implementing SPCC demonstrated an effective performance in mitigating surface runoff, regulating inspection well overflow, and reducing overflow volume in the study region. However, the efficacy of runoff control diminished proportionally with the escalation of rainfall return period. Simultaneously, the implementation of low impact development (LID) measures can significantly decrease the extent and magnitude of surface inundations. The reduction rate of SPCC on the area of waterlogging ranged from 55.84% to 72.50%. But the control rate decreased with increasing rainfall return periods, demonstrating that adopting SPCC can effectively mitigate the severity of urban flooding resulting from low rainfall return period events (Tr < 20 years). This study can provide scientific foundation for environment managers to evaluate the impact of urban flooding prevention and control on runoff pollution mitigation when adopting the implementation of SPCC.

Assessing the Performance of Permeable Pavement in Mitigating Flooding in Urban Areas

In the case of rapid urban development, the impact of extreme climates on the world is gradually increasing, resulting in frequent flood events. However, Taiwan is still in the stage of urban development, and it is necessary to develop more roads. Therefore, determining how to reduce the impact of road engineering on the environment is one of the major issues currently faced. Therefore, a demonstration road of a general pavement and a permeable pavement was built in Dahua North Street, Taoyuan City, Taiwan, and rainwater was stored in a central irrigation ditch and a permeable pavement through an innovative construction method for reuse in agricultural irrigation. In addition, monitoring instruments and management systems were built, and the flow law formula was established, with R2 greater than 0.9. The actual discharge and peak discharge of the permeable pavement and general pavement were analyzed. According to the data analysis results, it can be seen that the permeable pavement can effectively reduce the peak discharge of 60~75%, which not only can achieve the benefit of low-impact development but also can reuse rainwater. The patent application can be used as an example for the application of permeable pavement in Taiwan in the future.

Advancing flood resilience: the nexus between flood risk management, green infrastructure, and resilience

IntroductionClimate change and the fast pace of urbanization are two major factors contributing to the exacerbated risk of flooding in urban areas. Flood resilience strategies, underpinned by the principles of green infrastructure, are gaining importance as within broader spatial planning approaches, and various global cities are adopting revised policies and frameworks to improve flood risk management. Yet, such responsive approaches are still limited and context-specific.MethodsIn this article, thematic analysis using NVivo was employed to analyse 49 documents related to flood risk management, resilience, and green infrastructure planning.ResultsThis paper reflects on the concepts of flood risk management, flood resilience and green infrastructure planning to identify the synergies between these concepts, and identify challenges that are prohibiting global flood resilience.DiscussionEnhancing flood resilience requires coordinated efforts, effective communication, and collaborative governance among stakeholders. The paper also draws planning recommendations for advancing flood resilience through governance and an integrated planning approach, in support of the global goals toward flood resilience.

Risk assessment for hurricane-induced pluvial flooding in urban areas using a GIS-based multi-criteria approach: A case study of Hurricane Harvey in Houston, USA

As one of the most destructive nature hazards, hurricane-induced flooding generates serious adverse impacts on populations, infrastructure, and the environment globally. In urban areas, complex characteristics such as high population and infrastructure densities increase flood disaster risks. Consequently, the assessment of flood risks is becoming increasingly important for understanding potential impacts on an urban area and proposing disaster risk mitigation strategies. After conducting a comprehensive literature review, this study finds that most urban flood risk assessments often overlook urban ecosystem elements, focusing more on social and economic aspects. Hence, the role of urban ecosystems cannot be fully understood. To address this gap, this study proposes a social-ecological systems (SES) flood risk assessment framework for urban areas. Based on this framework, a comprehensive list of indicators collected through a literature review is provided for urban flood risk assessments. A comparative study of flood risk during Hurricane Harvey (2017) in Houston, Texas, USA, is carried out using the improved analytic hierarchy process (IAHP) weighting method and the equal weighting method for indicator weighting. Results are then compared with the damage data of Hurricane Harvey published by the U.S. Federal Emergency Management Agency (FEMA). The analysis identifies that the western part of Houston had the highest flood risks, while the center of Houston was at lower flood risk. Comparisons between the results from the IAHP and equal weighting methods show that the latter produces a broader range of high flood risk areas than the former. This study also highlights the role of urban ecosystems in mitigating flood risks and advocates for more holistic, social-ecological assessments of flood risk. Such assessments could utilize the proposed framework and the indicator list but contextualize these to the specific urban area's contexts being investigated.