Hydrochemical evaluation and identification of geochemical processes in the shallow and deep wells in the Ramganga Sub-Basin, India

Abstract

Groundwater samples were collected from 44 wells in the Ramganga Sub-Basin (RSB), India, and analysed for major ions, nutrients and trace metals. The primary goal of this study is to evaluate the hydrochemistry and to identify the geochemical processes that govern the water chemistry in the shallow and deep tube wells in the study area using geochemical methods. The knowledge of changes in hydrochemistry of the aquifers is important for both groundwater recharge and use in the region. This study found that there are substantial differences of water chemistry between shallow and deep wells. In the shallow wells, the average concentrations of total dissolved solid (TDS), Na, K, Ca, Mg, HCO, Cl, SO, NO, PO, F, Cu, Mn, Fe and Cr are twofold higher than the deep wells. The concentrations of dissolved silica in the groundwater do not vary with the depth, which implies that the variation in the water chemistry is not due to mineral dissolution alone. Major ion ratios and saturation indices suggest that the water chemistry is predominantly controlled by dissolution of carbonate minerals, silicate weathering and ion exchange reactions. Thermodynamic evaluation (ion activity ratios and stability filed diagrams) indicates that the kaolinite and gibbsite controlled the water chemistry in the both shallow and deep wells. In addition, the groundwater chemistry in the shallow wells is affected by the vertical infiltration of contaminated water from surface contamination sources and nitrification process. In the deep wells, absence of NO and low concentrations of Cl, SO, PO and F imply the role of regional flow and denitrification in the groundwater. Results concluded that proper management plan is necessary to protect the shallow aquifer in the RSB since shallow aquifer pumping is less expensive than the deeper one.

Coastal Aquifer Contamination and Geochemical Processes Evaluation in Tugela Catchment, South Africa—Geochemical and Statistical Approaches

“…However, wells with mNa/Cl < 1 reveal that the water Ionic ratios are commonly used to explain various processes in the aquifer. The ratio of (Ca + Mg)/(HCO 3 + CO 3 + SO 4 ) is equal or close to one if the water chemistry is solely regulated by the dissolution of carbonates and sulfate minerals [16]. In this study, this ratio is greater than one in 15 wells and <1 in 21 wells.…”

“…The molar Na/Cl ratio is also useful to differentiate mineral dissolution, saline sources, and ion exchange reactions. Dissolution of halite will approximately maintain mNa/Cl ratio equal to one whereas higher or lower ratios suggest ion exchange reactions and silicate weathering [16,51]. In this study, few wells plotted on mNa/Cl = 1 line and most of them deviated from this ratio (Figure 7).…”

“…Further, it is less than one in 9 samples and 2 < mCa/Mg > 1 in 25 samples, which suggests that the dissolution of calcite has major impact on water chemistry compared to dolomite and silicate minerals in this aquifer. Further, plot of mCa + Mg versus mHCO 3 + CO 3 also imply the contribution of carbonate mineral dissolution and most samples plotted on or near to Y = 2X line ( Figure 7) [16].…”

“…However, wells with mNa/Cl < 1 reveal that the water chemistry is affected by reverse ion exchange reactions. Likewise, molar Ca/Mg ratio is employed to differentiate the influence of carbonate and silicate weathering on groundwater chemistry [9,16,52,53]. If the mCa/Mg equal to one, dissolution of dolomite dominates in the water chemistry whereas higher ratios (mCa/Mg > 2) suggest the impact of silicate weathering.…”

“…are reported as major root causes for groundwater contamination worldwide [12,13]. Geochemistry and multivariate statistics are broadly used in groundwater contamination assessment and several researchers applied major ion chemistry and multivariate statistics to assess the geochemical processes and groundwater contamination in the aquifer [9,[14][15][16][17]. Even though multivariate statistics do not directly identify the geochemical characterization, it establishes data redundancy through key factors [18][19][20].…”