Water quality assessment a review in the era of smart technologies: Methods, indices, statistical and geospatial applications

Le résumé fourni par la source

Water quality assessment is crucial for ensuring sustainable water resources management in the face of increasing pollution and climate change. This review examines how methods for evaluating water quality have changed over time, moving from traditional field-based methods to cutting-edge technology like artificial intelligence, remote sensing, and IoT (internet of things)- enabled devices. The evaluation of important physicochemical, bacteriological, and heavy metal factors that affect the safety and usability of water is emphasized. Both surface and groundwater quality are examined in relation to the use of tools like the water quality index (WQI), geographic information systems (GIS), multivariate statistical analysis (MSA), and regression-based machine learning models, such as artificial neural networks (ANN) and Hammerstein-Wiener (HW) models. Strong connections between geospatial analysis, water quality, pollution risk assessment, and statistical analysis are revealed by bibliometric analysis, which also identifies research hotspots and interdisciplinary trends in water quality studies. Through the integration of contemporary data analytics and geographical tools, this review advances the creation of sustainable and comprehensive water resource management.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.