SpringerLink
Log in

Applications of Geospatial Technologies and Frequency Ratio Method in Groundwater Potential Map** in Iyenda River Catchment, Konso Area, Rift Valley, Ethiopia

  • Conference paper
  • First Online:
Recent Advances in Civil Engineering (CTCS 2021)

Part of the book series: Lecture Notes in Civil Engineering ((LNCE,volume 256))

Abstract

The present study aimed to map the potential groundwater zones in the Iyenda river catchment, Konso area, Rift Valley, Ethiopia. The potential groundwater zones were defined in this study using a frequency ratio (FR) model. The following nine thematic layers were considered in the present study, such as lithology, lineament density, slope, drainage density, land use/land cover (LULC), topographic wetness index (TWI), normalized difference vegetation index (NDVI), drainage density, rainfall, and soil types. The above-mentioned thematic layers were prepared using primary and satellite data in the ArcGIS software environment. During fieldwork, thirty-four water points, including deep bore wells, springs, and hand pump locations, were collected using GPS. In the FR model, 24 well points were used to calculate the success rate, and the rest ten well points were used to calculate the prediction rate. Groundwater prospect zones were further categorized into three groups: very good, moderate, and very low. Low groundwater prospective zones account for 39.23% of the current study, whereas medium and high potential groundwater zones account for 38.33 and 22.44%. The area under curve (AUC) technique was used to examine the accuracy of the potential groundwater zones. The AUC value for the success rate prediction rate is 0.735 and 0.732, respectively, and the same indicates the model produces excellent results in the current study. The findings of this study may aid in effective water resources management in the present study area, allowing planners and decision-makers to design suitable groundwater development plans for a sustainable environment.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Nampak H, Pradhan B, Abd Manap M (2014) Application of GIS based data driven evidential belief function model to predict groundwater potential zonation. J Hydrol 513:283–300

    Article  Google Scholar 

  2. Chen W, Li H, Hou E, Wang S, Wang G, Panahi M, Niu C (2018) GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models. Sci Total Environ 634:853–867

    Article  Google Scholar 

  3. Arulbalaji P, Padmalal D, Sreelash K (2019) GIS and AHP techniques based delineation of groundwater potential zones: a case study from southern Western Ghats, India. Sci Rep 9(1):1–17

    Article  Google Scholar 

  4. Das S (2019) Comparison among influencing factor, frequency ratio, and analytical hierarchy process techniques for groundwater potential zonation in Vaitarna basin, Maharashtra, India. Groundwater Sustain Dev 8:617–629

    Article  Google Scholar 

  5. Ahmed N, Hoque MAA, Pradhan B (2021) Spatio-temporal assessment of groundwater potential zone in the drought-prone area of Bangladesh using GIS-based bivariate models. Nat Resour Res. https://doi.org/10.1007/s11053-021-09870-0

    Article  Google Scholar 

  6. Mengistu HA, Demlie MB, Abiye TA (2019) Review: groundwater resource potential and status of groundwater resource development in Ethiopia. Hydrogeol J 27:1051–1065. https://doi.org/10.1007/s10040-019-01928-x

    Article  Google Scholar 

  7. Semu M (2012) Agricultural use of groundwater in Ethiopia: assessment of potential and analysis of economics, policies, constraints and opportunities. IWMI, Addis Ababa Ethiopia

    Google Scholar 

  8. Berhanu KG, Hatiye SD (2020) Identification of groundwater potential zones using proxy data: case study of Megech watershed, Ethiopia. J Hydrol Reg Stud 28:100676. https://doi.org/10.1016/J.EJRH.2020.100676

  9. Moges DM, Bhat HG, Thrivikramji KP (2019) Investigation of groundwater resources in highland Ethiopia using a geospatial technology. Model Earth Syst Environ 5:1333–1345. https://doi.org/10.1007/s40808-019-00603-0

    Article  Google Scholar 

  10. Ahmad I, Dar MA, Teka AH, Teshome M, Andualem TG, Teshome A, Shafi T (2020) GIS and fuzzy logic techniques-based demarcation of groundwater potential zones: a case study from Jemma River basin, Ethiopia. J Afr Earth Sci 169:103860. https://doi.org/10.1016/J.JAFREARSCI.2020.103860

  11. Tolche AD (2021) Groundwater potential map** using geospatial techniques: a case study of Dhungeta-Ramis sub-basin, Ethiopia. Geol Ecol Landscapes 5(1):65–80. https://doi.org/10.1080/24749508.2020.1728882

    Article  Google Scholar 

  12. MacDonald AM, Bonsor HC, Dochartaigh BÉÓ, Taylor RG (2012) Quantitative maps of groundwater resources in Africa. Environ Res Lett 7(2):024009. British Geological Survey Groundwater Programme Internal Report Ir/10/103. https://doi.org/10.1088/1748-9326/7/2/024009

  13. Das S, Pardeshi SD (2018) Morphometric analysis of Vaitarna and Ulhas river basins, Maharashtra, India: using geospatial techniques. Appl Water Sci 8:158. https://doi.org/10.1007/s13201-018-0801-z

  14. Kumar T, Gautam AK, Kumar T (2014) Appraising the accuracy of GIS-based multi-criteria decision making technique for delineation of groundwater potential zones. Water Resour Manag 28(13):4449–4466. https://doi.org/10.1007/s11269-014-0663-6

    Article  Google Scholar 

  15. Al-Shabeeb AA, Al-Adamat R, Al-Fugara A, Al-Amoush H, Al-Ayyash S (2018) Delineating groundwater potential zones within the Azraq basin of central Jordan using multi-criteria GIS analysis. Groundwater Sustain Dev 7:82–90. https://doi.org/10.1016/j.gsd.2018.03.011

  16. Senapati U, Das TK (2021) Assessment of basin-scale groundwater potentiality map** in drought-prone upper Dwarakeswar River basin, West Bengal, India, using GIS-based AHP techniques. Arab J Geosci 14:960. https://doi.org/10.1007/s12517-021-07316-8

    Article  Google Scholar 

  17. Muralitharan J, Palanivel K (2015) Groundwater targeting using remote sensing, geographical information system and analytical hierarchy process method in hard rock aquifer system, Karur district, Tamil Nadu, India. Earth Sci Inf 8:827–842. https://doi.org/10.1007/s12145-015-0213-7

    Article  Google Scholar 

  18. Mohammadi-Behzad HR, Charchi A, Kalantari N, Nejad AM, Vardanjani HK (2018) Delineation of groundwater potential zones using remote sensing (RS), geographical information system (GIS) and analytic hierarchy process (AHP) techniques: a case study in the Leylia–Keynow watershed, southwest of Iran. Carbonates Evaporites 34(4):1307–1319. https://doi.org/10.1007/S13146-018-0420-7

  19. Muniraj K, Jesudhas CJ, Chinnasamy A (2020) Delineating the groundwater potential zone in Tirunelveli Taluk, South Tamil Nadu, India, using remote sensing, geographical information system (GIS) and analytic hierarchy process (AHP) techniques. Proc Natl Acad Sci India Sect A Phys Sci 90(4):661–676. https://doi.org/10.1007/S40010-019-00608-5

    Article  Google Scholar 

  20. Andualem TG, Demeke GG (2019) Groundwater potential assessment using GIS and remote sensing: a case study of Guna tana landscape, upper blue Nile Basin, Ethiopia. J Hydrol Reg Stud 24:100610. https://doi.org/10.1016/J.EJRH.2019.100610

  21. Pourtaghi Z, Pourghasemi HR (2014) GIS-based groundwater spring potential assessment and map** in the Birjand Township, southern Khorasan Province, Iran. Hydrogeology 22:643–662. https://doi.org/10.1007/s10040-013-1089-6

  22. Razandi Y, Pourghasemi HR, Neisani NS, Rahmati O (2015) Application of analytical hierarchy process, frequency ratio, and certainty factor models for groundwater potential map** using GIS. Earth Sci Inf 8(4):867–883. https://doi.org/10.1007/s12145-015-0220-8

  23. Jothibasu A, Anbazhagan S (2016) Modeling groundwater probability index in Ponnaiyar River basin of South India using analytic hierarchy process model. Earth Syst Environ 2:109. https://doi.org/10.1007/s40808-016-0174

  24. Naghibi A, Pourghasemi HR (2015) A comparative assessment between three machine learning models and their performance comparison by bivariate and multivariate statistical methods for groundwater potential map** in Iran. Water Resour Manag 29(14):5217–5236. https://doi.org/10.1007/s11269-015-1114-8

  25. Zabihi M, Pourghasemi HR, Pourtaghi ZS, Behzadfar M (2016) GIS-based multivariate adaptive regression spline and random forest models for groundwater potential map** in Iran. Environ Earth Sci 75:665. https://doi.org/10.1007/s12665-016-5424-9

    Article  Google Scholar 

  26. Davoodi MD, Rezaei M, Pourghasemi HR, Pourtaghi ZS, Pradhan B (2015) Groundwater spring potential map** using bivariate statistical model and GIS in the Taleghan watershed Iran Arab. J Geosci 8:913–929. https://doi.org/10.1007/s12517-013-1161-5

    Article  Google Scholar 

  27. Manap MA, Nampak H, Pradhan B, Lee S, Sulaiman WNA, Ramli MF (2012) Application of probabilistic-based frequency ratio model in groundwater potential map** using remote sensing data and GIS. Arab J Geosci 7(2):711–724. https://doi.org/10.1007/S12517-012-0795-Z

  28. Guru B, Seshan K, Bera S (2017) Frequency ratio model for groundwater potential map** and its sustainable management in cold desert, India. J King Saud Univ Sci 29(3):333–347. https://doi.org/10.1016/J.JKSUS.2016.08.003

    Article  Google Scholar 

  29. Nejad SG, Falah F, Daneshfar M, Haghizadeh A, Rahmati O (2017) Delineation of groundwater potential zones using remote sensing and GIS-based data-driven models. Geocarto Int 32(2):167–187

    Google Scholar 

  30. Sahoo S, Munusamy SB, Dhar A, Kar A, Ram P (2017) Appraising the accuracy of multiclass frequency ratio and weights of evidence method for delineation of regional groundwater potential zones in canal command system. Water Resour Manag 31(14):4399–4413

    Article  Google Scholar 

  31. Jothimani M, Abebe A, Dawit Z (2020) Map** of soil erosion-prone sub-watersheds through drainage morphometric analysis and weighted sum approach: a case study of the Kulfo River basin, Rift valley, Arba Minch, Southern Ethiopia. Model Earth Syst Environ 6:2377–2389. https://doi.org/10.1007/s40808-020-00820-y

    Article  Google Scholar 

  32. Jothimani M, Abebe A, Duraisamy R (2021) Drainage morphometric analysis of Shope watershed, Rift Valley, Ethiopia: remote sensing and GIS-based approach. IOP Conf Ser Earth Environ Sci 796(1):012009. https://doi.org/10.1088/1755-1315/796/1/012009

  33. Ayazi MH, Pirasteh S, Arvin AKP, Pradhan B, Nikouravan B, Mansor S (2010) Disasters and risk reduction in groundwater: Zagros Mountain southwest Iran using geo-informatics techniques. Dis Adv 3(1):51–57

    Google Scholar 

  34. Anbazhagan S, Balamurugan G, Biswal TK (2011) Remote sensing in delineating deep fracture aquifer zones. In: Anbazhagan S, Subramanian SK, Yang X (eds) Geoinformatics in applied geomorphology. Taylor and Francis, CRC Press, pp 205–229

    Chapter  Google Scholar 

  35. Prasad RK, Mondal NC, Banerjee P, Nandakumar MV, Singh VS (2008) Deciphering potential groundwater zone in hard rock through the application of GIS. Environ Geol 55(3):467–475

    Article  Google Scholar 

  36. Maidment D (2002) ArcHydro GIS for water resources. ESRI Press, Redlands, CA

    Google Scholar 

  37. Bhattacharya AK (2010) Artificial ground water recharge with a special reference to India. Int J Res Rev Appl Sci 4:214–221

    Google Scholar 

  38. Das S, Gupta A, Ghosh S (2017) Exploring groundwater potential zones using MIF technique in semi-arid region: a case study of Hingoli district, Maharashtra. Spat Inf Res 25(6):749–756. https://doi.org/10.1007/s41324-017-0144-0

    Article  Google Scholar 

  39. Lone MS, Nagaraju D, Mahadavesamy G, Siddalingamurthy S (2013) Applications of GIS and remote sensing to delineate artificial recharge zones (DARZ) of groundwater in HD Kote taluk, Mysore district, Karnataka, India. Int J Remote Sens Geosci 2(3):92–97

    Google Scholar 

  40. Lillesand T, Kiefer RW, Chipman J (2007) Remote sensing and image interpretation. Wiley, Hoboken

    Google Scholar 

  41. Rajaveni SP, Brindha K, Elango L (2015) Geological and geomorphological controls on groundwater occurrence in a hard rock region. Appl Water Sci 7(3):1377–1389. https://doi.org/10.1007/s13201-015-0327-6

  42. Food and Agriculture Organization (FAO) (1997) The digital soil and terrain database of East Africa (SEA), via delle Terme di Caracalla, Rome, Italy

    Google Scholar 

  43. Sar N, Khan A, Chatterjee S (2015) Hydrologic delineation of ground water potential zones using geospatial technique for Keleghai river basin, India. Model Earth Syst Environ 1:25. https://doi.org/10.1007/s40808-015-0024-3

    Article  Google Scholar 

  44. Teshome A, Halefom A, Ahmad I (2020) Fuzzy logic techniques and GIS-based delineation of groundwater potential zones: a case study of Anger river basin, Ethiopia. Model Earth Syst Environ. https://doi.org/10.1007/s40808-020-01035-x

    Article  Google Scholar 

  45. Bonham-Carter GF (1994) Geographic information systems for geoscientists, modeling with GIS. Pergamon Press, Oxford

    Google Scholar 

  46. Pradhan B (2013) A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility map** using GIS. Comput Geosci 51:350–365

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the Arba Minch University, Ethiopia, for funding the present research (Grant No. GOV/AMU/TH4/GEOL/02/2011).

Author information

Authors and Affiliations

  1. Department of Geology, Arba Minch University, Arba Minch, Ethiopia

    Muralitharan Jothimani, Abel Abebe & Gosaye Berhanu

Authors
  1. Muralitharan Jothimani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Abel Abebe
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gosaye Berhanu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Muralitharan Jothimani .

Editor information

Editors and Affiliations

  1. Water Resources and Ocean Engineering, National Institute of Technology Karnataka, Mangalore, India

    Lakshman Nandagiri

  2. Department of Civil Engineering, National Institute of Technology Karnataka, Mangalore, India

    M. C. Narasimhan

  3. Civil Engineering, N.M.A.M. Institute of Technology, Karkala, Karnataka, India

    Shriram Marathe

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Jothimani, M., Abebe, A., Berhanu, G. (2023). Applications of Geospatial Technologies and Frequency Ratio Method in Groundwater Potential Map** in Iyenda River Catchment, Konso Area, Rift Valley, Ethiopia. In: Nandagiri, L., Narasimhan, M.C., Marathe, S. (eds) Recent Advances in Civil Engineering. CTCS 2021. Lecture Notes in Civil Engineering, vol 256. Springer, Singapore. https://doi.org/10.1007/978-981-19-1862-9_9

Download citation

  • DOI: https://doi.org/10.1007/978-981-19-1862-9_9

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-1861-2

  • Online ISBN: 978-981-19-1862-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation