Geospatial modeling of water quality for emerging irrigation challenges in Ethiopia’s Awash Basin

Recent data on the water quality and suitability dynamics of the Awash River, Ethiopia's most heavily used river for irrigated agriculture, with water that spatiotemporally varies in the transport pathways, is scarce. Increasing anthropogenic activities and the effects of climate change are exa...

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Main Authors: Kassa Girma, Tsegay Aderaw, Minaleshoa Melese
Format: Article
Language:English
Published: University of Brawijaya 2025-04-01
Series:Journal of Degraded and Mining Lands Management
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Online Access:https://jdmlm.ub.ac.id/index.php/jdmlm/article/view/16969
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author Kassa Girma
Tsegay Aderaw
Minaleshoa Melese
author_facet Kassa Girma
Tsegay Aderaw
Minaleshoa Melese
author_sort Kassa Girma
collection DOAJ
description Recent data on the water quality and suitability dynamics of the Awash River, Ethiopia's most heavily used river for irrigated agriculture, with water that spatiotemporally varies in the transport pathways, is scarce. Increasing anthropogenic activities and the effects of climate change are exacerbating concerns about salinity and water quality degradation, presenting significant challenges for the sustainable management of the Awash River This study addresses these issues by using big data analytics and Geo-spatial Sci-tech to assess water quality in a robust framework, enabling precise, timely insights essential for sustainable irrigation management. The vast volume, high velocity, and complex variety of big data including pH, EC, and ion concentrations align well with these demands. Leveraging geospatial analysis, this research valorized extensive data from ten water quality monitoring stations over a period of twenty years  for tracking and visualizing water quality trends across time and space. A slightly to moderately alkaline pH, between 7.4 and 8.4, was observed in the results., while EC ranged from 0.209  to 1.161dS/m between 2004 and 2019. Ion concentrations generally followed the northward sequence of Ca²? > Na? > Mg²? > K?, HCO?? > Cl? > SO?²?, and Na? > Ca²? > Mg²? > K?. Spatial trend analysis demonstrated a positive progression of ECw, SAR, RSC, and other ionic constituents, with temporal variations indicating a progressive decline in water quality, largely due to human activities. The findings also indicated slight to moderate sodicity hazards across samples. These spatio--temporal variations underscore the importance of using updated water quality evaluations and spatiotemporal analysis to inform water management strategies.
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spelling doaj-art-640f22edbf4a4256b67639b53d4f3bde2025-08-20T01:50:37ZengUniversity of BrawijayaJournal of Degraded and Mining Lands Management2339-076X2502-24582025-04-011237689770410.15243/jdmlm.2025.123.768916971Geospatial modeling of water quality for emerging irrigation challenges in Ethiopia’s Awash BasinKassa Girma0Tsegay Aderaw1Minaleshoa Melese2Ethiopian Institute of Agricultural Research; BARC, P.O.Box 32, Bishoftu, East Shoa, EthiopiaEthiopian Institute of Agricultural Research; DZARC,P.O.Box 32, Debre Zeit, East Shoa, EthiopiaEthiopian Institute of Agricultural Research; DZARC,P.O.Box 32, Debre Zeit, East Shoa, EthiopiaRecent data on the water quality and suitability dynamics of the Awash River, Ethiopia's most heavily used river for irrigated agriculture, with water that spatiotemporally varies in the transport pathways, is scarce. Increasing anthropogenic activities and the effects of climate change are exacerbating concerns about salinity and water quality degradation, presenting significant challenges for the sustainable management of the Awash River This study addresses these issues by using big data analytics and Geo-spatial Sci-tech to assess water quality in a robust framework, enabling precise, timely insights essential for sustainable irrigation management. The vast volume, high velocity, and complex variety of big data including pH, EC, and ion concentrations align well with these demands. Leveraging geospatial analysis, this research valorized extensive data from ten water quality monitoring stations over a period of twenty years  for tracking and visualizing water quality trends across time and space. A slightly to moderately alkaline pH, between 7.4 and 8.4, was observed in the results., while EC ranged from 0.209  to 1.161dS/m between 2004 and 2019. Ion concentrations generally followed the northward sequence of Ca²? > Na? > Mg²? > K?, HCO?? > Cl? > SO?²?, and Na? > Ca²? > Mg²? > K?. Spatial trend analysis demonstrated a positive progression of ECw, SAR, RSC, and other ionic constituents, with temporal variations indicating a progressive decline in water quality, largely due to human activities. The findings also indicated slight to moderate sodicity hazards across samples. These spatio--temporal variations underscore the importance of using updated water quality evaluations and spatiotemporal analysis to inform water management strategies.https://jdmlm.ub.ac.id/index.php/jdmlm/article/view/16969awash river basinbigdata analytics with gissethiopiaspatio-temporal trendwater quality
spellingShingle Kassa Girma
Tsegay Aderaw
Minaleshoa Melese
Geospatial modeling of water quality for emerging irrigation challenges in Ethiopia’s Awash Basin
Journal of Degraded and Mining Lands Management
awash river basin
bigdata analytics with giss
ethiopia
spatio-temporal trend
water quality
title Geospatial modeling of water quality for emerging irrigation challenges in Ethiopia’s Awash Basin
title_full Geospatial modeling of water quality for emerging irrigation challenges in Ethiopia’s Awash Basin
title_fullStr Geospatial modeling of water quality for emerging irrigation challenges in Ethiopia’s Awash Basin
title_full_unstemmed Geospatial modeling of water quality for emerging irrigation challenges in Ethiopia’s Awash Basin
title_short Geospatial modeling of water quality for emerging irrigation challenges in Ethiopia’s Awash Basin
title_sort geospatial modeling of water quality for emerging irrigation challenges in ethiopia s awash basin
topic awash river basin
bigdata analytics with giss
ethiopia
spatio-temporal trend
water quality
url https://jdmlm.ub.ac.id/index.php/jdmlm/article/view/16969
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AT tsegayaderaw geospatialmodelingofwaterqualityforemergingirrigationchallengesinethiopiasawashbasin
AT minaleshoamelese geospatialmodelingofwaterqualityforemergingirrigationchallengesinethiopiasawashbasin