[HTML][HTML] Groundwater level prediction using machine learning models: A comprehensive review

H Tao, MM Hameed, HA Marhoon… - Neurocomputing, 2022 - Elsevier
Develo** accurate soft computing methods for groundwater level (GWL) forecasting is
essential for enhancing the planning and management of water resources. Over the past two …

A review of the artificial intelligence methods in groundwater level modeling

T Rajaee, H Ebrahimi, V Nourani - Journal of hydrology, 2019 - Elsevier
This study is a review to the special issue on artificial intelligence (AI) methods for
groundwater level (GWL) modeling and forecasting, and presents a brief overview of the …

Groundwater level prediction using machine learning algorithms in a drought-prone area

QB Pham, M Kumar, F Di Nunno, A Elbeltagi… - Neural Computing and …, 2022 - Springer
Groundwater resources (GWR) play a crucial role in agricultural crop production, daily life,
and economic progress. Therefore, accurate prediction of groundwater (GW) level will aid in …

Graph neural network for groundwater level forecasting

T Bai, P Tahmasebi - Journal of Hydrology, 2023 - Elsevier
Accurate prediction of groundwater level (GWL) over a period of time is of great importance
for groundwater resources management. Machine learning techniques due to their great …

[HTML][HTML] Groundwater level modeling with machine learning: a systematic review and meta-analysis

A Ahmadi, M Olyaei, Z Heydari, M Emami… - Water, 2022 - mdpi.com
Groundwater is a vital source of freshwater, supporting the livelihood of over two billion
people worldwide. The quantitative assessment of groundwater resources is critical for …

Multiscale groundwater level forecasting: Coupling new machine learning approaches with wavelet transforms

ATMS Rahman, T Hosono, JM Quilty, J Das… - Advances in Water …, 2020 - Elsevier
Groundwater level (GWL) forecasting is crucial for irrigation scheduling, water supply and
land development. Machine learning (ML)(eg, artificial neural networks) has been …

Predictive modeling of groundwater nitrate pollution using Random Forest and multisource variables related to intrinsic and specific vulnerability: A case study in an …

V Rodriguez-Galiano, MP Mendes… - Science of the Total …, 2014 - Elsevier
Watershed management decisions need robust methods, which allow an accurate predictive
modeling of pollutant occurrences. Random Forest (RF) is a powerful machine learning data …

A comprehensive review of conventional, machine leaning, and deep learning models for groundwater level (GWL) forecasting

J Khan, E Lee, AS Balobaid, K Kim - Applied Sciences, 2023 - mdpi.com
Groundwater level (GWL) refers to the depth of the water table or the level of water below the
Earth's surface in underground formations. It is an important factor in managing and …

Groundwater level prediction in Apulia region (Southern Italy) using NARX neural network

F Di Nunno, F Granata - Environmental Research, 2020 - Elsevier
In the Mediterranean area, the high water demand frequently leads to an excessive
exploitation of the water resource, which involves a qualitative degradation of the …

Time series-based groundwater level forecasting using gated recurrent unit deep neural networks

H Lin, A Gharehbaghi, Q Zhang, SS Band… - Engineering …, 2022 - Taylor & Francis
In this research, the mean monthly groundwater level with a range of 3.78 m in Qoşaçay
plain, Iran, is forecast. Regarding three different layers of gated recurrent unit (GRU) …