Water is the source of life, and in recent years, with the progress in technology, water quality data have shown explosive growth; how to use the massive amounts of data for water quality prediction services has become a new opportunity and challenge...
Water quality monitoring plays a vital role in the water environment management, while efficient monitoring provides direction and verification of the effectiveness of water management. Traditional water quality monitoring for a variety of water para...
Water quality prediction plays a crucial role in both enterprise management and government environmental management. However, due to the variety in water quality data, inconsistent frequency of data acquisition, inconsistency in data organization, an...
Characterization of the spatiotemporal water quality variation is of utmost importance for water resource management. Changes in water quality have been shown to be significantly affected by uncertain factors such as environmental conditions and anth...
Accurate prediction of water quality involves early identification of future pollutant concentrations and water quality indicators, which is an important prerequisite for optimizing water environment management. Although deep learning algorithms have...
Effective water quality monitoring is essential for protecting aquatic environments and supporting sustainable management of urban rivers. Accurate prediction and visualization of water quality parameters (WQPs) distributions across spatial, temporal...
Recently, machine learning (ML) and deep learning (DL) models based on artificial intelligence (AI) have emerged as fast and reliable tools for predicting water quality index (WQI) in various regions worldwide. In this study, we propose a novel stack...
Floating photovoltaic (FPV) systems represent a promising advancement in renewable energy technology; however, a comprehensive understanding of their environmental impacts is essential. The effects of FPV installation on lake water temperature remain...
Sudden water pollution events in Chaohu Lake pose serious public environmental risks, making reliable short-term prediction of water quality grades essential for effective water quality early warning systems and scientific lake management. Existing a...
Water quality prediction is a fundamental prerequisite for effective water resource management and pollution prevention. Accurate predictions of water quality information can provide essential technical support and strategic planning for the protecti...
This study presents an explainable artificial intelligence (XAI)-based explainable planning management (EPM) framework designed to provide interpretable prediction-driven insights for water quality management. Although deep learning models such as th...
Water quality is a major concern globally and in headwater catchments of developing countries it is often poorly managed. In these catchments, having scarce and heterogeneous information hinders the development of water quality assessments and predic...
Water environmental Internet of Things (IoT) system, which is composed of multiple monitoring points equipped with various water quality IoT devices, provides the possibility for accurate water quality prediction. In the same water area, water flows...
Sensors are a key component of water distribution networks due to their role in monitoring system variables. Specifically, water quality (WQ) sensors are utilized to measure chlorine concentrations in order to maintain water quality standards. Howeve...
In the context of smart cities with advanced Internet of Things (IoT) systems, ensuring the sustainability and safety of freshwater resources is pivotal for public health and urban resilience. This study introduces EWAIS (Ensemble Learning and Explai...
Water quality is an essential part of maintaining a healthy environment for fish farming. The quality of the water is related to a few of the chemical and biological characteristics of water. The conventional evaluation methods of the water quality a...
Freshwater quality and quantity are some of the fundamental requirements for sustaining human life and civilization. The Water Quality Index is the most extensively used parameter for determining water quality worldwide. However, the traditional appr...
Planning, managing and optimising surface water quality is a complex and multifaceted process, influenced by the effects of both climate uncertainties and anthropogenic activities. Developing an innovative and robust decision support framework (DSF)...
With environmental degradation and water scarcity becoming increasingly serious, it is urgent to carry out effective management of water resources. The key task of water environment monitoring is to conduct statistics and analysis of changes in water...
DO is an important index to characterize environmental water quality. The time series fluctuation of DO can be analyzed via frequency band decomposition, which is very valuable for water quality simulations. In this paper, DO in the Chengdu area of C...
The continuous variability in the microbiological quality of surface waters presents significant challenges for ensuring the production of safe drinking water in compliance with public health regulations. Inadequate treatment of surface waters can le...
Climate change might potentially cause extreme weather events to become more frequent and intense. It could also enhance water scarcity and reduce food security. More efficient water management techniques are thus required to ensure a stable food sup...
Water quality monitoring is crucial for public health and environmental protection, but traditional methods lack real-time accuracy. This study addresses this gap by combining feature augmentation methods (e.g., sliding window) with Principal Compone...
Water quality data cleaning is important for the management of water environments. A framework for water quality time series cleaning is proposed in this paper. Considering the nonlinear relationships among water quality indicators, support vector re...
Water quality prediction serves as a crucial basis for water environment supervision and is of great significance for water resource protection. This study utilized meteorological and water quality data from 40 monitoring stations in the Tuojiang Riv...
Dissolved oxygen (DO) is a crucial indicator for characterizing water quality and ecosystem status in freshwater lakes, and its concentration is closely correlated with the surrounding aquatic environment, particularly meteorological conditions. Howe...
Multi-site water quality sequences are jointly affected by seasonal periodicity, meteorological disturbances, and inter-site differences in the Jianghuai Watershed region. Conventional quality prediction models struggle to simultaneously achieve mult...
High-turbidity exceedance events are important indicators of abnormal coastal water quality conditions, but their relatively low frequency compared with normal observations makes reliable classification challenging. This study developed a scenario-ba...
The potential contamination of underground drinking water (UDW) caused by CO2 leakage is a critical decision input for risk assessment and management decision making. This paper presents an overview of the potential alterations to UDW quality caused...
Flow control flushing water from reservoirs has been imposed in South Korea for mitigating harmful cyanobacterial blooms (CyanoHABs) in rivers. This measure, however, can cause water shortage in reservoirs, as the measure adopting this flow control m...
The increasing prevalence of marine pollution during the past few decades motivated recent research to help ease the situation. Typical water quality assessment requires continuous monitoring of water and sediments at remote locations with labour-int...
Dissolved oxygen (DO) is widely recognized as a fundamental parameter in assessing water quality, given its critical role in supporting aquatic ecosystems. Accurate estimation of DO levels is crucial for effective management of riverine environments,...
Predictive maintenance is considered as one of the most important strategies for managing the utility systems of commercial buildings. This research focused on chilled water system (CWS) components and proposed a methodological framework to build a c...
Water quality monitoring is crucial for ecological protection and water resource management. However, traditional monitoring methods suffer from limitations in temporal, spatial, and spectral resolution, which constrain the effective evaluation of ur...
Water quality monitoring is important for protecting aquatic life and supporting informed water quality assessment and environmental decision support. However, many existing systems mainly focus on data collection and threshold-based alerts, without...
Water quality monitoring is critical for public health, ecology, and economic sustainability, but traditional methods are limited by temporal-spatial coverage and cost, failing to meet real-time assessment needs. Deep learning for water quality predi...
Accurate and efficient surface water quality monitoring is essential for ecological protection and sustainable development. However, conventional monitoring methods, such as fixed-site observations, often suffer from spatial limitations and overlook...
This study presents an improved data-centric approach to short-term water demand forecasting using univariate time series from water reservoir levels. The dataset comprises water level recordings from 21 reservoirs in Eastern Thessaloniki collected o...
Predicting algal proliferation in freshwater systems is crucial for effective water quality management and ecological sustainability. This study proposes a novel data-driven framework that integrates correlation-based feature ranking with a concatena...
River water quality monitoring data are often non-stationary and nonlinear and may contain occasional abnormal values. To support anomaly early warning, this study proposes an LSTM–SOA–DA framework. Water quality monitoring data for six i...
The dissolved oxygen concentration (DOC) is an important indicator of water quality. Accurate DOC predictions can provide a scientific basis for water environment management and pollution prevention. This study proposes a hybrid DOC forecasting frame...
We address the challenging problem of predicting the biological quality of a water body based on a set of environmental and management-related drivers. While modelling approaches for predicting water quality from hydrological and pollution-load varia...
Monitoring river water quality is essential for environmental sustainability and public health. This study proposes a machine learning (ML)-based framework to model, predict, and classify the Water Quality Index (WQI) using river water samples collec...
In the wake of frequent and intensive human activities, highly urbanized areas consistently grapple with severe water environmental challenges. It becomes imperative to establish corresponding water environment models for simulating and forecasting r...
The seasonal and interannual irregularity of temperature and precipitation is a feature of the Mediterranean climate that is intensified by climate change and constitutes a relevant driver of water and soil degradation. This study was developed durin...
The contamination of shellfish harvesting areas by fecal bacteria in the Annapolis Basin of Nova Scotia, Canada, is a recurring problem which has consequences for industry, government, and local communities. This study contributes to the development...
Rapid urbanization in Malaysian cities such as Kuala Lumpur, Johor Bahru, and Penang has significantly increased water demand while placing considerable pressure on aging water infrastructure. Traditional monitoring approaches lack real-time visibili...
The extensive deployment of automatic water quality monitoring stations has generated substantial volumes of time-series data. Effectively utilizing these data is crucial for enhancing prediction accuracy. To address the limitations of existing model...
The monitoring and prediction of water quality parameters are important tasks in the management of water resources. In this work, the performances of time series statistical models were evaluated to predict and forecast the dissolved oxygen (DO) conc...
Monitoring water quality is critical for protecting freshwater ecosystems and supporting sustainable water resource management. Lake Tana, Ethiopia’s largest freshwater lake, faces increasing agricultural and urban pressures, while conventional monit...
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