An Optimized Approach for Predicting Water Quality Features and A Performance evaluation for Mapping Surface Water Potential Zones Based on Discriminant Analysis (DA), Geographical Information System (GIS) and Machine Learning (ML) Models in Baitarani River Basin, Odisha DOI Creative Commons

Abhijeet Das

Desalination and Water Treatment, Journal Year: 2025, Volume and Issue: 321, P. 101039 - 101039

Published: Jan. 1, 2025

Language: Английский

Geostatistical and multivariate analysis of phosphate evolution and its relationship with heavy metals in shallow groundwater in a Semi-Arid Basin DOI
Saadu Umar Wali,

Noraliani Alias,

Abdulqadir Abubakar Usman

et al.

Earth Science Informatics, Journal Year: 2025, Volume and Issue: 18(3)

Published: Feb. 18, 2025

Language: Английский

Citations

2
Geo-Spatial Insights into Heavy Metal Contamination and Ecological Implications in River Sediments: Identifying Agrochemical Impacts Through Pollution Indices in Morocco’s Sidi Allal Tazi Region, Sebou Basin DOI
Hatim Sanad, Rachid Moussadek,

Latifa Mouhir

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 18, 2025

Abstract Sediments in agricultural ecosystems serve as critical indicators of environmental pollution, particularly regions subjected to intensive practices. This research evaluates the hazards and implications heavy metal (HM) contamination river sediments from Sidi Allal Tazi area within Morocco’s Sebou basin. Twenty sediment samples were extracted strategically designated locations, levels analyzed using a multi-index integration approach, multi-statistical analyses (MSA), Geographic Information Systems (GIS). The results revealed considerable spatial variability HM concentrations, with Cd As displaying highest levels. Statistical analysis, incorporating Principal Component Analysis (PCA), identified anthropogenic activities primary contributors contamination. Hierarchical Cluster (HCA) categorized metals based on common pollution pathways, while GIS mapping distribution across vulnerable areas. Pollution like Geo-accumulation Index (Igeo) well Load (PLI). that 75% sites under “very high pollution”, emphasizing severity Contamination Factor (CF) classified 90% 100% contamination”. Risk indices indicated significant ecological threats, contributing an RI exceeding 600 many areas, signifying risk”. These findings highlight urgent need for targeted mitigation strategies sustainable methodologies provides comprehensive framework assessing managing contamination, offering insights policymakers managers.

Language: Английский

Citations

0
Geochemical fingerprints, evolution, and driving forces of groundwater in an alpine basin on Tibetan Plateau: Insights from unsupervised machine learning and objective weight allocation approaches DOI Creative Commons

Hongjie Yang,

Yong Xiao,

Shaokang Yang

et al.

Journal of Hydrology Regional Studies, Journal Year: 2024, Volume and Issue: 56, P. 102054 - 102054

Published: Nov. 5, 2024

Language: Английский

Citations

3
An Optimized Approach for Predicting Water Quality Features and A Performance evaluation for Mapping Surface Water Potential Zones Based on Discriminant Analysis (DA), Geographical Information System (GIS) and Machine Learning (ML) Models in Baitarani River Basin, Odisha DOI Creative Commons

Abhijeet Das

Desalination and Water Treatment, Journal Year: 2025, Volume and Issue: 321, P. 101039 - 101039

Published: Jan. 1, 2025

Language: Английский

Citations

0