Geospatial Assessment of Ground Water Quality and Associated Health Problems in the Western Region of India

Implementation of remote sensing algorithms to estimate TOC, Chl-a, and TDS in a tropical water body; Sanalona reservoir, Sinaloa, Mexico

The present study implements a methodology to estimate water quality values using statistical tools and remote sensing techniques in a tropical water body Sanalona. Linear regression models developed by Box-Cox transformations and processed data from LANDSAT-8 imagery (bands) were used to estimate TOC, TDS, and Chl-a of the Sanalona reservoir from 2013 to 2020 at five sampling sites measured every 6 months. A band discriminant analysis was carried out to statistically fit and optimize the proposed algorithms. Coefficients of determination beyond 0.9 were obtained for these water quality parameters (r2TOC = 0.90, r2TDS = 0.95, and r2Chl-a = 0.96). A comparison between the estimated and observed water quality was carried out using different data for validation. The validation of the models showed favorable results with R2TOC = 0.8525, R2TDS = 0.8172, and R2Chl-a = 0.9256. The present study implemented, validated, and compared the results obtained by using an ordered and standardized methodology proposed for the estimation of TOC, TDS, and Chl-a values based on water quality parameters measured in the field and using satellite images.

Application of fuzzy C-means clustering and fuzzy EDAS to assess groundwater irrigation suitability and prioritization for agricultural development in a complex hydrogeological basin

The current research is focused on detecting a river basin suitable for agriculture and priority for management using a new clustering tool of groundwater quality with fuzzy logic technique in R and Geographical Information System. A new fuzzy clustering-soft computing technique has been executed to determine the different hydrochemical zones considering 13 essential parameters such as electrical conductivity, hardness, chloride, sodium adsorption ratio, residual sodium carbonate, soluble sodium percent, magnesium hazard, permeability index, potential salinity, residual sodium bicarbonate, Kelly's ratio, synthetic harmful coefficient, and exchangeable sodium percentage. The derived fuzzy C-mean clustering (FCM) outperformed other available hard computing techniques like hierarchical clustering, K-means clustering, and agglomerative clustering. It divided the sampling sites into 2 clustering groups (FCM I and FCM II) which has been validated using fuzzy silhouette index (0.85), the partition coefficient (0.76), the partial entropy (0.68), and the modified partition coefficient (0.52). The hydrogeochemical analysis confirmed that the rock-water interaction, chemical weathering, and ion exchange process are predominant in the aquifer system of the study area. According to the correlation plots, the studied groundwater samples largely evolved from [Formula: see text], mixed [Formula: see text] types, and [Formula: see text] types. The spatial distribution map and the hydrochemical analysis also gives a clear depiction of the fluoride (> 1.0 mg/l) and high iron (> 0.3 mg/l) contamination in groundwater quality, making it unsuitable for both drinking and irrigation. A fuzzy EDAS priority map has been prepared based on all the irrigation suitability parameters which concludes that the groundwater at the upstream and downstream section of the basin requires the most attention. Based on the highest priority for management, five zones have been delineated: very high (5.98%), high (22.31%), medium (16.39%), low (32.30%), and very low (23.02). The findings of this study will be beneficial to planners and policymakers as they can develop schemes to solve similar problems across the country.

Seasonal fluctuation of water quality and ecogenomic phylogeny of novel potential microbial pollution indicators of Veshaw River Kashmir-Western Himalaya

Nearly a billion people, especially in underdeveloped nations, need safe drinking water. Indian studies suggest that most drinking water sources have high coliform levels, and quality assurance is required. This study was conducted in rural parts of South Kashmir in the Western Himalaya from February 2019 to January 2020. Standard river water sampling was done from upstream to downstream of the river. This study examined the detection, molecular identification, and chemical water quality of coliform-contaminated drinking water, which sums up river water pollution. Water quality varied significantly, indicating downstream contamination. Sangam (downstream) had the highest coliform count, showing 72.2600 cfu per litre in summer, while Kongwaton (upstream), near the Veshaw River, had no coliform count in winter. In summer, Sangam (downstream) had the highest water quality metrics (pH 6.847, Electrical conductivity (EC) 71.620 dS/m, Biological oxygen demand (BOD) 1.120 mg/L, and Chemical oxygen demand (COD) 24.637 mg/L) in all seasons. The lowest winter water quality metrics in Kongwaton were pH 8.947, EC 253.680 dS/m, BOD 4.963 mg/L, and COD 51.440 mg/L. Coliforms in water suggest faecal contamination. This study examines the water quality attributes of drinking water and associated factors to determine river pollution. Total DNA was collected and sequenced for 16 S rDNA and metagenomics. Universal primers were used to amplify the bacterial 16 S rRNA. Using BLAST, the amplified 16 S rRNA gene sequence was matched to the NCBI database. A metagenomic study revealed 27 species with different relative abundance. These species include Escherichia coli, E. fergusonii, E. albertii, Klebsiella grimontii, and Shigella dysenteriae. This study is thought to be the first to discriminate against E. fergusonii, E. albertii, K. grimontii, and S. dysenteriae from E. coli and to report on E. fergusonii and E. albertii, K. grimontii, and S. dysenteriae in the river Veshaw water sources in Kulgam, Western Himalaya.