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Application of Morphometric Ranking Approach using Geospatial Techniques for Flash Flood Susceptibility Modelling in District Shangla, Pakistan
Author(s)
Muhammad Akmal Sardar Ali Directorate General Soil & Water Conservation,Peshawar,Pakistan; National Centre of Excellence in Geology, University of Peshawar,Peshawar,Pakistan
Abid Sarwar Directorate General Soil & Water Conservation,Peshawar,Pakistan; National Centre of Excellence in Geology, University of Peshawar,Peshawar,Pakistan
Muhammad Ali National Centre of Excellence in Geology, University of Peshawar,,Pakistan
Shazia Gulzar Directorate General Soil & Water Conservation,Peshawar,Pakistan; National Centre of Excellence in Geology, University of Peshawar,Peshawar,Pakistan
Abdul Majid Directorate General Soil & Water Conservation,Peshawar,Pakistan
Muhammad Ismail Khan Directorate General Soil & Water Conservation,Peshawar,Pakistan
Jabir Nazir National Centre of Excellence in Geology, University of Peshawar,,Pakistan
Arbaz Ahmad Department of Geography and Geomatics, University of Peshawar,,Pakistan
Abstract
Every year, disaster strikes, and led to thousands of casualties and deaths around the world. A meteorological disaster such as a flash flood is a multifaceted hydro-meteorological phenomenon that can cause a huge loss of human life and can create severe economic problems. In this study, techniques based on Geographic information systems and Remote sensing were used to get the flood susceptibility map for District Shangla, Pakistan. For the susceptibility of flash floods, geo-morphometric ranking model was used. Various causative factors were considered including; topography, river pattern, and flow accumulation. ALOS PALSAR digital elevation model was used for calculating the required causative factors. Eleven diferent sub-basins were delineated in the Shangla basin. A total of eighteen morphometric parameters were studied. The morphometric ranking approach (MRA) score was determined with a range of 1 to 5. Rank 5 represents high risk while rank 1 exhibits low risk. The results of the model were categorized into five flood vulnerability classes; very low, low, moderate, high and very high. The total population of Shangla district is 757,810 with a population density of 480 persons per sq km2, and results from this study revealed that 23% of the total geographic area (364.11 km2) of the district is vulnerable to high flash floods.
Publication Details
Page(s) 243-255
DOI 10.53560/PPASB(60-2)830
Published Journal: Proceedings of the Pakistan Academy of Sciences: B. Life and Environmental Sciences, Volume: 60, Issue: 2, Year: 2023
Keywords
GIS susceptibility Remote Sensing vulnerability Flash Flood Geomorphometric
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