[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 …

Prediction of groundwater level fluctuations using artificial intelligence-based models and GMS

KS Mohammed, S Shabanlou, A Rajabi… - Applied Water …, 2023 - Springer
Groundwater level fluctuations are one of the main components of the hydrogeological cycle
and one of the required variables for many water resources operation models. 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) …

Prediction of groundwater level variations using deep learning methods and GMS numerical model

S Amiri, A Rajabi, S Shabanlou, F Yosefvand… - Earth Science …, 2023 - Springer
One of the key elements of the hydrogeological cycle and a variable used by many water
resource operating models is the variation in groundwater level (GWL). One of the biggest …

Effects of climate change on groundwater level variations affected by uncertainty (case study: Razan aquifer)

MM Fallahi, S Shabanlou, A Rajabi, F Yosefvand… - Applied Water …, 2023 - Springer
In this research, the impact of the human factors and climate change on groundwater level
fluctuations affected by uncertainty within 27-year upcoming period (2018–2045) in the …

A novel committee-based framework for modeling groundwater level fluctuations: A combination of mathematical and machine learning models using the weighted …

A Mazraeh, M Bagherifar, S Shabanlou… - Groundwater for …, 2024 - Elsevier
Abstract water level (GWL) fluctuations simulation can be divided into three general
categories: Analytical solution, conceptual or physical-based models, and data-based or …

[HTML][HTML] Determination of groundwater buoyancy reduction coefficient in clay: Model tests, numerical simulations and machine learning methods

W Sun, W Zhang, L Han - Underground Space, 2023 - Elsevier
Groundwater plays an essential role in stabilizing underground structures. However,
hydrostatic uplift forces from groundwater can create safety hazards. This paper obtained the …

A hybrid machine learning model for modeling nitrate concentration in water sources

A Mazraeh, M Bagherifar, S Shabanlou… - Water, Air, & Soil …, 2023 - Springer
Nitrate is one of the most dangerous contaminants that can pollute water sources; as a
result, it is always tried to use accurate methods to monitor its quantity. The goal of this study …

Modelling and prediction of groundwater level using wavelet transform and machine learning methods: A case study for the Sahneh Plain, Iran

E Azizi, F Yosefvand, B Yaghoubi… - Irrigation and …, 2023 - Wiley Online Library
Due to the complexity of numerical models and the need for much information and data in
these models, one of the important solutions is to use artificial intelligence models with a …

Prediction of groundwater level using GMDH artificial neural network based on climate change scenarios

E Azizi, F Yosefvand, B Yaghoubi, MA Izadbakhsh… - Applied Water …, 2024 - Springer
One of the main challenges regarding the prediction of groundwater resource changes is the
climate change phenomenon and its impacts on quantitative variations of such resources …