Water quality analysis of ground water from locations in North Bangalore

M, Sonia Angeline; Vijayanand, S; Akkara, Priya Josson; Gretel, Andrea; John, Nitin Ashok; Josephine, Maria

doi:10.5530/ctbp.2021.3s.37

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…The growing demands of groundwater resources has subjected to more strain than ever before (Vijayanand et al, 2021;Khatri et al, 2020). Also, the long-term viability of water is under threat due to excess extraction of water in many parts of the world.…”

Section: Introductionmentioning

confidence: 99%

Aquifer salinization: A groundwater appraisal of northeast coast of Odisha using water quality index (WQI) and geospatial interpretation

Das,

Das

2023

EEC

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Groundwater is an important source of drinking water supply in the northeast coastal tract of Odisha. Salinization of aquifer is one of the major problems in the coastal aquifers. An attempt has been made to analyze the hydro-geochemistry of groundwater and its suitability through statistical and geospatial data interpretation. A total 60 water samples are collected from coastal villages of Balasore Sadar and Remuna block of the Balasore district of Odisha during pre-monsoon period and analyzed. The water quality parameters like pH, electrical conductivity, total dissolved solid, carbonate, bicarbonate, calcium, magnesium, potassium, sulphate, chloride, fluoride was analyzed using standard analytical procedure (APHA, 2012) for determination of salinity and groundwater facies. The analytical results are compared with WHO and BIS drinking water quality standard. The hydro chemical facies of the study area are determined based on Schoeller's Plot and Langelier-Ludwig diagrams. Scholler's diagram revealed the dominance of Na + cation as well as Clanion along the coastal tract. And dominance of Ca 2+ , Mg 2+ and HCO -3 in other localities. Stiff diagrams' results are consistent with Schoeller's plot and Langelier-Ludwig diagram showing three types of groundwater. The result reveals that, Ca 2+ -HCO 3 type gradually changes to Na + -Cltype through Ca 2+ -Mg 2+ -Cltype mixed waters, which might be an indication of change of hydrogeological conditions. The Stiff diagram shows that the water type along the coast is sodium-chloride, which suggests the intrusion of saline water into the deeper aquifer from adjacent seawater. The classification of water based on water quality index (WQI) results majority of the water samples falling under good category and suitable for drinking except samples of Rupsa, Hasanpur, Haldipada bazar, Chakulia (Baharde), Parikhi, Remunabasant market-2, Majhikia and Mala which show poor WQI. Fluoride concentrations also found in some samples above the permissible limit. Iso-concentration maps represent the spatial distribution of concentration of different parameters throughout the study area.

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Section: Introductionmentioning

confidence: 99%

Aquifer salinization: A groundwater appraisal of northeast coast of Odisha using water quality index (WQI) and geospatial interpretation

Das,

Das

2023

EEC

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Computational assessment of groundwater salinity distribution within coastal multi-aquifers of Bangladesh

Jamei

Karbasi

Malik

et al. 2022

Sci Rep

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The rising salinity trend in the country’s coastal groundwater has reached an alarming rate due to unplanned use of groundwater in agriculture and seawater seeping into the underground due to sea-level rise caused by global warming. Therefore, assessing salinity is crucial for the status of safe groundwater in coastal aquifers. In this research, a rigorous hybrid neurocomputing approach comprised of an Adaptive Neuro-Fuzzy Inference System (ANFIS) hybridized with a new meta-heuristic optimization algorithm, namely Aquila optimization (AO) and the Boruta-Random forest feature selection (FS) was developed for estimating the salinity of multi-aquifers in coastal regions of Bangladesh. In this regard, 539 data samples, including ten water quality indices, were collected to provide the predictive model. Moreover, the individual ANFIS, Slime Mould Algorithm (SMA), and Ant Colony Optimization for Continuous Domains (ACOR) coupled with ANFIS (i.e., ANFIS-SMA and ANFIS-ACOR) and LASSO regression (Lasso-Reg) schemes were examined to compare with the primary model. Several goodness-of-fit indices, such as correlation coefficient (R), the root mean squared error (RMSE), and Kling-Gupta efficiency (KGE) were used to validate the robustness of the predictive models. Here, the Boruta-Random Forest (B-RF), as a new robust tree-based FS, was adopted to identify the most significant candidate inputs and effective input combinations to reduce the computational cost and time of the modeling. The outcomes of four selected input combinations ascertained that the ANFIS-OA regarding the best accuracy in terms of (R = 0.9450, RMSE = 1.1253 ppm, and KGE = 0.9146) outperformed the ANFIS-SMA (R = 0.9406, RMSE = 1.1534 ppm, and KGE = 0.8793), ANFIS-ACOR (R = 0.9402, RMSE = 1.1388 ppm, and KGE = 0.8653), Lasso-Reg (R = 0.9358), and ANFIS (R = 0.9306) models. Besides, the first candidate input combination (C1) by three inputs, including Cl− (mg/l), Mg2+ (mg/l), Na+ (mg/l), yielded the best accuracy among all alternatives, implying the role importance of (B-RF) feature selection. Finally, the spatial salinity distribution assessment in the study area ascertained the high predictability potential of the ANFIS-OA hybrid with B-RF feature selection compared to other paradigms. The most important novelty of this research is using a robust framework comprised of the non-linear data filtering technique and a new hybrid neuro-computing approach, which can be considered as a reliable tool to assess water salinity in coastal aquifers.

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Water quality analysis of ground water from locations in North Bangalore

Cited by 2 publications

References 4 publications

Aquifer salinization: A groundwater appraisal of northeast coast of Odisha using water quality index (WQI) and geospatial interpretation

Aquifer salinization: A groundwater appraisal of northeast coast of Odisha using water quality index (WQI) and geospatial interpretation

Computational assessment of groundwater salinity distribution within coastal multi-aquifers of Bangladesh

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