Spatio-Statistical Analysis of Flood Susceptibility Assessment Using Bivariate Model in the Floodplain of River Swat, District Charsadda, Pakistan

The landscape of Pakistan is vulnerable to flood and periodically affected by floods of different magnitudes. The aim of this study was aimed to assess the flash flood susceptibility of district Jhelum, Punjab, Pakistan using geospatial model and Frequency Ratio and Analytical Hierarchy Process. Also, the study considered eight most influential flood-causing parameters are Digital Elevation Model, slop, distance from the river, drainage density, Land use/Land cover, geology, soil resistivity (soil consisting of different rocks and soil formation) and rainfall deviation. The rainfall data was collected from weather stations in the vicinity of the study area. Estimated weight was allotted to each flood-inducing factors with the help of AHP and FR. Through the use of the overlay analysis, each of the factors were brought together, and the value of drainage density was awarded the maximum possible score. According to the study several areas of the region based on the parameters have been classified in flood zones viz, very high risk, high risk, moderate risk, low risk, and very low risk. In the light of the results obtained, 4% of the study area that accounts for 86.25 km2 is at high risk of flood. The areas like Bagham, Sohawa, Domeli, Turkai, Jogi Tillas, Chang Wala, Dandot Khewra were located at the very high elevation. Whereas Potha, Samothi, Chaklana, Bagrian, Tilla Jogian, Nandna, Rawal high-risk zones and have been damaged badly in the flood history of the area. This study is the first of its kind conducted on the Jhelum District and provides guidelines for disaster management authorities and response agencies, infrastructure planners, watershed management, and climatologists.

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“…In this simulation, we chose a 70/30 split. All these steps were carried out using Arc GIS 10.8 (Moazzam et al, 2020).…”

Section: Training and Record Set Generationmentioning

confidence: 99%

“…Flood susceptibility modeling is one of the key components of flood disaster studies (Dang et al, 2011;Siddayao et al, 2014;Moazzam et al, 2018Moazzam et al, , 2020Kundzewicz et al, 2019). Jhelum River is the lower catchment of the Indus water basin and has experienced flood calamities periodically.…”

Section: Introductionmentioning

confidence: 99%

Prediction of flash flood susceptibility using integrating analytic hierarchy process (AHP) and frequency ratio (FR) algorithms

Majeed

Anwar

et al. 2023

Front. Environ. Sci.

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“…As the amount of flood organization is much higher in the plains and floodplain areas, methods and statistics on flood vulnerability, risk analysis, and mapping are essential to analyze the flood susceptible character of those areas. These methods include Analytical Hierarchy Process (AHP) (Goumrasa et al 2021) as an expert knowledge-based model, Frequency ratio (FR) (Sarkar and Mondal 2020), Information value (IV) (Ul Moazzam et al 2020), Certainly factor (CF) (Cao et al 2020), Logistic regression (LR) (Fustos et al 2017), Weights ofevidence (WOE) (Tehrany et al 2017), fuzzy logic (Perera and Lahat 2015), neuro-fuzzy logic (Kambalimath and Deka 2020) as expert-based models; Artificial neural network (ANN) (Pham et al 2020), Adaptive neuro-fuzz inference system (ANFIS) (Samantaray et al 2021), Decision tree (DT) (Khosravi et al 2021), Support vector machine (SVM) (Costache et al 2021), Random Forest (RF) (Chen et al 2020) as a machine learning model. Hydraulic engineering centre-river analysis system (HEC-RAS) (Namara et al 2021) and soil water assessment tool (SWAT) (Nasir et al 2020) models are also used as hydrological models for determining flood vulnerability and risk.…”

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confidence: 99%

Evaluating the performance of flood susceptibility through novel hybrid machine learning approach in tropical plateau basin, India

Kundu

Zafor²,

Maity

2022

Preprint

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Floods are catastrophic natural disasters that inundate large areas and cause loss of life and property, property, and crops. The nature and extent of floods are much higher in the lowland plains than in the plateau region through the accumulation and inundation of a higher volume of water from the upland. The flood susceptibility model is essential to identifying the proper inundation zone for socio-cultural, industrial, and human development. This article highlights the flood susceptibility zonation along the Rupnarayan basin in southwestern West Bengal. It carries through the Rarh region, using a new approach by integrating Multi-Criteria Decision Analysis (MCDA) and machine learning (ML) techniques. An integrated model was employed using two or more individual models to obtain the best combination for delineating the flood susceptible zone of the study area. The result reveals that the probability of flood risk is much higher in the lower part of the study area, and in the western part, about 60% of the study area belongs to the moderate to very high class. Cross-validation using the ROC curve implies a good prediction accuracy, and KNN has the highest prediction rate (0.971). Nonetheless, this study recommended adapting several management techniques such as the dam's construction, check dam, embankment, ban on sand mining, change in land-use practices, to resist the severity of flood effect in this study area.

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Methods and Approaches of Flood Susceptibility Assessment and Mapping: A Review in Geographical Perspective

Bibi

Siddique

Gul

et al. 2022

Geography of the Physical Environment

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Spatio-Statistical Analysis of Flood Susceptibility Assessment Using Bivariate Model in the Floodplain of River Swat, District Charsadda, Pakistan

Cited by 11 publications

References 25 publications

Prediction of flash flood susceptibility using integrating analytic hierarchy process (AHP) and frequency ratio (FR) algorithms

Prediction of flash flood susceptibility using integrating analytic hierarchy process (AHP) and frequency ratio (FR) algorithms

Evaluating the performance of flood susceptibility through novel hybrid machine learning approach in tropical plateau basin, India

Methods and Approaches of Flood Susceptibility Assessment and Mapping: A Review in Geographical Perspective

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