Flood Vulnerability Research Articles

Beyond the banks and deluge: understanding riverscape, flood vulnerability, and responses in kashmir

AbstractFlooding in Kashmir results from a complex interplay of physical, sociopolitical, and economic factors, which presents a severe environmental challenge. The intricate interplay between the Jhelum’s riverscape, social interactions, and economic factors is profoundly shaped by the persistent problem of flooding and its associated vulnerabilities. In this study, we examine the vulnerability of Kashmir to flooding and provide a comprehensive assessment of the recent floods. The purpose of this vulnerability assessment is to delve into these intricacies and offer deeper understanding of flood vulnerability in Kashmir. We explore the concept of riverscape in the context of the Jhelum River to encompass a holistic view of the river, understanding its physical features and socio-economic aspects, and examining the spatial and temporal dynamics of river ecosystems. This study analyses the spatial distribution of the inundated population, rainfall and hydrological analysis, flood gauge analysis of the Jhelum River, hydrological trends, and annual peak discharge at key discharge stations from 2003 to 2023. We analyse the policy landscape, social capital, and responses to recent flooding and provide a historical analysis of these policies. Using a mixed methods approach of qualitative as well as remote sensing methods to analyse recent flooding in Kashmir, we assessed the impact of flooding on population and LULC. We analyse how marginalised communities, lacking essential services and resources, disproportionately bear the brunt of these floods.

PEMODELAN SPASIAL DALAM MENGIDENTIFIKASI TINGKAT KERENTANAN BANJIR DI KECAMATAN MEJOBO, KABUPATEN KUDUS, JAWA TENGAH, INDONESIA

The occurrence of flood disasters is an annual unavoidable event in the Mejobo District, Kudus Regency. This study aims to map the vulnerable areas to floods in the Mejobo District using spatial modelling. The parameters used to determine the vulnerability areas include soil type, elevation, population density, river buffer, rainfall, and land use. The research location is situated in the Mejobo District. The research method employed is the models and multicriteria decision-making (MCDM) techniques, with the assistance of ArcGIS software for data processing and analysis. The research findings yield a final map depicting flood vulnerability, which indicates the distribution of flood-prone areas. Areas with a high level of flood vulnerability are dispersed across agricultural fields and areas adjacent to rivers, covering an area of 1,770 hectares. Meanwhile, areas with a moderate level of vulnerability are predominantly distributed in residential areas, covering an area of 1,907 hectares.

Application of sma method and ahp to predict the level of tidal flood vulnerability in Tegal City

Application of sma method and ahp to predict the level of tidal flood vulnerability in Tegal City

A novel approach to flood risk assessment: Synergizing with geospatial based MCDM-AHP model, multicollinearity, and sensitivity analysis in the Lower Brahmaputra Floodplain, Assam

Floods persist as a recurring and daunting peril in the Brahmaputra plain of Assam. Notwithstanding advancement, Bongaigaon is a highly flood-afflicted district in the lower part of this region, inflicting significant damage to both lives and property almost every consecutive year. Hence, the delineation of precise and reliable flood risk susceptibility zones within the district constitutes the foremost concern of the study. The present work considered a total of sixteen multi-collinearity free parameters integrating with the GIS- based Multi-Criteria Decision Making-Analytical Hierarchy Process (MCDM-AHP) model for identifying potential flood hazard zones (FHZ), flood vulnerability zones (FVZ), and flood risk zones (FRZ) for the region. The result revealed that over 28% of the district's total area falls under the high to very high flood risk zone. Srijangram circle covers the highest flood risk zone with 343.19 sq. km. The FHZ map of the district demonstrated reliability exceeding 90% in ROC-AUC and below 40% in MSE and RMSE. Additionally, sensitivity analyses depict the role indicators in the predictive model, placed as a virgin gap for study in the region. Moreover, a multivariate correlation statistic is used to examine the potential risk zones and temporal flood effects on different Revenue Circles (RC), showing R2 over 0.6 in each category. The robustness of this model manifests sensible findings, aiding in fortifying sustainable flood management strategies to mitigate risks at different levels. Strategies adopted here contain greater potential for current as well as future trends in similar domains of research. This study may provide invaluable insights for decision-makers, thinkers, administrators, and developers working in this region.

Assessment of vulnerability to flood risk in the Padma River Basin using hydro-morphometric modeling and flood susceptibility mapping.

An evaluation of flood vulnerability is needed to identify flood risk locations and determine mitigation methods. This research introduces an integrated method combining hydro-morphometric modeling and flood susceptibility mapping to assess Padma River Basin's flood risk. Flood zoning, flooding classes, and resource flood risk were explicitly analyzed in this river basin study. Flood risk was calculated using GIS-based hydro-morphometric modeling. Using Horton's and Strahler's methods, drainage density, stream density, and stream order of the Padma River Basin were determined. The Padma River Basin has five sub-basins: A, B, C, D, and E, with stream densities of 0.53km-2, 0.13km-2, 0.25km-2, 0.30km-2, and 0.28km-2 and drainage densities of 0.63km-1, 0.16km-1, 0.29km-1, 0.35km-1, and 0.33km-1, respectively. Sub-basin A is the most prone to floods due to its high stream and drainage density, whereas B and C are the least susceptible. This study used elevation, TWI, slope, precipitation, NDVI, distance from road, drainage density, distance from river, LU/LC, and soil type to create a flood vulnerability map incorporating GIS and AHP with pair-wise comparison matrix (PCM). The study's flood zoning shows that the northeastern part of this basin is more likely to flood than the southwestern part due to its elevation and high-order streams. Moderate River Flooding, the region's most hazardous flood class, covers 48.19% of the flooding area, including 1078.30 km2 of agricultural land, 94.86 km2 of bare soil, 486.39 km2 of settlements, 586.42 km2 of vegetation cover, and 39.34 km2 of water bodies. The developed hydro-morphometric model, the flood susceptibility map, and the analysis of this data may be utilized to offer long-term advance alarm insight into areas potentially to be invaded by a flood catastrophe, boosting hazard mitigation and planning.

Mapping of Flood Prone Areas in West Lombok Based on Analytic Hierarchy Process and Geographic Information System

The development and management of flood-prone information systems is needed by many parties, especially the public. In this research, the Analytic Hierarchy Process (AHP) presents an approach to detecting flood-prone areas by combining it with a Geographic Information System (GIS). AHP analysis is used to determine the weight and value of each assessment criterion, and then the results are integrated into the GIS system to produce a flood forecast map. The results obtained show that mapping of flood-prone zones can be carried out rationally and consistently based on AHP by considering four criteria, namely land use, soil type, slope, and rainfall. The results of the analysis of the zoning map show that the areas with a high level of flood vulnerability are on the north and west sides. The area around the Lembar port has a high level of vulnerability. Eyat Mayang Village also has a high level of vulnerability. Locations with a high level of flood vulnerability, caused by flooding through rivers located not far from the sea estuary.

Assessing Reliability, Resilience and Vulnerability of Water Supply from SuDS

In recent decades, the impacts of urbanization on the hydrological cycle have led to an increase in the frequency and magnitude of urban flooding events, and this is also amplified by the effects of climate change. Sustainable Drainage Systems (SuDS) provide a revolutionary change in this field, improving the sustainability and resilience of cities. This research explores the integration of different SuDS with the aim of significantly reducing both the flow volume and celerity of floods in a residual urban catchment area of the metropolitan city of Querétaro (Mèxico), where extreme rainfall frequently occurs. This catchment is a representative suburb of urban pressure and environmental degradation problems. Currently, managing storm water under climate uncertainty through a multi-disciplinary approach is a major concern in this urban area. A 1D–2D coupling model of shallow water equations, the finite volume method, an unstructured meshing method, and a hybrid parallel computing application defined the optimal configuration of SuDS at catchment scale to reduce the flood vulnerability in Querétaro. Specifically, in this paper, we explore the management issues of the proposed SuDS configuration that acts as a water resource system with multiple purposes. A generic simulation model called MODSIM was applied to simulate the designed urban drainage system under a balanced IPCC future climate scenario in terms of reliability, resilience and vulnerability against water scarcity. The proposed hierarchical Reliability–Resilience–Vulnerability approach appears to be effective in evaluating the system performance, showing that the complete satisfaction of non-essential water uses in Querétaro can be assured at a 65% rate of reliability for a large range of reservoir storage conditions.

Spatial analysis of socio-economic and demographic factors influencing urban flood vulnerability

Rapid urbanization and climate change require a thorough understanding of flood vulnerability in order to assure urban safety and resilience. Understanding the factors that contribute to flood vulnerability, allows us to develop effective initiatives that could mitigate the destructive consequences of flooding, while also protecting communities. The objective of this research is to identify and model the socio-economic and demographic factors that significantly influence flood vulnerability in the floodplains of Jackson, Mississippi, and Birmingham, Alabama, USA. First we analyzed the correlation between socio-economic and demographic factors then employed Principal Component Analysis (PCA) to address multicollinearity, a common challenge in multivariate statistical modeling. Subsequently, PCs-based global regression (PCR) and geographically weighted regression (PCGWR) analysis are used to identify key drivers of flood vulnerability. The findings demonstrate that a significant proportion of the variance (>80%) of these factors can be captured by first two to three Principal Components (PCs). Consistent with existing research, African American, poverty, seniors, and the number of less educated people positively correlate with flood vulnerability, while income and housing prices exhibit a negative correlation. Additionally, PCGWR outperformed the Principal Component Regression (PCR) in most cases, highlighting the spatial heterogeneity of flood vulnerability. This study focuses on two U.S. cities, and the methodology is applicable to other cities with similar characteristics. The identified factors align with global research on flood vulnerability, making the proposed research and findings valuable worldwide. The findings of this research are useful for local governments, policymakers, and urban developers to make detailed location specific flood vulnerability plan to reduce impact of flood and improve urban resilience.

Data-driven urban configuration optimization: An XGBoost-based approach for mitigating flood susceptibility and enhancing economic contribution

The indiscriminate evolution of urban configurations aggravates flood vulnerabilities, threatening sustainable urban expansion. Present methodologies fall short in supplying urban planners with flood mitigative strategies centered on urban configuration facets. Leveraging the power of the XGBoost algorithm, this study posits an advanced optimization schema, adroitly balancing the dual objectives of mitigating urban flooding and enhancing economic growth, with minimal disruption to established urban layouts. Shenzhen serves as the investigative ground, where the model displays exceptional accuracy, resilience, and interpretability in predicting Pluvial Flooding Susceptibility (PFS) and Economic Contribution (EC). Model interpretation divulges the profound influence of three-dimensional urban configuration elements, primarily the Building Congestion Degree, on PFS and EC. Pareto solution exploration for multi-objective optimization unveils the ideal urban configuration interval. To minimize PFS while maximizing EC, the research suggests pertinent measures: augmenting vegetation density, regulating the impervious coverage ratio within 50–70%, limiting two- and three-dimensional building density thresholds, and moderately escalating urban drainage network density. Additionally, it encourages a comprehensive appreciation of function-oriented land usage and intrinsic site topographical characteristics to reconcile varied urban development goals during planning. By fusing data-derived insights with multi-objective optimization, this research anticipates influencing urban planning models, thus enhancing decision-making related to urban configuration and fostering flood-resilient, sustainable, and economically prosperous urban habitats.

The Resilience of the Built Environment to Flooding: The Case of Alappuzha District in the South Indian State of Kerala

In recent years, floods and climate-induced cataclysms have caused significant annual damage to livelihoods worldwide, with limited research on their vulnerability, impact, resilience, and long-term adaptation strategies in developing countries. In the South Indian State of Kerala, the major flood in 2018 caused immense economic losses in the low-lying and densely populated Alappuzha District. While the region has a heightened risk of periodic flooding, the considerable destruction of buildings and infrastructure highlights the need for effective solutions for flood resilience in the existing housing stock and new construction. In this context, this study examines flood resilience in the built environment of Alappuzha, focusing on flood vulnerability, building practices, and potential approaches suitable for the region that the current literature does not address. This study employs a qualitative research approach to understand current trends in adaptation strategies and the influencing socioeconomic and cultural factors. The study employs various data collection methods, including interviews, site observations, and content analyses of existing government reports, journal articles, and popular media sources. The findings indicate that although there are three types of established flood resilience techniques (static elevated, floating, and amphibious structures), their suitability for the low-lying areas of Alappuzha depends on the geographic, climatic, socioeconomic, and cultural contexts. Stilted houses have become the most common construction method, in response to climatic and socioeconomic conditions. In addition, the findings highlight the bounce-forth resilience quality of amphibious building techniques and suggest further exploration by integrating them with local technologies and materials. The study concludes that a comprehensive approach is needed that integrates traditional and modern knowledge and practices in disaster risk reduction and management to enhance the resilience of the built environment to flooding.

Integrated assessment of flood susceptibility and exposure rate in the lower Niger Basin, Onitsha, Southeastern Nigeria

BackgroundVarious methods have been utilized to investigate and mitigate flood occurrences, yet there is a paucity of literature on factors, such as soil compositions, that contribute to persistent flooding in river basins like the Lower Niger catchment, specifically at Onitsha. Furthermore, the study seeks to furnish essential geospatial data concerning flood vulnerability, flood risks, and exposure rates in the Lower Niger Catchment area, situated in Onitsha, southeastern Nigeria.Materials and methodsSoil samples were collected from 10 specific locations identified through GPS and ground-truthing techniques. Additionally, satellite imagery from the Landsat Enhanced Thematic Mapper (ETM +) was utilized, with supervised classification employed to extract feature classes. Analysis operations were conducted using IDRISI software, resulting in the creation of digital elevation models (DEMs), susceptibility maps, and flood-risk zones.ResultsAnalysis revealed that the predominant soil composition in the study area comprises sandy (84.8%), silt (8.1%), and clayey (7.1%) soils. Utilizing these soil characteristics alongside relevant aerial data, exposure rates were determined at various scales to delineate the most flood-vulnerable zones in the basin. It was found that certain areas, accommodating a population exceeding 79,426 across 2,926.2 ha, were particularly susceptible to flooding. Notably, major markets such as Bridgehead, Textile, and Biafra were identified as highly susceptible, with varying degrees of risk. The prevalence of sandy soil, which facilitates increased rainwater infiltration but is also prone to rapid saturation and runoff, likely contributes to the heightened susceptibility to flooding in these areas.ConclusionGeospatial analysis employing remote sensing data indicates the high susceptibility and exposure to flooding in the lower Niger River Basin around Onitsha. Urgent mitigation efforts are imperative, necessitating the establishment of zoned areas equipped with effective drainage systems to safeguard vulnerable populations.

CLASS STUDY AND MAP OF FLOOD VULNERABILITY LEVELS IN THE KRUENG JREUE SUB WATERSHED ACEH Besar

The increasing intensity of land conversion in the Krueng Jreue Aceh Besar Sub-watershed due to changes in land use causes changes in the biophysical characteristics of the land. Changes in the biophysical characteristics of land cause an increase in the level of flood vulnerability. This research uses a descriptive method (survey). The research results show: The variables determining the level of flood vulnerability are based on the biophysical aspects of the land, namely: dynamic factors (rainfall, land use) and static factors (soil infiltration, slope slope). Flood Vulnerability Level Classes and Maps (TKB), consisting of: Very Vulnerable, residential areas, rice fields (42≤TKB≤50); Vulnerable, moor (34≤TKB≤41); and Medium, open land, shrubs, grasslands, secondary forests, primary forests (26≤TKB≤33), average 32.38 (medium class).Primary forests and secondary forests in non-cultivation areas, covering an area of ​​12,598.00 ha or 54.26% of the total area of ​​the Krueng Jreue Sub-watershed (23,218.06 ha), have the lowest level of flood vulnerability. Flood disasters occur in November-December, when rainfall is high, which causes residents to be exposed, physical and economic losses and land damage.

From data to decisions: evaluating flood vulnerability in the Sindh watershed through Analytical Hierarchy Process

Floods are recurrent global catastrophes causing substantial disruptions to human life, extensive land degradation, and economic losses. This study aims to identify flood-triggering watershed features and employ a Multi-Criteria Decision-Making (MCDM) approach based on the Analytical Hierarchy Process (AHP) model to delineate flood-prone zones. Weights for various flood-influencing factors (slope, rainfall, drainage density, land-use/land-cover, geology, elevation, and soil) were derived using a 7 × 7 AHP decision matrix, reflecting their relative importance. A Consistency Ratio (CR) of 0.089 (within acceptable limits) confirms the validity of the assigned weights. The analysis identified approximately 128.51 km2 as highly vulnerable to flooding, particularly encompassing the entire stretch of riverbanks within the watershed. Historically, snow avalanches and flash floods have been the primary water-related disasters in the region, posing significant threats to critical infrastructure. In this context, this model-based approach facilitates the proactive identification of susceptible areas, thereby promoting improved flood risk mitigation and response strategies.

Flood vulnerability mapping in an urban area with high levels of impermeable coverage in southern Brazil

Flood vulnerability mapping in an urban area with high levels of impermeable coverage in southern Brazil

Enhancing regional resilience: assessing tidal flood vulnerability and adaptation strategies in a coastal community

Abstract This study aims to assess the vulnerability of communities in Sungai Pauh, Sungai Pauh Pusaka, and Sungai Pauh Tanjung, Langsa, Aceh Province to tidal flooding, and understand their adaptation strategies and the main socio-economic and environmental contributors to vulnerability. A mixed methods approach combines quantitative vulnerability index calculations with qualitative data from interviews. We assessed the vulnerability index using secondary data sources (population density, gender, vulnerable age, poor population, and disabled population) to evaluate the vulnerability of communities. The 34 key informants represent various levels of society, including village officials, government employees, and the community. High social vulnerability was identified, related to population density, gender, age, poverty, and disability, while economic vulnerability was low due to dependence on fishing. The recommendations include knowledge dissemination, public awareness campaigns, the formation of community groups for flood relief, and infrastructure development, with a focus on channel reconstruction to increase resilience and reduce the impact of tidal floods.

Impact of Land Use/Land Cover Change on Future Flash Flood Vulnerability and Monsoon Runoff in an Ungauged Himalayan Watershed

Impact of Land Use/Land Cover Change on Future Flash Flood Vulnerability and Monsoon Runoff in an Ungauged Himalayan Watershed

A Comprehensive Review of Studies Focusing on the Intersection of Urban Flooding and Historic Urban Landscapes

Abstract Due to evolving climate patterns and the deterioration of infrastructure in historic cities, these urban locales confront escalating flood-related risks. A profusion of academic discourse has separately explored the subjects of urban flooding and historic urban landscapes, but an integrative, systematic review of both areas concurrently remains scarce. This review presents a holistic perspective of the convergence between urban flooding and historic urban landscapes, meticulously evaluating 101 scholarly articles sourced from the Web of Science database spanning from 2006 to 2022. The disciplinary classification encompasses 24 categories. A careful examination of the methodologies employed in these articles reveals flood vulnerability mapping as a prevalent tool in urban heritage conservation, while nature-based solutions emerge as potent strategies for mitigating urban flooding challenges. The insights derived from this review shed light on the present state of affairs regarding urban flooding risks in historic cities, and provide a wealth of information beneficial to decision-makers and practitioners engaged in urban stormwater management.

FLOOD VULNERABILITY AND ADAPTATION ASSESSMENT IN PADANG TERAP DISTRICT, KEDAH, MALAYSIA

Padang Terap, Kedah in Malaysia experienced frequent floods, incurring financial losses to the flood victims and the government for flood mitigation. For an effective mitigation strategy, there is a need for a reliable database on the vulnerability and adaptation levels of flood victims. Therefore, this study is important to provide the data. The objectives of this paper are to analyse the factors that cause flood vulnerability and to determine and assess the existing adaptation to flood in Padang Terap. The research utilised a quantitative approach, through a household survey of 680 respondents. The data were analysed using descriptive and crosstabulation tests. The findings show that topography, distance between houses and rivers, and flood relief centres affect the vulnerability of the flood victims. The vulnerability to flood is higher than the adaptation level, implying that the Padang Terap flood victims are still not adapting to flood and prone to losses incurred related to flood.

Flood Disaster Prediction Model Using Long Short-Term Memory (LSTM) in Pekalongan, Central Java.

Pekalongan is located in the northern part of Java Island, directly adjacent to the sea in the north. Natural disasters that often occur in Pekalongan are floods, especially in the north of the area, which has a height of 0 meters above sea level. In addition, Pekalongan also has a relatively low land slope of around 0 – 5%, which makes it challenging to distribute water and construct drainage. This study aims to be able to perform predictive modeling of flood-prone areas for the next five years. This study used eight parameters: rainfall, elevation, slope, distance to the river, distance to the sea, groundwater table to surface, soil type, and land use. This research used the Long Short-Term Memory (LSTM) method to predict rainfall parameters using the Python programming language with Jupyter Notebook software. Later, the data will be used as training and test data. Training data testing and tests are conducted to find the minimum failure or error value. The weight scoring method is carried out on each parameter to indicate areas with a high flood vulnerability level. The results showed that Pekalongan has a medium to very high vulnerability level, with a dominant high vulnerability level. The very high level of vulnerability is prevalent in the northern part of the research area, which is directly adjacent to the sea or in the North Pekalongan District. Floods that occur in the northern part of the study area are not only due to high levels of rainfall but can also occur due to the inflow of seawater towards the mainland resulting from high tides and high sea waves. The southern region of the study area has a smaller vulnerability level than the northern region, which has a medium to high vulnerability level.Keywords: Flood ∙ Hazard ∙ Precipitation ∙ LSTM ∙ Rainfall

Climate Change and Flood Vulnerability Analysis in the Narayani River of Nepal

Flood disasters annually devastate livelihoods, particularly during the monsoon season, with no apparent reduction in impacts in low-lying regions of developing countries like Nepal. Given the increasing effects of climate change globally, this study aims to assess climate change effects and biophysical vulnerability of riverine communities to floods in the Narayani River of Nepal, elucidating the interrelationship between these phenomena. This paper presents an analysis of trends and extreme events of climatological variables, such as temperature, precipitation, and daily river discharge and hazard mapping and risk assessments in the river stretch of two Village Development Committees (VDCs) in the country’s inner Terai region of Nawalparasi district for different return-period floods, with the aid of the HEC-RAS (Hydrologic Engineering Centre’s River Analysis System) and HEC-GeoRAS. A long-term climatological data was collected from the Department of Hydrology and Meteorology, Kathmandu, and the analysis was performed using statistical softwares, SigmaStat, and SigmaPlot. In addition, flood conditions representing 2, and 100-year periods were determined using Gumbel’s distribution. The study revealed a narrowing temperature range, with increasing minimum temperatures and decreasing maximum temperatures, precipitation, and river discharge. However, there was a notable increase in extreme events. The hazard mapping indicated the people’s vulnerability to inundation and soil erosion along the low-lying riverbanks. The findings underscore the necessity for reliable technological and socio-economic vulnerability mapping to provide early warnings to at-risk populations. This paper argues that unplanned and mismanaged settlements in riverine areas may lead to population displacements, creating environmental refugees.