Flood Susceptibility Mapping through the GIS-AHP Technique Using the Cloud

• Published in: ISPRS international journal of geo-information Vol. 9; no. 12; p. 720
• Main Authors: Swain, Kishore Chandra, Singha, Chiranjit, Nayak, Laxmikanta
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 02.12.2020
• Subjects: Analytic hierarchy process; analytical hierarchy process (AHP); Anthropogenic factors; area; Cloud computing; Decision making; Decision support systems; dynamics; Environmental risk; Flood mapping; flood susceptibility; Floods; geographic information system (GIS); Geographic information systems; Geographical information systems; Google Earth Engine (GEE); Hydrology; India; Information processing; Information systems; Interference; Internet; Land cover; Landslides & mudslides; Mapping; Mitigation; Morphometry; multi-criteria decision making; multi-criteria decision support system; Multiple criterion; Permeability; planning; Population; Precipitation; Remote sensing; risk; River networks; Rivers; Runoff; Software; spatial data; Susceptibility; Topography; Tropical diseases; Vegetation; Iran; China; India
• ISSN: 2220-9964; 2220-9964
• DOI: 10.3390/ijgi9120720

Flood susceptibility mapping is essential for characterizing flood risk zones and for planning mitigation approaches. Using a multi-criteria decision support system, this study investigated a flood susceptible region in Bihar, India. It used a combination of the analytical hierarchy process (AHP) and geographic information system (GIS)/remote sensing (RS) with a cloud computing API on the Google Earth Engine (GEE) platform. Five main flood-causing criteria were broadly selected, namely hydrologic, morphometric, permeability, land cover dynamics, and anthropogenic interference, which further had 21 sub-criteria. The relative importance of each criterion prioritized as per their contribution toward flood susceptibility and weightage was given by an AHP pair-wise comparison matrix (PCM). The most and least prominent flood-causing criteria were hydrologic (0.497) and anthropogenic interference (0.037), respectively. An area of ~3000 sq km (40.36%) was concentrated in high to very high flood susceptibility zones that were in the vicinity of rivers, whereas an area of ~1000 sq km (12%) had very low flood susceptibility. The GIS-AHP technique provided useful insights for flood zone mapping when a higher number of parameters were used in GEE. The majorities of detected flood susceptible areas were flooded during the 2019 floods and were mostly located within 500 m of the rivers’ paths.