Articles | Volume 18, issue 12
https://doi.org/10.5194/hess-18-5149-2014
https://doi.org/10.5194/hess-18-5149-2014
Research article
 | 
12 Dec 2014
Research article |  | 12 Dec 2014

Analyzing runoff processes through conceptual hydrological modeling in the Upper Blue Nile Basin, Ethiopia

M. Dessie, N. E. C. Verhoest, V. R. N. Pauwels, T. Admasu, J. Poesen, E. Adgo, J. Deckers, and J. Nyssen

Related authors

Uncovering a Key Predictors for Enhancing Daily Streamflow Simulation Using Machine Learning
Arash Aghakhani, David E. Robertson, and Valentijn R. N. Pauwels
EGUsphere, https://doi.org/10.5194/egusphere-2025-553,https://doi.org/10.5194/egusphere-2025-553, 2025
Short summary
Identification of compound drought and heatwave events on a daily scale and across four seasons
Baoying Shan, Niko E. C. Verhoest, and Bernard De Baets
Hydrol. Earth Syst. Sci., 28, 2065–2080, https://doi.org/10.5194/hess-28-2065-2024,https://doi.org/10.5194/hess-28-2065-2024, 2024
Short summary
Probabilistic Hydrological Estimation of LandSlides (PHELS): global ensemble landslide hazard modelling
Anne Felsberg, Zdenko Heyvaert, Jean Poesen, Thomas Stanley, and Gabriëlle J. M. De Lannoy
Nat. Hazards Earth Syst. Sci., 23, 3805–3821, https://doi.org/10.5194/nhess-23-3805-2023,https://doi.org/10.5194/nhess-23-3805-2023, 2023
Short summary
Impact of agricultural management on soil aggregates and associated organic carbon fractions: analysis of long-term experiments in Europe
Ioanna S. Panagea, Antonios Apostolakis, Antonio Berti, Jenny Bussell, Pavel Čermak, Jan Diels, Annemie Elsen, Helena Kusá, Ilaria Piccoli, Jean Poesen, Chris Stoate, Mia Tits, Zoltan Toth, and Guido Wyseure
SOIL, 8, 621–644, https://doi.org/10.5194/soil-8-621-2022,https://doi.org/10.5194/soil-8-621-2022, 2022
Short summary
Estimating global landslide susceptibility and its uncertainty through ensemble modeling
Anne Felsberg, Jean Poesen, Michel Bechtold, Matthias Vanmaercke, and Gabriëlle J. M. De Lannoy
Nat. Hazards Earth Syst. Sci., 22, 3063–3082, https://doi.org/10.5194/nhess-22-3063-2022,https://doi.org/10.5194/nhess-22-3063-2022, 2022
Short summary

Related subject area

Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Technical note: What does the Standardized Streamflow Index actually reflect? Insights and implications for hydrological drought analysis
Fabián Lema, Pablo A. Mendoza, Nicolás A. Vásquez, Naoki Mizukami, Mauricio Zambrano-Bigiarini, and Ximena Vargas
Hydrol. Earth Syst. Sci., 29, 1981–2002, https://doi.org/10.5194/hess-29-1981-2025,https://doi.org/10.5194/hess-29-1981-2025, 2025
Short summary
Long short-term memory networks for enhancing real-time flood forecasts: a case study for an underperforming hydrologic model
Sebastian Gegenleithner, Manuel Pirker, Clemens Dorfmann, Roman Kern, and Josef Schneider
Hydrol. Earth Syst. Sci., 29, 1939–1962, https://doi.org/10.5194/hess-29-1939-2025,https://doi.org/10.5194/hess-29-1939-2025, 2025
Short summary
Assessing the value of high-resolution rainfall and streamflow data for hydrological modeling: an analysis based on 63 catchments in southeast China
Mahmut Tudaji, Yi Nan, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 29, 1919–1937, https://doi.org/10.5194/hess-29-1919-2025,https://doi.org/10.5194/hess-29-1919-2025, 2025
Short summary
Catchments do not strictly follow Budyko curves over multiple decades, but deviations are minor and predictable
Muhammad Ibrahim, Miriam Coenders-Gerrits, Ruud van der Ent, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 1703–1723, https://doi.org/10.5194/hess-29-1703-2025,https://doi.org/10.5194/hess-29-1703-2025, 2025
Short summary
Scale dependency in modeling nivo-glacial hydrological systems: the case of the Arolla basin, Switzerland
Anne-Laure Argentin, Pascal Horton, Bettina Schaefli, Jamal Shokory, Felix Pitscheider, Leona Repnik, Mattia Gianini, Simone Bizzi, Stuart N. Lane, and Francesco Comiti
Hydrol. Earth Syst. Sci., 29, 1725–1748, https://doi.org/10.5194/hess-29-1725-2025,https://doi.org/10.5194/hess-29-1725-2025, 2025
Short summary

Cited articles

Abbaspour, K. C., Yang, J., Maximov, I., Siber, R., Bogner, K., Mieleitner, J., Zobrist, J., and Srinivasan, R.: Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT, J. Hydrol., 333, 413–430, 2007.
Allen, R. G., Pereira, L. S., Raes D., and Smith, M.: Crop evapotranspiration. Guide- lines for computing crop water requirements, FAO Irrigation and Drainage Paper 56, FAO, Rome, 1998.
Antar, M. A., Elassiouti, I., and Allam, M. N.: Rainfall-runoff modeling using artificial neural networks technique: a Blue Nile catchment case study, Hydrol. Process., 20, 1201–1216, 2006.
Arnold, J. G., Srinivasin, R., Muttiah, R. S., and Williams, J. R.: Large Area Hydrologic Modeling and Assessment: Part I. Model Development, JAWRA J. Am. Water Resour. Assoc., 34, 73–89, 1998.
Bayabil, H. K., Tilahun, S. A., Collick, A. S., and Steenhuis, T. S.: Are runoff processes ecologically or topographically driven in the Ethiopian Highlands? The case of the Maybar, Ecohydrology, 3, 457–466, https://doi.org/10.1002/eco.170, 2010.
Download
Short summary
In this study, topography is considered as a proxy for the variability of most of the catchment characteristics. The model study suggests that classifying the catchments into different runoff production areas based on topography and including the impermeable rocky areas separately in the modeling process mimics the rainfall–runoff process in the Upper Blue Nile basin well and yields a useful result for operational management of water resources in this data-scarce region.
Share