Flood Susceptibility Mapping Using GIS and Multi-criteria Decision Analysis in Dibrugarh District of Assam, North-East India

Bora, Sudipta Sankar; Das, Jayanta; Bhuyan, Kalyan; Hazarika, Partha Jyoti

doi:10.1007/978-3-031-15377-8_4

Cited by 4 publications

(3 citation statements)

References 27 publications

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“…According to the literature, there is no common rule for automatically identifying class borders; instead, most studies use their own knowledge and expertise to do so [51]. Flood-prone areas, according to many experts, have a mix of very low elevation, low slope, and high drainage density [52,53]. Using the natural breaking slope approach in the "ArcGIS 10.4.1 environment," the hazard was divided into five main groups: very high, high, moderate, low, and very low hazard zones.…”

Section: Flood Hazard Mappingmentioning

confidence: 99%

GIS-based flood risk assessment using multi-criteria decision analysis of Shebelle River Basin in southern Somalia

Osman

Das²

2023

SN Appl. Sci.

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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.

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Section: Flood Hazard Mappingmentioning

confidence: 99%

GIS-based flood risk assessment using multi-criteria decision analysis of Shebelle River Basin in southern Somalia

Osman

Das²

2023

SN Appl. Sci.

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“…Various methods and techniques have been used to assess flood hazards. The majority of studies on flood risk rely on climate and hydrological factors that affect the flood occurrence likelihood (i.e., [15][16][17][18]). Hydrological models are commonly used to predict the extent of flooding and the potential impacts of floods on people and infrastructure.…”

Section: Introductionmentioning

confidence: 99%

Comparison of the Fuzzy Analytic Hierarchy Process (F-AHP) and Fuzzy Logic for Flood Exposure Risk Assessment in Arid Regions

et al. 2023

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Flood risk assessment is an important tool for urban planning, land development, and hydrological analysis. The flood risks are very high in arid countries due to the nature of the rainfall resulting from thunderstorms and the land cover, which comprises mostly very dry arid soil. Several methods have been used to assess the flood risk, depending on various factors that affect the likelihood of occurrence. However, the selection of these factors and the weight assigned to them remain rather arbitrary. This study assesses the risk of flood occurrence in arid regions based on land cover, soil type, precipitation, elevation, and flow accumulation. Thematic maps of the aforementioned factors for the study area were prepared using GIS. The Fuzzy Analytic Hierarchy Process (F-AHP) was used to calculate the likelihood of the flood occurrence, and land use was used to assess the exposure impact. Using the likelihood map (i.e., probability) from the Fuzzy-AHP and an exposure map, the flood risk was assessed. This method was applied to Qatar as a case study. Results were compared with those produced by fuzzy logic. To explore the pairwise importance of the F-AHP, equal weight analysis was performed. The resulting risk map shows that the majority of urbanized areas in Qatar are within the high-risk zone, with some smaller parts within the very high flood-risk area. The majority of the country is within the low-risk zone. Some areas, especially land depressions, are located within the intermediate-risk category. Comparison of Fuzzy logic and the F-AHP showed that both have similarities in the low-risk and differences in the high-risk zones. This reveals that the F-AHP is probably more accurate than other methods as it accounts for higher variability.

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“…The existing literature on ood risk analyzed the vicious link between vulnerability and poverty in the state (Das, 2022;Mahanta & Das, 2017). The ood risk mapping for the state indicates areas with high ood risks across several districts, which shows the severity of ood impact on the overall physical and socio-economic condition of the state (Bhuyan et al, 2023;Bora et al, 2022;Harshasimha & Bhatt, 2023). Many scholars have studied the ood vulnerability in Assam at the macro and the community level (Chaliha et al, 2012;Giupponi et al, 2013;Joseph, 2013).…”

Section: Introductionmentioning

confidence: 99%

How much vulnerable the flood-affected villagers are? An assessment of Livelihood Vulnerability to Flood Hazard in Assam, India

Saikia,

Borthakur

2023

Preprint

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This study is a micro-level analysis of the households’ livelihood vulnerability in a flood-prone district of Assam by employing LVI and LVI-IPCC approaches. A total of eight major components of livelihood vulnerability along with fifty-three sub-components or variables are considered in this study. Based on the geographic and socioeconomic specificities of the study area, new variables have been incorporated by the authors in estimating the Livelihood Vulnerability Index. The empirical results categorize the villages into most vulnerable, moderately vulnerable, and low vulnerable. Villages with exposure to natural disasters are more vulnerable due to low adaptive capacity and high sensitivity. However, many villages despite high exposure and sensitivity have been able to enhance adaptive capacity by adopting crop diversification, non-farm activities, out-migration, etc. The livelihood vulnerability assessment carried out in this paper is helpful in identifying the vulnerable communities, households, and societies in any developing region. Less variation in the sensitivity parameters of the communities is one of the key findings of this study. The low livelihood vulnerability of some villages is a result of their lack of exposure to flooding and erosion. In the lack of adaptive capacity, future exposure to erosion and flood may increase the livelihood risk of the low-susceptible villages. Therefore, in a flood-prone state like Assam, policy measures targeting adaptative behavior are crucial.

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Flood Susceptibility Mapping Using GIS and Multi-criteria Decision Analysis in Dibrugarh District of Assam, North-East India

Cited by 4 publications

References 27 publications

GIS-based flood risk assessment using multi-criteria decision analysis of Shebelle River Basin in southern Somalia

GIS-based flood risk assessment using multi-criteria decision analysis of Shebelle River Basin in southern Somalia

Comparison of the Fuzzy Analytic Hierarchy Process (F-AHP) and Fuzzy Logic for Flood Exposure Risk Assessment in Arid Regions

How much vulnerable the flood-affected villagers are? An assessment of Livelihood Vulnerability to Flood Hazard in Assam, India

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