Application of geospatial techniques in delineating groundwater potential zones: a case study from South India

Mageshkumar, P.; Subbaiyan, Anandakumar; Elango, L.; Thirumoorthy, Pradeep

doi:10.1007/s12517-019-4289-0

Cited by 27 publications

(6 citation statements)

References 28 publications

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“…The Korba area is mainly covered by six types of lithological units that were ranked based on available porosity and permeability values of aquifer rocks. Sedimentary features, such as sand and sandstone, generally demonstrate very high porosity (20-31%) and permeability (500-7000 mD) and they are capable of accumulating and storing large volumes of groundwater [54][55][56].…”

Section: Preparation Of Input Databasementioning

confidence: 99%

“…The representative weight of a factor influencing recharge potential is the sum of all weights from each factor. Major effects were assigned a weight of 1.0 whereas minor influential relationships were given a weight of 0.5 [55][56][57]. Furthermore, the classes with no effect on groundwater recharge were assigned a weight of zero.…”

Section: Multi-influencing Factors (Mif)mentioning

confidence: 99%

“…LD LD , + RF RF + DD DD + SL SL , where GWRZ is the groundwater recharge zone, Wi is the weight of each thematic layer, Ri is the rating of each class of each thematic layer, LI is the lithology of the aquifer, LU/LC is the landuse/land-cover, SLO is the slope, GM is the geomorphology, LD is the lineament, RF is the rainfall, DD is the drainage density and SL is the soil cover. The subscripts c and w refer, respectively, to the factor class of a thematic layer and its percent influence on recharge [46,56]. It means that each layer class rank (each individual class has a rank) was multiplied by the weight from Saaty's assumption of each layer (each layer has a unique weight) to obtain the position of layers in the overlay analysis to map GWRZ.…”

Section: Factor Major Effect Minor Effect Relative Effect Proposed Wementioning

confidence: 99%

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Using Analytical Hierarchy Process and Multi-Influencing Factors to Map Groundwater Recharge Zones in a Semi-Arid Mediterranean Coastal Aquifer

Zghibi

Mirchi

Msaddek

et al. 2020

Water

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Mapping groundwater recharge zones (GWRZs) is essential for planning artificial recharge programs to mitigate groundwater decline and saltwater intrusion into coastal aquifers. We applied two multi-criteria decision-making approaches, namely the analytical hierarchy process (AHP) and the multi-influencing factors (MIF), to map GWRZs in the Korba aquifer in northeastern Tunisia. GWRZ results from the AHP indicate that the majority (69%) of the area can be classified as very good and good for groundwater recharge. The MIF results suggest larger (80.7%) very good and good GWRZs. The GWRZ maps improve groundwater balance calculations by providing estimates of recharge-precipitation ratios to quantify percolation. Lithology, land use/cover and slope were the most sensitive parameters followed by geomorphology, lineament density, rainfall, drainage density and soil type. The AHP approach produced relatively more accurate results than the MIF technique based on correlation of the obtained GWRZs with groundwater well discharge data from 20 wells across the study area. The accuracy of the approaches ultimately depends on the classification criteria, mean rating score and weights assigned to the thematic layers. Nonetheless, the GWRZ maps suggest that there is ample opportunity to implement aquifer recharge programs to reduce groundwater stress in the Korba aquifer.

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Section: Preparation Of Input Databasementioning

confidence: 99%

Section: Multi-influencing Factors (Mif)mentioning

confidence: 99%

Section: Factor Major Effect Minor Effect Relative Effect Proposed Wementioning

confidence: 99%

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Using Analytical Hierarchy Process and Multi-Influencing Factors to Map Groundwater Recharge Zones in a Semi-Arid Mediterranean Coastal Aquifer

Zghibi

Mirchi

Msaddek

et al. 2020

Water

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“…where IFHZ is the localization of the identified intra-field heterogeneity zones; Wi is the weight of each thematic layer, Ri is the rating of each class of each thematic layer; Ph, Po, Sa, Hu, Cu, Zn, B, Ca, Mn are soil parameters; the subscripts r and w refer, respectively, to the factor class of a thematic layer and its percent influence [Mageshkumar et al, 2019].…”

Section: Discussion and Resultsmentioning

confidence: 99%

Using analytical hierarchy process to determine intra-field heterogeneity zones upon implementation of precision farming

Myslyva,

Nadtochyj,

Kutsayeva

et al. 2022

Baltic Surveying

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The study aimed to develop a methodology for determining zones of intra-field heterogeneity for precision farming. In this study, we took into account the Belarussian national land use system which provides for the absence of private ownership of agricultural land. The spatial distribution of intra-field heterogeneity zones within the land use area of 7549.49 thousand hectares was identified using the analytical hierarchy process (AHP). The algorithm for determining zones of spatial heterogeneity provides for: (1) the selection of indicators and their ranking; (2) developing a pairwise comparison matrix, (3) estimating relative weights and (4) assessing matrix consistency. It is recommended to use data from agrochemical soil studies which are conducted centrally every 4 years for each agricultural enterprise as input parameters. These data include the humus content in the soil, the content of available phosphorus and potassium, soil pH, and the content of B, Cu, Zn, Ca, and Mg. The data should be carefully examined using spatial statistics tools to provide a more accurate delineation of the management-zones boundaries. The developed technique makes it possible to determine fertile and marginal areas within each field and differentiate the use of fertilizers, taking into account the presence of intra-field heterogeneity. This will reduce the total cost of purchasing and applying phosphorus fertilizers by 34 $·ha-1 and potash fertilizers by 9 $·ha-1 due to the redistribution of the fertilizer dose calculated for the planned yield, taking into account the identified site-specific management zones. At the same time, the level of chemical pressure per hectare of arable land will decrease by 6.7% without loss of crops productivity.

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“…2), and coherence ratio (CR -Eq. 5) (Mageshkumar et al, 2019): where: CI -coherence index, λmax -maximum value of the matrix, n -number of factors, CR -coherence ratio, RI' -the value of hazard index depending on a number of factors.…”

Section: Veri Cation Of the Matrix Coherencementioning

confidence: 99%

Mapping Favorable Groundwater Potential Recharge Areas Using a GIS-Based Analytical Hierarchical Process: A Case Study of Ferkla Oasis, Morocco

Ait Lahssaine,

Kabiri,

Messaoudi

et al. 2024

Ecol. Eng. Environ. Technol.

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In the Ferkla Oasis, much like in numerous other oases across the southeastern region of Morocco, a range of socioeconomic and environmental challenges are intricately linked to the inadequate management of water resources. One proposed remedy to address these concerns is the implementation of artificial aquifer recharge, which stands as an alternative strategy to safeguard the crucial oasis ecosystems. Thus, to evaluate the viability of this method in promoting sustainable water resource usage, it becomes imperative to delineate groundwater recharge potential zones (GRPZs). This study aims to achieve this objective by mapping GRPZs within the Ferkla Oasis, employing a fusion of the analytical hierarchy process (AHP), geospatial information derived from remote sensing (RS), and geographic information system (GIS) technologies. In pursuit of this goal, an array of geological, topographical, pedological, hydrological, and climatic criteria have been meticulously selected, classified, and assigned weights following their relevance to water infiltration suitability. This comprehensive approach culminates in the generation of seven thematic maps: slope, lineament density, lithology, soil type, drainage density, land use/land cover, and rainfall distribution. Through the integration of these aforementioned maps, a tripartite classification of potential GRPZs emerges, comprising low, medium, and high categories. The findings underscore the distribution: 30% of the total study area exhibits a low potential for GRPZs, 50% of the total land area is characterized as having medium potential GRPZs, while the remaining 20% is designated as high potential GRPZs. These outcomes have been substantiated through validation against piezometric levels, which have been ascertained through recent field surveys. Consequently, these results stand as a testament to the efficacy of the presented approach as a robust decision-making tool. The approach effectively facilitates the establishment of conditions conducive to viable artificial recharge, thereby offering a means to safeguard the groundwater reservoirs that sustain the fragile oasis environments.

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Application of geospatial techniques in delineating groundwater potential zones: a case study from South India

Cited by 27 publications

References 28 publications

Using Analytical Hierarchy Process and Multi-Influencing Factors to Map Groundwater Recharge Zones in a Semi-Arid Mediterranean Coastal Aquifer

Using Analytical Hierarchy Process and Multi-Influencing Factors to Map Groundwater Recharge Zones in a Semi-Arid Mediterranean Coastal Aquifer

Using analytical hierarchy process to determine intra-field heterogeneity zones upon implementation of precision farming

Mapping Favorable Groundwater Potential Recharge Areas Using a GIS-Based Analytical Hierarchical Process: A Case Study of Ferkla Oasis, Morocco

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