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Selecting potential locations for groundwater recharge by means of remote sensing and GIS and weighting based on Boolean logic and analytic hierarchy process

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Abstract

Growing demand for water, as a consequence of population growth, farmland irrigation, and industrial expansion, results in groundwater resources exploitation. This, in combination with droughts induced by climate change, has caused a sharp drop in groundwater levels throughout arid and semiarid countries. In Iran, all these factors are resulting in alarming water scarcity. Appropriate management and control of existing water resources can overcome water shortages, with healthy and sustainable management of groundwater as one of the most efficient tools. Artificial recharge of aquifers can be used to replenish water supplies and restore the water resources in Iran and other semiarid and arid countries, but selection of the right location for runoff collection is essential to achieve success. Precipitation, slope, geology, lineament density, drainage density, aquifer water quality, groundwater level, vegetation, and land use were selected in this study as key factors in locating suitable sites for artificial recharge. The weight of each, in terms of importance and impact on aquifer recharge, was determined using remote sensing techniques to prepare layers and analytic hierarchy process (AHP) and Boolean logic to identify the optimal weight for each factor. Geographic information system (GIS) was used for modeling, applying the weight of each criterion, and producing a final map. The results showed better performance of AHP than Boolean logic. For artificial recharge, 9.9% of the total study area (Mahdishahr in northern Iran) was found to be in a very good position and 22.6% in a good position. On filtering the privacy layer of fountains and aqueducts, the very good and good area declined to 8.4% and 14.7% of the total area, respectively, and mainly comprised alluvial valleys and coarse alluvial sediments with low slope and drainage density.

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Authors and Affiliations

  1. Department of Management of Arid and Desert Regions, College of Natural Resources and Desert, University of Semnan, Semnan, Iran

    Amir Hossien Hatefi Ardakani

  2. Department of Arid and Mountainous Regions Reclamation, Faculty of Natural Resources, University of Tehran, Tehran, Iran

    Saeed Shojaei

  3. School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran

    Ali Reza Shahvaran

  4. Department of Sustainable Development, Environmental Science and Engineering (SEED), KTH Royal Institute of Technology, Stockholm, Sweden

    Zahra Kalantari

  5. Department of Physical Geography and Bolin Center for Climate Research, Stockholm University, 10691, Stockholm, Sweden

    Zahra Kalantari

  6. Soil Erosion and Degradation Research Group, Departament de Geografia, Universitat de València, Blasco Ibàñez, 28, 46010, València, Spain

    Artemi Cerdà

  7. Department of Geography, Texas State University, San Marcos, TX, USA

    John Tiefenbacher

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  1. Amir Hossien Hatefi Ardakani
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This article is part of a Topical Collection in Environmental Earth Sciences on “GeosphereAnthroposphere Interlinked Dynamics: Geocomputing and New Technologies”, guest edited by Sebastiano Trevisani, Marco Cavalli, and Fabio Tosti.

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Ardakani, A.H.H., Shojaei, S., Shahvaran, A.R. et al. Selecting potential locations for groundwater recharge by means of remote sensing and GIS and weighting based on Boolean logic and analytic hierarchy process. Environ Earth Sci 81, 8 (2022). https://doi.org/10.1007/s12665-021-10071-4

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