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Watershed prioritization for conservation planning using RUSLE and morphometric methods, Northwestern Ethiopia

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Abstract

Soil erosion and the subsequent sedimentation are serious environmental problems. Improper land management coupled with intense rainfall has complicated the problem in the Ethiopian highlands. Consequently, soil loss costs a profound amount of the national GDP and deters land productivity. Quantifying soil loss and prioritizing areas for conservation is imperative for proper planning and resource management. Therefore, this study aimed at estimating the mean annual soil loss rate of Gilgel Abay watershed which has critical implications on Lake Tana and Abbay River (Upper Blue Nile River), using RUSLE and morphometric analysis methods. Datasets including rainfall, soil, Digital Elevation Model and land use/land cover were used to generate important parameters required for the soil loss estimation. Data collected through field observation, consultation with experts and document analysis were used for validation purposes. The results of the study reveal that the watershed experienced an average soil loss rate of 39.8 t ha−1 yr−1. Subsequently, nearly 25% (37,038 ha) of the watershed is threatened by moderate to very severe soil loss. Among the four sub watersheds, sub watershed 3 (S3) and sub watershed 4 (S4), which consist of about 65% (105,000 ha) of the total area of the study watershed, experienced an annual soil loss rate of over 30 t ha−1 yr−1. The amount of soil loss that the study watershed has experienced is above the soil loss tolerance level of Ethiopia (2–18 t ha−1 yr−1) and the tropical region (10 t ha−1 yr−1). Similarly, the results of morphometric analysis showed that the studied watershed has S-shaped hypsometric curve, an indication for maturity stage of landscape development. The studied watershed is also characterized by a non-circular shaped drainage with rugged and dissected topography that contributes to high flash flood, peak discharge and incidence of soil loss. The result of both models signified that S3 and S4 are highly susceptible to soil erosion. Therefore, these two sub watersheds need priority for soil and water conservation (SWC) measures. Furthermore, the study demonstrated the importance of the integration of different models in the identification of soil erosion prone areas and prioritization for the proper implementation of SWC measures.

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Acknowledgments

This research didn’t receive any fund. The authors greatly acknowledge ANRS BoFED and MoA for providing soil data; Ethiopian Metrological Agency for providing metrological data and the North Gojjam Zone Agricultural office for their cooperation in collecting field data. We would also like to express our deepest gratitude to anonymous editors and reviewers for their inevitable and valuable comments for the betterment of this paper.

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Authors and Affiliations

  1. Department of General Forestry, Debre Markos University, Bure, 18, Ethiopia

    Agumassie Genet Gela

  2. Department of Geography and Environmental Studies, Bahir Dar University, Bahir Dar, 79, Ethiopia

    Daniel Ayalew Mengistu & Daniel Asfaw Bekele

  3. Geo-spatial Data and Technology Center (GDTC), Bahir Dar University, Bahir Dar, 79, Ethiopia

    Agumassie Genet Gela, Daniel Ayalew Mengistu & Daniel Asfaw Bekele

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  1. Agumassie Genet Gela
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  2. Daniel Ayalew Mengistu
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  3. Daniel Asfaw Bekele
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Contributions

Agumassie Genet Gela: Conceived and investigation, performed the experiments and analyzed and interpreted the data, wrote the paper. Daniel Ayalew Megistu: Conceived and review and editing the paper. Daniel Asfaw Bekele: Conceived and designed the experiments, validating the result and wrote and edit the paper

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Correspondence to Daniel Asfaw Bekele.

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Data Availability: The data are available from the corresponding author on reasonable request.

Conflict of Interest: The authors declare no conflict of interest.

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Gela, A.G., Mengistu, D.A. & Bekele, D.A. Watershed prioritization for conservation planning using RUSLE and morphometric methods, Northwestern Ethiopia. J. Mt. Sci. 20, 2242–2262 (2023). https://doi.org/10.1007/s11629-022-7742-6

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  • DOI: https://doi.org/10.1007/s11629-022-7742-6

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