Advertisement

Arabian Journal for Science and Engineering

, Volume 42, Issue 6, pp 2487–2499 | Cite as

A GIS-Based Integrated Fuzzy Logic and Analytic Hierarchy Process Model for Assessing Water-Harvesting Zones in Northeastern Maysan Governorate, Iraq

  • Alaa M. Al-AbadiEmail author
  • Shamsuddin Shahid
  • Hussein B. Ghalib
  • Amna M. Handhal
Research Article - Earth Sciences

Abstract

Identifying potential sites for water harvesting (WH) is a crucial task for efficient water resources management in arid regions. In response, this paper proposes a geographical information system-based model that combines fuzzy logic and analytic hierarchy process (AHP) to delineate suitable areas for constructing WH structures in arid southern Iraq. Based on a literature review and available data, five influential factors were selected to develop the model: hydrological soil group, land cover, surface runoff depth, slope, and distance to an intermittent river. A fuzzy logic-based approach was used to standardize the factors, and AHP was used to derive weights. The total score for land suitability was obtained from a linear aggregation of the products of fuzzy standard criteria and AHP-derived weights. The WH suitability levels obtained were classified into five different classes: unsuitable, poor, moderate, good, and excellent. The study revealed that 393 \(\hbox {km}^{2}\) (18% of the area) is unsuitable or poor, 538 \(\hbox {km}^{2}\) (26%) is moderately suitable, and 1167 \(\hbox {km}^{2}\) (56%) is good or excellent for WH in the study area. Field data revealed that the only existing WH dam in the area is situated within an excellent WH-suitable zone, which indicates the capability of the developed model to identify areas suitable for different WH structures.

Keywords

Water harvesting Fuzzy logic Analytic hierarchy process Geographical information system Iraq 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    African Development Bank: Rainwater Harvesting Handbook: Assessment of Best Practises and Experience in Water Harvesting. African Development Bank, Tunis (2009)Google Scholar
  2. 2.
    Botha, J.J.; Joseph, L.F.; Anderson, J.J.; Berhanu, A.F.: Classifiation of Rainwater Harvesting Technologies. Paper Read at 3rd International Forum on Water and Food, Tshwane, South Africa. CGIAR Challenge Program on Water and Food. Colombo, Sri Lanka (2011)Google Scholar
  3. 3.
    Mekdaschi Studer, R.; Liniger, H.: Water Harvesting: Guidelines to Good Practice. Centre for Development and Environment (CDE), Bern; Rainwater Harvesting Implementation Network (RAIN), Amsterdam; MetaMeta, Wageningen; The International Fund for Agricultural Development (IFAD), Rome (2013)Google Scholar
  4. 4.
    Yousif, M.; Bubenzer, O.: Geoinformatics application for assessing the potential of rainwater harvesting in arid regions. Case study: El Dabaa area, Northwestern Coast of Egypt. Arab. J. Geosci. 8(11), 9169–9191 (2015). doi: 10.1007/s12517-015-1837-0 CrossRefGoogle Scholar
  5. 5.
    Sur, H.S.; Bhardwaj, A.; Jindal, P.K.: Performance evaluation and impact assessment of a small water-harvesting structure in the Shiwalik foothills of northern India. Am. J. Altern. Agric. 16, 124–129 (2001). doi: 10.1017/S0889189300009036 CrossRefGoogle Scholar
  6. 6.
    Li, F.; Cook, S.; Geballe, G.T.; Burch Jr., W.R.: Rainwater Harvesting Agriculture: An Integrated System for Water Management on Rainfed Land in China’s Semiarid Areas. Ambio. J. Hum. Environ. 29(8), 477 (2000). doi: 10.1579/0044-7447-29.8.477 CrossRefGoogle Scholar
  7. 7.
    Mbilinyi, B.; Tumbo, S.; Mahoo, H.; Mkiramwinyi, F.: GIS-based decision support system for identifying potential sites for rainwater harvesting. Phys. Chem. Earth Parts A/B/C 32(15), 1074–1081 (2007)CrossRefGoogle Scholar
  8. 8.
    El-Awar, F.A.; Makke, M.K.; Zurayk, R.A.; Mohtar, R.H.: A hydro-spatial hierarchical method for siting water harvesting reservoirs in dry areas. Appl. Eng. Agric. 16, 395–404 (2000). doi: 10.13031/2013.5223 CrossRefGoogle Scholar
  9. 9.
    Ramakrishnan, D.; Bandyopadhyay, A.; Kusuma, K.: SCS-CN and GIS-based approach for identifying potential water harvesting sites in the Kali Watershed, Mahi River Basin, India. Earth Syst. Sci. 118(4), 355–368 (2009). doi: 10.1007/s12040-009-0034-5 CrossRefGoogle Scholar
  10. 10.
    Singh, J.; Singh, D.; Litoria, P.: Selection of suitable sites for water harvesting structures in Soankhad watershed, Punjab using remote sensing and geographical information system (RS&GIS) approach–A case study. J. Indian Soc. Remote Sens. 37(1), 21–35 (2009). doi: 10.1007/s12524-009-0009-7 CrossRefGoogle Scholar
  11. 11.
    Nykänen, V.: Prospectivity mapping in GIS :integrate geochemistry data with geophysics and geology in the 25th International Applied Geochemistry Symposium In: Vuorimiesyhdistys, vol. B92-5. p. 88 Rovaniemi, Finland (2011)Google Scholar
  12. 12.
    Gbanie, S.P.; Tengbe, P.B.; Momoh, J.S.; Medo, J.; Kabba, V.T.S.: Modelling landfill location using geographic information systems (GIS) and multi-criteria decision analysis (MCDA): case study Bo. Southern Sierra Leone. Appl. Geogr. 36, 3–12 (2013). doi: 10.1016/j.apgeog.2012.06.013 CrossRefGoogle Scholar
  13. 13.
    Lai, S.-K.: A preference-based interpretation of AHP. Omega 23(4), 453–462 (1995). doi: 10.1016/0305-0483(95)00025-J CrossRefGoogle Scholar
  14. 14.
    Saaty, T.L.: The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. McGraw-Hill International Book Co, New York (1980)zbMATHGoogle Scholar
  15. 15.
    Hajkowicz, S.; Collins, K.: A review of multiple criteria analysis for water resource planning and management. Water Resour. Manage 21(9), 1553–1566 (2007). doi: 10.1007/s11269-006-9112-5 CrossRefGoogle Scholar
  16. 16.
    Rahmati, O.; Samani, A.N.; Mahdavi, M.; Pourghasemi, H.R.; Zeinivand, H.: Groundwater potential mapping at Kurdistan region of Iran using analytic hierarchy process and GIS. Arab. J. Geosci. 8(9), 1–13 (2014). doi: 10.1007/s12517-014-1668-4 Google Scholar
  17. 17.
    Bui, D.T.; Pradhan, B.; Lofman, O.; Revhaug, I.; Dick, O.B.: Spatial prediction of landslide hazards in Hoa Binh province (Vietnam): a comparative assessment of the efficacy of evidential belief functions and fuzzy logic models. Catena 96, 28–40 (2012). doi: 10.1016/j.catena.2012.04.001 CrossRefGoogle Scholar
  18. 18.
    Gorsevski, P.V.; Jankowski, P.: An optimized solution of multi-criteria evaluation analysis of landslide susceptibility using fuzzy sets and Kalman filter. Comput. Geosci. 36(8), 1005–1020 (2010). doi: 10.1016/j.cageo.2010.03.001 CrossRefGoogle Scholar
  19. 19.
    Lee, S.: Application and verification of fuzzy algebraic operators to landslide susceptibility mapping. Environ. Geol. 52(4), 615–623 (2007). doi: 10.1007/s00254-006-0491-y CrossRefGoogle Scholar
  20. 20.
    Al-Taiee, T.; Rasheed, A.: Hydro engineering study of surface runoff water harvesting in Al-Ajeej basin, north of Iraq. Tikrit. J. Eng. Sci. 18(1), 15–28 (2011)Google Scholar
  21. 21.
    Zakaria, S.; Al-Ansari, N.; Knutsson, S.; Ezz-Aldeen, M.: Rain Water Harvesting at Eastern Sinjar Mountain, Iraq. J. Geosci. Res. 3(2), 100–108 (2012)Google Scholar
  22. 22.
    Kareem, I.R.: Artificial groundwater recharge in Iraq through rainwater harvesting (Case Study). Eng. Tech. J. 31(6), 1069–1080 (2012)Google Scholar
  23. 23.
    Al-Ansari, N.; Ezz-Aldeen, M.; Knutsson, S.; Zakaria, S.: Water harvesting and reservoir optimization in selected areas of South Sinjar mountain. Iraq. J. Hydrol. Eng. 18(12), 1607–1616 (2013)CrossRefGoogle Scholar
  24. 24.
    Hameed, H.: Water harvesting in Erbil Governorate, Kurdistan region, Iraq: detection of suitable sites using geographic information system and remote sensing. Unpublished Master thesis (2013)Google Scholar
  25. 25.
    Al-Ansari, N.; Ali, A.A.; Knutsson, S.: Present conditions and future challenges of water resources problems in Iraq. J. Water Res. Prot. 6(12), 1066–1098 (2014)CrossRefGoogle Scholar
  26. 26.
    Al-Abadi, A.M.; Shahid, S.: A comparison between index of entropy and catastrophe theory methods for mapping groundwater potential in an arid region. Environ. Monit. Assess 187(9), 1–21 (2015). doi: 10.1007/s10661-015-4801-2 CrossRefGoogle Scholar
  27. 27.
    Al-Abadi, A.M.; Al-Shammaa, A.M.; Aljabbari, M.H.: A GIS-based DRASTIC model for assessing intrinsic groundwater vulnerability in northeastern Missan governorate, southern Iraq. Appl. Water. Sci. (2014). doi: 10.1007/s13201-014-0221-7 Google Scholar
  28. 28.
    Al-Abadi, A.: Hydrological and Hydrogeological Analysis of Northeaster Missan Governorate, South of Iraq Using Geographic Information System. Doctoral Thesis, Baghdad University (2012)Google Scholar
  29. 29.
    Jassim, S.Z.; Goff, J.C.: Geology of Iraq. Dolin, Prague and Moravian Museum, Brno, Czech Republic (2006)Google Scholar
  30. 30.
    Bellen, R.C.; Dunnington, H.V.; Wetzel, R.; Morton, D.: Lexique Stratigraphique International, Asie . Iraq. Intern Geol Conger Comm Stratigr, 3,Fasc, 10a: 333p (1959)Google Scholar
  31. 31.
    Drobne, S.; Lisec, A.: Multi-attribute decision analysis in GIS: weighted linear combination and ordered weighted averaging. Informatica 33, 459–474 (2009)zbMATHGoogle Scholar
  32. 32.
    Eastman, J.R.; Clark, L.: IDRISI kilimanjaro: Guide to GIS and Image Processing. Clark Labs, Clark University, Worcester (2003)Google Scholar
  33. 33.
    Lohani, A.; Goel, N.; Bhatia, K.: Takagi-Sugeno fuzzy inference system for modeling stage-discharge relationship. J. Hydrol. 331(1), 146–160 (2006). doi: 10.1016/j.jhydrol.2006.05.007 CrossRefGoogle Scholar
  34. 34.
    Rezaee, M.R.; Ilkhchi, A.K.; Barabadi, A.: Prediction of shear wave velocity from petrophysical data utilizing intelligent systems: an example from a sandstone reservoir of Carnarvon Basin. Aust. J. Petrol. Sci. Eng. 55(3), 201–212 (2007). doi: 10.1016/j.petrol.2006.08.008 CrossRefGoogle Scholar
  35. 35.
    Saggaf, M.; Nebrija, L.: A fuzzy logic approach for the estimation of facies from wire-line logs. AAPG Bull. 87(7), 1223–1240 (2003)CrossRefGoogle Scholar
  36. 36.
    Tsoukalas, L.; Uhrig, R.: Fuzzy and Neural Approaches in Engineering. Wiley, London (1997)Google Scholar
  37. 37.
    Yazdi, Z.; Rad, A.R.J.; Ajayebi, K.S.: Analysis and modeling of geospatial datasets for porphyry copper prospectivity mapping in Chahargonbad area, Central Iran. Arab. J. Geosci. 8, 1–12 (2015)CrossRefGoogle Scholar
  38. 38.
    Carr, M.H.; Zwick, P.D.: Smart Land-Use Analysis: The LUCIS Model Land-Use Conflict Identification Strategy. ESRI Press, Redlands (2007)Google Scholar
  39. 39.
    Saaty, T.L.; Vargas, L.G.: Models, Methods, Concepts and Applications of the Analytic Hierarchy Process, International Series in Operations Research and Management Science, vol. 34. Kluwer, Boston (2000)Google Scholar
  40. 40.
    Mustafa, M.; Al-Bahar, J.F.: Project risk assessment using the analytic hierarchy process. IEEE Trans. Eng. Manag. 38(1), 46–52 (1991)CrossRefGoogle Scholar
  41. 41.
    Mahmoud, S.H.; Alazba, A.: The potential of in situ rainwater harvesting in arid regions: developing a methodology to identify suitable areas using GIS-based decision support system. Arab. J. Geosci. 8, 1–13 (2014). doi: 10.1007/s12517-014-1535-3 CrossRefGoogle Scholar
  42. 42.
    de Winner, G.; Jewitt, G.P.W.; Horan, M.: A GIS-based approach for identifying potential runoff harvesting sites in the Thukela River basin, South Africa. Phys. Chem. Earth 32, 1058–1067 (2007). doi: 10.1016/j.pce.2007.07.009 CrossRefGoogle Scholar
  43. 43.
    Munyao, J.: Use of Satellite Products to Assess Water Harvesting Potential in Remote Areas of Africa. A case study of Unguja Island, Zanzibar. M.Sc. thesis, Faculty of Geoinformation Science and Earth Observation in Water Resource and Environmental Mangement, ITC, Enschede (2010)Google Scholar
  44. 44.
    US Department of Agriculture.: Urban hydrology for small watersheds. Engineering Division, Soil Conservation Service, U.S. Dept. of Agriculture, [Washington, D.C.] (1975)Google Scholar
  45. 45.
    USDA-SCS: Storm Rainfall Depth. In: National Engineering Handbook Series, Part 630, Chapter 4, Washington, DC (1993)Google Scholar
  46. 46.
    SCS: Hydrology National Engineering Handbook, Supplement A, Section 4 Chapter 10, Soil Conservation Service, USDA, Washington, DC. Washington (1956)Google Scholar
  47. 47.
    Cronshey, R.: Urban hydrology for small watersheds. U.S. Dept. of Agriculture, Soil Conservation Service, Engineering Division, [Washington, D.C.] (1986)Google Scholar
  48. 48.
    Al-Abadi, A.; Al-Aboodi, A.: Optimum rain-Gauges network design of some cities in Iraq. J. Babylon Univ. Eng. Sci. 22(4), 946–958 (2014)Google Scholar
  49. 49.
    Al-Abadi, A.M.; Shahid, S.; Al-Ali, A.K.: Environ. Earth Sci 75, 687 (2016). doi: 10.1007/s12665-016-5523-7 CrossRefGoogle Scholar

Copyright information

© King Fahd University of Petroleum & Minerals 2017

Authors and Affiliations

  1. 1.Department of Geology, College of ScienceUniversity of BasraBasraIraq
  2. 2.Faculty of Civil EngineeringUniversiti Teknologi MalaysiaJohor BahruMalaysia

Personalised recommendations