Remote Sensing‐Based Ecohydrogeological Characterisation and Perceptual Model of the Bale Mountains, Ethiopia

ABSTRACT The Bale Mountains are a volcanic region in south‐central Ethiopia comprising Africa's largest alpine plateau and its adjacent montane forest. The region is recognised biologically as a centre of endemism, and hydrologically as a ‘water tower’, being the source of several rivers of critical importance for East Africa. However, little formal hydrologic data exist, and land management decisions are being made based largely on a mental model that assumes high vulnerability to changes in land use and land cover. We questioned this model using remote sensing data via Google Earth Engine to map spatial and temporal patterns of key hydrologic variables over the 20‐year period spanning 2001–2020. We combined a quantitative water balance analysis with qualitative interpretation of the region's geologic and geomorphic features. Our results show that, on average, annual evapotranspiration in the forested area exceeds annual precipitation. Evapotranspiration for the forest was seen to increase throughout the long dry season, exceeding its equilibrium value, suggesting that forest vegetation is neither water‐limited nor energy‐limited, and may be subsidised by groundwater and/or soil moisture flow derived from upslope areas and thermal vents. These results confound assumed relationships among forests, wetlands, and human activity embedded in much of the region's scientific research and conservation policies. We conclude by offering a new model and set of working hypotheses from which future scientific studies and management policies can benefit.

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Publication Details

Journal
Hydrological Processes
Published
2025-02-01
DOI
https://doi.org/10.1002/hyp.70006
Citations
1
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
1.11

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article

Remote Sensing‐Based Ecohydrogeological Characterisation and Perceptual Model of the Bale Mountains, Ethiopia

Yeonuk Kim, Stephen M. Chignell, Mark S. Johnson
1 citations
Hydrological Processes
Flood Risk Assessment and Management
1.11
article

Remote Sensing‐Based Ecohydrogeological Characterisation and Perceptual Model of the Bale Mountains, Ethiopia

Yeonuk Kim, Stephen M. Chignell, Mark S. Johnson
article en
1 citations

Abstract

ABSTRACT The Bale Mountains are a volcanic region in south‐central Ethiopia comprising Africa's largest alpine plateau and its adjacent montane forest. The region is recognised biologically as a centre of endemism, and hydrologically as a ‘water tower’, being the source of several rivers of critical importance for East Africa. However, little formal hydrologic data exist, and land management decisions are being made based largely on a mental model that assumes high vulnerability to changes in land use and land cover. We questioned this model using remote sensing data via Google Earth Engine to map spatial and temporal patterns of key hydrologic variables over the 20‐year period spanning 2001–2020. We combined a quantitative water balance analysis with qualitative interpretation of the region's geologic and geomorphic features. Our results show that, on average, annual evapotranspiration in the forested area exceeds annual precipitation. Evapotranspiration for the forest was seen to increase throughout the long dry season, exceeding its equilibrium value, suggesting that forest vegetation is neither water‐limited nor energy‐limited, and may be subsidised by groundwater and/or soil moisture flow derived from upslope areas and thermal vents. These results confound assumed relationships among forests, wetlands, and human activity embedded in much of the region's scientific research and conservation policies. We conclude by offering a new model and set of working hypotheses from which future scientific studies and management policies can benefit.

Hydrological ProcessesVol. 39(2)
University of British Columbia (CA)
Canadian Space Agency, Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 27%
Flood Risk Assessment and Management
1.11
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