Drought susceptibility modeling with geospatial techniques and AHP model: a case of Bilate River Watershed, Central Rift Valley of Ethiopia

Drought continues to be the worst natural hazard in the worldaffecting ecosystems, economies and overall human welfare withsevere consequences in developing countries. While drought is anunavoidable climatic phenomenon, actions can be made toimprove preparedness and mitigate the impacts upon properf...

Full description

Bibliographic Details
Main Authors: Burka, A., Biazin, B., Bewket, W.
Format: Journal Article
Language:Inglés
Published: Informa UK Limited 2024
Subjects:
Online Access:https://hdl.handle.net/10568/152053
_version_ 1855533538258976768
author Burka, A.
Biazin, B.
Bewket, W.
author_browse Bewket, W.
Biazin, B.
Burka, A.
author_facet Burka, A.
Biazin, B.
Bewket, W.
author_sort Burka, A.
collection Repository of Agricultural Research Outputs (CGSpace)
description Drought continues to be the worst natural hazard in the worldaffecting ecosystems, economies and overall human welfare withsevere consequences in developing countries. While drought is anunavoidable climatic phenomenon, actions can be made toimprove preparedness and mitigate the impacts upon properforecast on susceptibility. Drought susceptibility modeling plays akey role in determining how best to mitigate and adapt todrought occurrences. This research explores the application ofgeospatial techniques and Analytic Hierarchy Process (AHP) indrought susceptibility modeling for the drought-prone BilateRiver watershed, located in the central Rift Valley drylands ofEthiopia. A total of 15 parameters were used including rainfall,temperature, evapotranspiration, soil moisture, normalized differ-ence vegetation index, land surface temperature, soil texture, landuse-land cover, topographic wetness index, modified normalizeddifference water index, drainage density, slope, elevation, popula-tion density and aspect to model drought susceptibility. Findingsshowed that nearly 70.2% of the area falls under the moderatedrought category, followed by the severe (23.2%), mild drought(6.6%) and extreme (0.02%) drought categories in the watershed.Based on zonal administration, Wolayta Zone has a high spatialcoverage of severe drought with 54.1% (659.3 km2) while Hadiyahas a high spatial coverage of moderate drought with 24.6%(908.9 km2). The drought susceptibility model (DSM) receiver oper-ating characteristic (ROC) curve was then created, and the areaunder curve (AUC) was calculated. The results of the analysisshowed that the AUC is 0.701 (70.1%) indicating that the modelis reasonably good model. Hence, geospatial approaches in con-junction with the AHP model improved the drought susceptibilitymodeling’s reliability, which has significant implications fordrought adaptive management and preparedness planning.
format Journal Article
id CGSpace152053
institution CGIAR Consortium
language Inglés
publishDate 2024
publishDateRange 2024
publishDateSort 2024
publisher Informa UK Limited
publisherStr Informa UK Limited
record_format dspace
spelling CGSpace1520532025-12-08T10:06:44Z Drought susceptibility modeling with geospatial techniques and AHP model: a case of Bilate River Watershed, Central Rift Valley of Ethiopia Burka, A. Biazin, B. Bewket, W. drought rift valleys Ethiopia climate change water management Drought continues to be the worst natural hazard in the worldaffecting ecosystems, economies and overall human welfare withsevere consequences in developing countries. While drought is anunavoidable climatic phenomenon, actions can be made toimprove preparedness and mitigate the impacts upon properforecast on susceptibility. Drought susceptibility modeling plays akey role in determining how best to mitigate and adapt todrought occurrences. This research explores the application ofgeospatial techniques and Analytic Hierarchy Process (AHP) indrought susceptibility modeling for the drought-prone BilateRiver watershed, located in the central Rift Valley drylands ofEthiopia. A total of 15 parameters were used including rainfall,temperature, evapotranspiration, soil moisture, normalized differ-ence vegetation index, land surface temperature, soil texture, landuse-land cover, topographic wetness index, modified normalizeddifference water index, drainage density, slope, elevation, popula-tion density and aspect to model drought susceptibility. Findingsshowed that nearly 70.2% of the area falls under the moderatedrought category, followed by the severe (23.2%), mild drought(6.6%) and extreme (0.02%) drought categories in the watershed.Based on zonal administration, Wolayta Zone has a high spatialcoverage of severe drought with 54.1% (659.3 km2) while Hadiyahas a high spatial coverage of moderate drought with 24.6%(908.9 km2). The drought susceptibility model (DSM) receiver oper-ating characteristic (ROC) curve was then created, and the areaunder curve (AUC) was calculated. The results of the analysisshowed that the AUC is 0.701 (70.1%) indicating that the modelis reasonably good model. Hence, geospatial approaches in con-junction with the AHP model improved the drought susceptibilitymodeling’s reliability, which has significant implications fordrought adaptive management and preparedness planning. 2024-01 2024-09-09T15:45:30Z 2024-09-09T15:45:30Z Journal Article https://hdl.handle.net/10568/152053 en Open Access Informa UK Limited Burka, A.; Biazin, B.; Bewket, W. 2024. Drought susceptibility modeling with geospatial techniques and AHP model: a case of Bilate River Watershed, Central Rift Valley of Ethiopia. Geocarto International. ISSN 1752-0762. 39(1). 27 p. https://doi.org/10.1080/10106049.2024.2395319
spellingShingle drought
rift valleys
Ethiopia
climate change
water management
Burka, A.
Biazin, B.
Bewket, W.
Drought susceptibility modeling with geospatial techniques and AHP model: a case of Bilate River Watershed, Central Rift Valley of Ethiopia
title Drought susceptibility modeling with geospatial techniques and AHP model: a case of Bilate River Watershed, Central Rift Valley of Ethiopia
title_full Drought susceptibility modeling with geospatial techniques and AHP model: a case of Bilate River Watershed, Central Rift Valley of Ethiopia
title_fullStr Drought susceptibility modeling with geospatial techniques and AHP model: a case of Bilate River Watershed, Central Rift Valley of Ethiopia
title_full_unstemmed Drought susceptibility modeling with geospatial techniques and AHP model: a case of Bilate River Watershed, Central Rift Valley of Ethiopia
title_short Drought susceptibility modeling with geospatial techniques and AHP model: a case of Bilate River Watershed, Central Rift Valley of Ethiopia
title_sort drought susceptibility modeling with geospatial techniques and ahp model a case of bilate river watershed central rift valley of ethiopia
topic drought
rift valleys
Ethiopia
climate change
water management
url https://hdl.handle.net/10568/152053
work_keys_str_mv AT burkaa droughtsusceptibilitymodelingwithgeospatialtechniquesandahpmodelacaseofbilateriverwatershedcentralriftvalleyofethiopia
AT biazinb droughtsusceptibilitymodelingwithgeospatialtechniquesandahpmodelacaseofbilateriverwatershedcentralriftvalleyofethiopia
AT bewketw droughtsusceptibilitymodelingwithgeospatialtechniquesandahpmodelacaseofbilateriverwatershedcentralriftvalleyofethiopia