| Peer-Reviewed

Soil Erosion Risk Assessment and Prioritization of Midhagdu Micro Watersheds for Conservation Measure Using RUSLE, GIS, RS and SPSS in Eastern, Ethiopia

Received: 9 March 2022     Accepted: 21 April 2022     Published: 7 May 2022
Views:       Downloads:
Abstract

Soil erosion is being detected as a risk to human survival by diminishing the food and water availability of the planet Earth in the 21st century. Assessment and management of this resource are becoming extremely important. This study aimed to investigate Soil Erosion Risk and Prioritize for soil and water conservation measures in the study area. Satellite data, SRTM DEM, Land sat 8 OLI with 30m resolution; rainfall and soil data were used to generate all soil erosion risk factor maps and integrated to generate a composite map of soil loss for the watershed. The RUSLE model in combination with remote sensing and GIS techniques was used to identify the five thematic maps as an input to estimate mean annual soil loss. The results of the spatial distribution of soil erosion risk factors indicated that rainfall erosivity, soil erodibility, slope length and steepness, cover management, and anthropogenic soil erosion control practices values ranged from 41.365 to 43.793MJ mm ha−1yr−1, 0.26 to 0.31t ha−1MJ−1mm−1, 0 to 220.512, 0.21 to 0.87 and 0.11 to 1 respectively. And the most powerful factor that influences soil erosion risk is topography followed by anthropogenic soil erosion control practices. The results of the study showed that the annual soil loss rate in the watershed ranged from 0 in gentle slopes to 1504 t ha-1yr-1 at the steepest slope of the watershed with a mean annual soil loss of 48.5 t ha-1yr-1 at Midhagdu watershed level. The soil loss map was categorized into five soil loss numerical ranges and soil loss risk nominal scales: low, moderate, high, very high, and extremely high using Ethiopian highland maximum soil loss threshold level 18 t ha-1yr-1. The soil loss risk levels identified at 28 micro watersheds showed that twelve micro watersheds rated as first, eleven micro watersheds as second, and three micro watersheds as the third priority for soil and water conservation measures implementation. Out of 28 micro watersheds, 26 fell above Ethiopian highland maximum soil loss threshold levels. Therefore, the study result indicated that the Midhagdu watershed needs immediate intervention for better for soil and water conservation measures implementation planning by considering identified soil erosion risk areas and priority classes to control soil erosion risk below the national threshold level.

Published in International Journal of Environmental Monitoring and Analysis (Volume 10, Issue 3)
DOI 10.11648/j.ijema.20221003.11
Page(s) 45-58
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Erosion Risk, Micro Watershed, Midhagdu, Prioritization, RUSLE Model, Soil and Water Conservation Measures

References
[1] Alexandridis, T. K., Sotiropoulou, A. M., Bilas, G., Karapetsas, N., Silleos, NG. 2015. The effects of seasonality in estimating the C-factor of soil Erosion studies. Land Degradation and Development, 26: 596–603.
[2] Legese, K. G. and Gelanew, A. 2019. Soil degradation extent and dynamics of soil fertility improvement technologies In Majete Watershed, North Ethiopia, 10 (3): 39-45.
[3] Sumudu, S., Biswajeet, P., Alfredo, H., and Jane B. 2020. A Review on Assessing and Mapping Soil ErosionHazard Using Geo-Informatics Technology for farming System Management, Remote Sensing, 12: 1-25.
[4] Gnacadja, L., 2012. From combating desertification in drylands to global land degradation neutrality – the Zero Net Land Degradation. TheBen-Gurion University of the Negev.
[5] Arekhi, S., 2008. Evaluating Long Term annual Sediment yields Estimation Potential of GIS Interface MUSLE Model on Two Micro-Watersheds, Pakistan. Journal of Biological Sciences 11 (2): 270-274.
[6] Bewket, W., Teferi, E. 2009. Assessment of soil erosion hazard and prioritization for treatment at the watershed level: case study in the Chemoga watershed, Blue Nile basin, Ethiopia. Land Degradation and Development. 20 (6): 609–622.
[7] Hailu, M. Ch. andBiru, J. D. 2019. A Geographic Information System Based Soil Erosion Assessment for Conservation Planning at West Hararghe, Eastern Ethiopia. Civil and Environmental Research, 11 (2).
[8] El Gaatib, R., Larabi, A., Faouzi, M. 2015. Integrated elaboration of priority planning of vulnerable areas to soil erosion hazard using Remote Sensing and GIS techniques: A pilot case of the Oued Beth Watershed (Morocco). Journal of matter and environmental science, 6 (11): 3110-3127.
[9] Belayneh, M., Yirgu, T., Tsegaye, D. 2019. Potential Soil Erosion Estimation and Area Prioritization for Better Conservation Planning in Gumera Watershed Using RUSLE and GIS Techniques. Environmental Systems Research, Mettu University, Mettu, Ethiopia 8 (20): 1-17.
[10] Ahmed, I., Das, N., Debnath, J., and Bhowmik, M. 2017. An Assessment to Prioritize the critical Erosion-Prone Sub-watersheds for Soil Conservation in the Gumti Basin of Tripura, North-East India, 10 (22): 1-18.
[11] Afera, H., Asirat, T. and Ermias, S. 2019. GIS-Based MCDA Model to Assess Erosion Sensitivity in Gumara watershed, Blue Nile, Basin Ethiopia. Asian Journal of Applied Sciences, 12 (2): 61-70.
[12] Tizita, E. 2016. Dynamics of Soil Physico-Chemical Properties in Area Closures at Hirna Watershed of West Hararghe Zone of Oromia Region, Ethiopia. International Journal of Soil Science, 11 (1): 1-8.
[13] Dessalegn, W. 2018. Theoretical and Empirical Review of Ethiopian Water Resource Potentials, Challenges, and Future Development Opportunities. International Journal of Waste Resources, 8 (4): 1-7.
[14] TWOoECP (TuloWoreda Office of Economic Cooperation and Planning). 2018. Tulo District Socioeconomic Information.
[15] Amsalu, T., and Mengaw, A. 2014. GIS-Based Soil Loss Estimation Using RUSLE Model: The Case of JabiTehinanWoreda, Amhara National Regional State, Ethiopia. Natural Resources, 5 (11): 616-626.
[16] Wischmeier, W., and Smith, D. 1978. Predicting Rainfall Erosion Losses: a Guide to Conservation Planning. U.S. Department of Agriculture Handbook No. 537. The U.S.A.
[17] Renard, K. G., Foster, G. R., Weesies, G. A., McCool, and Yoder, D. C., 1997. Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE). USDA, Agriculture Handbook, 703: 382.
[18] Nyssen, J., Poesen, J. and Gebremichael, D. 2007. On-site evaluation of stone bunds to control soil erosion on cropland in northern Ethiopia. Soil and Tillage Research, 94: 151–163.
[19] Negese, A., Fekadu, E. and Getnet, H. 2021. Potential Soil Loss Estimation and Erosion-Prone Area Prioritization Using RUSLE, GIS, and Remote Sensing in Chereti Watershed, Northeastern Ethiopia. Air, Soil and Water Research, 14: 1–17.
[20] Mesfin, G., Mamo, Y. Mohammed, Y., Mohammed, D. 2019. Potential Soil Erosion Mapping Using RUSLE, Remote Sensing and GIS: The Case Study of WolaitaSodo Town and Surrounding Area, SNNPR, Ethiopia. International Journal of Science, Engineering, and Technology. 7: 1.
[21] Morgan, R. P. C. 1996. Soil erosion and conservation: 2nd ed. Essex, UK: Longman Limited Group.
[22] P. Mhangara, V., Kakembo and K. Lim. 2012. “Soil Erosion Risk Assessment of the Keiskamma Catchment, South Africa Using GIS and Remote Sensing,” Environmental Earth Science, 65 (7): 2087-2102.
[23] Geleta, H. I. 2011. Watershed Sediment Yield Modeling for Data Scarce Areas. Ph.D. Dissertation, University of Stuttgart.
[24] George Ashiagbor, Eric K Forkuo, Prosper Laari, Raymond Aabeyir. 2013. MODELING SOIL EROSION USING RUSLE AND GIS TOOLS, International Journal of Remote Sensing and Geoscience (IJRSG), 2 (4): 1-17.
[25] Van der Knijff, J. M., Jones R. J. A and Montanarella, L. 1999. Soil erosion risk assessment in Italy, European Soil Bureau. EUR 19044 EN.
[26] Van der Knijff, J. M., Jones, R. J. A. and Montanarella, L. 2000. Soil erosion risk assessment in Italy. European Soil Bureau, Joint Research Center of the European Commission. In press.
[27] Alkharabsheha, M. Alexandridis, M., Bilas, T. K., Misopolinos, G. and Silleos, N. 2013. Impact of land cover change on soil erosion hazard in northern Jordan using remote sensing and GIS. Procedia Environmental Sciences 19: 912–921.
[28] Kamuju, N. 2016. Spatial Identification and Classification of Soil erosion-prone zones using remote sensing and GIS integrated ‘RUSLE’Model and ‘SATEEC GIS system’. 5 (10): 676-686.
[29] Wang, G. Q., Jiang, H., Xu, Z. X., Wang, L. J., Yue, W. F. 2012. Evaluating the effect of land-use changes on soil erosion and sediment yield using a grid-based distributed modeling approach. Hydrology Process, 26 (23): 3579–3592.
[30] Moore, I. D., and Burch, G. J. 1986. Modeling erosion and deposition. Topographic effects. Transactions of the ASABE, 29 (6), 1624–1630.
[31] Pandey, A., Chowdary, VM., Mal, BC. 2007. Identification of criticalerosion-prone areas in the small agricultural watershed using USLE, GIS, and Remote Sensing. Water Resource Management, 21: 729-746.
[32] Shi, Z. H., Cai, C. F., Ding, S. W., Li, Z. X., Wang, T. W. and Sun, Z. C. 2002. Assessment of Erosion Risk with the RUSLE and GIS in the Middle and Lower Reaches of Hanjiang River. Huazhong Agricultural University, Wuhan, 430070, the People’s Republic of China, 12th ISCO Conference, 73-78.
[33] Markose, V. J, Jayappa, K. S. 2016. Soil loss estimation and prioritization of sub-watersheds of Kali River basin, Karnataka, India, using RUSLE and GIS. Environmental Monitoring Assessment, 188: 225.
[34] Silva, R. M., Montenegro, S. M. G. L., Santos, C. A. G. 2012. Integration of GIS and remote sensing for estimation of soil loss and prioritization of critical sub-catchments: a case study of Tapacura catchment. Natural Hazards, 62: 953–970.
[35] Kushwah, A N. L. and Bhardwaj, A. 2020. Micro-watershed Prioritization Using RUSLE, remote sensing and GIS, 585-590.
[36] Girmay, G., Moges, A., Muluneh, A. 2021. Assessment of Current and Future Climate Change Impact on Soil Loss Rate of Agewmariam Watershed, Northern Ethiopia, Air, Soil and Water Research, 14: 1-11.
Cite This Article
  • APA Style

    Sultan Mohammed Heyder, Abdurahman Ousman Dansa, Solomon Asfaw, Solomon Tekalign. (2022). Soil Erosion Risk Assessment and Prioritization of Midhagdu Micro Watersheds for Conservation Measure Using RUSLE, GIS, RS and SPSS in Eastern, Ethiopia. International Journal of Environmental Monitoring and Analysis, 10(3), 45-58. https://doi.org/10.11648/j.ijema.20221003.11

    Copy | Download

    ACS Style

    Sultan Mohammed Heyder; Abdurahman Ousman Dansa; Solomon Asfaw; Solomon Tekalign. Soil Erosion Risk Assessment and Prioritization of Midhagdu Micro Watersheds for Conservation Measure Using RUSLE, GIS, RS and SPSS in Eastern, Ethiopia. Int. J. Environ. Monit. Anal. 2022, 10(3), 45-58. doi: 10.11648/j.ijema.20221003.11

    Copy | Download

    AMA Style

    Sultan Mohammed Heyder, Abdurahman Ousman Dansa, Solomon Asfaw, Solomon Tekalign. Soil Erosion Risk Assessment and Prioritization of Midhagdu Micro Watersheds for Conservation Measure Using RUSLE, GIS, RS and SPSS in Eastern, Ethiopia. Int J Environ Monit Anal. 2022;10(3):45-58. doi: 10.11648/j.ijema.20221003.11

    Copy | Download

  • @article{10.11648/j.ijema.20221003.11,
      author = {Sultan Mohammed Heyder and Abdurahman Ousman Dansa and Solomon Asfaw and Solomon Tekalign},
      title = {Soil Erosion Risk Assessment and Prioritization of Midhagdu Micro Watersheds for Conservation Measure Using RUSLE, GIS, RS and SPSS in Eastern, Ethiopia},
      journal = {International Journal of Environmental Monitoring and Analysis},
      volume = {10},
      number = {3},
      pages = {45-58},
      doi = {10.11648/j.ijema.20221003.11},
      url = {https://doi.org/10.11648/j.ijema.20221003.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20221003.11},
      abstract = {Soil erosion is being detected as a risk to human survival by diminishing the food and water availability of the planet Earth in the 21st century. Assessment and management of this resource are becoming extremely important. This study aimed to investigate Soil Erosion Risk and Prioritize for soil and water conservation measures in the study area. Satellite data, SRTM DEM, Land sat 8 OLI with 30m resolution; rainfall and soil data were used to generate all soil erosion risk factor maps and integrated to generate a composite map of soil loss for the watershed. The RUSLE model in combination with remote sensing and GIS techniques was used to identify the five thematic maps as an input to estimate mean annual soil loss. The results of the spatial distribution of soil erosion risk factors indicated that rainfall erosivity, soil erodibility, slope length and steepness, cover management, and anthropogenic soil erosion control practices values ranged from 41.365 to 43.793MJ mm ha−1yr−1, 0.26 to 0.31t ha−1MJ−1mm−1, 0 to 220.512, 0.21 to 0.87 and 0.11 to 1 respectively. And the most powerful factor that influences soil erosion risk is topography followed by anthropogenic soil erosion control practices. The results of the study showed that the annual soil loss rate in the watershed ranged from 0 in gentle slopes to 1504 t ha-1yr-1 at the steepest slope of the watershed with a mean annual soil loss of 48.5 t ha-1yr-1 at Midhagdu watershed level. The soil loss map was categorized into five soil loss numerical ranges and soil loss risk nominal scales: low, moderate, high, very high, and extremely high using Ethiopian highland maximum soil loss threshold level 18 t ha-1yr-1. The soil loss risk levels identified at 28 micro watersheds showed that twelve micro watersheds rated as first, eleven micro watersheds as second, and three micro watersheds as the third priority for soil and water conservation measures implementation. Out of 28 micro watersheds, 26 fell above Ethiopian highland maximum soil loss threshold levels. Therefore, the study result indicated that the Midhagdu watershed needs immediate intervention for better for soil and water conservation measures implementation planning by considering identified soil erosion risk areas and priority classes to control soil erosion risk below the national threshold level.},
     year = {2022}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Soil Erosion Risk Assessment and Prioritization of Midhagdu Micro Watersheds for Conservation Measure Using RUSLE, GIS, RS and SPSS in Eastern, Ethiopia
    AU  - Sultan Mohammed Heyder
    AU  - Abdurahman Ousman Dansa
    AU  - Solomon Asfaw
    AU  - Solomon Tekalign
    Y1  - 2022/05/07
    PY  - 2022
    N1  - https://doi.org/10.11648/j.ijema.20221003.11
    DO  - 10.11648/j.ijema.20221003.11
    T2  - International Journal of Environmental Monitoring and Analysis
    JF  - International Journal of Environmental Monitoring and Analysis
    JO  - International Journal of Environmental Monitoring and Analysis
    SP  - 45
    EP  - 58
    PB  - Science Publishing Group
    SN  - 2328-7667
    UR  - https://doi.org/10.11648/j.ijema.20221003.11
    AB  - Soil erosion is being detected as a risk to human survival by diminishing the food and water availability of the planet Earth in the 21st century. Assessment and management of this resource are becoming extremely important. This study aimed to investigate Soil Erosion Risk and Prioritize for soil and water conservation measures in the study area. Satellite data, SRTM DEM, Land sat 8 OLI with 30m resolution; rainfall and soil data were used to generate all soil erosion risk factor maps and integrated to generate a composite map of soil loss for the watershed. The RUSLE model in combination with remote sensing and GIS techniques was used to identify the five thematic maps as an input to estimate mean annual soil loss. The results of the spatial distribution of soil erosion risk factors indicated that rainfall erosivity, soil erodibility, slope length and steepness, cover management, and anthropogenic soil erosion control practices values ranged from 41.365 to 43.793MJ mm ha−1yr−1, 0.26 to 0.31t ha−1MJ−1mm−1, 0 to 220.512, 0.21 to 0.87 and 0.11 to 1 respectively. And the most powerful factor that influences soil erosion risk is topography followed by anthropogenic soil erosion control practices. The results of the study showed that the annual soil loss rate in the watershed ranged from 0 in gentle slopes to 1504 t ha-1yr-1 at the steepest slope of the watershed with a mean annual soil loss of 48.5 t ha-1yr-1 at Midhagdu watershed level. The soil loss map was categorized into five soil loss numerical ranges and soil loss risk nominal scales: low, moderate, high, very high, and extremely high using Ethiopian highland maximum soil loss threshold level 18 t ha-1yr-1. The soil loss risk levels identified at 28 micro watersheds showed that twelve micro watersheds rated as first, eleven micro watersheds as second, and three micro watersheds as the third priority for soil and water conservation measures implementation. Out of 28 micro watersheds, 26 fell above Ethiopian highland maximum soil loss threshold levels. Therefore, the study result indicated that the Midhagdu watershed needs immediate intervention for better for soil and water conservation measures implementation planning by considering identified soil erosion risk areas and priority classes to control soil erosion risk below the national threshold level.
    VL  - 10
    IS  - 3
    ER  - 

    Copy | Download

Author Information
  • School of Geography and Environmental Studies, Climate Change and Disaster Risk Management Program, West Hararghe Agriculture and Natural Resource Office, Chiro, Ethiopia

  • College of Social Science and Humanities, Climate Change and Disaster Risk Management Program, West Hararghe High Court of Oromia Regional State, Chiro, Ethiopia

  • College of Social Science and Humanities, School of Geography and Environmental Studies, Haramaya University, Dire Dawa, Ethiopia

  • College of Social Science and Humanities, School of Geography and Environmental Studies, Haramaya University, Dire Dawa, Ethiopia

  • Sections