RESUMEN
The Water Quality Index (WQI) is used to monitor the health and usability of a water body. In this study, we aimed to construct time series prediction models using groundwater WQI (GW-WQI) at four sites: IISCO-Asansol, Durgapur Town, Burdwan University, and Burdwan Station. While statistical spatio-temporal analysis has been reported earlier, no time series analysis of the data or predictive modelling has been done. Pre-monsoon and post-monsoon physico-chemical data from 2010 to 2022 were obtained from the West Bengal Pollution Control Board website to calculate the GW-WQI. Prediction modelling was performed using R 4.1.3 software. Best fit forecast models were selected to predict future trends of GW-WQI with 80% of the data. Subsequently, the models were validated using R-squared, root mean square error (RMSE), mean absolute error (MAE), maximum absolute percentage error (MAPE), and Thiel's U for the model using 20% of the data. Our results show that GW-WQI was good in pre-monsoon but unfit for drinking in post-monsoon in IISCO-Asansol, Durgapur Town, Burdwan University, and Burdwan Station. Arsenic, fluoride, and mercury were the major contaminants resulting in poor GW-WQI. Seasonal ARIMA was the best model for Burdwan University and IISCO-Asansol, ETS for Durgapur Station, and BaggedARIMA for Burdwan Station. The forecast model for Durgapur and Burdwan Station predicted a sharp increase until 2027 but was fluctuating for IISCO-Asansol and Burdwan University. Thus, GW-WQI is a major problem in the industrial belt of West Bengal that is likely to remain high or worsen in the future.
Asunto(s)
Agua Subterránea , Contaminantes Químicos del Agua , Humanos , Monitoreo del Ambiente/métodos , Contaminantes Químicos del Agua/análisis , Calidad del Agua , Agua Subterránea/análisis , IndiaRESUMEN
Increasing levels of pollution put plants under stress, leading to changes in their biochemical factors, which can be measured using the pollution tolerance index (APTI). APTI is a measure of environmental stress on flora, and it is calculated using four parameters (chlorophyll, ascorbic acid, relative water content, and pH). Earlier work in the same belt showed a positive correlation between stress and APTI but concentrated on woody trees only. This study was conducted in the Durgapur industrial belt, West Bengal, from August 2019 to February 2020. Eighteen plant species (herbs) were collected, assessed, and categorized as sensitive, intermediate, and tolerant based on their seasonal APTI values. Results showed that Solanum sisymbriifolium fell in the intermediate range in all three seasons. Persicaria sp. was identified as a tolerant species throughout and could be used to form a green belt. Persicaria orientalis was a sensitive species and can be used as an indicator of pollution.