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Establishing appropriate boundary conditions is essential for developing high-accuracy hydrodynamic models. However, this task is particularly challenging in topographically varying urban domains without monotonous slopes due to insufficient boundary information. This study investigates five different boundary conditions and establishes modeling practices of boundary conditions in pluvial urban flood modeling. A numerical test model within the city of Berlin is used, employing the 2D hydrodynamic finite element module of the open-source TELEMAC system. It performs unsteady simulations with nodal rainfall inputs for various precipitation scenarios, excluding infiltration. The results demonstrate that the suitability of boundary conditions is critically dependent on the surrounding topography. For boundary segments with a positive slope, a stage–discharge curve is found to outperform the other boundary conditions investigated in this study. Conversely, for segments with a negative slope, a closed wall boundary condition appears clearly preferable. Additionally, a drainage reservoir boundary condition performs effectively for more complex boundary segments but necessitates extensive preprocessing. Based on these insights, simulations were repeated with segment-tailored boundary conditions. The results indicate that this combined model outperforms the global application of each individual model. [ABSTRACT FROM AUTHOR]

When a large-scale flood disaster occurs, it is important to identify the flood areas in a short time in order to effectively support the affected areas afterwards. Synthetic Aperture Radar (SAR) is promising for flood detection. A number of change detection methods have been proposed to detect flooded areas with pre- and post-event SAR data. However, it remains difficult to detect flooded areas in built-up areas due to the complicated scattering of microwaves. To solve this issue, in this paper we propose the idea of analyzing the local changes in pre- and post-event SAR data as well as the larger-scale changes, which may improve accuracy for detecting floods in built-up areas. Therefore, we aimed at evaluating the effectiveness of multi-scale SAR analysis for flood detection in built-up areas using ALOS-2/PALSAR-2 data. First, several features were determined by calculating standard deviation images, difference images, and correlation coefficient images with several sizes of kernels. Then, segmentation on both small and large scales was applied to the correlation coefficient image and calculated explanatory variables with the features at each segment. Finally, machine learning models were tested for their flood detection performance in built-up areas by comparing a small-scale approach and multi-scale approach. Ten-fold cross-validation was used to validate the model, showing that highest accuracy was offered by the AdaBoost model, which improved the F1 Score from 0.89 in the small-scale analysis to 0.98 in the multi-scale analysis. The main contribution of this manuscript is that, from our results, it can be inferred that multi-scale analysis shows better performance in the quantitative detection of floods in built-up areas. [ABSTRACT FROM AUTHOR]

With accelerated urbanization and escalating severity and frequency of extreme precipitation events, urban flooding has become increasingly prevalent, posing significant threats to human life and economic well-being. Given the scarcity of land resources, the integration of flood mitigation measures into public spaces, particularly in the form of multi-functional storage spaces (MFSs), emerges as an effective strategy for rainwater retention. To assess the efficacy of MFS, a coupled modeling framework, comprising the Storm Water Management Model (SWMM) and the LISFLOOD-FP hydrodynamic model, was employed in the study. Under rainstorms of varying design characterized by diverse return periods and peak rainfall intensity locations, the study simulated and compared the performance of low-impact-development (LID) strategies, MFS, and a combined approach utilizing both LID and MFS (ALL). The findings indicate that the performance of these strategies significantly varies under diverse rainfall intensity and peak coefficients. Specifically, as the return period increases, the reduction rates of the three projects gradually diminish. For lower return periods (P ≤ 10), the order of reduction effectiveness was LID < MFS < ALL; whereas, for higher return periods (P ≥ 20), the order was LID < ALL < MFS. LID exhibited superior performance under low return periods with an early-peak-rainfall position, and under high return periods with a mid-peak position. MFS and the ALL approach achieved the most significant reduction effects under early-peak-rainfall positions. LID may introduce uncertainties into the performance of MFS during rainfall events with higher return periods and peak coefficients. The outcomes of this research offer valuable technical insights that can inform urban planning strategies and enhance the design of flood mitigation measures in urban environments. [ABSTRACT FROM AUTHOR]

Urbanization and climate change increasingly challenge urban water management. In this context, the design of stormwater drainage systems, which traditionally relies on historical rainfall records, is being questioned. Although significant efforts have been dedicated to optimizing drainage networks, the upgrading of existing systems remains understudied. This research devised a set of viable stormwater drainage networks, referencing the road network of the Sino-Singapore Tianjin Eco-City (data from Google Maps). On this basis, utilizing design rainfall data (sourced from the local meteorological center), an extensive array of scenario analyses was conducted. The investigation assessed the performance of implementing two redundancy-based interventions—introducing loops and enlarging pipe diameters—as well as the patterns of flood risk response, and by integrating a multi-objective optimization algorithm, this study proposes a framework for the optimization of grey infrastructure upgrades based on component replacement. The findings suggest that a precise deployment strategy for grey infrastructure is essential. The former improves the effective flow distribution of the drainage system, while the latter enhances its flow capacity, making each intervention suitable for drainage systems with a different degree of centralization. Further research shows that an integrated hybrid scheme brings significant flood risk improvement with strong applicability for most urban drainage systems. The upgrade model proposed in this study could be a valuable initiative, offering theoretical insights for the construction and development of resilient cities. [ABSTRACT FROM AUTHOR]

Throughout history, natural disasters have caused severe damage to people and properties worldwide. Flooding is one of the most disastrous types of natural disasters. A key feature of flood assessment has been making use of the information derived from remote-sensing imagery from optical sensors on satellites using spectral indices. Here, a study was conducted about a recent spectral index, the Normalised Difference Inundation Index, and a new ensemble spectral index, the Concatenated Normalised Difference Water Index, and two mature spectral indices: Normalised Difference Water Index and the differential Normalised Difference Water Index with four different machine learning algorithms: Decision Tree, Random Forest, Naive Bayes, and K-Nearest Neighbours applied to the PlanetScope satellite imagery about the Brisbane February 2022 flood which is in urban environment. Statistical analysis was applied to evaluate the results. Overall, the four algorithms provided no significant difference in terms of accuracy and F1 score. However, there were significant differences when some variations in the indices and the algorithms were combined. This research provides a validation of existing measures to identify floods in an urban environment that can help to improve sustainable development. [ABSTRACT FROM AUTHOR]

The rapid urbanization process and high-intensity construction mode have greatly changed the underlying surface structure and spatial distribution of the natural land surface, further amplified the possibility of urban floods, and made urban security face more serious threats. Urban forest could help to mitigate urban floods through water holding and interception by its unique structures, especially the litter layer. This paper compared the ability of different forest tree species on urban floods mitigation, through analyzing their litter accumulation, litter water holding characteristics, and water interception features of different decomposed layers. The results concluded that Quercus mongolica Fisch. ex Ledeb. (QM) forest, Betula platyphylla Sukaczev (BP) forest, Larix gmelinii (Rupr.) Kuzen. (LG) forest, and Picea koraiensis Nakai (PK) forest were the best choices for improving urban floods resistance in a high-urbanization winter city, for they had larger litter mass and higher maximum water holding and interception capacity. The corresponding results of this study could help environmental management departments worldwide in the selection of tree species in urban greening projects focusing on urban flood control. [ABSTRACT FROM AUTHOR]

Frequency analysis has long been an important theme of hydrology research. Although meteorological techniques (physical approaches) such as radar nowcasting, remote sensing, and forecasting heavy rainfall events using meteorological simulation models are quite effective for urban disaster prevention, statistical and stochastic theories that include frequency analysis, which are usually used in flood control plans, are also valuable for flood control plans for disaster prevention. Master plans for flood control projects in urban areas often use the concept of T-year hydrological values with a T-year return period. A flood control target is a "landside area that is safe against heavy rainfall or floods with a return period of T years". This review emphasizes discussions of parameter estimation of stochastic models and selection of optimal statistical models, which include evaluation of goodness-of-fit techniques of statistical models. Based on those results, the authors criticize Japanese standard procedures recommended by the central government. Consistency between parameter estimation and evaluation of goodness-of-fit is necessary. From this perspective, we recommend using the maximum likelihood method and AIC, both of which are related to Kullback–Leibler divergence. If one prefers using SLSC, we recommend not SLSC itself but SLSC's non-exceedance probability. One important purpose of this review is the introduction of well-used Japanese methods. Because some techniques that are slightly different from the international standard have been used for many years in Japan, we introduce those in the review article. [ABSTRACT FROM AUTHOR]

Cities must develop actions that reduce flood risk in the face of extreme rainfall events. In this study, the dynamic resilience of the Gregorio catchment (São Carlos, Brazil) was assessed. The catchment lacks environmental monitoring and suffers from recurrent floods. The resilience curves were made considering the water depth in the drainage system as the performance index, obtained by simulations with SWMM and HEC-RAS. The calibration of the flood extension was performed using citizen science data. The contribution to increasing the dynamic resilience by implementing decentralized low impact development (LID) practices was also evaluated. For this purpose, bioretention cells were added to the SWMM simulations. The resilience curves were then calculated for the current and future climate scenario, with and without LID, for return periods of 5, 10, 50, and 100 years and duration of 30, 60, and 120 min. Intensity–duration–frequency curves (IDFs) updated by the regional climate model MIROC5 for 2050 and 2100 were used. The results showed a significant improvement in the system's resilience for light storms and the current period due to LID practice interventions. Efficiencies were reduced for moderate and heavy storms with no significant drops in floodwater depth and resilience regardless of the scenario. [ABSTRACT FROM AUTHOR]

Global climate change and rapid urbanization have caused increases in urban floods. Urban flood risk assessment is a vital method for preventing and controlling such disasters. This paper takes the central region of Cangzhou city in Hebei Province as an example. Detailed topographical information, such as the buildings and roads in the study area, was extracted from GF-2 data. By coupling the two models, the SWMM and MIKE21, the spatial distribution of the inundation region, and the water depth in the study area under different return periods, were simulated in detail. The results showed that, for the different return periods, the inundation region was generally consistent. However, there was a large increase in the mean inundation depth within a 10-to-30-year return period, and the increase in the maximum inundation depth and inundation area remained steady. The comprehensive runoff coefficient in all of the scenarios exceeded 0.8, indicating that the drainage system in the study area is insufficient and has a higher flood risk. The flood risk of the study area was evaluated based on the damage curve, which was obtained from field investigations. The results demonstrate that the loss per unit area was less than CNY 250/m2 in each return period in the majority of the damaged areas. Additionally, the total loss was mainly influenced by the damaged area, but, in commercial areas, the total loss was highly sensitive to the inundation depth. [ABSTRACT FROM AUTHOR]

Urban floods research has been attracting extensive attention with the increasing threat of flood risk and environmental hazards due to global climate change and urbanization. However, there is rarely a comprehensive review of this field and it remains unclear how the research topics on urban floods have evolved. In this study, we analyzed the development of urban floods research and explored the hotspots and frontiers of this field by scientific knowledge mapping. In total, 3314 published articles from 2006 to 2021 were analyzed. The results suggest that the number of published articles in the field of urban floods generally has an upward trend year by year, and the research focus has shifted from exploring hydrological processes to adopting advanced management measures to solve urban flood problems. Moreover, urban stormwater management and low impact development in the context of climate change and urbanization have gradually become research hotspots. Future research directions based on the status and trends of the urban floods field were also discussed. This research can not only inspire other researchers and policymakers, but also demonstrates the effectiveness of scientific knowledge mapping analysis by the use of the software CiteSpace and VOSviewer. [ABSTRACT FROM AUTHOR]

The growth of urban population, combined with an increase of extreme events due to climate change call for a better understanding and representation of urban floods. The uncertainty in rainfall distribution is one of the most important factors that affects the watershed response to a given precipitation event. However, most of the investigations on this topic have considered theoretical scenarios, with little reference to case studies in the real world. This paper incorporates the use of spatially-variable precipitation data from a long-range radar in the simulation of the severe floods that impacted the city of Hull, U.K., in June 2007. This radar-based rainfall field is merged with rain gauge data using a Kriging with External Drift interpolation technique. The utility of this spatially-variable information is investigated through the comparison of computed flooded areas (uniform and radar) against those registered by public authorities. Both results show similar skills at reproducing the real event, but differences in the total precipitated volumes, water depths and flooded areas are illustrated. It is envisaged that in urban areas and with the advent of higher resolution radars, these differences will be more important and call for further investigation. [ABSTRACT FROM AUTHOR]

Urban public space is extraordinarily adaptable under a pattern of relatively stable changes. However, when facing unprecedented and potentially extreme climatic changes, public spaces may not have the same adaptation capacity. In this context, planned adaptation gains strength against "business as usual". While public spaces are among the most vulnerable areas to climatic hazards, they entail relevant characteristics for adaptation efforts. As such, public space design can lead to effective adaptation undertakings, explicitly influencing urban design practices as we know them. Amongst its different intrinsic roles and benefits, such as being a civic common gathering place of social and economic exchanges, public space may have found an enhanced protagonism under the climate change adaptation perspective. In light of the conducted empirical analysis, which gathered existing examples of public spaces with flood adaptation purposes, specific public space potentialities for the application of flood adaptation measures are here identified and characterized. Overall, this research questions the specific social potentiality of public space adaptation in the processes of vulnerability tackling, namely considering the need of alternatives in current flood management practices. Through literature review and case study analysis, it is here argued that: people and communities can be perceived as more than susceptible targets and rather be professed as active agents in the process of managing urban vulnerability; that climate change literacy, through the design of a public space, may endorse an increased common need for action and the pursuit of suitable solutions; and that local know-how and locally-driven design can be considered as a service with added value for adaptation endeavors. [ABSTRACT FROM AUTHOR]

Floods are the most destructive, widespread, and frequent natural hazards. The extent of flood events is accelerating in the context of climate change, where flood management and disaster mitigation remain important long-term issues. Different studies have been utilizing data and images from various types of sensors for mapping, assessment, forecasting, early warning, rescue, and other disaster prevention and mitigation activities before, during, and after floods, including flash floods, coastal floods, and urban floods. These monitoring processes evolved from early ground-based observations relying on in situ sensors to high-precision, high-resolution, and high-coverage monitoring by airborne and remote sensing sensors. In this study, we have analyzed the different kinds of sensors from the literature review, case studies, and other methods to explore the development history of flood sensors and the driving role of floods in different countries. It is found that there is a trend towards the integration of flood sensors with artificial intelligence, and their state-of-the-art determines the effectiveness of local flood management to a large extent. This study helps to improve the efficiency of flood monitoring advancement and flood responses as it explores the different types of sensors and their effectiveness. [ABSTRACT FROM AUTHOR]

This paper develops a method integrating Geographic Information Systems (GIS) and the Decision-Making Trials and Evaluation Laboratory (DEMATEL) for the analysis of factors influencing urban flood risk and the identification of flood-prone areas. The method is based on nine selected factors: land use/land cover (LULC: the ratio of built-up areas, the ratio of greenery areas), elevation, slope, population density, distance from the river, soil, Topographic Wetness Index (TWI), and Normalized Difference Vegetation Index (NDVI). The DEMATEL method is used to determine the cause–effect relationship between selected factors, allowing for key criteria and their weights to be determined. LULC and population density were identified as the most important risk factors for urban floods. The method was applied to a case study—the Serafa River watershed (Poland), an urbanized catchment covering housing estates of cities of Kraków and Wieliczka frequently affected by flooding. GIS analysis based on publicly available data using QGIS with weights obtained from DEMATEL identified the vulnerable areas. 45% of the total catchment area was classified as areas with a very high or high level of flood risk. The results match the actual data on inundation incidents that occurred in recent years in this area. The study shows the potential and possibility of using the DEMATEL-GIS method to determine the significance of factors and to designate flood-prone areas. [ABSTRACT FROM AUTHOR]

As global water resources decline and demand increases due to population growth and climate change, innovative rainwater storage systems (IRSSs) have become crucial. This review examines the potential of IRSSs to sustainably address rainwater challenges by analyzing key factors that influence their success. Drawing on research from Scopus and Google Scholar, it evaluates IRSSs in both urban and rural settings across different countries and regions, focusing on their contribution to Sustainable Development Goal (SDG) 6. This review highlights how social, environmental, economic, and policy factors affect the success of IRSS compared to traditional systems common in developing nations. IRSSs can outperform traditional methods in sustainability, encouraging their adoption. However, there is a significant gap in policy integration that needs to be addressed for successful implementation. Further research is needed to better understand the contributing factors and their role in achieving sustainability. Integrating rainwater harvesting into national water policies could offer valuable guidance for policymakers and water resource managers in addressing issues like urban floods, water scarcity, and related social and environmental challenges in developing countries. [ABSTRACT FROM AUTHOR]

In recent years, urban floods have occurred frequently in China. Therefore, there is an urgent need to strengthen urban flood resilience. This paper proposed a hybrid multi-criteria group decision-making method to assess urban flood resilience based on heterogeneous data, group decision-making methodologies, the pressure-state–response model, and social–economic–natural complex ecosystem theory (PSR-SENCE model). A qualitative and quantitative indicator system is formulated using the PSR-SENCE model. Additionally, a new weighting method for indicators, called the synthesis weighting-group analytic hierarchy process (SW-GAHP), is proposed by considering both intrapersonal consistency and interpersonal consistency of decision-makers. Furthermore, an extensional group decision-making technology (EGDMT) based on heterogeneous data is proposed to evaluate qualitative indicators. The flexible parameterized mapping function (FPMF) is introduced for the evaluation of quantitative indicators. The normal cloud model is employed to handle various uncertainties associated with heterogeneous data. The evaluations for Beijing from 2017 to 2021 reveal a consistent annual improvement in urban flood resilience, with a 14.1% increase. Subsequently, optimization recommendations are presented not only for favorable indicators such as regional economic status, drainability, and public transportation service capacity but also for unfavorable indicators like flood risk and population density. This provides a theoretical foundation and a guide for making decisions about the improvement of urban flood resilience. Finally, our proposed method shows superiority and robustness through comparative and sensitivity analyses. [ABSTRACT FROM AUTHOR]

The development of cities has always had a very close relation with water. However, cities directly impact land use patterns and greatly change natural landscapes, aggravating floods. Considering this situation, this paper intends to discuss lowland occupation and city sustainability in what regards urban stormwater management, fluvial space, and river restoration, aiming at minimizing flood risks and improving natural and built environment conditions. River plains tend to be attractive places for a city to grow. From ancient times, levees have been used to protect lowland areas along major watercourses to allow their occupation. However, urban rivers demand space for temporary flood storage. From a systemic point of view, levees along extensive river reaches act as canalization works, limiting river connectivity with flood plains, rising water levels, increasing overtopping risks and transferring floods downstream. Departing from this discussion, four case studies in the Iguaçu-Sarapuí River Basin, a lowland area of Rio de Janeiro State, Brazil, are used to compose a perspective in which the central point refers to the need of respecting watershed limits and giving space to rivers. Different aspects of low-lying city planning are discussed and analyzed concerning the integration of the built and natural environments. [ABSTRACT FROM AUTHOR]

This paper addresses the riverine flood events that have occurred in Greece over the last 136 years (i.e., during the 1886–2022 period), focusing, amongst others, on the case of urban floods. The flood record of various sites of the country has been collected and analyzed to determine their spatial and temporal distribution. Greece is a country where flood data and records are very scarce. Therefore, as there is not an integrated catalog of Greek floods spanning from the 19th century to recently, this is the first attempt to create an integrated catalog for Greece. The sources used include published papers, local and regional newspapers and public bodies (mainly the Ministry of Environment and Energy and the official websites of Greek municipalities). Additionally, the main factors responsible for their occurrence have been issued, regarding the country's climatic, geological and geomorphological setting, as well as human interventions. In addition, the atmospheric circulation driving factors of floods are assessed via an unsupervised neural network approach (i.e., Self-Organizing Maps). Based on the results of this research, an online GIS-based database has been created, depicting the areas that have been struck by riverine floods in Greece. By clicking a flood event in the online database, one can view several characteristics, depending on data availability, such as duration and height of the rainfall that caused them and number of fatalities. Long-term trends of mean and extremes seasonal precipitation also linked to the spatial distribution of floods. Our analysis shows that urban floods are a very large portion of the overall flood record, and they mainly occur in the two large urban centers, Athens and Thessaloniki, as well as near large rivers such as Pineios. Autumn months and mainly November are the periods with higher flood hazards, based on past records and cyclonic atmospheric circulation constitutes the principal driving factor. Our results indicate that a flood catalog at national level is of fundamental importance, as it can provide valuable statistical insights regarding seasonality, spatial distribution of floods, etc., while it can also be used by stakeholders and researchers for flood management and flood risk analysis and modelling. [ABSTRACT FROM AUTHOR]

This paper examines the challenges of and facilitating strategies for linking disaster risk reduction (DRR) and climate change adaptation (CCA) in addressing urban floods, drawing from Indonesia's experience. The fragmentation between efforts to implement DRR and CCA leading to unnecessary duplication could increase confusion at both the community and wider governance levels and reduce the effectiveness of urban flood management. Through the lens of collaborative governance, this paper analyzes the barriers for integrating DRR and CCA and options to better align their practices in the context of a megapolitan city, Jakarta, Indonesia. The key findings of this study confirmed that institutional fragmentation, in concert with inconsistent facilitation and collaboration mechanisms, were the strongest barriers to aligning DRR and CCA action. The absence of accountable leadership was a key impediment for successful partnership-building processes to support political and technical collaboration. Leadership in these contexts plays an important role in (1) developing sustainable relationships, (2) convincing potential stakeholders to collaborate, (3) persuading partners to commit to sharing resources, and (4) agreeing/sharing a common vision of the partnership actions needed to mitigate harm and reduce urban vulnerability. These factors are critically important for reducing the direct and indirect impacts of flooding in Jakarta. Such lessons from Indonesia on linking DRR and CCA offer valuable insights to inform the development of policies and strategies to deal with urban floods for global cities faced with similar challenges. [ABSTRACT FROM AUTHOR]

The authors showed that the method based on time series analysis achieved a stable forecast, and indicated that the method can be applied as a water level forecast method for basins with an extremely fast flood arrival times and limited observation data. All four of the review papers are related to the problems associated with flash flood phenomena, among the many broad topics mentioned above, but they focus on very different aspects of the phenomena, such as urban runoff modeling in Japan [[1]], real-time urban flood forecasting systems for Southeast Asia [[2]], frequency analysis of urban floods [[3]], and the reduction of non-point pollution as well as flood runoff by porous concrete infiltration [[4]]. Urban areas are considered to be the most vulnerable to water-related problems, which involve a lack or excess of water problems from the perspectives of quantity and quality. The authors summarized the recent radar data utilization methods for rainfall forecasting, physical-process-based hydraulic models for flood inundation prediction, and data-driven artificial intelligence (AI) models for the real-time forecasting systems. [Extracted from the article]

The emergency response is crucial in preventing and mitigating urban floods. Both remote sensing and social media data offer distinct advantages in large-scale flood monitoring and near-real-time flood monitoring. However, current research lacks a thorough exploration of the application of social media data and remote sensing imagery in the urban flood emergency response. To address this issue, this paper, while extracting disaster information based on social media data, deeply mines the spatiotemporal distribution characteristics and dynamic spatial accessibility of rescue points. Furthermore, SAR imagery and social media data for monitoring urban flooding are compared. This study took the Zhengzhou 7.20 urban flood as a case study and created a methodological framework to quickly extract flood disaster information (flood, landslide, and rescue points) using these two types of data; spatiotemporal analysis and random forest classification were also conducted to mine valuable information. Temporally, the study revealed that disaster information did not increase proportionally with the amount of rainfall during the rainfall process. Spatially, specific regions with higher susceptibility to flooding, landslides, and rescue points were identified, such as the central region characterized by low drainage standards and high-density urban areas, as well as the eastern region with low-lying terrain. Moreover, this study examined the spatial accessibility of rescue resources in real flood scenarios and found that their service coverage varied throughout the day during and after the disaster. In addition, social media excelled in high-density urban areas' flood point extraction, while SAR performed better in monitoring floods at the edges of low-density urban areas and large water bodies, allowing them to complement each other, to a certain extent. The findings of this study provide scientific reference value for the optimal selection of rescue paths and the allocation of resources in the emergency response to urban floods caused by extreme rainstorms. [ABSTRACT FROM AUTHOR]

Urban flooding is a severe and pervasive hazard caused by climate change, urbanization, and limitations of municipal drainage systems. Cities face risks from different types of floods, depending on various geographical, environmental, and hydrometeorological conditions. In response to the growing threat of urban flooding, a better understanding of urban flood vulnerability is needed. In this study, a comprehensive method was developed to evaluate the vulnerability of different types of urban floods. First, a coupled urban flood model was built to obtain the extent of influence of various flood scenarios caused by rainfall and river levee overtopping. Second, an assessment framework for urban flood vulnerability based on an indicator method was used to evaluate the vulnerability in different flood hazard scenarios. Finally, the method was applied to Lishui City, China, and the distribution and pattern of urban flood vulnerability were studied. The results highlight the spatial variability of flooding and the vulnerability distributions of different types of urban floods. Compound floods were identified to cause more severe effects in the urban areas. [ABSTRACT FROM AUTHOR]

As a result of urbanization and climate change, urban areas are increasingly vulnerable to flooding, which can have devastating effects on the loss of life and property. Remote sensing technology can provide practical help for urban flood disaster management. This research presents a review of urban flood-related remote sensing to identify research trends and gaps, and reveal new research opportunities. Based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), the systematic literature search resulted in 347 documents classified as geography, disaster management application, and remote sensing data utilization. The main results include 1. most of the studies are located in high-income countries and territories and inland areas; 2. remote sensing for observing the environment was more popular than observing the building; 3. the most often applied disaster management activities were vulnerability assessment and risk modeling (mitigation) and rapid damage assessment (response); 4. DEM is often applied to simulate urban floods as software inputs. We suggest that future research directions include 1. coastal urban study areas in non-high-income countries/territories to help vulnerable populations; 2. understudied disaster management activities, which often need to observe the buildings in more urban areas; 3. data standardization will facilitate integration with international standard methods for assessing urban floods. [ABSTRACT FROM AUTHOR]

Urban floods caused by extreme rainstorm events have increased in recent decades, particularly in concave-down bridge zones. To simulate urban flooding processes accurately, an integrated urban flood model (IUFM) was constructed by coupling a distributed urban surface runoff model based on the cellular automata framework (CA-DUSRM), a widely used pipe convergence module in the storm water management model (SWMM), with an inundation module that describes the overflow expansion process associated with terrain and land-cover. The IUFM was used in a case study of the Anhua Bridge (a typical concave-down overpass) study area in Beijing, China. The spatial-temporal variations in flood depth modeled by the IUFM were verified to be reliable by comparison with actual measurements and other simulations. The validated IUFM was used to obtain temporal variations in flood range, depth, and volume under four rainstorm scenarios (return periods of 3-year, 10-year, 50-year, and 100-year). The results showed that the surface runoff process, overflow from drainage networks, and overflow expansion process could affect the flooding status by changing the composition and spatial configuration of pervious or impervious patches, drainage capacity, and underlying surface characteristics (such as terrain and land-cover). Overall, although the simulation results from the IUFM contain uncertainties from the model structures and inputs, the IUFM is an effective tool that can provide accurate and timely information to prevent and control urban flood disasters and provide decision-making support for long-term storm water management and sponge city construction. [ABSTRACT FROM AUTHOR]

Using radar to estimate and forecast precipitation as input for hydrological models has become increasingly popular in recent years because of its superior spatial and temporal simulation compared with using rain gauge data. This study used radar-based quantitative precipitation estimation (QPE) to select the optimal parameter set for the MIKE URBAN hydrological model and radar-based quantitative precipitation forecasting (QPF) to simulate inundation in Nam Dinh city, Vietnam. The results show the following: (1) radar has the potential to improve the modeling and provide the data needed for real-time smart control if proper bias adjustment is obtained and the risk of underestimated flows after heavy rain is minimized, and (2) the MIKE URBAN model used to calculate two simulation scenarios with rain gauge data and QPE data showed effectiveness in combining the application of radar-based precipitation for the forecasting and warning of urban floods in Nam Dinh city. The results in Scenario 2 with rainfall forecast data from radar provide better simulation results. The average relative error in Scenario 2 is 9%, while the average relative error in Scenario 1 is 15%. Using the grid radar-based precipitation forecasting as input data for the MIKE URBAN model significantly reduces the error between the observed water depth and the simulated results compared with the case using an input rain gauge measured at Nam Dinh station (the difference in inundation level of Scenario 2 using radar-based precipitation is 0.005 m, and it is 0.03 m in Scenario 1). The results obtained using the QPE and QPF radar as input for the MIKE URBAN model will be the basis for establishing an operational forecasting system for the Northern Delta and Midland Regional Hydro-Meteorological Center, Viet Nam Meteorological and Hydrological Administration. [ABSTRACT FROM AUTHOR]

Malaysia, being a tropical country located near the equatorial doldrums, experiences the annual occurrence of flood hazards due to monsoon rainfalls and urban development. In recent years, environmental policies in the country have shifted towards sustainable flood risk management. As part of the development of flood forecasting and warning systems, this study presented the urban flood simulation using InfoWorks ICM hydrological−hydraulic modeling of the Damansara catchment as a case study. The response of catchments to the rainfall was modeled using the Probability Distributed Moisture (PDM) model due to its capability for large catchments with long-term runoff prediction. The interferometric synthetic aperture radar (IFSAR) technique was used to obtain high-resolution digital terrain model (DTM) data. The calibrated and validated model was first applied to investigate the effectiveness of the existing regional ponds on flood mitigation. For a 100-year flood, the extent of flooded areas decreased from 12.41 km2 to 3.61 km2 as a result of 64-ha ponds in the catchment, which is equivalent to a 71% reduction. The flood hazard maps were then generated based on several average recurrence intervals (ARIs) and uniform rainfall depths, and the results showed that both parameters had significant influences on the magnitude of flooding in terms of flood depth and extent. These findings are important for understanding urban flood vulnerability and resilience, which could help in sustainable management planning to deal with urban flooding issues. [ABSTRACT FROM AUTHOR]

Increasingly frequent, high-intensity rain events associated with climatic change are driving urban drainage systems to function beyond their design discharge capacity. It has become an urgent issue to mitigate the water resource management challenge. To address this problem, a real-time procedure for predicting the inundation risk in an urban drainage system was developed. The real-time procedure consists of three components: (i) the acquisition and forecast of rainfall data; (ii) rainfall-runoff modeling; and (iii) flood inundation mapping. This real-time procedure was applied to a drainage system in the Sukhumvit area of Bangkok, Thailand, to evaluate its prediction efficacy. The results showed precisely that the present real-time procedure had high predictability in terms of both the water level and flood inundation area mapping. It could also determine hazardous areas with a certain amount of lead time in the drainage system of the Sukhumvit area within an hour of rainfall data. These results show the real-time procedure could provide accurate flood risk warning, resulting in more time to implement flood management measures such as pumping and water gate operations, or evacuation. [ABSTRACT FROM AUTHOR]

The increasing interest in hydrological studies in the United Arab Emirates (UAE) has resulted in the publication of several papers on hydrology and its broad use for addressing contemporaneous challenges confronting humans and the environment in the region. However, for several reasons, these efforts have remained invisible and unrecognized. This paper has reviewed the literature on hydrological research in the UAE to provide a comprehensive source of information for researchers, practitioners, policymakers, and other stakeholders. The documented studies were carefully selected, relying on a bibliometric analysis methodology of five phases to specify the boundary of the study area, adopt the primary keywords for the search, evaluate the obtained papers, exclude the non-conforming ones, and classify the final results into four distinguished topics—namely, rainfall analysis, urban growth and flood hazards, cloud seeding and changing climate, and groundwater situation and utilization. The evaluation process considered assessing the papers' relevancy, authenticity, and coverage of the main issues of interest. In all, a total of 50 published papers were identified based on the specified criteria and reviewed. The main findings were first that the amount of rainfall over the UAE has been declining in the last decade, and this trend is expected to continue, although intensities are rising, suggesting shorter duration events. Secondly, the extensive urban growth in the country has resulted in increasing incidences of urban floods and declining groundwater recharge. Both of these are to be expected as consequences of the increased imperviousness from urbanization and the higher intensities from shorter-duration rainfall events. Thirdly, although the cloud-seeding program has proved to be successful in increasing precipitation amounts, the impact of this on flooding due to more extreme rainfall intensities and on air quality remains worrisome. Finally, groundwater analyses have shown that it is still the main freshwater resource in the country, but its long-term sustainability and quality are being threatened by the declining recharge. This calls for a national policy for groundwater management in the UAE to tackle the challenges associated with the increasing demand for water in all sectors of the economy. The study recommended addressing the gap in the hydrological literature of the UAE, specifically in the field of big meteorological data analysis, the socioeconomic impacts of urban floods, the impacts of climate change in urbanized regions, and the possibility of using alternative resources to recharge groundwater as part of sustainable water management. [ABSTRACT FROM AUTHOR]

Community resilience is a key index for describing the response of human habitat systems to hazards. Evaluating and enhancing the community resilience requires indicators, identification, and quantitative measurements, especially for urban flooding management. In this study, an advanced index framework for measuring community resilience to urban flooding is proposed, integrating the fuzzy Delphi method (FDM) and the analytic network process (ANP). Seven indicators (public facilities, spatial structure of land use, flood management organizations, rescue capability, accuracy of weather forecasts, vulnerable population, and individual capability) of community resilience are identified using the fuzzy Delphi method. The indicators are classified into four dimensions, and the weights are determined by the analytic network process. This approach is applied to three different types of communities, namely, a newly built neighborhood, an ancient college, and a flood-prone village in the city of Nanning, China, using data collected from questionnaires, interviews, and field investigations. The neighborhood (with a total averaged score of 2.13) has the largest community resilience to urban flooding, followed by the college (1.8), and finally the village (0.91). Flooding management organizations play a leading role in the urban flooding resilience of the neighborhood and college, while the vulnerable population has a great impact on the community resilience of the village. Results of the strategy analysis suggest that science and technology improvement (0.543) is more important than social–economic status improvement (0.325) and built-environment improvement (0.132) for mitigating urban hazards in Nanning. The proposed framework in this study contributes to the interdisciplinary understanding of community resilience for urban flooding and is expected to be applied to sustain urban planning and flood evacuations. [ABSTRACT FROM AUTHOR]

Vulnerability assessment is an essential tool in mitigating the impact of urban flooding. To date, most flood vulnerability research has focused on one type of flood, such as a pluvial or fluvial flood. However, cities can suffer from urban flooding for several reasons, such as precipitation and river levee overtopping. Therefore, a vulnerability assessment considering different types of floods (pluvial floods, fluvial floods, and compound flooding induced by both rainfall and river overtopping) was conducted in this study. First, a coupled urban flood model, considering both overland and sewer network flow, was developed using the storm water management model (SWMM) and LISFLOOD-FP model to simulate the different types of flood and applied to Lishui, China. Then, the results of the flood modeling were combined with a vulnerability curve to obtain the potential impact of flooding on different land-use classes. The results indicated that different types of floods could have different influence areas and result in various degrees of flood vulnerability for different land-use classes. The results also suggest that urban flood vulnerability can be underestimated due to a lack of consideration of the full flood-induced factors. [ABSTRACT FROM AUTHOR]

In this study, multi-temporal satellite images combined with rainfall data and field observations were used to assess the spatial and temporal changes in urban flooding and urban water harvesting potential in the coastal city of Sharjah, United Arab Emirates (UAE) during the period from 1976 to 2016. During the study period, the population increased by approximately 14-fold with about a 4-fold increase in built areas. Being in a hot, dry region with average rainfall of about 100 mm/year, the city did not invest in a comprehensive drainage infrastructure. As a result, the frequency, extent and risk associated with urban floods increased significantly. The expansion of built areas progressively increased the impervious land cover in the city, decreasing the minimum precipitation required to generate runoff by approximately 32% and significantly increasing the runoff coefficient. In parallel to rapid urbanization, the urban rainwater harvesting potential significantly increased over 1976–2016. Urban flood maps were generated using three thematic factors: excess rain, land elevation and land slope. The flood maps were confirmed by locating urban flood locations in the field using GPS. This study demonstrates the impact of urbanization through assessing the relationship between urbanization, runoff, local floods and rainwater harvesting potential in Sharjah and provides a basis for developing sustainable urban storm water management practices for the city and similar cities. [ABSTRACT FROM AUTHOR]

The 400-year history of Dhaka says that the city once had several well-known natural canals (khals) that drained stormwater and graywater. In addition to city's combined sewer system, these water bodies offered an essential natural drainage system that allowed to manage the monsoon rainfall effectively. However, over the past three decades, due to rapid urbanization, these khals have significantly depleted to the point where they are no longer capable of draining the city's monsoon runoff. Using past, present, and future Land Use and Land Cover (LULC) and urban drainage modeling, this study identified the effects of such LULC change on pluvial flooding of the northern part of the city. Analysis shows that the rapid and extensive changes in LULC over the past decades have resulted in significant shrinkage of these khals, consequently leading to escalated rates of urban flooding in this region. The western part of Turag thana, low-lying areas close to the Baunia Khal depression, and the upstream region of Abdullahpur Khal are highly vulnerable to future urban floods. The projected LULC change indicates an increase of 8.47%, 8.11%, and 4.05% in the total inundation area by 2042 for rainfall events with return periods of 50 years, 25 years, and 2.33 years, respectively. The findings also indicate that 11% more area is likely to experience long-duration flooding due to LULC change. [ABSTRACT FROM AUTHOR]

Assessing the resilience of urban drainage systems requires the consideration of future disturbances that will disrupt the system's performance and trigger urban flooding failures. However, most existing resilience assessments of urban drainage systems rarely consider the uncertain threats from future urban redevelopment and climate change, which leads to the underestimation of future disturbances toward system performance. This paper fills in the gap of assessing the combined and relative impacts of future impervious land cover and rainfall changes on flooding resilience in the context of a densely infilled urban catchment served by an urban drainage system in Salt Lake City, Utah, USA. An event-based resilience index is proposed to measure climate change and urbanization impacts on urban floods. Compared with the traditional resilience metric, the event-based resilience index can consider climatic and urbanized impacts on each urban flooding event; the new resilience index assist engineers in harvesting high-resolution infrastructure adaptation strategies at vulnerable spots from the system level to the junction level. Impact comparison for the case study shows that impervious urban surface changes induce greater effects on the system performance curves by magnifying the maximum failure level, lengthening the recovery duration, and aggravating the flooding severity than rainfall intensity changes. A nonlinear logarithmic resilience correlation is found; this finding shows that flooding resilience is more sensitive to the land imperviousness change due to urban redevelopment than rainfall intensity changes in the case study. This research work predicts the system response to the disturbances induced by climate change and urban redevelopment, improving the understanding of impact analysis, and contributes to the advancement of resilient urban drainage systems in changing environments. [ABSTRACT FROM AUTHOR]

Water scarcity affects at least 11% of the population and 17% of the territory of the European Union. Simultaneously in cities there is a problem of urban floods caused by violent and intense rainfalls. Decentralized drainage systems are designed to capture rainwater runoff at the place of precipitation and improve the hydrological conditions through the use of surface and subsurface infiltration, retention, and evapotranspiration techniques. The purpose of this paper was to evaluate the financial profitability of selected Low Impact Development (LID) methods for decentralized management of rainwater disposed from the roofs of two different buildings. In the presented conditions, the use of dual installations and infiltration tunnels turned out to be cost-effective solutions, whereas infiltration boxes were unprofitable for both buildings. The most unprofitable solution would become profitable if the investment costs were reduced by as much as 67% or if it was possible to generate 2.28 times more benefits. Although the research was carried out for specific conditions, the obtained results may be helpful in the implementation of similar investments. They are also a kind of contribution to the assessment of the cost-effectiveness of LID on a global scale due to the universality of the proposed research methodology. [ABSTRACT FROM AUTHOR]

The occurrence of flash floods is an increasingly common phenomenon. In many parts of the world, it is associated with an increase in the intensity of rainfall. Reducing the financial and social losses caused by the occurrence of local urban floods is possible through the use of hydrodynamic modeling and real-time flood forecasting. The purpose of this study is to assess the ability of the modeling technique to simulate the flow in a small catchment area and to determine the time remaining to reach the set warning and danger levels. SWMM 5.2 and QuantumGIS software were used in the study. The analysis showed that for the considered catchment area with a short length of the main stream (1612 m), the time possible for implementing countermeasures and evacuating the population is 70 to 120 min. The study also confirmed that short-term rainfall requires less depth to reach high stormwater elevations than long-term rainfall. In addition, a relationship was noted between the preceding rainfall and the height of stormwater and the forecast time. There was an unfavorable reduction in forecasting time as the depth of rainfall increased and its duration shortened. In the case of the analyzed catchment, the maximum elevation of stormwater (Esw,max) is generated by rainfall that is characterized by the highest intensity in the final phase of their duration. Similarly, the longest forecast time (tf) for the maximum stormwater elevation is caused by rainfall, which is characterized by the highest intensity in its final phase. The results of the study can significantly assist local governments when developing a catchment management plan and when trying to implement practices to minimize the negative effects of flash floods. [ABSTRACT FROM AUTHOR]

Urban flooding is a frequent disaster in cities. With the increasing imperviousness caused by rapid urbanization and the rising frequency and severity of extreme events caused by climate change, the hydrological status of the urban area has changed, resulting in urban floods. This study aims to identify trends and gaps and highlight potential research prospects in the field of urban flooding in South Asia. Based on an extensive literature review, this paper reviewed urban flood hazard assessment methods using hydraulic/hydrological models and urban flood management practices in South Asia. With the advancement of technology and high-resolution topographic data, hydrologic/hydraulic models such as HEC-RAS/HMS, MIKE, SWMM, etc., are increasingly used for urban flood hazard assessment. Urban flood management practices vary among countries based on existing technologies and infrastructures. In order to control urban flooding, both conventional physical structures, including drainage and embankments, as well as new innovative techniques, such as low-impact development, are implemented. Non-structural flood mitigation measures, such as improved flood warning systems, have been developed and implemented in a few cities. The major challenge in using process-based hydraulic models was the lack of high-resolution DEM and short-duration rainfall data in the region, significantly affecting the model's simulation results and the implementation of flood management measures. Risk-informed management must be implemented immediately to reduce the adverse effects of climate change and unplanned urbanization on urban flooding. Therefore, it is crucial to encourage emergency managers and local planning authorities to consider a nature-based solution in an integrated urban planning approach to enhances urban flood resilience. [ABSTRACT FROM AUTHOR]

Over the past 10 years, urban floods have increased in frequency because of extreme rainfall events and urbanization development. To reduce the losses caused by floods, various urban flood models have been developed to realize urban flood early warning. Using CiteSpace software's co-citation analysis, this paper reviews the characteristics of different types of urban flood models and summarizes state-of-the-art technologies for flood model development. Artificial intelligence (AI) technology provides an innovative approach to the construction of data-driven models; nevertheless, developing an AI model coupled with flooding processes represents a worthwhile challenge. Big data (such as remote sensing, crowdsourcing geographic, and Internet of Things data), as well as spatial data management and analysis methods, provide critical data and data processing support for model construction, evaluation, and application. The further development of these models and technologies is expected to improve the accuracy and efficiency of urban flood simulations and provide support for the construction of a multi-scale distributed smart flood simulation system. [ABSTRACT FROM AUTHOR]

Urban flood risk communication continues to challenge governments. Community-based organizations (CBOs) aim to rapidly detect deficiencies in capacity to deal with flood risk in vulnerable communities and disseminate accessible risk information to assist in the selection and implementation of risk mitigation measures. This paper discusses the methods through which CBO members think their work is beneficial in the response to urban floods. Grounded theory is utilized to guide a mixed-method approach that included semistructured interviews with CBO members (N = 34), participatory observations, and policy document analysis. The findings show that localization of risk knowledge and the emergence of new social networks are important factors in flood risk communication in vulnerable communities. This discovery may highlight the varied aspects of creating community resilience and explain why traditional risk communication is currently unsuccessful. Our findings also shed light on the priorities associated with urban flood risk communication. Only by linking flood risk management to actual livelihoods can we ensure the smooth execution of relevant disaster mitigation measures, especially for vulnerable groups. [ABSTRACT FROM AUTHOR]

Increasing urbanization and climate change challenges are leading to relevant environmental, economic and social pressures on European cities. These include increasing flood hazards and the urban heat island (UHI) effect. Nature-Based Solutions (NBS) are increasingly recognized within strategies to provide multiple ecosystem services to mitigate existing risks and pressures, as well as to make cities more resilient and livable. Although being increasingly addressed within the literature, NBS implementation on the ground still faces many technical and financial barriers. This paper aims to test the potential of selected NBS in mitigating the effects of identified climate change risks, i.e., the UHI effect and urban floods, in the Turin urban area (north-western Italy). Four different intervention NBS-based scenarios are developed. The supply of ecosystem services by NBS in each scenario is assessed using InVEST models and the effectiveness of NBS investments is analyzed by calculating and comparing the associated costs and benefits. Different results in terms of effectiveness and economic viability are observed for each scenario and each NBS. Flood risk mitigation oriented NBS seem to have the most impact, in particular forested green areas and retention ponds. The results are relevant to suggest policy mix strategies to embed NBS in city planning. [ABSTRACT FROM AUTHOR]

Modern societies face various challenges, including climate change, rapid urbanization, and sometimes inadequate urban planning policies. In recent years, extreme weather events have received increasing attention for their impacts on cities, humans, and ecosystems worldwide, particularly on coastal towns in Mozambique, such as cyclones, floods, water pollution, and water scarcity, demonstrating their vulnerability to climate change. Cities must adapt to cope with the pressure on their water resources, and it is essential to ensure that communities have access to safe, reliable, and affordable water. A viable way to promote this resilience and simultaneously reduce costs in domestic budgets is to use rainwater to meet daily needs where water quality parameters are not required for consumption. According to the results of this study, it is possible to significantly reduce potable water use from the municipal water supply network by harvesting rainwater, up to 40% when the use does not require potable water at all, proactively protecting this vital resource. In addition to these direct benefits, the large-scale deployment of rainwater harvesting (RWH) systems in densely urbanized areas can also provide indirect benefits, such as reducing peak flow volumes in stormwater drainage systems and potentially reducing the frequency of urban floods. These benefits result from the reduction in the volume and duration of water sent to the drainage network, which can help to improve the overall resilience of communities in the face of climate change and other challenges. [ABSTRACT FROM AUTHOR]

Climate change is impacting the ecological, social and technological aspects of urban gardens. Gardens experience threats (e.g., water scarcity) but are also responding through adaptation strategies (e.g., selecting drought-resilient plants). A synthetic overview of how urban gardens are affected by climate change and responding to climate change is unclear. Here, we systematically reviewed articles and book chapters published in the last two decades (2000–2022) to illustrate the relationship between climate change and urban gardening. From 72 documents analyzed with Nvivo Software, we found that there has been an increase in academic publications. Universities from the US (14) and Germany (9) universities are the dominant producers. Evidence shows that climate change can have negative impacts on cities, people and urban food. Suggestions on how to build the adaptation capacity of urban gardens include collecting rainwater, changing plant selection, changing planting times, applying vegetative cover on the soil and other practices. For cities, community and allotment gardens are helpful for adaptation, mitigation and resilience. This includes the capacity to regulate the microclimate, to reduce urban heat island effects and to buffer urban floods, the power to capture carbon, the ability to create social networks and other socio-environmental benefits for urban climate planning. [ABSTRACT FROM AUTHOR]

Reliable time-efficient prediction of urban floods is one of the essential tasks for planning of disaster prevention and mitigation measures. A key challenge of urban flood models is to obtain reliable input data. While geometric data can be directly measured, some other data, such as roughness and head loss of each flow system, are not easy to measure. This study proposes a novel approach for the auto-tuning of these unmeasurable data based on Particle Swarm Optimization (PSO). In this paper, we first performed a sensitivity analysis of the present urban flood model to find important parameters, which dominantly determine the predictive skills of the present urban flood model. We then developed a PSO-based auto-tuning system for estimation of these parameters. The entire computation domain was evenly split into square segments, and optimum values of these parameters were determined in each segment. The capability of this method was confirmed by comparisons of Nash–Sutcliffe efficiency, normalized root-mean square error, Kling–Gupta efficiency, and Akaike Information Criteria. As a result, it was found that important parameters for the present urban flood model were Manning's roughness of the pipeline and a coefficient for determination of the discharge from the ground surface to sewer pipelines. It was also found that the present PSO-based auto-tuning system showed reasonably good performance in tuning these parameters, which clearly improve the predictive skills of the present urban flood model. [ABSTRACT FROM AUTHOR]

Urban rainstorm drainage systems are used to collect the surface runoff from streets and other land surfaces through grate or curb openings that convey it to the drains. The quantity of surface runoff that is not discharged to the urban rainstorm drainage systems due to inadequate grate size or because the grate capacity is exceeded can cause flooding, immoderate hazards to drivers and pedestrians, and disrupt urban activities. This study aims to carry out experimental work to investigate the hydraulic efficiency of urban rainstorm drainage systems using different types of grates (shape and size of inlet area) for harvesting excess rainwater. Different grate shapes (five) with different inlet areas were investigated, as well as using three relative grate inlet areas (26%, 51%, and 64%). The results of the experimental work indicated that the best grate shape is the grate type 4 which provided the smallest reduction in discharge efficiency within 8.7%. The results specified that changing the size of the inlet area of grates from (26%) to (64%) has a significant impact on urban rainstorm drainage systems efficiency which decreased by 4%. In addition, the dimensional analysis principle with multi regression analysis were used to develop an empirical equation to compute the efficiency of urban rainstorm drainage systems. The relation between grate shapes and the relative inlet area with the efficiency of grate capture provides an indication to the decisionmakers to increase the time period for maintenance which will save the cost for further maintenance. The presented empirical equation can help decisionmakers for monitoring the current situation of grate blockage (relative grate inlet areas) and the corresponding efficiency. This study is beneficial for future road drainage system construction to avoid problems by assessing the performances of the current drainage systems and proposing mitigation measures to avoid improper functioning. Finally, this methodology can help to improve the efficiency of urban rainstorm drainage systems that can reduce the risks of urban floods. [ABSTRACT FROM AUTHOR]

Urbanisation and ever-intensified rainstorms exacerbated urban waterlogging in some Chinese cities. In 2013, the Chinese government proposed a nationwide initiative, Sponge City, for managing the flood risk using the nature-based solution (NBS) approach. Pilot projects have been implemented among thirty selected cities, including Wuhan. Because the effectiveness of implementing NBS relies on the participation of the well-informed public, this study aims at identifying the factors affecting the awareness of the public about the Sponge City program. The viewpoint of people in Wuhan on urban floods and the Sponge City initiatives was surveyed among 1600 participants using a face-to-face questionnaire in mostly Wuchang area of Wuhan; more than 900 of them were further interviewed. The majority of participants, though recognising the threats from flooding, were lacking awareness and understanding of the Sponge City initiatives. The Chi-square analyses of association revealed that the level of awareness is affected by education, age and residential time; these demographic factors also affected their interpretation of the direct experiences of the water environment and governmental water management. To optimise communicating the relevant policy to the public, the content and the advertising tools for promoting Sponge City may need to be mindfully customised for targeted demographic groups. [ABSTRACT FROM AUTHOR]

The Tulcea municipality is frequently exposed to rainfall-generated floods, with its lower downtown area (located in the Danube' former meadow, now protected by dikes) being flooded two to three times per year. In this study, our objective was to understand the generation mechanism of these rainfall-triggered urban floods and to identify tailored mitigation options. Due to the lack of reliable information on the sewage network (diameters, slope, material) and the uncertain sewage outflows during heavy rain events, a rather simplified approach was preferred by the authors of this paper. The data processing was performed using GIS tools, with appropriate accounting of the digital terrain modelling, ortho-photos, administrative boundaries of the Tulcea municipality, delineation of the urban catchments, imagery of the frequently flooded areas, and the urban sewage network. Subsequently, a fast hydrological modelling and a volume-based flooding approach were developed in order to identify and evaluate the flooded urban areas under extreme rainfall events. Upon the completion of the calibration and validation processes, numerical simulations were run that considered the design storms of different return periods. Due to the high slopes of the hills, hence the short concentration time of the pluvial waters, a Sponge City approach does not seem as though it would be easy to implement. A more efficient solution utilising large-capacity buried urban retention tanks in the lower part of the municipality was alternatively identified. Further on, this solution will be supported by a set of green measures. [ABSTRACT FROM AUTHOR]

Increased impervious surfaces due to urbanization have reduced evaporation and infiltration into the soil compared with existing natural water cycle systems, which causes various problems, such as urban floods, landslides, and deterioration of water quality. To effectively solve the urban water cycle issue, green infrastructure using urban green space has emerged to reduce runoff and increase evaporation. It has the advantage of restoring the water cycle system of urban areas by complementing the failure of conventional stormwater treatment systems. However, urban areas under high-density development have limited green space for stormwater treatment. Hence, it is necessary to efficiently utilize street trees and small green spaces to improve the urban water cycle through green space. In this study, we simulated different green space distribution scenarios in the virtual domain to find the optimal strategy of green space planning. Compared to clustered scenarios, dispersed green space distribution scenarios and placing green space downstream were more effective in reducing the runoff amount. The paper provides insights into the considerations for determining green space spatial plan and zoning regulations for stormwater treatment by green infrastructure. [ABSTRACT FROM AUTHOR]

Urban floods have adverse effects on the population and the economy, and they are increasing in frequency and magnitude. The State of Veracruz is the region of Mexico with the highest number of disasters, more than 50% of the total number nationwide, in the 1970–2015 period. During the 1990s, disasters in this region increased from 5 to 10 events per year, mostly in relation to intense rains and floods. This study analyzes the factors that increase the risk of urban floods in the regions: (i) the Pánuco River, (ii) the Papaloapan River, and (iii) the Coatzacoalcos River regions, combining hazard data and estimates of vulnerability factors. The 95th percentile of daily precipitation (P95) is used as a threshold of heavy rain, i.e., the natural hazard. Vulnerability is estimated in terms of the percentage of natural vegetation loss due to changes in land cover and land use in the hydrological basins and the expansion of the urban areas in the regions under study. The risk of flood was compared with records of flood events focusing on the low-frequency variations of risks and disaster activity. The trends in urban flood activity are related to the loss of natural vegetation and deterioration of the basins leading to a loss of infiltration, i.e., larger runoffs. Even when the intensity of precipitation in recent decades remains without clear trends, or shows negative tendencies in the number of intense events, the number of floods is higher mostly because of the deterioration of hydrologic basins. Therefore, the risk of flooding in the state of Veracruz is mainly related to environmental factors that result in vulnerability rather than changes in the trends of extreme precipitation activity. This result means that disaster risk reduction actions should be mainly related to rehabilitation of the basins. [ABSTRACT FROM AUTHOR]