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The sudden and unpredictable breach of landslide dams in the Yarlung Tsangpo river basin usually causes megafloods, posing great risks to human lives and infrastructures in the downstream areas. This study proposed an efficient and quantitative risk assessment framework of breach floods caused by landslide dam failures in the mainstream and tributaries of the Yarlung Tsangpo river basin with limited data. The impact of dam breach floods on human risks was evaluated. The flood attenuation along rivers, strategies for mitigating overlapping floods, and sensitivity analysis of human risks were also discussed. The results show that the developed framework successfully assessed flood risks caused by the breach of landslide dams. The flood attenuation ratio increased with river length but decreased with the peak discharge at dam site. A higher peak discharge and a larger inundated area downstream were predicted when the breach floods of two landslide dams, one in mainstream and the other in a tributary, overlapped at the confluence. The overlapping flood could be mitigated by reducing peak discharges of the two landslide dams or increasing time interval between the two peaks. The simulations also outlined the downstream peak discharge resulting from the cascading breach was larger than that of a single dam. However, it was smaller than the combined peak discharges of two separate dams, because the erosion during the breach of the downstream dam incurred energy dissipation. The human risks in the Pasighat village were greater when overlapping flood occurred due to the increased water depth and more hazardous inundated buildings. In the case of multi-peak floods, the warnings for the former peak flood would also warn the peak flood thereafter when individuals were notified multiple peaks. Otherwise, individuals might be misled by the warning of the previous peak flood, resulting in catastrophic flood impacts. A parametric analysis indicated that early evacuation warnings were needed to avoid serious loss of life and flood damages, especially in cases of dam breaches occurring at nighttime or for areas in close proximity to the dam site. [ABSTRACT FROM AUTHOR]

This paper explores Hull's histories of living with water and flood in the period between the foundation of the town in the 1260s and c. 1700, examining how the inhabitants, Corporation and Commissioners of Sewers managed and governed water in order to survive and thrive in a risky yet resilient estuarine environment. It does that as part of a bigger project utilising 'learning histories' drawing on Hull's 800-year experience of living with water and flood to drive climate awareness and flood resilience in a city which has experienced major flooding in recent years and is increasingly vulnerable in the face of future climate change. Here, we use civic and other records to reconstruct a flood timeline for medieval and early modern Kingston-Upon-Hull, revealing a history of repeated flood events impacting the town and surrounding area in the centuries after its foundation in c. 1260. We explore who managed and governed water and flood risk, and how this was achieved, arguing that water management was a pervasive concern as well as a collective and shared responsibility which ultimately generated a 'living with water mentality'. [ABSTRACT FROM AUTHOR]

The Ganges-Brahmaputra Delta (GBD) in Bangladesh exists at a nexus of stability and vulnerability, as the rivers annually carry ~ 800–1000 MT of sediment from the Himalayan Mountains, yet coastal poldering and sediment extraction within the rivers remove elevation capital from the low-lying delta plain. Recent research in the GBD has begun to unravel how the world's largest fluvio-deltaic mangrove forest—the Sundarbans—is keeping pace with sea level rise (SLR); however, this is contingent on adequate sediment supply delivered to the platform during semi-diurnal tides and the seasonal monsoon. Little is known about the elevation dynamics within human-modified polders by comparison, other than an elevation deficit of 1–1.5 m exists. In this study, seasonal data from Rod Surface Elevation Tables (RSETs) installed within a polder in the southwest region (Polder 32) are compared to the Sundarbans. Over ~ 8 years, results show that surface elevation is gaining within the Sundarbans at a more significant rate (~ 58.4%), and this is due to the higher vertical accretion rates measured in the Sundarbans (~ 67%) from abundant sources of allochthonous material. Elevation gain in the polder, particularly close to the embankment, appears to be attributed to sediment supplied from eroded embankments and local sluice gates, in addition to seasonal subsurface clay swelling during the monsoon. Shallow subsidence within both study areas appears to take place seasonally, but with less delivery of new sediment, the rate of shallow subsidence is lower in the polder compared to the Sundarbans. Despite seasonal shallow subsidence, the elevation change is net positive in both study areas if taken as a whole; however, interior poldered regions exhibit net elevation loss. This comparison in change of elevation, vertical accretion, and shallow subsidence shows how human modification has drastically changed the natural processes. Furthermore, our results are compared to rates of relative and effective SLR, which show that the Sundarbans is keeping pace in this region, while Polder 32 is not. These results are vital to inform embankment mitigation and flood risk in this dynamic delta system. [ABSTRACT FROM AUTHOR]

Flood events continue to disproportionately impact low-income and minority groups in Jefferson County, especially in the highly urbanized regions and other areas undergoing major land-use modifications. This paper analyzes the socio-demographic factors, such as race and income, which define the spatial distribution and vulnerability of the population residing in high flood-risk zones. 2D deterministic flood model and risk maps were developed for Jefferson County using HEC RAS and ArcGIS software, and the socio-demographic data were analyzed using JMP software. Correlation and regression data analysis show flash flooding impacts affluent and low-income neighborhoods. However, approximately 73% of the census tracts impacted by flooding are predominantly African American neighborhoods (85% and higher). A statistically significant positive correlation exists between the median household income (MHI) and the average elevation (AE). The White neighborhoods have a strong positive correlation with the AE and MHI correlation with AE and MHI. The median value of owned property units strongly correlates with MHI in the high flood-risk zones. At the same time, the median value of owned property units is moderately correlated with the AE levels in the high flood-risk zones. The correlation between AE and MHI for the median value of owner-occupied units shows an increasing trend with increasing property value. Similarly, higher educational attainment levels show a growing trend in income and AE, especially with those having a bachelor's degree or higher education showing a positive association. Thus, recognizing these differences in the socio-demographic factors and their impact on perceived vulnerability can help address the disproportionate impact of flooding on the identified vulnerable groups and raise public awareness. [ABSTRACT FROM AUTHOR]

The rapid expansion of China's Urban Metro System (UMS) corresponds with the burgeoning growth of urban areas driven by the country's swift urbanization. In the context of escalating extreme rainstorm events linked to global climate change, the UMS confront a growing risk of flood inundation. Using the central urban area of Tianjin as an example, the Infoworks ICM hydrological model was utilized to simulate inundation extents and depths in the study area for four selected rainstorm return periods. Furthermore, the vulnerability of the metro stations was assessed by utilizing analytical hierarchy process-technique for order preference by similarity to ideal solution (AHP-Topsis) and constructing a multi-indicator system. The study employed the H-E-V risk assessment framework for the quantification of rainstorm flood risk. The findings reveal noteworthy insights. (1) The variations in the metro operating periods can significantly impact the rainstorm flood risk of the UMS, and the number of higher and highest risk metro stations is greater during rush hours than during offpeak hours. (2) The installation of exit steps emerges as a feasible measure to mitigate the potential impact of rainstorm floods on the UMS. (3) In addition to being in the central area of the case zone, highest risk metro stations are also distributed around the periphery of the study area. [ABSTRACT FROM AUTHOR]

The natural environment and infrastructure are severely damaged by floods, which are becoming frequent occurrences. It may not be able to stop floods given the impending climate change and variability of the weather. Yet mapping flood risk can help with both mitigation and prevention of flooding. The Shah Alam experiences flash floods yearly, which is why it was chosen. An interactive approach to decision-making under multi-criteria decision analysis (MCDA), the analytical hierarchy process (AHP), is used. The flood risk zone is divided into five categories very low-risk (32.38%), low-risk (22.25%), moderate-risk (23.17%), high-risk (18.87%), and very high-risk (3.33%) respectively. Based on the data gathered for this study, the economic losses are identified, low-risk areas (RM 2091), moderate-risk areas (RM 2343), and high-risk areas (RM 2728). The historical flood events occur in the Seksyen 36, 18, 17, and most of the southern part of Shah Alam, Malaysia. Rainfall and the Klang River have the biggest effects on these regions, with water drainage systems being critical in the Shah Alam area to reduce the risk of floods. When analysing flood risks in the Shah Alam region and throughout the nation, important stakeholders both state and non-state actors can benefit greatly from the flood susceptibility map provided by this study. [ABSTRACT FROM AUTHOR]

This study explores the main elements causing flooding in Pakistan's Swabi area and finds that elevation, slope, precipitation, and vicinity of rivers all play a major role in flooding occurrences. Low‐lying areas, steeper slopes, intense monsoon rainfall, and proximity to rivers increase vulnerability to floods. Additional factors such as curvature, normalized difference vegetation index (NDVI), topographic wetness index (TWI), land use and land cover (LULC), and soil type exhibit comparatively less impact on flooding. The evaluation of flood risk incorporates nine factors through the AHP procedure, assigning weights that emphasize the importance of rainfall, slope, elevation, and distance to rivers using GIS software. The resulting flood hazard map categorizes the region into high‐, moderate‐, low‐, and very low‐risk zones, with approximately 49.42% identified as high flood risk areas. Evacuation planning designates secure zones, moderate‐risk areas, and high‐risk zones, emphasizing the need for flexible and adaptable routes in response to evolving flood scenarios. The study's comprehensive approach, integrating GIS and AHP, provides valuable insights for effective flood management in the Swabi district, despite limitations related to data quality. The findings contribute to resolving flooding issues and offer a foundation for coordinated actions by authorities and communities in flood‐prone areas. [ABSTRACT FROM AUTHOR]

In recent years, Ghana, particularly the inhabitants of the Upper East Region, has experienced profound impact of flooding, largely attributable to the complex interplay of climatic factors. This research embarks on a comprehensive assessment of flood risk zones nestled within the White Volta Basin, situated in the Upper East Region. The study employs advanced cartographic methodologies and uses Geographic Information Systems (GIS) in conjunction with the Analytical Hierarchy Process (AHP) to systematically categorize areas susceptible to inundation. Leveraging geospatial datasets acquired from satellites such as Landsat and Sentinel. Topographic, slope, and Land Use/Land Cover (LULC) maps have been constructed. The empirical findings underscore the susceptibility of specific regions, including the Talensi District, territories within Bawku West, and some segments of the Bolgatanga Municipal area, to escalated flood risk. Additionally, the research underscores the high vulnerability of communities such as Nunku, Tolla, Zaare, Pwalugu, Balungu, Winkongo, Biung, and Tongo to the negative impact of inundation. Significantly, the study unveils a pivotal factor in the perpetuation of flood devastation—namely, the role of water discharge. This intrinsic linkage between discharge rates and flood occurrences underscores the pressing need to address this critical component in mitigation strategies to reduce adverse impacts on the basin's resident communities. The insights derived from the study offer some level of hope for residents, providing essential knowledge concerning flood-prone areas and optimal timing for agricultural activities to safeguard their cherished livelihoods. [ABSTRACT FROM AUTHOR]

Floods are the most common and costly disasters worldwide, while spatial flood risk assessment is still challenging due to fewer observations and method limitations. In this study, the flood risk zonation in the Nile districts of the Damietta branch, Egypt, is delineated and assessed by integrating remote sensing with a geographic information system, and an analytical hierarchy process (AHP). Twelve thematic layers (elevation, slope, normalized difference vegetation index, topographic wetness index, modified normalized difference water index, topographic positioning index, stream power index, modified Fournier index, drainage density, distance to the river, sediment transport index, and lithology) are used for producing flood susceptibility zonation (FSZ) and six parameters (total population, distance to hospital, land use/land cover, population density, road density, and distance to road) are utilized for producing flood vulnerability zonation. Multicollinearity analysis is applied to identify highly correlated independent variables. Sensitivity studies have been used to assess the effectiveness of the AHP model. The results indicate that the high and very high flood risk classes cover 21.40% and 8.26% of the area, respectively. In 14.07%, 27.01%, and 29.26% of the research area, respectively, flood risk zones classified as very low, low, and moderate are found. Finally, FSZ is validated using the receiver operating characteristics curve and area under curve (AUC) analysis. A higher AUC value (0.741) in the validation findings demonstrated the validity of this AHP approach. The results of this study will help planners, hydrologists, and managers of water resources manage areas that are susceptible to flooding and reduce potential harm. [ABSTRACT FROM AUTHOR]

China's global infrastructure financing flagship, the Belt and Road Initiative (BRI) encompasses countries hosting over 60% of the global population and one-third of worldwide GDP. It is based mainly on long-term loans that will mature decades into the future, and timely repayments are only possible if they remain commercially viable. But despite its vast global scope, little is known about the climate risks that could imperil the operations of BRI projects over the next few decades, and, consequently, threaten their long-term sustainability. We narrow this gap by estimating the impacts of future climate change on 217 BRI projects across 70 countries and 9 sectors in two dimensions. First, the effects of increased heat stress on human physical work capacity are calculated using the wet bulb globe temperature and an assessment of the workload for each selected BRI project. Second, the potential structural damages from more frequent flooding incidents are measured by return period (RP), where a shorter RP signals heightened risk. Both have direct impacts on human productivity and infrastructural integrity, which are essential to maintaining the operational viability and financial stability of BRI projects. We compared projected changes on both measures for the mid- and late-twentieth centuries (2041–2060 and 2081–2100) to the historical baseline (1981–2010). We found that BRI projects face escalating vulnerability to climatic risks on both counts. The results underscore a broad variance across different future carbon emission scenarios measured under the Shared Socioeconomic Pathways (including SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). BRI's aggregated climatic risks are substantially elevated under a high carbon emission scenario compared to a low emission scenario. By the end of the twentieth century, labor workability under SSP3-7.0 (31%) could potentially decrease three times more compared to SSP1-2.6 (10%). Under an intermediate-emission scenario (SSP2-4.5), floods with a historical return period of 10 years could have a return period of 5 years in the future. Significantly hampering the utilization and economic return generation potential of infrastructure projects. In addition, regional geography contributes to risk heterogeneity, with 100-year floods occurring every 15 years in South Asia and every 24 years in Sub-Saharan Africa. Such climate risk implications, potentially overlooked by development financiers, represent significant risks to the sustenance of the BRI, estimated to be worth $1 trillion. [ABSTRACT FROM AUTHOR]

Floods are the most common and costly disasters worldwide, while spatial flood risk assessment is still challenging due to fewer observations and method limitations. In this study, the flood risk zonation in the Nile districts of the Damietta branch, Egypt, is delineated and assessed by integrating remote sensing with a geographic information system, and an analytical hierarchy process (AHP). Twelve thematic layers (elevation, slope, normalized difference vegetation index, topographic wetness index, modified normalized difference water index, topographic positioning index, stream power index, modified Fournier index, drainage density, distance to the river, sediment transport index, and lithology) are used for producing flood susceptibility zonation (FSZ) and six parameters (total population, distance to hospital, land use/land cover, population density, road density, and distance to road) are utilized for producing flood vulnerability zonation. Multicollinearity analysis is applied to identify highly correlated independent variables. Sensitivity studies have been used to assess the effectiveness of the AHP model. The results indicate that the high and very high flood risk classes cover 21.40% and 8.26% of the area, respectively. In 14.07%, 27.01%, and 29.26% of the research area, respectively, flood risk zones classified as very low, low, and moderate are found. Finally, FSZ is validated using the receiver operating characteristics curve and area under curve (AUC) analysis. A higher AUC value (0.741) in the validation findings demonstrated the validity of this AHP approach. The results of this study will help planners, hydrologists, and managers of water resources manage areas that are susceptible to flooding and reduce potential harm. [ABSTRACT FROM AUTHOR]

Societal risks from flooding are evident at a range of spatial scales and climate change will exacerbate these risks in the future. Assessing flood risks across broad geographical regions is a challenge, and often done using streamflow time-series records or hydrologic models. In this study, we used a national-scale hydrological model to identify, assess, and map 16 different streamflow metrics that could be used to describe flood risks across 34,987 HUC12 subwatersheds within the Mississippi-Atchafalaya River Basin (MARB). A clear spatial difference was observed among two different classes of metrics. Watersheds in the eastern half of the MARB exhibited higher overall flows as characterized by the mean, median, and maximum daily values, whereas western MARB watersheds were associated with flood indicative of high extreme flows such as skewness, standardized streamflow index and top days. Total agricultural and building losses within HUC12 watersheds were related to flood metrics and those focused on higher overall flows were more correlated to expected annual losses (EAL) than extreme value metrics. Results from this study are useful for identifying continental scale patterns of flood risks within the MARB and should be considered a launching point from which to improve the connections between watershed scale risks and the potential use of natural infrastructure practices to reduce these risks. [ABSTRACT FROM AUTHOR]

This study evaluates flood susceptibility and risk on Bulk Supply Points in the Greater Accra region (GAR) using a Frequency Ratio model based on 15 flood conditioning factors. The model explores the influence of natural, meteorological and anthropogenic factors on flooding occurrences under the Shared Socioeconomic Pathway (SSP) scenarios and assesses flood risks at Bulk Supply Points (BSPs). Flood susceptibility mapping was conducted for both current and future periods under various SSP scenarios. Results reveal that elevation, slope, soil type, distance from urban areas, and SPI are the most influential factors contributing to flooding susceptibility in the region. The current flood map, about 37% of the total area of GAR categorized under the moderate flood-susceptible zone category followed by about 30% categorized under the low flood-vulnerable zone. However, about 16% was categorized under the very high flood-vulnerable zone. The study projects increasing flood susceptibility under the SSP scenarios with intensification under SSP2 and SSP3 scenarios. For instance, the areas categorized as high and very high flood susceptibility zones are projected to expand to approximately 32% and 26% each by 2055 under SSP3. The study also assesses flood risks at Bulk Supply Points (BSPs), highlighting the escalating susceptibility of power assets to flooding under different scenarios. For instance, in the very high scenario, flooding is estimated to reach 640 h in 2045 and exceed 800 h in 2055—more than double the 2020 baseline. The analysis shows the bulk supply points face increasing flood susceptibility, with risks escalating most sharply under the severe climate change SSP3 and SSP5 scenarios. Over 75% of BSPs are expected to fall in the low- to medium-risk categories across SSPs while more than 50% of BSPs are within medium- to high-risk categories in all scenarios except SSP1, reflecting the impact of climate change. SSP3 and SSP5 stand out with over 60% of BSPs facing high or very high flooding risks by 2055. It indicates moderate resilience with proper adaptation but highlights potential disruptions in critical infrastructure, such as BSPs, during persistent flooding. The findings of the study are expected to inform Ghana's contributions towards addressing Sustainable Development Goals (SDGs) 7, 11 and 13 in Ghana. [ABSTRACT FROM AUTHOR]

Runoff from glaciated catchments is an integrated process that includes glacier melt, snowmelt, rainfall and surface and subsurface runoff of meltwater from glacierized and non-glacierized areas. Monitoring and quantifying the contribution of the hydrologic components (snow, ice and rain) to river discharge in the Himalayan basins is essential for decision-making in the water sector, particularly in water resources management and flood risk reduction in the region. An attempt has been made to characterize and hydrologically model streamflow (Bhagirathi River) for the Gangotri Glacier (Central Himalaya, India). A semi-distributed conceptual hydrological model is used for the streamflow modelling and assessing the major streamflow components (snow melt, glacier melt and rainfall runoff). Initially, the model was calibrated using the available in situ hydro-meteorological records for the ablation seasons of 2013–14 to 2015–16 (3 years), and further validated for the ablation seasons of 2016–17 to 2018–19 (3 years). The model performed well for all the studied years except for some months, where abrupt changes in the contrasting weather parameters (precipitation and temperature) were recorded. In the Gangotri Glacier Valley (upper Bhagirathi River catchment), snowmelt contributed the largest portion (55.5%) to total streamflow followed by glacier melt (29.7%) and rainfall runoff components (14.7%). [ABSTRACT FROM AUTHOR]

Flood forecasting is crucial for flood prevention and mitigation in both watersheds and urban areas. In watersheds, the development of flood forecasting methods is relatively mature, while their application in urban areas is still in the research and exploration stage. In practice, high-precision hydrological and hydrodynamic modeling during large floods is constrained to varying degrees by power, timeliness, and transmission conditions, whereas the unit hydrograph method is simple, efficient, has fewer constraints, and plays an important role. To address the current situation, this study introduces an improved synthetic unit hydrograph method to evaluate its practical effectiveness in watershed and urban flood forecasting. Firstly, based on the Snyder's synthetic unit hydrograph method, the flooding process in Muyangxi watershed in Fujian Province was calculated and compared with the results of the Xin'anjiang model and the measured data; secondly, based on the Snyder's synthetic unit hydrograph method, the urban synthetic unit hydrograph was established by taking into account the impermeability of the sub-surface and the slope, which was then applied to the calculation of the flooding process line in the urban area of Zhengzhou, and the differences of the simulation results between this method and the mainstream SWMM model were compared. The differences between this method and the mainstream SWMM model simulation results are compared. The results show that the synthetic unit hydrograph method is close to the measured and hydrological model results in the selected watersheds, and the forecast pass rate is 91.7%, with no peak-present time difference; compared with the SWMM model results, the relative error of the peak flow of the most floods is within 10%, and the coefficient of certainty of the floods in 72.7% is above 0.9. The example application shows that compared with the hydrological and hydrodynamic modeling methods, the partial rise and fall process of the flood calculated by the synthetic unit hydrograph method is better than the model results, which are more in line with the actual process, and its calculation is concise. The synthetic unit hydrograph method requires fewer parameters, and has strong implementation and popularity. The research further verifies the superiority of the synthetic unit hydrograph method in flood forecasting and provides an effective method for flood process calculation. [ABSTRACT FROM AUTHOR]

Hydrological model is an important tool for flood simulation, and most of the models contain a certain number of parameters. There? fore, parameter calibration is one of the keys to improve the precision of hydrological model runoff simulation and ensure the accuracy of mod? el results. As the optimization standard of parameter calibration process, there is currently no detailed classification system to provide a clear selection basis for the selection of objective function. In order to explore the effects of different types of objective functions on the calibration results of hydrological model parameters and the precision of runoff simulation, this paper comprehensively considered various types of objectives, such as Nash efficiency coefficient, Kling-Gupta coefficient, flood relative error, etc., and constructed an objective function classification system that includes high flow target, low flow target, flood volume target, flood process target and weighted target. According to the requirements of the current hydrological forecast information standard, some criteria were provided for the selection of objective function. Further, the Xinanjiang model was established, and the optimization algorithms of SCE-UA and NSGA-II were introduced. A variety of objective function selection schemes were set up for different algorithms, and the influence of different objective function schemes and optimization algorithms on the precision of runoff simulation was analyzed by taking Muma River in Hanjiang River basin as an example. The results show that using a single objective function can improve the simulation accuracy of hydrological elements embodied by the objective function; Selecting the appropriate objective function is the key to improve the precision of runoff simulation. Under the requirements of existing norms, selecting flood process target and high flow target is the best choice to ensure the accuracy of hydrological model. Compared with Nash efficiency coefficient, Kling Gupta coefficient has better performance in flood volume simulation accuracy and is a better choice for flood process target. The simulation results of weighted single target method and multi-target method are different in the high-flow part. [ABSTRACT FROM AUTHOR]

Flood early warning requires rainfall data with a high temporal and spatial resolution for flood risk analysis to simulate flood dynamics in all small and large basins. However, such high-quality data are still very scarce in many developing countries. In this research, in order to identify the best and most up-to-date rainfall estimation tools for early flood forecasting in arid and semi-arid regions, the northeastern region of Iran with 17 meteorological stations and four rainfall events was investigated. The rainfall products of satellites (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record, Global Satellite Mapping of Precipitation, Climate Hazards Group InfraRed Precipitation with Station, European Reanalysis (ERA5), Global Precipitation Measurement) along with the most widely used microphysical schemes of Weather Research and Forecasting (WRF) model (Purdue-Lin (Lin), WRF Single-Moment class 3, 6, and WRF Double-Moment class 6. were used for rainfall modeling. The efficiency of each of these models to forecasting the amount of rainfall was verified by four methods: Threat Scores (TS), False Alarm Ratio, Hit Rate (H), and False Alarm (F). Analysis of research findings showed that the WRF meteorological model has better accuracy in rainfall modeling for the next 24 h. In this model, Lin's microphysical scheme has the highest accuracy, and its threat score (TS) quantity is up to 98% efficient in some stations. The best accuracy of satellite products for estimating the amount of rainfall is up to 50%. This accuracy value is related to the satellite product (ERA5). In this method, an 18 km distance from the ground station is the best distance for setting up the space station, which is used for input to hydrological/hydraulic models. Based on the results of this research, by using the connection of the WRF model with hydrology/hydraulic models, it is possible to predict and simulate rainfall-runoff up to 72 h before its occurrence. Also, by using these space stations, the amount of rainfall is estimated for the entire area of the basin and an early flood warning is issued. [ABSTRACT FROM AUTHOR]

The Lower Teesta River basin in northern Bangladesh, which is prone to recurrent annual flooding, requires refined flood susceptibility analysis. In this context, this paper presents a novel approach for quantifying flood susceptibility in the Lower Teesta River Basin through the Analytical hierarchy process (AHP) and Multi-criteria decision analysis (MCDA) using geographic information system (GIS) and remote sensing techniques. Ten flood conditioning parameters were selected for flood susceptibility modelling, based on a comprehensive literature review and expert opinion. These parameters include the topographic wetness index (TWI), elevation, slope, rainfall, proximity to rivers and roads, soil type, drainage density, land use and land cover type, and the normalised difference vegetation index (NDVI). This comprehensive assessment resulted in the creation of an exact flood risk map that delineates areas within the basin that are prone to high or very high flood risk. The model was subjected to rigorous validation using ROC-AUC analysis, yielding an impressive AUC score of 0.848, underscoring its robust predictive capabilities. These results highlight the importance of continued monitoring and targeted flood risk reduction measures in this region, particularly in high-risk areas. Although the study was conducted on a regional scale, it has a broad readership appeal and impact that extends beyond the region. The approach employed in this study is transferable to a range of environmental settings, both within Bangladesh and globally. [ABSTRACT FROM AUTHOR]

This research focuses on improving flood management of the Malwathu Oya River in Anuradhapura Historical City, Sri Lanka, by designing an efficient gate system for the weir of Halpan Ela in the Malwathu Oya River. Frequent flooding threatens agriculture, infrastructure, and public safety in this region. This research aims to enhance water level control in the upper reach of Halpan Ela Anicut by evaluating rainfall patterns, tank spillway efficiency, and gate operation challenges. Historical data on rainfall and tank spillage were analyzed. Flow simulations revealed significant pressure differences, with the existing gate structure showing an upstream pressure of 114,492.5 Pa at a maximum flow of 1740 m3/s, compared to 105,406 Pa for the new flap gate system at the same flow rate. This represents a pressure difference of 9 kPa, equivalent to a 0.9 m water head. Despite the system's estimated cost of USD 0.1 million, the potential reduction in river flood damage, which currently exceeds USD 0.2 million annually, demonstrates its value. This research emphasizes the effectiveness of the flap gate system in reducing flood risks in Anuradhapura City compared to the existing gate type, though it is only a part of a broader flood mitigation strategy. [ABSTRACT FROM AUTHOR]

Flash floods are catastrophic phenomena that pose a serious risk to coastal infrastructures, towns, villages, and cities. This study assesses the risk of flash floods in the ungauged Mekkah province region based on specific and effective morphometric and topographic features characterizing the study region. Shuttle Radar Topography Mission (SRTM) data were employed to construct a digital elevation model (DEM) for a detailed analysis, and the geographical information systems software 10.4 (GIS) was utilized to assess the linear, area, and relief aspects of the morphometric parameters. The ArcHydro tool was used to prepare the primary parameters, including the watershed border, flow accumulation, flow direction, flow length, and stream ordering. The study region's flash flood hazard degrees were assessed using several morphometric characteristics that were measured, computed, and connected. Two different and effective methods were used to independently develop two models of flood vulnerability behaviors. The integrated method analysis revealed that most of the eastern and western parts of the studied province provide high levels of flood vulnerability. Due to it being one of the most helpful topographic indices, the integrated flood vulnerability final map was overlayed with the topographic position index (TPI). The integrated results aided in understanding the link between the general basins' morphometric characteristics and their topographical features for mapping the different flood susceptibility locations over the entire studied province. Thus, this can be applied to investigate a surface-specific reduction plan against the impacts of flood hazards in the studied landscape. [ABSTRACT FROM AUTHOR]

Human-induced climate change has led to more frequent and severe flooding around the globe. We examined the association between flood risk and the prevalence of coronary heart disease, high blood pressure, asthma, and poor mental health in the United States, while taking into account different levels of social vulnerability. We aggregated flood risk variables from First Street Foundation data by census tract and used principal component analysis to derive a set of 5 interpretable flood risk factors. The dependent variables were census-tract level disease prevalences generated by the Centers for Disease Control and Prevention. Bayesian spatial conditional autoregressive models were fit on these data to quantify the relationship between flood risk and health outcomes under different stratifications of social vulnerability. We show that 3 flood risk principal components had small but significant associations with each of the health outcomes across the different stratifications of social vulnerability. Our analysis gives, to our knowledge, the first United States–wide estimates of the associated effects of flood risk on specific health outcomes. We also show that social vulnerability is an important moderator of the relationship between flood risk and health outcomes. Our approach can be extended to other ecological studies that examine the health impacts of climate hazards. This article is part of a Special Collection on Environmental Epidemiology. [ABSTRACT FROM AUTHOR]

Purpose: The study aims to investigate the nomenclature of structural versus non-structural building adaptation measures taken by occupants of residential properties located in flood-prone areas of Port Harcourt, Nigeria, to verify whether they are adapted or maladapted relative to their level of flood exposure and underscore the role of disaster resilience in property management. Design/methodology/approach: Using the survey research strategy, the uptake of structural and non-structural adaptation measures in spatially distributed areas of Port Harcourt was descriptively analyzed and tested to identify significant variation in the uptake of adaptation measures relative to increasing flooding levels, using a one-way ANOVA. Findings: The study outcome reveals that there are some distinctive features of buildings in Port Harcourt which provide wet-proofing structural adaptation qualities while dry-proofing structural adaptation measures are not adequate. However, although some key structural adaptation measures were adapted relative to the levels of flood exposure, most structural features of the buildings do not vary relative to flooding levels, indicating maladaptation even with increasing flood risk. The uptake of non-structural measures is also inadequate and maladapted relative to changes in the level of flood exposure, despite their non-intrusive and low-cost nature. Overall, the findings imply that maladaptation is more prevalent. Originality/value: The study provides a descriptive snapshot of the nomenclature of property-level flood risk adaptation in residential buildings, while highlighting the maladaptive tendencies/behavior of property occupants, within a metropolitan setting in the developing world, necessary to inform policy and provide sensitization for fostering disaster resilience in property management. [ABSTRACT FROM AUTHOR]

The upper reaches of the Yangtze River Basin (UYRB) are famous for their hydropower generation and water resources in China, relying greatly on precipitation. The UYRB summer precipitation has decreased since the early 2000s and has been exposed to a particularly dry period in the most recent two decades. By analyzing the long‐term variability from the beginning of the 20th Century, we found that the precipitation exhibits a profound periodic interdecadal variation, with a significant cycle of 30–50 years. The interdecadal variability of precipitation is shown to be significantly modulated by both the Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO), exerting their impact through related circulation anomalies. Moreover, the periodical nature of the UYRB precipitation variation and its correlation with AMO/PDO suggest that the UYRB might enter a wet period in the forthcoming decade, i.e. rich in hydroelectric resources but a high risk of flood. [ABSTRACT FROM AUTHOR]

Sea level rise induced flooding is projected to cause significant damage to the low-lying coastal areas of many countries around the planet. Many households located in vulnerable areas have already started to adapt to flooding, although some empirical studies indicate that informal adaptation is reaching its limit and that more formal countermeasures by governments will be necessary to cope with the increased flood risks. In such cases, public support for flood adaptation policy is crucial to ensure a successful and timely adaptation, as these strategies can directly affect coastal residents. However, there is limited understanding on the mechanisms and factors that determine public support for flood adaptation policy. Thus, this study proposes a new model – the Foundation of Adaptation Policy Support (FAPS) – which integrates the Protection Motivation Theory and the Risk Information Seeking and Processing models. FAPS was tested using structural equation modelling with latent variables and data that was collected from a household questionnaire survey conducted in the Tokyo lowland areas (n = 388), with the super levee representing a policy that could be applied to sea level rise adaptation. The proposed FAPS model showed a good fit with the collected data, indicating that the strongest predictors of policy support include the perceived effectiveness of the policy and the importance of the issue of flooding to individuals. Other important predictors of policy support include knowledge about flooding, the opinions of surrounding people (i.e. family and friends), and the systematic processing by respondents of information related to floods. The FAPS model sets the foundation for understanding the mechanisms of public support for adaptation policy and provides new insights into designing and planning such policies in practice. Key policy insights Perceived policy effectiveness and the importance of addressing floods are the strongest predictors of public support for adaptation policy. Increasing people's knowledge about flooding is essential to communicate the importance of adaptation policy. Investigating people's knowledge and the perceived importance of the issue of flooding prior to designing policies can predict public preferences for certain countermeasures. [ABSTRACT FROM AUTHOR]

Climate change and mental health are inextricably linked crises that demand urgent responses within the health sector and beyond. Mental health challenges associated with climate change are wide-ranging. They include depression, anxiety and post-traumatic stress resulting from increased exposure to extreme weather events, generalized climate anxiety and indirect impacts. However, there is a significant adaptation gap when it comes to addressing the mental health risks posed by climate change. Lack of capacity is frequently cited as a barrier to adaptation, yet 'capacity' covers many facets. This article examines the capacities of policy systems to design and implement adaptation initiatives for addressing the increasing risks to mental health posed by climate change. Focusing on England (UK) as an illustrative case study, this article deploys a policy capacity framework and draws on semi-structured interviews and policy document analysis. It identifies the ways that analytical, operational and political policy (in)capacities manifest across relevant policy areas, which include health, flood and coastal erosion risk management, spatial planning, natural environment and emergency management. Our analysis reveals that despite some strengths in analytical and political capacity, strained operational capacity is exacerbating and reinforcing adaptation gaps. We also demonstrate some of the complex interactions between different types of capacities that both enable and hamper adaptation. This article demonstrates the value of analysing policy capacity, and its potential in identifying and designing the necessary interventions to help circumvent a growing mental health crisis under climate change. Key policy insights In England, efforts to adapt to risks to mental health under climate change are supported through strong analytical capacity, involving research and knowledge generation, education and training, particularly in the mental health sector and Flood and Coastal Erosion Risk Management (FCERM). There is, however, room for improvement. Relatively strong political capacity, including advocacy and the role of policy champions, have led to increasing legitimation of the issue and fostered a growing policy landscape. However, some discernible gaps remain. There are significant weaknesses in operational capacity, restricting coordinated, preventative adaptation. This is partly due to significant resource constraints, and historic and current fragmentation within and between the health sector and others. [ABSTRACT FROM AUTHOR]

Flood risk management is a critical task which necessitates flood forecasting and identifying flood source areas for implementation of prevention measures. Hydrological models, multi-criteria decision models (MCDM) and data-driven models such as the Artificial Neural Networks (ANN) have been used to identify flood source areas within a watershed. The aim of this study was to compare the results of hydrological modeling, MCDM and the ANN approaches in order to identify and prioritize flood source areas. The study results show that the classification results of the hydrological model and the ANN have a significant correlation. The correlation between the TOPSIS method with the hydrological model indicate no meaningful correlation. Since the ANN model has simulated the HEC-HMS classifications very accurately, it can be a good substitute for the hydrological models in watersheds with limited data. [ABSTRACT FROM AUTHOR]

Morphometric analysis is important for conservation and management of watersheds including flood control measures, which is in turn related to topographical components. Prioritization of sub-watersheds based on morphometric factors is carried out to understand the vulnerability of different sub-watersheds to hazards like flooding, soil erosion and groundwater storage. It is carried out in the initial phase so as to enhance the efficacy in selection of water and soil management and remedial practices. In the present study, prioritization is attempted using multi criteria approach based on VIKOR on the sub-watersheds of Mahe river basin in southwest India vis-à-vis their susceptibility to flooding. Thirteen morphometric factors pertaining to twelve sub-watersheds of the river basin are used in the present analysis and they are classified (High, Moderate and Low) based on their risk of flooding. Sub-watersheds 3–8, upstream of the Mahe were identified as being the most prone to flooding. Sub-watersheds 1 and 2, offer a moderate risk of flooding, since the advantage of prominent runoff in their upper reaches is inhibited by the laterite dominated terrain downstream. The sub-basins 9–13 in the coastal plains, forming ~ 60% of total area of Mahe basin, fall in 'Least' category. The prioritization of sub-watersheds based on Multi Criteria Decision Analysis of their morphological factors is found to be useful in the discrimination of flooding prone areas. This would help in the selection of suitable management and remedial measures for the sub-watersheds based on their hazard of flooding. [ABSTRACT FROM AUTHOR]

The potential of using nature‐based solutions to address issues of climate change has continued to gain momentum, especially in developed nations. However, the same cannot be said for developing countries, particularly in Africa, where the knowledge and awareness of natural solutions are low, and research on their application within the built environment is scant. Using a sciento‐metric and narrative review of published literature, this paper makes a case for research exploration on nature‐based solutions for a sustainable built environment in Africa. The findings revealed an opportunity for significant research contributions on nature‐based solutions in addressing flood risk management, climate change and urban planning, water quality and carbon emission, sustainable development, and green infrastructure and urban development. These areas are the critical focus of past studies explored. Also, the findings offer guidance for further studies to be conducted in less explored areas, such as carbon sequestration, greenhouse gases, energy utilisation, indoor comfort, and numeric models for using nature‐based solutions within the African context. The findings of the study offer an excellent theoretical background to direct researchers and practitioners who seek to attain and promote sustainable built environments through nature‐based solutions, especially in Africa. [ABSTRACT FROM AUTHOR]

The city of Bni drar in the NE of Morocco experienced frequent and regular share of flood events, especially at its main road where it’s commonly submerged by floodwaters during these events. Because of its crucial significance and role in the transportation infrastructure of the region, this study aims to analyze and evaluate flood hazard in Bni Drar, with a specific focus on its impact on the national road N2 as it crosses the Sefrou wadi. Rainfall-runoff transformation was conducted using HEC-HMS model, resulting in flow hydrographs for 10, 20, 50, and 100 years return period. These hydrographs constituted an input for IBER hydrodynamic model, enabling the simulation of flood depth and velocity for a return period of 100 years. Flood hazard was categorized by taking into account both flood depth and velocity. The maximum water depth in the study area is 2.7 meters for 100 years return period. Regarding flow velocity, the maximum value is 2 meters per second. The acquired hazard maps possess the capability to bolster flood risk management within the research region by furnishing a geospatial decision support instrument to empower local authorities. This enables the prompt execution of preventive measures against flood risks and fortifies the resilience of the territory. [ABSTRACT FROM AUTHOR]

Reservoirs balance multiple conflicting objectives, including flood control and water supply. In California, shifts in seasonal hydrologic patterns under climate change will amplify the difficulties in balancing flood control with water supply. Current flood control policies are based on fixed seasonal rule curves determined by the observed timing and magnitude of floods in the record. These rule curves generally require the release of wet season inflows, reducing the available stored water for use during the dry season. Here we investigate the potential for forecast-informed reservoir operations (FIRO) to increase water supply availability while minimizing additional flood risk at 14 reservoirs in the Sacramento, San Joaquin, and Tulare river basins. We use a differential evolution algorithm to train risk-based reservoir operation policies with an ensemble of historical forecasts over the period 2013–2023. Results show an average 8.1% increase in storage normalized by capacity, though this varies across reservoirs. The forecast-informed policies also reduce the occurrence of high-magnitude releases throughout the system. The accumulation of benefits is sensitive to the timing and magnitude of flood events, and most of the cumulative benefit is obtained during a few years. Under cross-validation, we find that large floods are needed in the training data to avoid overfitting the policy. We further examine the relationship between reservoir properties and FIRO benefits, finding that the ratio of peak inflow magnitude to maximum safe release correlates with increased storage under the FIRO policy, while the ratio of mean inflow to capacity correlates to the reduction of high-magnitude releases. This study highlights how adaptive reservoir management policies can yield water supply benefits without an increase in flood risk, given adequate historical data for policy training. These policies may be a valuable adaptation to climate change but require careful validation and out-of-sample testing. [ABSTRACT FROM AUTHOR]

This study focuses on the Skalička Waterwork (SWW), a largely debated and media-covered water-related/flood-protection project in the Czech Republic. Relying primarily on stakeholder interviews, we traced back and reconstructed the project's development, including its key tipping points reflecting the changing societal preferences for particular measures, yet also the involvement of individual actors/stakeholders, and their differing views. The case eventually crystallized into the "dam versus polder" dispute; concerned by the repercussions for the local landscape, a joint initiative of NGOs, local activists, and politicians not only opposed the dam variant proposed by the state river basin administration but also succeeded in pushing through the alternative scheme of side dry polder. While in many ways specific (e.g. not entailing local resistance), the case exemplifies recent shifts (and respective struggles) within flood risk management, including the increasing importance attributed to complex, catchment-wide perspectives, joint local and scientific knowledge, participatory decision-making processes, or implementation of nature-based and hybrid solutions. [ABSTRACT FROM AUTHOR]

BACKGROUND AND OBJECTIVES: Flooding is one of the biggest challenges affecting the economy and people's well-being. Various approaches have been employed in prior research to examine spatial data and enhance flood response effectiveness, such as the utilization of machine learning methodologies to aid in decision-making within the realm of urban planning. However, different machine learning models serve different purposes depending on their learning processes and computation techniques. The objective of this study is to create a machine learning algorithm that can evaluate areas prone to flooding. The study purpose is to offer valuable insights to city authorities and aid in urban planning, ultimately enhancing the safety and adaptability of the city's inhabitants METHODS: In order to evaluate flood risk areas and offer valuable insights for urban management and planning, a technique was devised. A total of eleven multiclass classification algorithms were employed to analyze eight urban factors, enabling the assessment of flood risk. The outcomes were then visualized on a map using geographic information systems. FINDINGS: The study discovered that the Bagging Decision Tree Algorithm model produced the best flood risk assessment model, with an accuracy of 88.58 percent compared to the government's flood simulation model results. Furthermore, precipitation, building coverage ratio, and floor area ratio emerged as the top three crucial factors influencing the likelihood of flooding in the city. CONCLUSION: The Bagging Decision Tree Algorithm model provides a thorough evaluation of flood risk, presenting crucial information for urban governance and development. Integrating key variables such as rainfall, building coverage ratio, and floor area ratio into flood risk management strategies is crucial for mitigating the impact of floods in economically significant urban areas. [ABSTRACT FROM AUTHOR]

The present study discusses flood hazard characteristics in the lower reaches of the West Rapti River based on the results obtained from field surveys and numerical computations using depth averaged 2-D numerical models for flood flow and associated sediment transportation. To evaluate the inundation process with sediment erosion and deposition in the floodplain, a new erosion term was introduced into the mass conservation equations for suspended sediment and bed sediment. The results obtained from numerical computations indicated that field data on the spatial distributions of depths for inundation, and sediment erosion and deposition can be evaluated by the numerical model. Thus, numerical predictions were performed for the inundated areas, and the accumulated volumes of sediment erosion/deposition for floods with return periods of 50, 100, and 200 years, as a step towards damage assessment and risk assessment due to floods with active sediment transportation in the floodplains. [ABSTRACT FROM AUTHOR]

In recent years, urban flooding has emerged as a major challenge, with land cover change identified as a key contributing factor. This study investigates the sensitivity of urban flooding risk to land cover changes. Seven urban land cover maps from different years and five different rainfall events, were selected as the examples. Based on hydrodynamic model simulations, this study analyzed the relationship between the total area of urban flooding and the proportion of ponding depths across various depth intervals and the land cover change. The study region was divided into 41 sub-areas based on road classifications and building clusters. The urban flood risk considering the aggregation of urban flooding, maximum ponding depth, the extent of the ponded area, and the average ponding depth was quantified within these sub-regions. Additionally, ten characteristic points were extracted from two sub-area with significant risk changes to analyze the logic of urban flooding risk evolution under land use change. The results indicate that: (1) There is a positive correlation between the total area of urban flooding and the proportion of high ponding depths and increasing impervious surfaces. (2) Urbanization significantly increases urban flooding risk, with 28 out of 41 areas experiencing heightened risk, including 6 sub-areas with risk increases exceeding 100%. (3) When the rainfall event changes from a 20-year to a 100-year return period, the maximum ponding depth in cropland stabilizes compared to impervious surfaces. Conversion of cropland to impervious surfaces accelerates increases in ponding depth and can lead to higher maximum ponding depths. [ABSTRACT FROM AUTHOR]

Water resources in arid and semi-arid regions are constrained by several critical problems, including scarcity of water resources and extensive use of groundwater. Climate change and population growth will certainly result in a decline in water tables and degradation of groundwater quality. The purpose of this study is to create rainwater retention ponds in the Najran Valley located at the southern border of Saudi Arabia. Over the past decade, various researchers have reported a sharp decrease in the availability of water in the area. In addition to urban sprawl, excessive groundwater extraction is the primary cause of the decrease. Even though the valley receives a sufficient amount of rainfall throughout the year, there is no adequate rainwater management system in place. As a result of this combined water management issue, the authorities are seeking additional water storage options in addition to the Najran dam reservoir. To evaluate the flood characteristics of the region, an extensive GIS-based hydrological study is conducted. To estimate flood volumes, the critical flood-prone areas are identified and their catchments are calculated. To store rainwater generated by these catchments during rainfall events, a variety of suitable locations have been proposed for retention ponds. The construction of retention ponds would have numerous environmental benefits in addition to solving the problem of water scarcity. As a result of the study, the authorities will be able to implement a management strategy that maximizes the use of the region's water resources. [ABSTRACT FROM AUTHOR]

This study proposes a multidimensional framework for the assessment of cultural heritage vulnerability to flood hazards. In this framework, cultural heritage is framed within a landscape approach drawing on the concept of the historic urban landscape as a physical entity, a lived space and a layered socio-economic environment. In such manner, this study emphasises that climate change disturbs both tangible and intangible aspects of cultural heritage – such as social systems and daily life practices – by modifying the material conditions that sustain them. Thus, the proposed framework integrates built and natural heritage with area-based vulnerability and socio-economic deprivation, considering households' exposure to flood risk. The analysis follows a spatial and quantitative approach using open geospatial data available at the statistical unit level. The data are processed and analysed employing QGIS software and statistical analysis. Results confirm that cultural heritage vulnerability is highly associated with socio-economic deprivation and area-based vulnerability. The understanding of this interrelation is key to the identification of historic urban landscape qualities and priority areas for reconstruction and social support. [ABSTRACT FROM AUTHOR]

The "Returning Farmland to Lakes" (RFTL) project began in China following the catastrophic 1998 floods. It aims to recover flood storage capacity and mitigate flood risk to agriculture and people. This flood adaptation strategy divides the floodplain into three types of restoration polders with different flood control levels (double restoration polders, single restoration polders, and storage polders) and polders for intensive production and living (nonrestoration polders). During the substantial flooding in the Poyang Lake Basin in 2020, the double and single restoration polders were operated for flood diversion for the first time since 1999. This event provided an opportunity to assess the effectiveness of the RFTL project. Using satellite observations of rice planting and flooding areas, we found that 86% of paddy rice areas (3,400 km²) in the basin were successfully protected due to the timely flood diversion into different levels of polders. Compared to 1998, the flooded rice areas decreased overall by 58% (18 to 92% in different types of polders). Thus, the RFTL project has enhanced regional agricultural resistance to floods. A more comprehensive assessment of the RFTL project, including other ecosystem services and functions, is necessary in the future for regional sustainable development. [ABSTRACT FROM AUTHOR]

This editorial discusses the importance of preparing communities, cities, and nations for extreme flooding events. It highlights the need to adapt infrastructure to be more resilient, while acknowledging the tradeoff between efficiency and resilience. The editorial provides examples of infrastructure failures during past flooding events and discusses the challenges of adapting critical infrastructure systems to a changing climate. The document includes articles that explore different approaches to managing flood risk, the use of satellite data for monitoring and warning systems, and the vulnerability of industrial process facilities to flood damage. The authors emphasize the need for comprehensive solutions that consider uncertainties and involve collaboration between academia and the public and private sectors. The text also mentions the challenges of developing protective infrastructures, retrofitting existing infrastructures, and considering implications throughout the lifecycle. [Extracted from the article]

Flood is one of the worst natural disasters, which causes significant damage to economy and society. Flood risk assessment helps to reduce flood damage by managing flood risk in flood affected areas. For ungauged catchments, regional flood frequency analysis (RFFA) is generally used for design flood estimation. This study develops a Convolutional Neural Network (CNN) based RFFA technique using data from 201 catchments in south-east Australia. The CNN based RFFA technique is compared with multiple linear regression (MLR), support vector machine (SVM), and decision tree (DT) based RFFA models. Based on a split-sample validation using several statistical indices such as relative error, bias and root mean squared error, it is found that the CNN model performs best for annual exceedance probabilities (AEPs) in the range of 1 in 5 to 1 in 100, with median relative error values in the range of 29–44%. The DT model shows the best performance for 1 in 2 AEP, with a median relative error of 24%. The CNN model outperforms the currently recommended RFFA technique in Australian Rainfall and Runoff (ARR) guideline. The findings of this study will assist to upgrade RFFA techniques in ARR guideline in near future. [ABSTRACT FROM AUTHOR]

Flood risk has become a serious challenge for many cities, including New York City (NYC). Evaluating urban flood adaptability evaluation is crucial for regulating storm and rain risks. In this study, we proposed an integrated framework based on the Integrated Valuation of Ecosystem Services (InVEST) model and Geographic Information System (GIS). First, the InVEST model was used to assess the water yield, soil conservation, and water quality purification in NYC. Second, the entropy weighting method was employed to determine the weights of indicators for computing the flood adaptability evaluation (FAE). Third, a spatial correlation of FAE was conducted and finally delineated the flood adaptability zones in GIS. The results show that: (1) The spatial distribution of FAE was uneven, high in the surrounding area and low in the center. (2) The Moran's I for FAE was 0.644, showing an overall positive spatial relationship of FAE. High-scoring clusters were located in the southeastern area while low-scoring clusters were in the northern, central, and southwestern areas. (3) The FAE in NYC can be divided into five categories: the lower-adapted zone (0.22–0.27), low-adapted zone (0.28–0.31), medium-adapted zone (0.32–0.36), high-adapted zone (0.37–0.43) and higher-adapted zone (0.44–0.50). These results of the study can provide evidence and recommendations for flood risk management in NYC and other cities worldwide. [ABSTRACT FROM AUTHOR]

Advances in numerical algorithms, improvement of computational power and progress in remote sensing have led to the development of global flood models (GFMs), which promise to be a useful tool for large-scale flood risk management. However, performance and reliability of GFMs, especially in data-scarce regions, is still uncertain, as they are difficult to validate. Here we aim at contributing to develop alternative, more flexible, and consistent methods for GFM validation by applying a change detection analysis on synthetic aperture radar (CD-SAR) imagery obtained from the Sentinel-1 imagery, on a cloud-based geospatial analysis platform. The study addresses two main objectives. First, to validate four widely adopted GFMs with flood maps generated through the proposed CD-SAR approach. This exercise was conducted for eight different large river basins on four continents, to account for a diverse range of hydro-climatic environments. Second, to compare CD-SAR-derived flood maps with those obtained from alternative remote sensing sources. These comparative results offer valuable insights into the reliability of CD-SAR data as a validation tool, more specifically how it stacks up against flood maps generated by other remote sensing techniques. [ABSTRACT FROM AUTHOR]

Flooding is one of the most complicated and prolific natural hazards that communities face. Added to this, more people will be affected by this hazard than any other in the future. Within recent years, there has been a notable shift in flood risk management from risk-based approaches to resilience-based. Considered a novel and necessary approach, yet no single definition of flood resilience exists. Leading to confusion surrounding the applicability of the concept. A systematic review of flood resilience definitions was hence conducted, covering a 5-year period from 2017 to 2021, resulting in 65 papers, supplemented by a narrative review (to include papers outside of the scope of the study), which added a further 11 papers. Results indicated that whilst there is no singular definition for flood resilience, there are similarities between definitions through the use of synonymous language. Whilst there is evidence of these definitions evolving over time, there is still confusion over the definition. Further research is required to further comprehend the definitions of resilience, helping to develop the use of resilience within flood sciences and corresponding flood risk management practices. [ABSTRACT FROM AUTHOR]

In the Casablanca-Mohammedia corridor (Morocco), flooding episodes have happened frequently over the past 20 years, damaging coastal settlements through overtopping and overflowing processes. In this context, a realistic assessment of the flood risk on this coastline is required. For this, the marine water level variations were computed by combining the involved variables (astronomical tide, storm surge, wave run-up, and sea level rise) during energetic events. They were compared with the seafront altitude to delineate the maximum spatial extent of flooded areas for the current and future (2100) time horizons. These variables were obtained through numerical and empirical modeling using topobathymetry, tide gauge, wind, and reanalysis data for wave and atmospheric pressure. Statistical methods were used to determine trends and distributions, including linear regression and the GEV model. Our approach was validated by comparing the estimated results of the total water level with the observations made in situ during previous events. Results show that flooding occurs mainly at high tides. The run-up is the largest contributor to total water level during energetic events (45–60% in structure defense areas against ~ 35% in natural areas). Currently, the floodable area for all of Casablanca-Mohammedia's coastline (109 km2) is estimated to be ~ 23.5 km2, of which ~ 13.9 km2 is urban. This area would grow by 10.87% and 20.9% by 2100, respectively. The most vulnerable zones are Mohammedia, Ain Sbâa, and Merzeg quarters, as well as Tamaris beaches. The touristic quarters of Ain Diab and the promenades on either side of the Hassan II Mosque are also vulnerable and can be dangerous for pedestrians. This study is crowned by the proposal of numerous necessary protection and adaptation measures, considering the specificities of the sections characterizing this coastline. [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]

Water resources management and the broad concept of Integrated Water Resources Management (IWRM) attract varied perspectives about their effectiveness and equity as they address diverse needs across sectors and contextual situations. Managers in the water sector generally support their current governance models, while anti-poverty advocates seek more equity in the distribution of resources. Another group of stakeholders claims a lack of inclusivity in decision-making, leading to inequitable outcomes due to hegemony and colonialization of the water management domain by sector experts, officials, and other actors. IWRM focuses on reforms in water governance to achieve greater participation and sharing of power by all sectors of society in decision-making. It can facilitate the involvement of all groups of stakeholders, including those who may in some cases need to engage in social action to address water issues. This paper reviews the claims about the validity of IWRM and analyzes them according to management scenarios where water is a connector among sector issues. The scenarios show that participation in utility and local government decisions is the main pathway for urban water, wastewater, and stormwater management, while the same pathway is more difficult to organize in dispersed situations for domestic supply and irrigation in rural areas, some cases of aquifer management, and management of sprawling flood risk zones. The body of knowledge about participation in water resources management is robust, but organizational and financial capacities among existing entities pose barriers. Water resources management and IWRM do involve hegemony, and the field of practice has been colonialized, but the existential issues and complexity of the decisions and systems involved challenge society to manage successfully while assuring equity and participation through governance reform. The debates over hegemony and colonialization in water management provide an opportunity to continue improving the norms of practice and water resources education. [ABSTRACT FROM AUTHOR]

Several cities are facing an increasing flood risk due to the coupled effect of climate change and urbanization. Non-structural protection strategies, such as Early Warning Systems (EWSs), have demonstrated significant potential in mitigating hydraulic risk and often become the primary option when the implementation of structural measures is impeded by the complexities of urban environments. This study presents a new EWS designed specifically for fluvial floods in the city of Palermo (Italy), which is crossed by the Oreto River. The system is based on the preliminary definition of various Flood Event Scenarios (FESs) as a function of typical precursors, such as rainfall forecasts, and antecedent wetness and river flow conditions. Antecedent conditions are derived from real-time water stage observations at an upstream river section, while rainfall forecasts are provided by the Italian National Surveillance Meteorological Bulletins with a preannouncement time of up to 36 h. An innovative feature of the system is the use of rainfall Depth–Duration Thresholds to predict the expected hydrograph peak, significantly reducing warning issuing times. A specific FES, immediately accessible from a pre-built library, can be linked to any combination of precursors. Each FES predicts the timing and location of the first points of flooding; flood-prone areas and water depths; and specific hazard maps for elements typically exposed in cities, such as people, vehicles, and buildings. The EWS has been tested on a historical flood event, demonstrating satisfactory accuracy in reproducing the location, extent, and severity of the flood. [ABSTRACT FROM AUTHOR]

Floods in Germany have become increasingly frequent and severe over recent decades, with notable events in 2002, 2013, and 2021. This study examines the trends and drivers of flood occurrences in Germany from 1990 to 2024, focusing on the influence of climate-change-related variables, such as temperature, precipitation, and river discharge. Using a comprehensive time series analysis, including Auto-Regressive Integrated Moving Average (ARIMA) and Artificial Neural Network (ANN) models and correlation and regression analyses, we identify significant correlations between these climatic variables and flood events. Our findings indicate that rising temperatures (with a mean of 8.46 °C and a maximum of 9 °C) and increased precipitation (averaging 862.26 mm annually)are strongly associated with higher river discharge (mean 214.6 m3/s) and more frequent floods (mean 197.94 events per year). The ANN model outperformed the ARIMA model in flood forecasting, showing lower error metrics (e.g., RMSE of 10.86 vs. 18.83). The analysis underscores the critical impact of climate change on flood risks, highlighting the necessity of adaptive flood-management strategies that incorporate the latest climatic and socio-economic data. This research contributes to the understanding of flood dynamics in Germany and provides valuable insights into future flood risks. Combining flood management with groundwater recharge could effectively lower flood risks and enhance water resources' mitigation and management. [ABSTRACT FROM AUTHOR]

This study conducted a comprehensive analysis of flood control and water quality simulation for the urban water system in Runan County, with the aim of evaluating the conditions of urban waterlogging and changes in water quality before and after the management of the urban water system. This provides significant scientific basis and technical support for the water system management and water environment protection in Runan County and similar urban areas. The study employed a rapid modeling technique assisted by ArcGIS and the SWMM (Storm Water Management Model) for the first time to conduct an in-depth simulation study on the regulation of floods and the improvement of water quality in the central urban area of Runan County. By simulating design rainfall scenarios of 1-h and 6-h durations for return periods of 3, 5, 10, 20, and 50 years, a detailed analysis was performed on the extent of flood inundation in the urban area of Runan County under different rainfall conditions and the flood detention capacity of the river channels. Furthermore, for rainfall scenarios of 3, 10, and 50-year return periods, a meticulous simulation analysis was conducted on the water quality response and the attenuation process of pollutant concentrations in the main river channels. The results of the study revealed the significant effects of river channel regulation on enhancing the connectivity of the water system and the capacity for flood control: the regulation of river channels significantly increased the cross-sectional area and the volume of water in the channels, leading to a reduction in pollutant concentrations along the direction of the river flow. Comparing the data before and after the management, the extent of the flood-prone area and the volume of water entering the river in the non-managed water system were 1.4 times and 59% of those after management, respectively, indicating that the comprehensive management of the water system significantly reduced the risk of waterlogging. In addition, the self-purification capacity of the river channels and the efficiency of pollutant degradation improved significantly after the management, effectively enhancing the water quality environment. [ABSTRACT FROM AUTHOR]

Efficient flood risk management hinges on the precise mapping and assessment of areas vulnerable to flooding. This research endeavors to advance the flood susceptibility mapping in Jeddah, Saudi Arabia by harnessing the long short-term memory (LSTM) algorithm enriched with two sophisticated metaheuristic optimizers: invasive weed optimization (IWO) and harmony search (HS). The process commenced with the utilization of synthetic aperture radar (SAR) imagery to construct a detailed flood inventory map. A comprehensive geodatabase encompassing various flood conditioning factors—encompassing lithology, land use, proximity to water bodies, hydrologic soil group (HSG), topographical features (such as slope, plan curvature, and aspect), and hydrological indices [including profile curvature, Topographic Wetness Index (TWI), flow accumulation, Topographic Position Index (TPI), altitude, Terrain Ruggedness Index (TRI), and Stream Power Index (SPI)] was meticulously curated. To develop the model, 70% of this dataset was employed, while the remaining 30% served to validate the predictive efficacy of the resultant flood susceptibility maps. These maps' accuracy was quantitatively gauged through the receiver operating characteristic curve and the area under the curve (AUC) statistics. Findings reveal that the integration of LSTM with IWO and HS metaheuristic algorithms significantly enhances accuracy (LSTM-IWO: AUC = 0.900; LSTM-HS: AUC = 0.876) in comparison to the standalone LSTM approach (AUC = 0.863). The implementation of these hybrid algorithms manifests as a potent and economically viable approach for detailed geospatial modeling of flood susceptibility, providing invaluable insights to bolster flood mitigation, preparedness, and emergency response strategies. [ABSTRACT FROM AUTHOR]

Achieving more sustainable adaptation to social-environmental change demands the transformation of the narratives that provide the rationale for risk governance. These narratives often reflect long-standing beliefs about social and political relationships, ascribe actions and responsibilities, and specify solutions to risk. When such solutions are implemented through material investments in landscapes, these narratives become embedded in physical infrastructure with long legacies. Dominant narratives can mask a range of divergent problem framings. By masking alternatives, narratives can contribute to the persistence of unsustainable governance trajectories. Decision-support tools have begun to represent narratives as drivers of system dynamics; making narratives visible can reveal opportunities for more sustainable governance. We present the results of the project "The Dynamics of Multi-Scalar Adaptation in the Megalopolis", a dynamic, exploratory model of socio-hydrological risks in Mexico City that was designed to both endogenize and simultaneously challenge the dominant narratives that characterize water-risk governance in the city. Qualitative data characterize dominant narratives at city and borough scales. An agent-based model, informed by multicriteria decision analysis and coupled with hydrological, urbanization, and climatic model inputs, permitted the development of exploratory governance scenarios designed to challenge dominant narratives. Scenarios revealed how dominant narratives may contribute to the persistence of vulnerability "hotspots" in the city, despite stated goals of equity and vulnerability alleviation. Participatory workshops with representatives of the city government illustrate how making such narratives visible through exploratory modeling can lead to a questioning of prior assumptions and causal relations, recognition of a need for intersectoral collaboration, and insights into potential management strategies. [ABSTRACT FROM AUTHOR]