[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 …

Groundwater level forecasting with machine learning models: A review

KBW Boo, A El-Shafie, F Othman, MMH Khan… - Water Research, 2024 - Elsevier
Groundwater, the world's most abundant source of freshwater, is rapidly depleting in many
regions due to a variety of factors. Accurate forecasting of groundwater level (GWL) is …

Performance of Naïve Bayes Tree with ensemble learner techniques for groundwater potential mapping

T Van Phong, BT Pham - Physics and Chemistry of the Earth, Parts A/B/C, 2023 - Elsevier
Water supply is a key challenge and priority for achieving sustainable development goals in
many countries. Recognizing areas with groundwater potential is crucial in addressing this …

Artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) model for Forecasting groundwater level in the Pravara River Basin, India

V Navale, S Mhaske - Modeling Earth Systems and Environment, 2023 - Springer
The precise prediction of groundwater level is essential for water reserve management. In
this study, the two intelligence models, viz, Artificial Neural Network (ANN) and Adaptive …

Groundwater level forecasting using ensemble coactive neuro-fuzzy inference system

KBW Boo, A El-Shafie, F Othman, M Sherif… - Science of The Total …, 2024 - Elsevier
A modeling framework utilizing the coactive neuro-fuzzy inference system (CANFIS) has
been developed for multi-lead time groundwater level (GWL) forecasting in four different …

[HTML][HTML] Soft computing assessment of current and future groundwater resources under CMIP6 scenarios in northwestern Iran

Z Kayhomayoon, MR Jamnani, S Rashidi… - Agricultural Water …, 2023 - Elsevier
Excessive use of water resources in combination with climate change threaten to
significantly reduce groundwater in arid and semiarid regions. We studied the effects of …

Large discrepancy between future demand and supply of agricultural water in northwestern Iran; evidence from WEAP-MODFLOW-machine learning under the CMIP6 …

MR Jamnani, Z Kayhomayoon, NA Azar… - … and Electronics in …, 2024 - Elsevier
The agricultural sector in northwestern Iran uses about 95% of the region's available water
resources and nearly 98% of are aquifer water. Despite the regiońs previous richness in …

Spatial prediction of groundwater levels using machine learning and geostatistical models: a case study of coastal faulted aquifer systems in southeastern Tunisia

H Chihi, I Ben Cheikh Larbi - Hydrogeology Journal, 2023 - Springer
Developing efficient methods for groundwater level (GWL) prediction is essential for
identifying the groundwater flow pattern, characterizing the spatial extent of contaminant …

Integrating multi-source data to assess land subsidence sensitivity and management policies

X Yang, C Jia, H Sun, T Yang, Y Yao - Environmental Impact Assessment …, 2024 - Elsevier
Uneven land subsidence will cause damage to urban buildings and infrastructure and pose
risks to human production and life. This study proposes a new methodology for factor …

Novel ensemble models based on the Split‐Point Sampling and Node Attribute Subsampling Classifier for groundwater potential mapping

Z Wang, TD Le, K Tian, TV Phong… - Earth and Space …, 2024 - Wiley Online Library
Groundwater potential maps are crucial tools for effectively managing water resources,
particularly in agriculturally focused countries such as Vietnam. However, creating these …