Environment
Saahil Hembrom; Neeta Kumari
Abstract
Mining activities adversely affect the groundwater quality. Human health also subsequently gets affected because of many environmental and ecological risks due to mobilization of contaminants and alteration of hydrogeochemical processes. This review assesses the hydrogeochemical characteristics and groundwater ...
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Mining activities adversely affect the groundwater quality. Human health also subsequently gets affected because of many environmental and ecological risks due to mobilization of contaminants and alteration of hydrogeochemical processes. This review assesses the hydrogeochemical characteristics and groundwater quality in mining areas emphasizing the crucial processes like rock-water interaction, acid mine drainage formation, and heavy metal contamination. These processes impact the end uses of groundwater quality like drinking, irrigation and industrial uses. To understand the causes of contamination and the availability and suitability of the water, groundwater investigation is required such as assessment of physicochemical parameters and hydrogeochemical faces. By using isotopic techniques and integration of spatial and temporal changes with remote sensing and GIS application, pollution load can be evaluated on water resources. A bibliographic analysis highlights the current research progress in mining sector, focusing on global and regional studies and their impact on water resources. Contamination from heavy metals like arsenic, chromium, cadmium, and other toxic elements has posed serious illnesses to human health and the surrounding ecosystem. The review also highlights the research gaps and prospects for improving groundwater resources through appropriate mitigation strategies like sustainable mining practices and water treatment technologies.
Exploration
Naman Chandel; Sushindra Kumar Gupta; Anand Kumar Ravi
Abstract
Groundwater is an essential resource for human survival, but its quality is often degraded by the human activities such as improper disposal of waste. Leachate generated from landfill sites can contaminate groundwater, causing severe environmental and health problems. Machine learning techniques can ...
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Groundwater is an essential resource for human survival, but its quality is often degraded by the human activities such as improper disposal of waste. Leachate generated from landfill sites can contaminate groundwater, causing severe environmental and health problems. Machine learning techniques can be used to predict groundwater quality and leachate characteristics to manage this issue efficiently. This study proposes a machine learning-based model for the prediction of groundwater quality and leachate characteristics using the effective water quality index (EWQI). The leachate dataset used in this study was obtained from a landfill site, and the groundwater quality dataset was collected from literature review. The mean values of TDS, Ca, Mg, NO3-, and PO4- exceeded the prescribed limit for drinking water purposes. The proposed model utilizes a machine learning architecture based on a convolutional neural network (CNN) to extract relevant features from the input data. The extracted features are then fed into a fully connected network to estimate the EWQI of the input samples. The model, trained and tested on leachate and groundwater quality datasets, achieves a high accuracy and computational efficiency, aiding in predicting groundwater quality and leachate characteristics for waste management.
