Identification of groundwater potential zones using geospatial approach in Sivagangai district, South India

Vellaikannu, Agastheeswaran; Palaniraj, Udayaganesan; Sivakumar, K.; Senapathi, Venkatramanan; Prasanna, Mohan Viswanathan; Sekar, Selvam

doi:10.1007/s12517-020-06316-4

Cited by 31 publications

(6 citation statements)

References 40 publications

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“…The TRI is the most important conditioning variables for GWP modeling [19,20,23]. It was used to measure landscape heterogeneities since it represents the average discrepancy between a central pixel and its neighbouring cells, which affects drainage.…”

Section: Trimentioning

confidence: 99%

“…One of the best methods for this is scientific aquifer mapping, which is now almost nonexistent in most developing countries [19,20]. Geographic information systems (GIS) and remote sensing have ushered in a new era in this area, allowing multi-parametric research [14,16,[21][22][23]. The choices of conditioning variables and the utilization of an efficient integration approach are crucial to effective modeling [10,[24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Hybrid Model for Developing Groundwater Potentiality Model Using High Resolution Digital Elevation Model (DEM) Derived Factors

Mallick

Talukdar

Kahla

et al. 2021

Water

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The present work aims to build a unique hybrid model by combining six fuzzy operator feature selection-based techniques with logistic regression (LR) for producing groundwater potential models (GPMs) utilising high resolution DEM-derived parameters in Saudi Arabia’s Bisha area. The current work focuses exclusively on the influence of DEM-derived parameters on GPMs modelling, without considering other variables. AND, OR, GAMMA 0.75, GAMMA 0.8, GAMMA 0.85, and GAMMA 0.9 are six hybrid models based on fuzzy feature selection. The GPMs were validated by using empirical and binormal receiver operating characteristic curves (ROC). An RF-based sensitivity analysis was performed in order to examine the influence of GPM settings. Six hybrid algorithms and one unique hybrid model have predicted 1835–2149 km2 as very high and 3235–4585 km2 as high groundwater potential regions. The AND model (ROCe-AUC: 0.81; ROCb-AUC: 0.804) outperformed the other models based on ROC’s area under curve (AUC). A novel hybrid model was constructed by combining six GPMs (considering as variables) with the LR model. The AUC of ROCe and ROCb revealed that the novel hybrid model outperformed existing fuzzy-based GPMs (ROCe: 0.866; ROCb: 0.892). With DEM-derived parameters, the present work will help to improve the effectiveness of GPMs for developing sustainable groundwater management plans.

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Section: Trimentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Hybrid Model for Developing Groundwater Potentiality Model Using High Resolution Digital Elevation Model (DEM) Derived Factors

Mallick

Talukdar

Kahla

et al. 2021

Water

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“…Piper diagram is an analytic procedure in common use to determine the hydrochemistry ion composition, which can be used to intuitively analyze the general chemical characteristics and the types of water quality among the water sources [54][55][56][57][58][59]. In this study, based on the six ion compositions with a distinct meaning,…”

Section: Distribution Characteristics Of Mine Water Qualitymentioning

confidence: 99%

Recognition Method of Mine Water Sources Based on Factor Analysis

Shi

2020

Glob. J. Earth Sci. Eng.

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Taking Jiaozuo mining area as the research background, according to the survey of water samples among the main water-filled aquifers of the mine and water gushing sources due to the exploitation of the No.21 coal seams in Shanxi group, six kinds of water chemical composition were selected as the sample indexes, including Cl-, SO42-, HCO3-, Na++K+, Ca2+, Mg2+, based on the data of groundwater chemical composition, and a principal component analysis was applied to establish the mathematical model by the method of factor analysis. A piper diagram was used to intuitively conduct the synthetical analyses for the general chemical characteristics and water quality types of the water samples. At the same time, via the comparative analysis between the water properties of water exits and that of the main aquifers in the Jiaozuo mining area, discrimination of the hybridization of the multiple water gushing sources due to coal mining was done. Moreover, by dint of the SPSS factor analysis, the water chemical proxies were carried on dimensionality reduction from the six kinds of water chemical composition to the three major factors, which replaced the original variables to participate in the data modeling. The results of the study showed that the combination of the piper diagram and the factor analysis modeling could effectively identify the water gushing sources owing to exploiting the No.21 coal seams of the Shanxi group in the Jiaozuo mining area and rank on the basis of the contributions of each aquifer to the amounts of water bursting in the mine, solving the problems of information superposition and correlations consisted in the identification of water gushing sources, which provides a theoretical basis for the prevention and cure of the mine water disasters.

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“…Since the industrial revolution, natural and contaminated waters have been extensively investigated throughout the globe. The site-specific development has damaged and continues to pollute the groundwater system in multiple locations across India (1)(2)(3)(4) . Due to a lack of surface water resources, economic development in arid and semiarid areas is increasingly dependent on groundwater, which provides high-quality water for drinking, household, agricultural, and industrial purposes.…”

Section: Introductionmentioning

confidence: 99%

An Integrated assessment on LULC changes and Groundwater Quality in Ambattur Zone of Metropolitan Chennai, India

Singh¹,

Anbazhahan²,

Gowtham³

2022

IJST

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Objectives:The current study shows the magnitude of changes in land use and land cover (LULC) in the Ambattur Zone from 1990 to 2021 and examines its impact on groundwater quality through the Gibbs diagram, Piper diagram, multivariate statistical analysis, and water quality index (WQI) for drinking. Methods: Landsat images were collected to derive the LULC images through the supervised classification approach. Groundwater samples were collected from 31 wells for two seasons and analyzed for the hydrogeochemical study. Gibbs, Piper, multivariate statistical analysis and WQI were done to evaluate the groundwater quality for drinking purpose and to study the hydrogeochemical characteristics. Findings: The results show that barren land decreased from 7.4 to 4.31 km 2 , whereas, built-up land expanded from 21.37 to 24 km 2 . Compared to barren and built-up regions, water and vegetation land haven't changed much. LULC change analysis required assessing Ambattur groundwater quality. Physico-chemical investigations and ionic concentrations show that Ambattur industrial zone groundwater is contaminated and unsafe for human consumption. WQI shows that 60% of groundwater is unfit in both seasons. Evaporation and rock-water interaction alter the area's groundwater chemistry. Hydrogeochemical facies diagrams show alternating alkaline and alkali dominance, as well as strong and weak acids. According to correlation matrices, all analytical parameters except pH have a positive correlation. Four basic components and a cluster contribute to understanding industrial pollution. Novelty: (i) The present study integrates LULC changes and hydrogeochemistry for the evaluation of groundwater quality. (ii) The comprehensive approach of analyzing LULC changes in conjunction with evaluating the groundwater geochemistry gives new insights in groundwater management for the long-term development of any region. https://www.indjst.org/

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Identification of groundwater potential zones using geospatial approach in Sivagangai district, South India

Cited by 31 publications

References 40 publications

A Novel Hybrid Model for Developing Groundwater Potentiality Model Using High Resolution Digital Elevation Model (DEM) Derived Factors

A Novel Hybrid Model for Developing Groundwater Potentiality Model Using High Resolution Digital Elevation Model (DEM) Derived Factors

Recognition Method of Mine Water Sources Based on Factor Analysis

An Integrated assessment on LULC changes and Groundwater Quality in Ambattur Zone of Metropolitan Chennai, India

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