AIMC Topic: Water Quality

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Comprehensive monitoring of the spatiotemporal variation of water quality and its associated human health risks in Luvuvhu river catchment, Vhembe biosphere reserve, South Africa.

Scientific reports
This study investigates the spatiotemporal variations in water quality and assesses the associated human health risks in the Luvuvhu River Catchment (LRC), South Africa. Water quality parameters such as pH, total dissolved solids (TDS), turbidity, te...

Surface water quality evaluation impacting drinking water sources and sanitation using water quality index, multivariate techniques, and interpretable machine learning models in Mahanadi River, Odisha (India).

Environmental geochemistry and health
Water quality and quantity affect crop productivity, with surface water quality having a significant impact. The amount of surface water being used for drinking is gradually rising. Thus, assessing surface water quality and related hydro-chemical cha...

Developing highly accurate machine learning models for optimizing water quality management decisions in tilapia aquaculture.

Scientific reports
The optimization of water quality management is crucial for the success and sustainability of tilapia aquaculture. This study presents a novel approach for developing a decision-support system by comparing various machine learning models to predict o...

Prioritizing geochemical drivers of groundwater quality and health risks in coastal aquifers of Bangladesh using machine learning algorithms.

Environmental geochemistry and health
This study aims to evaluate key parameters of groundwater quality and associated health risks in three coastal aquifers of Cox's Bazar, Bangladesh, with a focus on manganese contamination and geochemical processes. A total of 288 groundwater samples ...

Machine learning-based prediction of drinking water quality index in Western Tehran using KAN, MLP, and traditional models.

Environmental monitoring and assessment
In this study, the water quality index (WQI) was calculated using multivariate statistics, incorporating physical, chemical, and microbiological analysis of water samples taken from water supply networks in the western district of Tehran from 2021 to...

River water quality forecasting: a novel LSTM-Transformer approach enhanced by multi-source data.

Environmental monitoring and assessment
Water quality prediction holds crucial importance as a fundamental technical support for efficient water resource management and strong ecological protection. In this study, aiming to meet the pressing requirement for eutrophication prevention and co...

Time series forecasting of chlorophyll-a concentrations in the Chesapeake Bay.

Scientific reports
Declining water quality poses serious environmental and public health risks, with chlorophyll-a serving as a key biological indicator of harmful algal blooms. This study evaluates the use of a Long Short-Term Memory (LSTM) neural network to forecast ...

Proof-of-concept evaluation at Cox's Bazar of the Safe Water Optimization Tool: water quality modelling for safe water supply in humanitarian emergencies.

BMJ global health
INTRODUCTION: Waterborne diseases are leading concerns in emergencies. Humanitarian guidelines stipulate universal water chlorination targets, but these fail to reliably protect water as postdistribution chlorine decay can leave water vulnerable to p...

An automated machine learning-based framework for predicting groundwater quality with sensor data.

Journal of environmental management
Groundwater quality monitoring stands as a critical aspect of groundwater management, necessitating real-time and accurate measurement technologies. In this study, we introduce an automated framework for predicting NH-N in groundwater using multipara...

Hybrid deep learning optimization for smart agriculture: Dipper throated optimization and polar rose search applied to water quality prediction.

PloS one
Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dippe...