Hydrochemical characterization and water quality perspectives for groundwater management for urban development

Subba Rao, N.; Das, Rashmirekha; Sahoo, H.K.; Gugulothu, Sakram

doi:10.1016/j.gsd.2023.101071

Cited by 43 publications

(2 citation statements)

References 82 publications

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“…Groundwater quality changes result from natural processes, such as ion exchange, sorption, dissolution, precipitation of soluble minerals, acid-base reactions, oxidation-reduction reactions, evapotranspiration, and weathering of minerals [ 7 , 9 , 10 , 13 , 16 , [25] , [26] , [27] , [28] , [29] , [30] , [31] , [32] , [33] , [34] ]. Total dissolved solids, salinity, chlorinity, etc, reflect the overall concentration of solutes in groundwater at a particular time.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive approach integrating remote sensing, machine learning, and physicochemical parameters to detect hydrodynamic conditions and groundwater quality deterioration in non-rechargeable aquifer systems

Eid,

Shebl,

Eissa

et al. 2024

Heliyon

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Section: Introductionmentioning

confidence: 99%

Comprehensive approach integrating remote sensing, machine learning, and physicochemical parameters to detect hydrodynamic conditions and groundwater quality deterioration in non-rechargeable aquifer systems

Eid,

Shebl,

Eissa

et al. 2024

Heliyon

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“…Hydro-geochemical methods coupling with multivariate statistics (P. Liu et al, 2017;Subba Rao et al, 2024), probability (De et al, 2023), principal component analysis (Maurice et al, 2011), and cluster analysis (Z. C. Wang et al, 2018) are also widely used to identify the groundwater source and pollution. The groundwater chemistry is generally closed linked with geology in nonpolluting area (Ehizemhen et al, 2020;Subba Rao et al, 2022), which the major ions in groundwater are determined by the water-rock reaction.…”

Section: Introductionmentioning

confidence: 99%

Research on the relation between hydro‐chemical and geological characteristics in karst area: Case study in Zhong Liang Mountain, Southwest China

Jing,

Ping,

Qing

et al. 2024

Water Environment Research

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Karst groundwater, which is one of most important drinking water sources, is vulnerable to be polluted as its closed hydraulic relation with surface water. Thus, it is very important to identify the groundwater source to control groundwater pollution. The Pearson correlation coefficient among major ions (Na + K+, Ca2+, Mg2+, HCO3−, SO42−, and Cl−) was employed to deduce the groundwater types in Zhong Liang Mountain, Southwest China. Then, the combined method of principal component analysis and cluster analysis were employed to identify the groundwater sources in a typical karst region of southwest China. The results shown that (1) the high positive correlation between cations and anions indicated the water–rock reaction of Ca‐HCO3, Ca‐SO4, (Na + K)‐Cl, and Mg‐SO4. (2) The major two principal components that would represent water–rock reaction of CaSO4 and Ca‐HCO3 would, respectively, explain 60.41% and 31.80% of groundwater information. (3) Based on the two principal components, 33 groundwater samples were clustered into eight groups through hierarchical clustering, each group has similar water–rock reaction. The findings would be employed to forecast the surge water, that was an important work for tunnel construction and operation.Practitioner Points The components of groundwater was highly correlated with water–rock reaction. The principal component analysis screens the types of groundwater. The cluster analysis identifies the groundwater sources.

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Assessing Groundwater Vulnerability to Pollution in a Rapidly Urbanizing River Basin Using a Modified DRASTIC Land Use–Lineament Density Method

Tsegay,

Birhanu,

Azagegn

et al. 2024

Geological Journal

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Groundwater quality assessment is crucial for ensuring safe drinking water, protecting public health, and maintaining sustainable water resources for agricultural and industrial uses. The Awash River basin faces significant groundwater quality challenges due to rapid population growth, high urbanization, large‐scale irrigation, and industrial pollution. The main objective of this study is to evaluate the intrinsic vulnerability of aquifers to pollution in the Awash Basin and identify hotspots requiring urgent intervention using a modified DRASTIC overlay analysis method. In addition to the seven parameters considered in the generic DRASTIC overlay analysis (depth to the water table, recharge, aquifer media, slope, soil media, vadose zone, and hydraulic conductivity), we incorporated land use/land‐cover (LULC) and lineament density (LD) distributions (DRASTIC‐LU‐LD). This modification allowed us to produce more realistic groundwater vulnerability maps for the basin. To identify the most influential parameters in the overlay, sensitivity analysis was conducted using Map Removal Sensitivity Analysis (MRSA) and Single Parameter Sensitivity Analysis (SPSA). Initially, the generic DRASTIC index in the area ranges from 69 to 181, categorizing the area into four vulnerability zones: very low (21%), low (51%), medium (27%), and high (1%). After incorporating LU and LD, the index values ranged from 90 to 240. Based on the percentage of the total area studied, the inclusion of LU decreased the very low and low vulnerability zones from 72% to 44% and the inclusion of LD increased the high‐ and very‐high‐vulnerability zones from 14% to 27%. The areas most vulnerable to groundwater pollution are in the western (upper Awash), middle Awash, and northwestern regions, particularly in city centers where groundwater abstraction is significant. These high‐vulnerability zones coincide with municipal, industrial, and agricultural pollution sources. The vadose zone parameter has the highest impact in both MRSA and SPSA, with a variation index value of 3.08% and a mean effective weight of 27.93%, respectively. By identifying areas vulnerable to groundwater pollution, this study provides a valuable basis for informed decision‐making and the development of effective strategies for protecting groundwater from urban, industrial, and agricultural pollution sources.

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Hydrochemical characterization and water quality perspectives for groundwater management for urban development

Cited by 43 publications

References 82 publications

Comprehensive approach integrating remote sensing, machine learning, and physicochemical parameters to detect hydrodynamic conditions and groundwater quality deterioration in non-rechargeable aquifer systems

Comprehensive approach integrating remote sensing, machine learning, and physicochemical parameters to detect hydrodynamic conditions and groundwater quality deterioration in non-rechargeable aquifer systems

Research on the relation between hydro‐chemical and geological characteristics in karst area: Case study in Zhong Liang Mountain, Southwest China

Assessing Groundwater Vulnerability to Pollution in a Rapidly Urbanizing River Basin Using a Modified DRASTIC Land Use–Lineament Density Method

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