Flood vulnerability assessment and mapping in selected communities of Langtang South Nigeria, using analytical hierarchy process and geographic information system

Flood is one of the most common hazards in many countries, affecting both life and properties. The recent climatic changes have brought a rise in both flood frequency and intensity making this phenomenon more devastating to people. Especially, the riparian communities of Jamalpur along the Jamuna river suffer at least once every year accounting for this natural hazard. In a scenario like this, precaution is a crucial task to fight against this natural phenomenon. Therefore, this study attempts to identify the flood vulnerable zones of Jamalpur district situating beside Jamuna river with a multi-criteria analysis. Assessment of flood vulnerability included consideration of physical indicators like rainfall, drainage density, distance from river, slope, land use land cover, elevation, soil classes as well as social indicators like population density, female density, literacy rate, number of shelters, unmetalled road and number of health personnel. All these parameters were analyzed in Geographic Information System (GIS) and assigned weightage with a multi-criteria decision-making technique namely- Analytic Hierarchy Process (AHP). Finally, a flood vulnerability map was generated for the seven Upazilas of Jamalpur district. Very high, high, moderate and low vulnerable zones were identified after overlaying all physical and social indicator maps under consideration. 45.96% portion of a total of 2115.2 sq. Km. Area was under very high and highly vulnerable zones in the final vulnerability map of Jamalpur. Such type of assessment process is significant for flood mitigation projects with a view to providing the greatest concern to the most vulnerable zones. The vulnerability maps can also help the policymakers to provide emergency aids and other privileges to those who are in most need of it.

The assessment of river flood vulnerability requires analysis of the whole physical-geographical environment, and taking into account the interaction between all natural and social–economic components of the study area. In the current paper a flood vulnerability map is elaborated in Geographical Information Systems (GIS) environment using fuzzy logic overlay analysis. Precipitation, distance from streams, flow accumulation, lithology, land use, slopes and altitude are considered and analysed as factors influencing the floods. In particular, the proposed methodology for an assessment of flood vulnerability by fuzzy logic is applied for the catchment of the river Luda Kamchia. This river is situated in the Eastern Bulgaria, Europa. It takes about 1600 km2. The relief is mainly low-mountainous and the annual amount of precipitation is between 600 and 800 mm, influenced by the Black sea in the eastern part of the river basin. Proposed methodology for the assessment of river flood vulnerability and elaboration of maps of flood vulnerability by fuzzy logic overlay analysis in GIS environment is a first step in development of the information system for integrated risk assessment from natural disasters.

This study aims at providing expertise for preparing public-based flood mapping and estimating flood risks in growing urban areas. To model and predict the magnitude of flood risk areas, an integrated Analytical Hierarchy Process (AHP) and Geographic Information System (GIS) analysis techniques are used for the case of Eldoret Municipality in Kenya. The flood risk vulnerability mapping follows a multi-parametric approach and integrates some of the flooding causative factors such as rainfall distribution, elevation and slope, drainage network and density, land-use/land-cover and soil type. From the vulnerability mapping, urban flood risk index (UFRI) for the case study area, which is determined by the degree of vulnerability and exposure is also derived. The results are validated using flood depth measurements, with a minimum average difference of 0.01 m and a maximum average difference of 0.37 m in depth of observed flooding in the different flood prone areas. Similarly with respect to area extents, a maximum error of not more than 8% was observed in the highly vulnerable flood zones. In addition, the Consistency Ratio which shows an acceptable level of 0.09 was calculated and further validated the strength of the proposed approach.

Effective disaster risk management and urban planning require robust flood vulnerability assessment methodologies, particularly in regions susceptible to flooding. Ferozepur district, Punjab, confronts substantial challenges concerning flood risk, underscoring the necessity for a comprehensive vulnerability assessment approach. This study presents an exhaustive investigation into flood vulnerability assessment in Ferozepur district, Punjab, employing Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP) as a multi-criteria framework. The primary aim is to develop a robust flood vulnerability assessment framework, integrating various thematic maps such as aspect, distance to river, elevation, flow accumulation, flow direction, drainage density, contour, Landsat 8 imagery, normalized difference vegetation index (NDVI), land use and land cover (LULC), annual rainfall, roughness, slope, stream network and topographic wetness index (TWI). Through the synthesis of these thematic maps, areas susceptible to flooding within Ferozepur district have been accurately delineated. The study underscores the significance of employing multiple criteria and GIS methodologies for precise flood vulnerability assessment. Findings reveal that regions characterized by high drainage density, low elevation and proximity to rivers exhibit heightened vulnerability to flooding. Factors such as land cover, rainfall intensity and terrain roughness exert substantial influence on flood vulnerability. Specifically, the study delineates regions highly susceptible and less susceptible to flood risks. The newly established flood vulnerability assessment framework provides essential guidance for policymakers, urban planners and emergency response agencies to mitigate flood risks.

An integral value ranked fuzzy analytical hierarchy process (AHP) and geographic information system (GIS)-based multi-criteria decision-making (MCDM) system for urban flood vulnerability mapping of Ile-Ife is presented. Elevation, slope, soil, rainfall, drainage density, geology and land use land cover information were used as input to the fuzzy-AHP MCDM system. The integral value method was used in prioritising and assigning weights to each input in the MCDM process due to its ability to represent the relative importance of two or more triangular fuzzy numbers (TFNs). Vulnerability maps were created using GIS techniques based on the aggregation of the input factor and their derived weights in the fuzzy AHP MCDM system. Validation of the methodology was carried out by simulating flooding across the study area. The flood vulnerability maps will help identify vulnerable areas and provide needed information to help mitigate the disaster risk posed by floods.

An integral value ranked fuzzy analytical hierarchy process (AHP) and geographic information system (GIS)-based multi-criteria decision-making (MCDM) system for urban flood vulnerability mapping of Ile-Ife is presented. Elevation, slope, soil, rainfall, drainage density, geology and land use land cover information were used as input to the fuzzy-AHP MCDM system. The integral value method was used in prioritising and assigning weights to each input in the MCDM process due to its ability to represent the relative importance of two or more triangular fuzzy numbers (TFNs). Vulnerability maps were created using GIS techniques based on the aggregation of the input factor and their derived weights in the fuzzy AHP MCDM system. Validation of the methodology was carried out by simulating flooding across the study area. The flood vulnerability maps will help identify vulnerable areas and provide needed information to help mitigate the disaster risk posed by floods.

A GIS based flood vulnerability modelling of Anambra State using an integrated IVFRN-DEMATEL-ANP model

Flooding is one of the most destructive natural catastrophes that can strike anywhere in the world. With the recent, but frequent catastrophic flood events that occurred in the narrow stretch of land in southern India, sandwiched between the Western Ghats and the Arabian Sea, this study was initiated. The goal of this research is to identify flood-vulnerable zones in this area by making the local self governing bodies as the mapping unit. This study also assessed the predictive accuracy of analytical hierarchy process (AHP) and fuzzy-analytical hierarchy process (F-AHP) models. A total of 20 indicators (nine physical-environmental variables and 11 socio-economic variables) have been considered for the vulnerability modelling. Flood-vulnerability maps, created using remotely sensed satellite data and geographic information systems, was divided into five zones. AHP and F-AHP flood vulnerability models identified 12.29% and 11.81% of the area as very high-vulnerable zones, respectively. The receiver operating characteristic (ROC) curve is used to validate these flood vulnerability maps. The flood vulnerable maps, created using the AHP and F-AHP methods, were found to be outstanding based on the area under the ROC curve (AUC) values. This demonstrates the effectiveness of these two models. The results of AUC for the AHP and F-AHP models were 0.946 and 0.943, respectively, articulating that the AHP model is more efficient than its chosen counterpart in demarcating the flood vulnerable zones. Decision-makers and land-use planners will find the generated vulnerable zone maps useful, particularly in implementing flood mitigation plans.

Floods are considered one of the world’s most overwhelming hydro meteorological disasters, which cause tremendous environmental and socioeconomic damages in a developing country such as Pakistan. In this study, we use a Geographic information system (GIS)-based multi-criteria approach to access detailed flood vulnerability in the District Shangla by incorporating the physical, socioeconomic vulnerabilities, and coping capacity. In the first step, 21 essential criteria were chosen under three vulnerability components. To support the analytical hierarchy process (AHP), the used criteria were transformed, weighted, and standardized into spatial thematic layers. Then a weighted overlay technique was used to build an individual map of vulnerability components. Finally, the integrated vulnerability map has been generated from the individual maps and spatial dimensions of vulnerability levels have been identified successfully. The results demonstrated that 25% of the western-middle area to the northern part of the study area comprises high to very high vulnerability because of the proximity to waterways, high precipitation, elevation, and other socioeconomic factors. Although, by integrating the coping capacity, the western-central and northern parts of the study area comprising from high to very high vulnerability. The coping capacities of the central and eastern areas are higher as compared to the northern and southern parts of the study area because of the numerous flood shelters and health complexes. A qualitative approach from the field validated the results of this study. This study’s outcomes would help disaster managers, decision makers, and local administration to quantify the spatial vulnerability of flood and establish successful mitigation plans and strategies for flood risk assessment in the study area.

An integrated indicator-based approach for constructing an urban flood vulnerability index as an urban decision-making tool using the PCA and AHP techniques: A case study of Alexandria, Egypt

Medan is the third largest city in Indonesia. It is a lowland with topography tend to ramps and as an encounter place of two rivers namely Deli River and Babura River. Medan city is prone to flood because it is a downstream area traversed by those two rivers. According to the Regional Disaster Management Agency, the most frequent disaster in Medan City is a flood, which occurred almost every year over the last 10 years. Climate change has caused increasing frequency and intensity of rainfall in North Sumatra in recent years. It triggers the occurrence of floods. The purpose of this study was to determine the area which is vulnerable and prone to flood. The objectives are making a map of flood prone area and flood vulnerability map. The research is descriptive, which used Geographical Information System (GIS) analysis. GIS is used to produce disaster-prone maps by sequencing data such as slope, land use and landform. From the research above, it found that Medan City is generally a flood-prone area and has a high vulnerability for flooding. Medium and high flood-prone areas reach 95% of the entire area of Medan City. Meanwhile vulnerable areas are low and medium reaching 98%.

Flooding, caused by the excessive accumulation of water on land, disrupts activities in floodplain regions, particularly during the rainy season. The main objective is to map Flood vulnerability areas and identify regions most vulnerable to flooding to inform effective flood management strategies using an integrated approach that combines remote sensing, geographic information systems (GIS), and the analytical hierarchy process (AHP) to assess Flood vulnerability in the Wuseta Watershed. The research was conducted in three phases: pre-fieldwork, fieldwork, and post-fieldwork. Key factors influencing Flood vulnerability such as drainage density, elevation, land use/land cover, and slope were hierarchically weighted to produce a Flood vulnerability map. Rainfall distribution was not considered as a contributing factor the Ethiopian Meteorological Agency has installed only one weather station in the study area, located in Wuseta watershed. As a result, the rainfall distribution is considered uniform throughout the watershed, making it unsuitable for flood susceptibility assessment. The Flood vulnerability map categorizes the watershed into five zones: very high (0.07km2), high (4.65km2), moderate (7.86km2), slight (4.41km2), and very slight (0.001km2). The results show that the upstream, northern, northwestern, and northeastern areas of the watershed face slight to very slight Flood vulnerability, while the southern region is highly vulnerable to flooding. These findings provide valuable insights for policymakers and local communities, aiding in the development of targeted mitigation strategies and raising awareness of flood-prone areas. This study underscores the value of integrating geospatial technologies and multi-criteria decision analysis in flood risk assessment, particularly in data-scarce regions, to enhance disaster preparedness and climate resilience.

The analytical hierarchy process (AHP) and frequency ratio model (FR), along with the integration of GIS, have proven to be successful approaches for assessing flood-prone areas. However, in Nepal flood vulnerability mapping based on GIS decision analysis is limited. Thus, this study focused on comparing the data-driven FR method and expert knowledge-based AHP technique in a GIS environment to prepare a flood vulnerability map for the Bagmati River basin, helping to explore the gap in flood vulnerability mapping methodologies and approaches. By combining all class-weighted contributing factors, like elevation, precipitation, flow accumulation, drainage density, soil, distance from the river, land use land cover, normalized difference vegetative index, slope and topographic wetness index, the study evaluated the efficiency of FR and AHP in assessing flood vulnerability maps. An inventory map of floods containing 107 flood points was created. Subsequently, the flood vulnerability maps generated using FR and AHP models revealed that 9.30% and 11.36% of regions were in highly vulnerable areas, respectively. Receiver operating characteristics validated the model outcomes, indicating that the FR model’s accuracy of 91% outperformed the AHP model’s 84% accuracy. The study findings will assist decision-makers in enacting sustainable management techniques to reduce future damage in the Bagmati basin.

Floods are the most common and expensive natural calamity, affecting every country. Flooding in the Shebelle River Basin (SRB) in southern Somalia has posed a significant challenge to sustainable development. The main goal of this study was to analyze flood hazard, vulnerability and risk in the part of SRB using GIS-based Multi-Criteria Decision Analysis (MCDA). The flood hazard map was constructed using seven important causative factors: elevation, slope, drainage density, distance to river, rainfall, soil and geology. The results demonstrate that very low, low, moderate, high, and very high flood hazard zones correspond to 10.92%, 24.97%, 29.13%, 21.93% and 13.04% of the area of SRB, respectively. The flood vulnerability map was created using five spatial layers: land use/land cover, population density, distance to road, Global man-made impervious surface (GMIS), and Human built-up area settlement extent (HBASE). In addition, the results of the flood susceptibility and vulnerability maps were used to create a flood risk map. The results demonstrate that for the Shebelle River Basin, 27.6%, 30.9%, 23.6%, 12.1%, and 5.7% area correspond to very low, low, moderate, high, and very high flood risk zones, respectively. The Receiver Operating Characteristics-Area Under the Curve (ROC-AUC) of the flood hazard model exhibited a good prediction accuracy of 0.781. The majority of the basin is at risk of flooding in the very low, low, and moderate ranges; however, some tiny areas are at risk of flooding in the high and very high ranges. Flood hazard, vulnerability and risk maps should be provided and distributed the authorities responsible for flood protection so that people are aware flood risk locations.

Flood vulnerability assessment and mapping: A case of Ben Hai-Thach Han River basin in Vietnam