Modeling Earth Systems and Environment

, Volume 5, Issue 1, pp 353–367 | Cite as

GIS-based approach for identification of potential rainwater harvesting sites in Arsi Zone, Central Ethiopia

  • Getachew Haile
  • K. V. SuryabhagavanEmail author
Original Article


Water plays a crucial role in fulfilling basic human needs, for socio-economic developments and for ecosystem services. Ethiopia is experiencing pressure on water shortage for agricultural and domestic uses. Arsi Zone frequently faces drought and crop failure due to lack of water sources. Eleven physical characteristics of the study area layers were adopted integrating multi criteria decision analysis, which uses analytical hierarchy processes with a fuzzy logic approach and geographical information system. Soil conservation service model was used to estimate the runoff depth layer of the study area. Weighting was made based on environmental, socio-economical and hydro-geological characteristics of the study area, and available literature. Results show that potential suitability class was not suitable with constraints 5769.8 km2 (27.88%), less suitable 3104.34 km2 (15%), suitable 5695.42 km2 (27.52%), very suitable 4097 km2 (19.8%) and extremely suitable 2027.38 km2 (9.8%). The area coverage of constraints were 4540.37 km2 (21.94%) of the study area. Outcome of this study emphasized the importance of geospatial modeling in assessing rainwater harvesting potential sites, proposed to assist in planning water facility and to address water scarcity problem in the study area. The model developed in this research can be used in other areas to determine the potential of rainwater harvesting and integrate rainwater as an alternative water source to ensure availability for domestic, agricultural and industrial uses. It is recommended that detailed ground validation and socio-economic factors should be analyzed to increase its effectiveness before implementation.


Analytic hierarchy process Fuzzy logic Geographical information system Remote sensing Rainwater 



We are thankful to the School of Earth Sciences, Addis Ababa University for support, facilities and funds. We are also grateful to the National Metrological Agency and Oromia Agricultural Research Institute for providing necessary data to support this study. Mr. Getachew Haile indebted to Oromia Agricultural Research Institute for sponsoring for higher studies in Remote Sensing and Geoinformatics.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.School of Earth SciencesAddis Ababa UniversityAddis AbabaEthiopia

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