IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i13p7871-d850315.html
   My bibliography  Save this article

Fusion of Remote Sensing Data Using GIS-Based AHP-Weighted Overlay Techniques for Groundwater Sustainability in Arid Regions

Author

Listed:
  • Mohamed Abdekareem

    (Geology Department, South Valley University, Qena 83523, Egypt
    Remote Sensing Lab, South Valley University, Qena 83523, Egypt)

  • Nasir Al-Arifi

    (Chair of Natural Hazards and Mineral Resources, Geology and Geophysics Department, King Saud University, Riyadh 11451, Saudi Arabia)

  • Fathy Abdalla

    (Geology Department, South Valley University, Qena 83523, Egypt
    Scientific Research Chairs Program, King Saud University, Riyadh 11451, Saudi Arabia)

  • Abbas Mansour

    (Geology Department, South Valley University, Qena 83523, Egypt)

  • Farouk El-Baz

    (Center for Remote Sensing, Boston University, 725 Commonwealth Ave., Boston, MA 02215, USA)

Abstract

Remote sensing and GIS approaches have provided valuable information on modeling water resources, particularly in arid regions. The Sahara of North Africa, which is one of the driest regions on Earth, experienced several pluvial conditions in the past that could have stored significant amounts of groundwater. Thus, harvesting the stored water by revealing the groundwater prospective zones (GWPZs) is highly important to water security and the management of water resources which are necessary for sustainable development in such regions. The Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM), Advanced Land Observing Satellite (ALOS)/Phased Array type L-band Synthetic Aperture Radar (PALSAR), Tropical Rainfall Measuring Mission (TRMM), and Landsat-8 OLI data have all successfully revealed the geologic, geomorphic, climatic, and hydrologic features of Wadi El-Tarfa east of Egypt’s Nile River. The fusion of eleven predictive GIS maps including lithology, radar intensity, lineament density, altitude, slope, depressions, curvature, topographic wetness index (TWI), drainage density, runoff, and rainfall data, after being ranked and normalized through the GIS-based analytic hierarchy process (AHP) and weighted overlay methods, allowed the GWPZs to be demarcated. The resulting GWPZs map was divided into five classes: very high, high, moderate, low, and very low potentiality, which cover about 10.32, 24.98, 30.47, 24.02, and 10.20% of the entire basin area, respectively. Landsat-8 and its derived NDVI that was acquired on 15 March 2014, after the storm of 8–9 March 2014, along with existing well locations validated the GWPZs map. The overall results showed that an integrated approach of multi-criteria through a GIS-based AHP has the capability of modeling groundwater resources in arid regions. Additionally, probing areas of GWPZs is helpful to planners and decision-makers dealing with the development of arid regions.

Suggested Citation

  • Mohamed Abdekareem & Nasir Al-Arifi & Fathy Abdalla & Abbas Mansour & Farouk El-Baz, 2022. "Fusion of Remote Sensing Data Using GIS-Based AHP-Weighted Overlay Techniques for Groundwater Sustainability in Arid Regions," Sustainability, MDPI, vol. 14(13), pages 1-26, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:7871-:d:850315
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/13/7871/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/13/7871/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ujjayini Priya & Muhammad Anwar Iqbal & Mohammed Abdus Salam & Md. Nur-E-Alam & Mohammed Faruque Uddin & Abu Reza Md. Towfiqul Islam & Showmitra Kumar Sarkar & Saiful Islam Imran & Aweng Eh Rak, 2022. "Sustainable Groundwater Potential Zoning with Integrating GIS, Remote Sensing, and AHP Model: A Case from North-Central Bangladesh," Sustainability, MDPI, vol. 14(9), pages 1-24, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shuhang Li & Mohamed Abdelkareem & Nassir Al-Arifi, 2023. "Mapping Groundwater Prospective Areas Using Remote Sensing and GIS-Based Data Driven Frequency Ratio Techniques and Detecting Land Cover Changes in the Yellow River Basin, China," Land, MDPI, vol. 12(4), pages 1-20, March.
    2. Xiaohan Zhang & Yuanfu Zhang & Yuxiu Li & Yunying Huang & Jianlong Zhao & Yuchuan Yi & Junyang Li & Jinchuan Zhang & Dawei Zhang, 2023. "Geothermal Spatial Potential and Distribution Assessment Using a Hierarchical Structure Model Combining GIS, Remote Sensing, and Geophysical Techniques—A Case Study of Dali’s Eryuan Area," Energies, MDPI, vol. 16(18), pages 1-24, September.
    3. Danqing Song & Wanpeng Shi & Chengwen Wang & Lihu Dong & Xin He & Enge Wu & Jianjun Zhao & Runhu Lu, 2023. "Numerical Investigation of a Local Precise Reinforcement Method for Dynamic Stability of Rock Slope under Earthquakes Using Continuum–Discontinuum Element Method," Sustainability, MDPI, vol. 15(3), pages 1-24, January.
    4. Mohamed Abdelkareem & Fathy Abdalla & Fahad Alshehri & Chaitanya B. Pande, 2023. "Mapping Groundwater Prospective Zones Using Remote Sensing and Geographical Information System Techniques in Wadi Fatima, Western Saudi Arabia," Sustainability, MDPI, vol. 15(21), pages 1-21, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Neslihan Beden & Nazire Göksu Soydan-Oksal & Sema Arıman & Hayatullah Ahmadzai, 2023. "Delineation of a Groundwater Potential Zone Map for the Kızılırmak Delta by Using Remote-Sensing-Based Geospatial and Analytical Hierarchy Processes," Sustainability, MDPI, vol. 15(14), pages 1-21, July.
    2. Saad S. Alarifi & Mohamed Abdelkareem & Fathy Abdalla & Mislat Alotaibi, 2022. "Flash Flood Hazard Mapping Using Remote Sensing and GIS Techniques in Southwestern Saudi Arabia," Sustainability, MDPI, vol. 14(21), pages 1-21, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:7871-:d:850315. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.