[HTML][HTML] Applications of machine learning to water resources management: A review of present status and future opportunities

AA Ahmed, S Sayed, A Abdoulhalik, S Moutari… - Journal of Cleaner …, 2024 - Elsevier
Water is the most valuable natural resource on earth that plays a critical role in the socio-
economic development of humans worldwide. Water is used for various purposes, including …

Applications of deep learning in water quality management: A state-of-the-art review

KP Wai, MY Chia, CH Koo, YF Huang, WC Chong - Journal of Hydrology, 2022 - Elsevier
Excellent water quality (WQ) is an indispensable element in ensuring sustainable water
resource development. It is highly associated with the 3rd (good health and well-being), the …

Predicting lake water quality index with sensitivity-uncertainty analysis using deep learning algorithms

S Talukdar, S Ahmed, MW Naikoo, A Rahman… - Journal of Cleaner …, 2023 - Elsevier
Regular monitoring and assessment of water quality is essential to maintain the quality of
lake water. A commonly used method for assessing water quality is the Water Quality Index …

Exploring potential machine learning application based on big data for prediction of wastewater quality from different full-scale wastewater treatment plants

QV Ly, VH Truong, B Ji, XC Nguyen, KH Cho… - Science of the Total …, 2022 - Elsevier
Water pollution generated from intensive anthropogenic activities has emerged as a critical
issue concerning ecosystem balance and livelihoods worldwide. Although optimizing …

Current status and prospects of algal bloom early warning technologies: A Review

Y Peng, W Zhang, X Yang, Z Zhang, G Zhu… - Journal of Environmental …, 2024 - Elsevier
In recent years, frequent occurrences of algal blooms due to environmental changes have
posed significant threats to the environment and human health. This paper analyzes the …

Short-term Lake Erie algal bloom prediction by classification and regression models

H Ai, K Zhang, J Sun, H Zhang - Water Research, 2023 - Elsevier
The recent outbreaks of harmful algal blooms in the western Lake Erie Basin (WLEB) have
drawn tremendous attention to bloom prediction for better control and management. Many …

A secondary modal decomposition ensemble deep learning model for groundwater level prediction using multi-data

X Cui, Z Wang, N Xu, J Wu, Z Yao - Environmental Modelling & Software, 2024 - Elsevier
Groundwater level (GWL) prediction is important for ecological protection and resource
utilization; it helps in formulating policies for artificial groundwater recharge, modifying the …

A deep learning method for cyanobacterial harmful algae blooms prediction in Taihu Lake, China

H Cao, L Han, L Li - Harmful Algae, 2022 - Elsevier
Abstract Cyanobacterial Harmful Algae Blooms (CyanoHABs) in the eutrophic lakes have
become a global environmental and ecological problem. In this study, a CNN-LSTM …

Assessment and a review of research on surface water quality modeling

J Bai, J Zhao, Z Zhang, Z Tian - Ecological Modelling, 2022 - Elsevier
Numerical simulation is an effective way to study the transport and transformation of
pollutants in surface water bodies. Widely used models include AQUATOX, CE-QUAL-W2 …

[HTML][HTML] Time-series modelling of harmful cyanobacteria blooms by convolutional neural networks and wavelet generated time-frequency images of environmental …

HG Kim, KH Cho, F Recknagel - Water Research, 2023 - Elsevier
Early warning systems for harmful cyanobacterial blooms (HCBs) that enable precautional
control measures within water bodies and in water works are largely based on inferential …