MCDA Approach for Identification of Rainwater Harvesting Site in Drought-Vulnerable Areas of Genale Dawa River Basin, Southern Ethiopia

Farmers in most parts of Ethiopia are limited in their ability to produce crops by a lack of rain and its inconsistency, and climate change may make matters worse. One of the most common natural disasters is drought because it depletes natural resources, causes environmental destruction, and destroys the ecology that supports all life. Water harvesting is a desirable strategy for mitigating this problem. However, the identification of optimal sites for rainwater harvesting (RWH) is an important step to maximize the amount of water harvested and minimize the ecological impact. In this study, the remotely sensed data and geospatial modeling with the analytical hierarchical process (AHP) and Multi-Criteria Decision Analysis (MCDA) approach were used to identify a potential site for rainwater harvesting in the drought-prone area of Genale Dawa River Basin. The analysis has taken into account several thematic layers, such as soil texture, soil depth, slope, rainfall, land use land cover, separation from a road and a settlement, and drainage density. To locate the potential site, the aforementioned thematic layers were given the appropriate weights based on their relative value by AHP integrated with a GIS environment. This study identifies five potential classifications on the suitability map range from extremely suitable to not suitable. According to our result, 11.4% of the study area is extremely suitable, 49% is highly suitable, 34.1% is moderately suitable, 5.4% is barely acceptable, and 0.02% is not suitable. The outcome of the suitability map is particularly practical for decision-makers and planners to choose the best locations for rainwater harvesting.

Authors

Institutions

Publication Details

Journal
Hydrospatial Analysis
Published
2025-03-14
DOI
https://doi.org/10.21523/gcj3.2025090102
Primary Topic
Soil and Land Suitability Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

MCDA Approach for Identification of Rainwater Harvesting Site in Drought-Vulnerable Areas of Genale Dawa River Basin, Southern Ethiopia

Gemechu Shuniye
Hydrospatial Analysis
Soil and Land Suitability Analysis
article

MCDA Approach for Identification of Rainwater Harvesting Site in Drought-Vulnerable Areas of Genale Dawa River Basin, Southern Ethiopia

Gemechu Shuniye
article en

Abstract

Farmers in most parts of Ethiopia are limited in their ability to produce crops by a lack of rain and its inconsistency, and climate change may make matters worse. One of the most common natural disasters is drought because it depletes natural resources, causes environmental destruction, and destroys the ecology that supports all life. Water harvesting is a desirable strategy for mitigating this problem. However, the identification of optimal sites for rainwater harvesting (RWH) is an important step to maximize the amount of water harvested and minimize the ecological impact. In this study, the remotely sensed data and geospatial modeling with the analytical hierarchical process (AHP) and Multi-Criteria Decision Analysis (MCDA) approach were used to identify a potential site for rainwater harvesting in the drought-prone area of Genale Dawa River Basin. The analysis has taken into account several thematic layers, such as soil texture, soil depth, slope, rainfall, land use land cover, separation from a road and a settlement, and drainage density. To locate the potential site, the aforementioned thematic layers were given the appropriate weights based on their relative value by AHP integrated with a GIS environment. This study identifies five potential classifications on the suitability map range from extremely suitable to not suitable. According to our result, 11.4% of the study area is extremely suitable, 49% is highly suitable, 34.1% is moderately suitable, 5.4% is barely acceptable, and 0.02% is not suitable. The outcome of the suitability map is particularly practical for decision-makers and planners to choose the best locations for rainwater harvesting.

Hydrospatial AnalysisVol. 9(1)
Wolkite University (ET)
Openalex Percentile: Top 93%
Soil and Land Suitability Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.