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Selection of Rainwater Harvesting Sites by Using Remote Sensing and GIS Techniques: A Case Study of Dawa Sub Basin Southern Ethiopia

Received: 3 September 2020     Accepted: 19 September 2020     Published: 23 November 2020
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Abstract

Water is one of the vital requirements for life, economic and social development. Water scarcity affects the environmental, economic and developmental activities of an area. The rainfall in the sub-basins is often very local, erratic, unreliable and unevenly distributed over the whole area of Dawa sub-basin. The pastoral and agro-pastoral communities are usually vulnerable to drought. The present study was an attempt to describe the state of Rain Water Harvesting (RWH) techniques and the contribution of Remote Sensing and GIS technologies for this RWH in the Dawa Sub basin. The study was conducted using physiographic factors of Dawa sub basin. Landsat image with spatial resolution 30m were used to identify LU/LC types. The thematic layers used were land use/land cover, slope, soil, drainage and runoff from derived from Landsat and collateral data. The image processing software Erdas IMAGINE and GIS software were used to process the image and to establish a geo information system by comprising digital data set of satellite image, topography, soil, metrology, drainage density and metrology. This data was used to study RWH was used to study the watershed network in the Dawa sub basin and to identify areas generally suitable for water harvesting in order to determine water harvesting techniques for those sites. Analytical Hierarchy Process (AHP) was used to calculate weighting and the analysis result indicates that the sub-basin supports promising opportunity for the establishment and development of RWH structures. From the total area of 17,402.7 km2, The GIS evaluation predicts that 3,092.342 km2 (22.853%) is extremely suitable, 4,524.221 km2 (33.435%) is very suitable, 2,968.685 km2 (21.939%) is suitable, 1,988.986 km2 (14.7%) is less Suitable and 957.18 km2 (7.07%) is not suitable for RWH.

Published in American Journal of Modern Energy (Volume 6, Issue 4)
DOI 10.11648/j.ajme.20200604.12
Page(s) 84-94
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), 2020. Published by Science Publishing Group

Keywords

GIS, Rainwater Harvesting (RWH), Remote Sensing (RS), Dawa Sub Basin

References
[1] D. Ramakrishnan, A. Bandyopadhyay, and K. N. Kusuma, “SCSCN and GIS-based approach for identifying potential water harvesting sites in the Kali Watershed, Mahi River Basin, India,” Journal of Earth System Science, vol. 118, no. 4, pp. 355–368, 2009.
[2] Kulkarni SJ. (2016). Review on studies, research and surveys on rainwater harvesting. Int J Res Rev.; 3 (9): 6-11.
[3] Kanime, N., R. Kaushal, S. K. Tewari, K. P. Raverkar, S. Chaturvedi and O. P. Chaturvedi. 2013. Biomass production and carbon sequestration in different trees based systems of central Himalaan Tarai region. Forests, Trees and Livelihoods, 22 (1): 38-50.
[4] Demisachew T. and Abiyot L., (2019). “Assessment of water resources management and past works on water points development in Borana Rangelands, Southern Oromia, Ethiopia.” International Journal of Water Resources and Environmental Engineering, Vol. 11 (2), pp. 39-44.
[5] Lillesand, T. M. and Kiefer, R. W. (2000): Remote Sensing and Image Interpretation. 4th ed. John Wiley and Sons, New York.
[6] Coppock, D. L., 1994. The Borana Plateau of Southern Ethiopia: Synthesis of pastoral research, development and change, 1980-91. Int. Livest. Centre for Africa, ILCA Systems Study.
[7] Amarea, A.; Simaneb, B.; Nyangagac, J.; Defisaa, A.; Hamzaa, D.; Gurmessaa, B., (2019). “Index-based livestock insurance to manage climate risks in Borena zone of southern Oromia, Ethiopia.” Clim. Risk Manag. 2019, 25, 100191. Hare, 1983, Climate and Desertification.
[8] OWWDSE 2010, “Borana ILUP Study Project-Dawa Sub-basin”.
[9] Donahue, Roy L., Raymond W. Miller, and John C. Shikluna. 1983. Soils: and introduction to soils and plant growth. Fifth Edition. Prentice-Hall, Inc.: Englewood Cliffs, N. J.
[10] Ball, J. (2001). Soil and Water Relationships [htt:// www.noble.org/Soils/soilWater Relationships/Index.htm] site visited on 21/6/2005.
[11] Hatibu N. and Mahoo H. (2000). Rainwater Harvesting for Natural Resources Management. A planning guide for Tanzania. RELMA, Nairobi.
[12] Prinz, D., Oweis, T. and Oberle, A. (1998). Water Harvesting for Dry Land Agriculture Developing a Methodology Based on Remote Sensing and GIS. [www.ubka.uni-karlsruhe.de/indexer-vvv/1998/bau-verm/4-25k] site visited on 9/5/2004.
[13] Saaty, T. L. (1977). A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15, 234–281.
[14] Saaty, T. L., 1980. The analytical hierarchy process. New York: Wiley.
[15] Haile, G., and Suryabhagavan, K. V. (2018). GIS-based approach for identification of potential rainwater harvesting sites in Arsi Zone, Central Ethiopia. Modeling Earth Systems and Environment, 5, 353-367.
[16] Saaty TL, Vargas LG (1991) Prediction, projection and forecasting. Kluwer Academic Publishers, Dordrecht.
[17] Saaty, T. L., “How to make a decision: the Analytic Hierarchy Process”, Interfaces, Vol. 24, No. 6, pp 19–43, 1994.
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    Getachew Haile Wondimu, Dinku Shiferaw Jote. (2020). Selection of Rainwater Harvesting Sites by Using Remote Sensing and GIS Techniques: A Case Study of Dawa Sub Basin Southern Ethiopia. American Journal of Modern Energy, 6(4), 84-94. https://doi.org/10.11648/j.ajme.20200604.12

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    ACS Style

    Getachew Haile Wondimu; Dinku Shiferaw Jote. Selection of Rainwater Harvesting Sites by Using Remote Sensing and GIS Techniques: A Case Study of Dawa Sub Basin Southern Ethiopia. Am. J. Mod. Energy 2020, 6(4), 84-94. doi: 10.11648/j.ajme.20200604.12

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    AMA Style

    Getachew Haile Wondimu, Dinku Shiferaw Jote. Selection of Rainwater Harvesting Sites by Using Remote Sensing and GIS Techniques: A Case Study of Dawa Sub Basin Southern Ethiopia. Am J Mod Energy. 2020;6(4):84-94. doi: 10.11648/j.ajme.20200604.12

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  • @article{10.11648/j.ajme.20200604.12,
      author = {Getachew Haile Wondimu and Dinku Shiferaw Jote},
      title = {Selection of Rainwater Harvesting Sites by Using Remote Sensing and GIS Techniques: A Case Study of Dawa Sub Basin Southern Ethiopia},
      journal = {American Journal of Modern Energy},
      volume = {6},
      number = {4},
      pages = {84-94},
      doi = {10.11648/j.ajme.20200604.12},
      url = {https://doi.org/10.11648/j.ajme.20200604.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajme.20200604.12},
      abstract = {Water is one of the vital requirements for life, economic and social development. Water scarcity affects the environmental, economic and developmental activities of an area. The rainfall in the sub-basins is often very local, erratic, unreliable and unevenly distributed over the whole area of Dawa sub-basin. The pastoral and agro-pastoral communities are usually vulnerable to drought. The present study was an attempt to describe the state of Rain Water Harvesting (RWH) techniques and the contribution of Remote Sensing and GIS technologies for this RWH in the Dawa Sub basin. The study was conducted using physiographic factors of Dawa sub basin. Landsat image with spatial resolution 30m were used to identify LU/LC types. The thematic layers used were land use/land cover, slope, soil, drainage and runoff from derived from Landsat and collateral data. The image processing software Erdas IMAGINE and GIS software were used to process the image and to establish a geo information system by comprising digital data set of satellite image, topography, soil, metrology, drainage density and metrology. This data was used to study RWH was used to study the watershed network in the Dawa sub basin and to identify areas generally suitable for water harvesting in order to determine water harvesting techniques for those sites. Analytical Hierarchy Process (AHP) was used to calculate weighting and the analysis result indicates that the sub-basin supports promising opportunity for the establishment and development of RWH structures. From the total area of 17,402.7 km2, The GIS evaluation predicts that 3,092.342 km2 (22.853%) is extremely suitable, 4,524.221 km2 (33.435%) is very suitable, 2,968.685 km2 (21.939%) is suitable, 1,988.986 km2 (14.7%) is less Suitable and 957.18 km2 (7.07%) is not suitable for RWH.},
     year = {2020}
    }
    

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  • TY  - JOUR
    T1  - Selection of Rainwater Harvesting Sites by Using Remote Sensing and GIS Techniques: A Case Study of Dawa Sub Basin Southern Ethiopia
    AU  - Getachew Haile Wondimu
    AU  - Dinku Shiferaw Jote
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    N1  - https://doi.org/10.11648/j.ajme.20200604.12
    DO  - 10.11648/j.ajme.20200604.12
    T2  - American Journal of Modern Energy
    JF  - American Journal of Modern Energy
    JO  - American Journal of Modern Energy
    SP  - 84
    EP  - 94
    PB  - Science Publishing Group
    SN  - 2575-3797
    UR  - https://doi.org/10.11648/j.ajme.20200604.12
    AB  - Water is one of the vital requirements for life, economic and social development. Water scarcity affects the environmental, economic and developmental activities of an area. The rainfall in the sub-basins is often very local, erratic, unreliable and unevenly distributed over the whole area of Dawa sub-basin. The pastoral and agro-pastoral communities are usually vulnerable to drought. The present study was an attempt to describe the state of Rain Water Harvesting (RWH) techniques and the contribution of Remote Sensing and GIS technologies for this RWH in the Dawa Sub basin. The study was conducted using physiographic factors of Dawa sub basin. Landsat image with spatial resolution 30m were used to identify LU/LC types. The thematic layers used were land use/land cover, slope, soil, drainage and runoff from derived from Landsat and collateral data. The image processing software Erdas IMAGINE and GIS software were used to process the image and to establish a geo information system by comprising digital data set of satellite image, topography, soil, metrology, drainage density and metrology. This data was used to study RWH was used to study the watershed network in the Dawa sub basin and to identify areas generally suitable for water harvesting in order to determine water harvesting techniques for those sites. Analytical Hierarchy Process (AHP) was used to calculate weighting and the analysis result indicates that the sub-basin supports promising opportunity for the establishment and development of RWH structures. From the total area of 17,402.7 km2, The GIS evaluation predicts that 3,092.342 km2 (22.853%) is extremely suitable, 4,524.221 km2 (33.435%) is very suitable, 2,968.685 km2 (21.939%) is suitable, 1,988.986 km2 (14.7%) is less Suitable and 957.18 km2 (7.07%) is not suitable for RWH.
    VL  - 6
    IS  - 4
    ER  - 

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Author Information
  • Oromia Agricultural Research Institute, Addis Ababa, Ethiopia

  • Department of Environmental Sciences, College of Natural and Computational Science, Madda Walabu University, Oromia Ethiopia

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