Groundwater delineation for sustainable improvement and development aided by GIS, AHP, and MIF techniques

Springer Science and Business Media LLC - Tập 14 Số 2 - 2024
Muhsan Ehsan1, Haider Shabbir1, Ayad M. Fadhil Al-Quraishi2, Nadhir Al‐Ansari3, Zulfiqar Ahmad4, Kamal Abdelrahman5, Muhammad Tayyab Sohail6, Zaira Manzoor7, Ahsan Shafi8, Ahmed Elbeltagi9
1School of Geosciences and Info-physics, Central South University, Changsha 410083, China
2Petroleum and Mining Engineering Department, Tishk International University, Erbil, Kurdistan Region, 44001, Iraq
3Civil, Environmental and Natural Resources Engineering, Lulea University of Technology, 97187, Lulea, Sweden
4Director ORIC, University of Wah, Wah Cantt, Pakistan
5Department of Geology and Geophysics, College of Science, King Saud University, P.O. Box 2455, 11451, Riyadh, Saudi Arabia
6School of Public Administration, Xiangtan University, Xiangtan, Hunan, China
7Department of Govt and Public Policy (GPP), Faculty of Contemporary Studies, National Defence University (NDU), Islamabad, Pakistan
8School of Public Administration, China University of Geosciences, Wuhan, Hubei Province, China
9Agricultural Engineering Department, Faculty of Agriculture, Mansoura University, Mansoura, 35516, Egypt

Tóm tắt

AbstractExploration of groundwater is an integral part of viable resource growth for society, economy, and irrigation. However, uncontrolled utilization is mainly reported in urban and industries due to the increasing demand for water in semi-arid and arid regions of the world. In the background, groundwater demarcation for potential areas is vital in meeting necessary demand. The current study applied an integrated method comprising the analytical hierarchy process (AHP), multiple influence factors (MIF), combined with a linear regression curve and observatory well data for groundwater prospects mapping. Thematic maps such as flow direction, flow accumulation, elevation map, land use land cover, slope, soil texture, hill shade, geomorphology, normalized vegetation index, and groundwater depth map were generated utilizing remote sensing techniques. The relative weight of each parameter was estimated and then assigned to major and minor parameters. Potential zones for groundwater were classified into five classes, namely very good, good, moderate, poor, and very poor, based on AHP and MIF methods. A spatially explicit sensitivity and uncertainty analysis method to a GIS-based multi-criteria groundwater potential zone model is presented in this research. The study addressed a flaw in the way groundwater potential mapping results are typically presented in GIS-based multi-criteria decision analysis studies, where discrete class outputs are used without any assessment of their certainty with respect to variations in criteria weighting, which is one of the main contributors to output uncertainty. The study region is categorized based on inferred results as very poor, poor, marginal, and very good in potential ground quality 3.04 km2 is considered extremely poor, 3.33 km2 is considered poor, 64.42 km2 is considered very good, and 85.84 km2 is considered marginal zones, which shows reliable and potential implementation. The outcomes of AHP and MIF were validated by linear regression curve and actual water table in a study area. The study results help to formulate the potential demarcation of groundwater zones for future sustainable planning and development of groundwater sources. This study may be helpful to provide a cost-effective solution to water resources crises. The current study finding may be helpful for decision-makers and administrative professionals for sustainable management of groundwater resources for present and future demands.

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