Relic surface water (clay-pore water) input triggers arsenic release into the shallow groundwater of Bengal aquifers

Pathak, Pousali; Ghosh, Prosenjit; Banerjee, Sanchita; Chatterjee, R. S.; Muzakkira, Noor; Sikdar, P. K.; Ghosal, Utsab; Liang, Mao-Chang; Meeran, Kathiravan

doi:10.1007/s12040-022-01819-y

Cited by 11 publications

(2 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We note that these conditions are simplified, since a patchy distribution of elevated concentrations exists throughout the Holocene aquifer. However, some research suggests that arsenic is released at or near land surface (e.g., Neumann et al., 2010; Pathak et al., 2022; Polizzotto et al., 2008), and these simplified boundary conditions allow direct comparison of the influence of heterogeneity on solute transport.…”

Section: Methodsmentioning

confidence: 99%

Predicting Subsurface Architecture From Surface Channel Networks in the Bengal Delta

Khan

Ahmed

et al. 2023

JGR Earth Surface

View full text Add to dashboard Cite

In the Bengal Delta, more than 150 million inhabitants rely on groundwater as their primary source of water due to its accessibility and lower risk of microbial contamination compared to surface water (Bangladesh Bureau of Statistics, 2011). However, 27.5 million people are drinking groundwater with high levels of geogenic arsenic in the shallow Abstract Groundwater is the primary source of water in the Bengal Delta but contamination threatens this vital resource. In deltaic environments, heterogeneous sedimentary architecture controls groundwater flow; therefore, characterizing subsurface structure is a critical step in predicting groundwater contamination. Here, we show that surface information can improve the characterization of the nature and geometry of subsurface features, thus improving the predictions of groundwater flow. We selected three locations in the Bengal Delta with distinct surface river network characteristics-the lower delta with straighter tidal channels, the mid-delta with meandering and braided channels, and the inactive delta with transitional sinuous channels. We used surface information, including channel widths, depths, and sinuosity, to create models of the subsurface with object-based geostatistical simulations. We collected an extensive set of lithologic data and filled in gaps with newly drilled boreholes. Our results show that densely distributed lithologic data from active lower and mid-delta are consistent with the object-based models generated from surface information. In the inactive delta, metrics from object-based models derived from surface geometries are not consistent with subsurface data. We further simulated groundwater flow and solute transport through the object-based models and compared these with simulated flow through lithologic models based only on variograms. Substantial differences in flow and transport through the different geologic models show that geometric structure derived from surface information strongly influences groundwater flow and solute transport. Land surface features in active deltas are therefore a valuable source of information for improving the evaluation of groundwater vulnerability to contamination. Plain Language SummaryThe structure of groundwater aquifers affects how groundwater and contaminants move through them. In deltas, dynamic river networks are responsible for depositing sediments that ultimately form subsurface aquifers. Therefore, the characteristics of the surface river channel network should provide information about the structure of the subsurface. We tested this idea using a large set of sedimentary data from the Bengal Basin. We created models of the subsurface based on the surface network and showed that the subsurface data reflect the model characteristics in deltas that are actively depositing sediment. Using these subsurface models as input for groundwater flow models, we showed that incorporating this surface information is important for being able to predict how contaminants move in groundwater.XU ET AL.

show abstract

Section: Methodsmentioning

confidence: 99%

Predicting Subsurface Architecture From Surface Channel Networks in the Bengal Delta

Khan

Ahmed

et al. 2023

JGR Earth Surface

View full text Add to dashboard Cite

show abstract

“…At present, for coal mines in the northern plains, mining surface subsidence is generally believed to be mainly related to the mining method, mining speed, mining depth, mining height, mining width and roof management [5][6][7][8][9][10][11][12]. At this stage, many scholars and experts have a relatively comprehensive understanding of the influencing factors of surface subsidence after coal mining in the northern plains [13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Identification of Surface Subsidence Evaluation Grades of Mines in Southwest China

Kong

Kong²,

Liu³

et al. 2022

Mathematics

View full text Add to dashboard Cite

Due to their complex geological structure, it is difficult to systematically analyze the surface subsidence of coal mines in southwest China, and the factors that cause surface subsidence are also different from other coal mines. Focusing on the problem of surface subsidence caused by mining in southwest China’s mines, a grade evaluation system for surface subsidence of southwest mines is constructed based on the analytic hierarchy process, and ten evaluation indicators are established from the perspectives of mining disturbance and geological structure. A matter–element model of surface subsidence based on matter–element extension theory and a cloud model of surface subsidence based on cloud theory are then constructed. A coal mine in Anshun, Guizhou, is taken as an example to calculate the evaluation level of surface subsidence and thus verify the scientificity of extension theory and cloud theory. The results show that the main factors that affect the surface subsidence of southwest mines are the number of coal seam layers, mining height and comprehensive Platt hardness of rock, similar to that of northern plain coal mines. Surface slope and subsidence area are also very important. The comprehensive correlation degree of each grade of the coal mine is −0.29836, 0.192232, −0.1093 and −0.46531, and the coal mine is concluded to be in grade 2. The calculated similarity of the overall index evaluation cloud map of the coal mine and each grade is 0, 0.3453, 0.7872 and 0, respectively. The coal mine is in grade 2, which is a relatively safe state. Consistent with the calculation results of the extension model and in line with the field situation, the extension matter–element model and cloud model built in this paper can verify each other and have a certain scientificity.

show abstract

Role of physical environment in groundwater contamination by arsenic in parts of West Bengal, India

Brahma

2023

J Earth Syst Sci

View full text Add to dashboard Cite

Relic surface water (clay-pore water) input triggers arsenic release into the shallow groundwater of Bengal aquifers

Cited by 11 publications

References 57 publications

Predicting Subsurface Architecture From Surface Channel Networks in the Bengal Delta

Predicting Subsurface Architecture From Surface Channel Networks in the Bengal Delta

Comprehensive Identification of Surface Subsidence Evaluation Grades of Mines in Southwest China

Role of physical environment in groundwater contamination by arsenic in parts of West Bengal, India

Contact Info

Product

Resources

About