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Identifying Dominant Runoff Processes at a Regional Scale – A GIS - Based Approach

Babatunde Joseph Fagbohun
  • Corresponding author
  • Assistant Lecturer, Department of Remote Sensing and Geoscience Information System, Federal University of Technology, P.M.B 704, Akure, Nigeria
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  • Other articles by this author:
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/ Oluwaseun Franklin Olabode / Abiodun Olufemi Adebola
  • Lecturer II, Department of Remote Sensing and Geoscience Information System, Federal University of Technology, P.M.B 704, Akure, Nigeria
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Published Online: 2018-06-22 | DOI: https://doi.org/10.2478/pesd-2018-0002


Identifying landscapes with similar hydrological characteristics is useful for the determination of dominant runoff process (DRP) and flood prediction. Several approaches used for DRP-mapping differ in respect to time and data requirement. Manual approaches based on field investigation and expert knowledge are time consuming and difficult to implement at regional scale. Automatic GIS-based approach on the other hand require simplification of data but are easier to implement and it is applicable on regional scale. In this study, GIS-based automated approach was used to identify the DRPs in Anambra area. The result showed that Hortonian Overland Flow (HOF) has the highest coverage of 1508.3 Km2 (33.5%) followed by Deep Percolation (DP) with coverage of 1455.3 Km2 (32.3%). Subsurface Flow (SSF) is the third dominant runoff process covering 920.6 Km2 (20.4%) while Saturated Overland Flow (SOF) covers the least area of 618.4 Km2 (13.7%) of the study area. The result reveal that considerable amount of precipitated water would be infiltrated into the subsurface through deep percolation process contributing to groundwater recharge in the study area. However, it is envisaged that HOF and SOF will continue to increase due to the continuous expansion of built-up area. With the expected increase in HOF and SOF and the change in rainfall pattern associated with perpetual problem of climate change, it is paramount that groundwater conservation practices be considered to ensure continued sustainable utilization of groundwater in the study area.

Keywords: DRP; GIS; Remote sensing; Groundwater sustainability


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About the article

Published Online: 2018-06-22

Published in Print: 2018-06-01

Citation Information: Present Environment and Sustainable Development, Volume 12, Issue 1, Pages 19–33, ISSN (Online) 2284-7820, DOI: https://doi.org/10.2478/pesd-2018-0002.

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© 2018 Babatunde Joseph Fagbohun, published by Sciendo. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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