Articles | Volume 28, issue 8
https://doi.org/10.5194/hess-28-1853-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-1853-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Unveiling hydrological dynamics in data-scarce regions: experiences from the Ethiopian Rift Valley Lakes Basin
Ayenew D. Ayalew
CORRESPONDING AUTHOR
Department of Hydrology and Water Resources Management, Christian-Albrechts-University, Kiel, Germany
Paul D. Wagner
Department of Hydrology and Water Resources Management, Christian-Albrechts-University, Kiel, Germany
Dejene Sahlu
Institute of Disaster Risk Management and Food Security Studies, Bahir Dar University, Bahir Dar, Ethiopia
Nicola Fohrer
Department of Hydrology and Water Resources Management, Christian-Albrechts-University, Kiel, Germany
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Cited
19 citations as recorded by crossref.
- Interpretable machine-learning intensity-duration-frequency (IDF) surface modeling in a data-scarce Ethiopian Rift Valley Lake Basin A. Tesfaye et al. https://doi.org/10.1016/j.ejrh.2026.103463
- Spatial Heterogeneity of Land Use and Land Cover Changes as a Driver of Disproportionate Hydrological Impacts in a Tropical Mountain Water Tower P. Ndung’u et al. https://doi.org/10.1007/s10666-025-10078-2
- Agricultural and meteorological drought variability assessment over the Rift Valley Lake Basin of Ethiopia T. Sinore et al. https://doi.org/10.1186/s12302-025-01238-y
- Groundwater Dynamics and Aquifer–Stream Interactions in California’s San Joaquin River Basin: Insights from a Coupled SWAT+ Gwflow Framework T. Tigabu et al. https://doi.org/10.3390/su18179111
- Lake-area shrinkage driven by the combined effects of climate change and human activities Q. Miao et al. https://doi.org/10.1016/j.ecolind.2025.113606
- Land-use change and lake eutrophication: Stakeholders’ perceptions on practices and policies in Ethiopia A. Debay et al. https://doi.org/10.1016/j.indic.2025.100880
- The Role of Metaheuristic Algorithms in Tuning Extreme Learning Machine Model for Lake Water Level Modeling G. Gelete et al. https://doi.org/10.1007/s11269-026-04633-z
- Modeling ecosystem dynamics and services in Abijata-Shalla Lakes National Park under pressures from land use and climate change B. Dadi et al. https://doi.org/10.1016/j.envc.2026.101515
- Climate-induced hydrological alterations in the Upper Blue Nile Basin, Ethiopia B. Tikuye et al. https://doi.org/10.1007/s40899-026-01339-3
- Impact of anthropogenic pollution on lake ecosystem: a review of Koka and Ziway lakes in the Central Rift Valley, Ethiopia M. Mito et al. https://doi.org/10.1007/s11356-025-37244-z
- Hydrochemical characterization and multivariate analysis of groundwater evolution in the Dabus River catchment, western Ethiopia G. Daddi et al. https://doi.org/10.1186/s12302-026-01392-x
- Deep Learning Algorithm and Physically‐Based Hybrid Models for Assessing Hydrological Water Balance Components Under Climate Variability and Land Use and Land Cover Change Using Earth Observations and Remote Sensing Data: The Case of Gumara Catchment, Lake Tana Sub‐Basin, Ethiopia A. Asitatikie et al. https://doi.org/10.1111/1752-1688.70119
- Bridging the gap: An interpretable coupled model (SWAT-ELM-SHAP) for blue-green water simulation in data-scarce basins Z. Guo et al. https://doi.org/10.1016/j.agwat.2024.109157
- Groundwater resource assessment methods in the Ethiopian Rift Valley Basin: a systematic review T. Takele et al. https://doi.org/10.1680/jenes.25.00189
- Climate change impacts on the small-scale hydropower potential for the Pungwe B hydropower scheme in Zimbabwe using a multi-model climate ensemble M. Muzava et al. https://doi.org/10.1016/j.pce.2025.104118
- Hybrid GR4J-LSTM modeling for streamflow prediction of extreme events in data-scarce regions: Upper Blue Nile Basin, Ethiopia T. Mihret et al. https://doi.org/10.1016/j.ejrh.2025.102977
- Integrated analysis of water storage variability using GRACE and SHETRAN modelling system in the Central Rift Valley basin of Ethiopia T. Tafesse et al. https://doi.org/10.1080/10106049.2025.2609391
- Hybrid emotional neural networks and novel multi-model stacking algorithms for multi-lake water level fluctuation modeling G. Gelete et al. https://doi.org/10.1007/s12145-025-01733-z
- Calibration and validation strategies of SWAT+ for streamflow simulation: a systematic review B. Admas et al. https://doi.org/10.3389/frwa.2026.1882804
19 citations as recorded by crossref.
- Interpretable machine-learning intensity-duration-frequency (IDF) surface modeling in a data-scarce Ethiopian Rift Valley Lake Basin A. Tesfaye et al. https://doi.org/10.1016/j.ejrh.2026.103463
- Spatial Heterogeneity of Land Use and Land Cover Changes as a Driver of Disproportionate Hydrological Impacts in a Tropical Mountain Water Tower P. Ndung’u et al. https://doi.org/10.1007/s10666-025-10078-2
- Agricultural and meteorological drought variability assessment over the Rift Valley Lake Basin of Ethiopia T. Sinore et al. https://doi.org/10.1186/s12302-025-01238-y
- Groundwater Dynamics and Aquifer–Stream Interactions in California’s San Joaquin River Basin: Insights from a Coupled SWAT+ Gwflow Framework T. Tigabu et al. https://doi.org/10.3390/su18179111
- Lake-area shrinkage driven by the combined effects of climate change and human activities Q. Miao et al. https://doi.org/10.1016/j.ecolind.2025.113606
- Land-use change and lake eutrophication: Stakeholders’ perceptions on practices and policies in Ethiopia A. Debay et al. https://doi.org/10.1016/j.indic.2025.100880
- The Role of Metaheuristic Algorithms in Tuning Extreme Learning Machine Model for Lake Water Level Modeling G. Gelete et al. https://doi.org/10.1007/s11269-026-04633-z
- Modeling ecosystem dynamics and services in Abijata-Shalla Lakes National Park under pressures from land use and climate change B. Dadi et al. https://doi.org/10.1016/j.envc.2026.101515
- Climate-induced hydrological alterations in the Upper Blue Nile Basin, Ethiopia B. Tikuye et al. https://doi.org/10.1007/s40899-026-01339-3
- Impact of anthropogenic pollution on lake ecosystem: a review of Koka and Ziway lakes in the Central Rift Valley, Ethiopia M. Mito et al. https://doi.org/10.1007/s11356-025-37244-z
- Hydrochemical characterization and multivariate analysis of groundwater evolution in the Dabus River catchment, western Ethiopia G. Daddi et al. https://doi.org/10.1186/s12302-026-01392-x
- Deep Learning Algorithm and Physically‐Based Hybrid Models for Assessing Hydrological Water Balance Components Under Climate Variability and Land Use and Land Cover Change Using Earth Observations and Remote Sensing Data: The Case of Gumara Catchment, Lake Tana Sub‐Basin, Ethiopia A. Asitatikie et al. https://doi.org/10.1111/1752-1688.70119
- Bridging the gap: An interpretable coupled model (SWAT-ELM-SHAP) for blue-green water simulation in data-scarce basins Z. Guo et al. https://doi.org/10.1016/j.agwat.2024.109157
- Groundwater resource assessment methods in the Ethiopian Rift Valley Basin: a systematic review T. Takele et al. https://doi.org/10.1680/jenes.25.00189
- Climate change impacts on the small-scale hydropower potential for the Pungwe B hydropower scheme in Zimbabwe using a multi-model climate ensemble M. Muzava et al. https://doi.org/10.1016/j.pce.2025.104118
- Hybrid GR4J-LSTM modeling for streamflow prediction of extreme events in data-scarce regions: Upper Blue Nile Basin, Ethiopia T. Mihret et al. https://doi.org/10.1016/j.ejrh.2025.102977
- Integrated analysis of water storage variability using GRACE and SHETRAN modelling system in the Central Rift Valley basin of Ethiopia T. Tafesse et al. https://doi.org/10.1080/10106049.2025.2609391
- Hybrid emotional neural networks and novel multi-model stacking algorithms for multi-lake water level fluctuation modeling G. Gelete et al. https://doi.org/10.1007/s12145-025-01733-z
- Calibration and validation strategies of SWAT+ for streamflow simulation: a systematic review B. Admas et al. https://doi.org/10.3389/frwa.2026.1882804
Saved (final revised paper)
Latest update: 09 Oct 2026
Short summary
The study presents a pioneering comprehensive integrated approach to unravel hydrological complexities in data-scarce regions. By integrating diverse data sources and advanced analytics, we offer a holistic understanding of water systems, unveiling hidden patterns and driving factors. This innovative method holds immense promise for informed decision-making and sustainable water resource management, addressing a critical need in hydrological science.
The study presents a pioneering comprehensive integrated approach to unravel hydrological...