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Erosion Sensitivity Mapping Using GIS and Multi-Criteria Decision Approach in Ribb Watershed Upper Blue Nile, Ethiopia

Received: 12 January 2019     Accepted: 14 February 2019     Published: 2 March 2019
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Abstract

Soil erosion considered as one of the most important obstacles in the way of sustainable development of agriculture and natural resources. In Ethiopia, soil erosion is a serious problem. The studies on erosion risk in the watershed show a trend towards increasing land use, accelerating erosion in the study area. The influencing factor for the give watershed are the land use, the elevation, the slope, TWI, SPI, and soil. This study focus to determine and mapping the hotspot areas to erosion of rib watershed with an area of 1174.7 km2. The sensitivity area for erosion was done by a multi-criteria decision evaluation method with parameters of influencing factors. The analysis of the maps using GIS analysis tools for different criteria which shows that the findings vary from one criterion to another. Considering all criteria, the finally obtained map shows that the areas with a high, moderate, low and very low vulnerability to erosion are 1.13%, 8.11%, 88.34% and 2.42% respectively in the given watershed. Overall, the soil erosion changes analysis and mapping as well as its distribution is effective and important for identifying natural resource prone areas. Therefore, the local experts and administrative bodies uses this information to prepare plan for those priority areas to conserve and monitor the degraded resources.

Published in International Journal of Energy and Environmental Science (Volume 3, Issue 6)
DOI 10.11648/j.ijees.20180306.11
Page(s) 99-111
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), 2019. Published by Science Publishing Group

Keywords

Soil Erosion, Ribb Watershed, MCE, GIS, Raster Calculator, Pairwise Comparison

References
[1] Borrelli, P., Van Oost, K., Meusburger, K., Alewell, C., Lugato, E. & Panagos, P. (2018). A Step towards a Holistic Assessment of Soil Degradation in Europe: Coupling on-Site Erosion with Sediment Transfer and Carbon Fluxes. Environmental Research, 161, 291-8.
[2] Tolosa, A. T., 2018. Evaluating the Dynamics of Land Use/Land Cover Change Using GIS and Remote Sensing Data in Case of Yewoll Watershed, Blue Nile Basin, Ethiopia.
[3] Rodrigo-Comino, J., Martínez-Hernández, C., Iserloh, T. & Cerdà, A. (2017). The Contrasted Impact of Land Abandonment on Soil Erosion in Mediterranean Agriculture Fields. Pedosphere.
[4] Mullan, D. (2013). Soil Erosion under the Impacts of Future Climate Change: Assessing the Statistical Significance of Future Changes and the Potential on-Site and Off- Site Problems. Catena, 109, 234-46.
[5] Halefom, A. and Teshome, A., 2019. Modelling and mapping of erosion potentiality watersheds using AHP and GIS technique: a case study of Alamata Watershed, South Tigray, Ethiopia. Modeling Earth Systems and Environment, pp. 1-13.
[6] Mekonnen, M. and Melesse, A. M., 2011. Soil erosion mapping and hotspot area identification using GIS and remote sensing in northwest Ethiopian highlands, near Lake Tana. In Nile River Basin (pp. 207-224). Springer, Dordrecht.
[7] Bewket, W. and 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 & Development, 20 (6), pp.609-622.
[8] Halefom, A., Teshome, A., Sisay, E. and Ahmad, I. (2018a) Dynamics of Land Use and Land Cover Change Using Remote Sensing and GIS: A Case Study of Debre Tabor Town, South Gondar, Ethiopia. Journal of Geographic Information System, 10, 165-174.
[9] Halefom, A., Teshome, A., Sisay, E., Khare, D., Dananto, M., Singh, L. and Tadesse, D., 2018b. Applications of Remote Sensing and GIS in Land Use/Land Cover Change Detection: A Case Study of Woreta Zuria Watershed, Ethiopia. Applied Research Journal of Geographic Information System Vol 1 (1), pp. 1-9.
[10] Halefom, A., Sisay, E., Worku, T., Khare, D., Dananto, M. and Narayanan, K., 2018c. Precipitation and Runoff Modelling in Megech Watershed, Tana Basin, Amhara Region of Ethiopia. American Journal of Environmental Engineering, 8 (3), pp.45-53.
[11] Tolosa, A. T., 2019. Modeling the Implication of Land Use Land Cover Change on Soil Erosion by Using Remote Sensing Data and GIS Based MCE Techniques in the Highlands of Ethiopia. International Journal of Environmental Monitoring and Analysis, 6 (6), p. 152.
[12] Hurni H. 1989. Soil for the Future. Environmental Research for Development Cooperation, Uni Press 62, University of Berne: Berne; 42–46.
[13] Kruger HJ, Berhanu F, Yohannes GM, Kefane K. 1996. Creating an inventory of indigenous soil and water conservation measures in Ethiopia. In Sustaining the Soil: Indigenous Soil and Water Conservation in Africa, Reij C, Scoones I, Toulmin C (eds). EarthScan Publications: London; 170–180.
[14] SCRP (Soil Conservation Research Programme). 1996. Soil Conservation Research Project Database Report 1982–1993. Ministry of Agriculture and University of Berne, Series Report III. Hundelafto Research Unit, Institute of Geography, University of Berne: Switzerland.
[15] Ethiopian Highlands Reclamation Study (EHRS). 1984. Annual Research Report (1983–984). Ministry of Agriculture: Addis Ababa.
[16] Voogd H. 1983. Multi-Criteria Evaluation for Urban and Regional Planning. Pion, Ltd.: London.
[17] Janssen R, Rietveld P. 1990. Multi-criteria Analysis and GIS: an application to agriculture land use in The Netherlands. In Geographical Information Systems for Urban and Regional Planning, Scholten H, Stilwell J. (eds.) Kluwer Academic Press: Dordrecht, The Netherlands; 129–138.
[18] Pereira JMC, Duckstein L. 1993. A multiple criteria decision-making approach to GIS-based land suitability evaluation. International Journal of Geographical Information Systems75: 407–424.
[19] Heywood I, Oliver J, Tomlinson S. 1995. Building an exploratory multi-criteria modelling environment for spatial decision support. In Innovations of GIS 2, Fisher P, (ed). Taylor and Francis: Leicester; 127–136.
[20] Malczewski JA. 1996. GIS-based approach to multiple criteria group decision-making. International Journal of Geographical Information Science 10 (8): 321–339.
[21] Tecle A, Yitayew M. 1990. Preference ranking of alternative irrigation technologies via a multi criterion decision making procedure. Transactions of ASAE3 (5): 1509–1517.
[22] Ceballos-Silva A, Lo’pez-Blanco J. 2003. Delineation of suitable areas for crops using a multi-criteria evaluation approach and land use/cover mapping: a case study in Central Mexico. Agricultural Systems 77: 117–136.
[23] Leskinena P, Kangas J. 2005. Multi-criteria natural resource management with preferentially dependent decision criteria. Journal of Environmental Management 77 (3): 244–251.
[24] Halefom, A., Sisay, E., Khare, D., Singh, L. and Worku, T., 2017. Hydrological modeling of urban catchment using semi-distributed model. Modeling Earth Systems and Environment, 3 (2), pp.683-692.
[25] Sisay, E., Halefom, A., Khare, D., Singh, L. and Worku, T., 2017. Hydrological modelling of ungauged urban watershed using SWAT model. Modeling Earth Systems and Environment, 3 (2), pp.693-702.
[26] Bello-Pineda J, Ponce-Hern´ andez R, Liceaga-Correa MA. 2006. Incorporating GIS and MCE for suitability assessment modelling of coral reef resources. Environmental Monitoring and Assessment114 (1–3): 225–256.
[27] Hajkowicz S, Higgins A. 2006. Comparisons of multiple criteria analysis techniques for water resource management. European Journal of Operational Research184 (1): 255–265.
[28] Lulseged, T. and Vlek, P. L. G. 2005. GIS-based landscape characterization to assess soil erosion and its delivery potential in the highlands of northern Ethiopia. In Proceedings of the 1st International Conference on Remote Sensing and Geo information processing in the assessment and monitoring of land degradation and desertification. 7–9 September, Trier, Germany. 332-339.
[29] Tripathi, M. P., Panda R. K. and Raghuwanshi, N. S. 2003. Identification and prioritization of critical sub-watersheds for soil conservation management using the SWAT model. Biosystems Engineering 85 (3), 365–379.
[30] Deore, S. J. 2005. Prioritization of Micro-watersheds of Upper Bhama Basin on the Basis of Soil Erosion Risk Using Remote Sensing and GIS Technology. PhD thesis, University of Pune, Pune.
[31] Alemu, A., Atnafu, A., Addis, Z., Shiferaw, Y., Teklu, T., Mathewos, B., Birhan, W., Gebretsadik, S. and Gelaw, B., 2011. Soil transmitted helminths and Schistosoma mansoni infections among school children in Zarima town, northwest Ethiopia. BMC infectious diseases, 11 (1), p.189.
[32] T. L. Saaty, 1980. “The Analytical Hierarchy Process,” McGraw- Hill, New York.
[33] V. Chankong and Y. Y. 1983. Haimes, “Multiobjective Decision Making: Theory and Methodology,” Elsevier-North Holland, New York.
[34] Abeyou Wale W., Amy S Collick, David G Rossiter, Simon Langan & Tammo S. Steenhuis 2013, Realistic assessment of irrigation potential in the Lake Tana basin, Ethiopia. Proceedings of the Nile Basin Development Challenge Science Meeting on Rainwater Management for Resilient Livelihoods.
[35] SaatyT. L. (1977) A scaling method for priorities in hierarchical structures, Journal of Mathematical Psychology 15, 234–281.
[36] Chapin, F. S., A. J. Bloom, C. B. Field, and R. H. Wari. 1987. Plant responses to multiple environmental factors. Bioscience 37 (1); 49–57.
Cite This Article
  • APA Style

    Afera Halefom, Asirat Teshome, Ermias Sisay, Mihret Dananto. (2019). Erosion Sensitivity Mapping Using GIS and Multi-Criteria Decision Approach in Ribb Watershed Upper Blue Nile, Ethiopia. International Journal of Energy and Environmental Science, 3(6), 99-111. https://doi.org/10.11648/j.ijees.20180306.11

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    ACS Style

    Afera Halefom; Asirat Teshome; Ermias Sisay; Mihret Dananto. Erosion Sensitivity Mapping Using GIS and Multi-Criteria Decision Approach in Ribb Watershed Upper Blue Nile, Ethiopia. Int. J. Energy Environ. Sci. 2019, 3(6), 99-111. doi: 10.11648/j.ijees.20180306.11

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    AMA Style

    Afera Halefom, Asirat Teshome, Ermias Sisay, Mihret Dananto. Erosion Sensitivity Mapping Using GIS and Multi-Criteria Decision Approach in Ribb Watershed Upper Blue Nile, Ethiopia. Int J Energy Environ Sci. 2019;3(6):99-111. doi: 10.11648/j.ijees.20180306.11

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  • @article{10.11648/j.ijees.20180306.11,
      author = {Afera Halefom and Asirat Teshome and Ermias Sisay and Mihret Dananto},
      title = {Erosion Sensitivity Mapping Using GIS and Multi-Criteria Decision Approach in Ribb Watershed Upper Blue Nile, Ethiopia},
      journal = {International Journal of Energy and Environmental Science},
      volume = {3},
      number = {6},
      pages = {99-111},
      doi = {10.11648/j.ijees.20180306.11},
      url = {https://doi.org/10.11648/j.ijees.20180306.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijees.20180306.11},
      abstract = {Soil erosion considered as one of the most important obstacles in the way of sustainable development of agriculture and natural resources. In Ethiopia, soil erosion is a serious problem. The studies on erosion risk in the watershed show a trend towards increasing land use, accelerating erosion in the study area. The influencing factor for the give watershed are the land use, the elevation, the slope, TWI, SPI, and soil. This study focus to determine and mapping the hotspot areas to erosion of rib watershed with an area of 1174.7 km2. The sensitivity area for erosion was done by a multi-criteria decision evaluation method with parameters of influencing factors. The analysis of the maps using GIS analysis tools for different criteria which shows that the findings vary from one criterion to another. Considering all criteria, the finally obtained map shows that the areas with a high, moderate, low and very low vulnerability to erosion are 1.13%, 8.11%, 88.34% and 2.42% respectively in the given watershed. Overall, the soil erosion changes analysis and mapping as well as its distribution is effective and important for identifying natural resource prone areas. Therefore, the local experts and administrative bodies uses this information to prepare plan for those priority areas to conserve and monitor the degraded resources.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - Erosion Sensitivity Mapping Using GIS and Multi-Criteria Decision Approach in Ribb Watershed Upper Blue Nile, Ethiopia
    AU  - Afera Halefom
    AU  - Asirat Teshome
    AU  - Ermias Sisay
    AU  - Mihret Dananto
    Y1  - 2019/03/02
    PY  - 2019
    N1  - https://doi.org/10.11648/j.ijees.20180306.11
    DO  - 10.11648/j.ijees.20180306.11
    T2  - International Journal of Energy and Environmental Science
    JF  - International Journal of Energy and Environmental Science
    JO  - International Journal of Energy and Environmental Science
    SP  - 99
    EP  - 111
    PB  - Science Publishing Group
    SN  - 2578-9546
    UR  - https://doi.org/10.11648/j.ijees.20180306.11
    AB  - Soil erosion considered as one of the most important obstacles in the way of sustainable development of agriculture and natural resources. In Ethiopia, soil erosion is a serious problem. The studies on erosion risk in the watershed show a trend towards increasing land use, accelerating erosion in the study area. The influencing factor for the give watershed are the land use, the elevation, the slope, TWI, SPI, and soil. This study focus to determine and mapping the hotspot areas to erosion of rib watershed with an area of 1174.7 km2. The sensitivity area for erosion was done by a multi-criteria decision evaluation method with parameters of influencing factors. The analysis of the maps using GIS analysis tools for different criteria which shows that the findings vary from one criterion to another. Considering all criteria, the finally obtained map shows that the areas with a high, moderate, low and very low vulnerability to erosion are 1.13%, 8.11%, 88.34% and 2.42% respectively in the given watershed. Overall, the soil erosion changes analysis and mapping as well as its distribution is effective and important for identifying natural resource prone areas. Therefore, the local experts and administrative bodies uses this information to prepare plan for those priority areas to conserve and monitor the degraded resources.
    VL  - 3
    IS  - 6
    ER  - 

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Author Information
  • Department of Hydraulic and Water Resourcing Engineering, Debre Tabor University, Debre Tabor, Ethiopia

  • Department of Hydraulic and Water Resourcing Engineering, Debre Tabor University, Debre Tabor, Ethiopia

  • Department of Hydraulic and Water Resourcing Engineering, Debre Tabor University, Debre Tabor, Ethiopia

  • Department of Water Supply and Environmental Engineering, Institute of Technology, Hawassa University, Hawassa, Ethiopia

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