Identification and validation of potential flood hazard area using GIS‐based multi‐criteria analysis and satellite data‐derived water index

Abstract This article identifies potential flood hazard areas through multi‐criteria analysis in Allahabad district, India. The study has incorporated eight criteria, namely, flow accumulation, draining capability, elevation, groundwater depth, land use, runoff coefficient, slope, and geology for pr...

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Main Authors: Pratik Dash, Jishnu Sar
Format: Article
Language:English
Published: Wiley 2020-09-01
Series:Journal of Flood Risk Management
Subjects:
GIS
Online Access:https://doi.org/10.1111/jfr3.12620
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spelling doaj-73a0ce603cd749aca32515f1053f7bb02020-11-25T03:42:16ZengWileyJournal of Flood Risk Management1753-318X2020-09-01133n/an/a10.1111/jfr3.12620Identification and validation of potential flood hazard area using GIS‐based multi‐criteria analysis and satellite data‐derived water indexPratik Dash0Jishnu Sar1Department of Geography, School of Science Adamas University Kolkata IndiaDepartment of Geography Banaras Hindu University Varanasi IndiaAbstract This article identifies potential flood hazard areas through multi‐criteria analysis in Allahabad district, India. The study has incorporated eight criteria, namely, flow accumulation, draining capability, elevation, groundwater depth, land use, runoff coefficient, slope, and geology for preparing hazard index. The weights of the criteria were obtained through the analytical hierarchy process (AHP) method based on their relative importance for occurring floods. Finally, a flood hazard index (FHI) was prepared by combining the parameter ratings and corresponding weights. The credibility of the present methodology was tested through validation with the satellite‐based inundation map of August 20, 2016. A normalized difference water index (NDWI) was prepared from Landsat‐8 OLI data and the inundated area was delineated by a binary classification of NDWI based on a threshold calculated following Otsu's method. The analysis found 81% of inundation is associated with high to very high flood hazard zones. Agricultural land is more prone to flood than other land use types. The results showed that the GIS‐based multi‐criteria analysis framework could be effectively applied for flood hazard analysis to support decision making in disaster management.https://doi.org/10.1111/jfr3.12620analytical hierarchy processflood hazard indexGISLandsat‐8 OLInormalized difference water index
collection DOAJ
language English
format Article
sources DOAJ
author Pratik Dash
Jishnu Sar
spellingShingle Pratik Dash
Jishnu Sar
Identification and validation of potential flood hazard area using GIS‐based multi‐criteria analysis and satellite data‐derived water index
Journal of Flood Risk Management
analytical hierarchy process
flood hazard index
GIS
Landsat‐8 OLI
normalized difference water index
author_facet Pratik Dash
Jishnu Sar
author_sort Pratik Dash
title Identification and validation of potential flood hazard area using GIS‐based multi‐criteria analysis and satellite data‐derived water index
title_short Identification and validation of potential flood hazard area using GIS‐based multi‐criteria analysis and satellite data‐derived water index
title_full Identification and validation of potential flood hazard area using GIS‐based multi‐criteria analysis and satellite data‐derived water index
title_fullStr Identification and validation of potential flood hazard area using GIS‐based multi‐criteria analysis and satellite data‐derived water index
title_full_unstemmed Identification and validation of potential flood hazard area using GIS‐based multi‐criteria analysis and satellite data‐derived water index
title_sort identification and validation of potential flood hazard area using gis‐based multi‐criteria analysis and satellite data‐derived water index
publisher Wiley
series Journal of Flood Risk Management
issn 1753-318X
publishDate 2020-09-01
description Abstract This article identifies potential flood hazard areas through multi‐criteria analysis in Allahabad district, India. The study has incorporated eight criteria, namely, flow accumulation, draining capability, elevation, groundwater depth, land use, runoff coefficient, slope, and geology for preparing hazard index. The weights of the criteria were obtained through the analytical hierarchy process (AHP) method based on their relative importance for occurring floods. Finally, a flood hazard index (FHI) was prepared by combining the parameter ratings and corresponding weights. The credibility of the present methodology was tested through validation with the satellite‐based inundation map of August 20, 2016. A normalized difference water index (NDWI) was prepared from Landsat‐8 OLI data and the inundated area was delineated by a binary classification of NDWI based on a threshold calculated following Otsu's method. The analysis found 81% of inundation is associated with high to very high flood hazard zones. Agricultural land is more prone to flood than other land use types. The results showed that the GIS‐based multi‐criteria analysis framework could be effectively applied for flood hazard analysis to support decision making in disaster management.
topic analytical hierarchy process
flood hazard index
GIS
Landsat‐8 OLI
normalized difference water index
url https://doi.org/10.1111/jfr3.12620
work_keys_str_mv AT pratikdash identificationandvalidationofpotentialfloodhazardareausinggisbasedmulticriteriaanalysisandsatellitedataderivedwaterindex
AT jishnusar identificationandvalidationofpotentialfloodhazardareausinggisbasedmulticriteriaanalysisandsatellitedataderivedwaterindex
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