Nowadays, mathematical models of hydrological systems are used routinely to guide
decision making in diverse subjects, such as: environmental and risk assessments, design …

Researchers have attempted to use machine learning algorithms to replace physically
based models for streamflow prediction. Although existing studies have contributed to …

This paper presents a review of papers specifically focused on the use of both numerical
and machine learning methods for groundwater level modelling. In the reviewed papers …

Land subsidence (LS) is among the most critical environmental problems, affecting both
agricultural sustainability and urban infrastructure. Existing methods often use either simple …

Numerous reservoirs around the world provide multiple flow regulation functions; key among
these are hydroelectricity production and water releases for irrigation. These functions …

This study mapped and analyzed groundwater potential using two different models, logistic
regression (LR) and multivariate adaptive regression splines (MARS), and compared the …

Accurate estimation of evapotranspiration (ET) is essential for understanding terrestrial
energy, water, and carbon cycles. This study proposes a hybrid model integrating in-situ and …

The Ardebil plain, which is located in northwest Iran, has been faced with a recent and
severe decline in groundwater level caused by a decrease of precipitation, successive long …

The reliable and accurate prediction of groundwater levels is important to improve water-use
efficiency in the development and management of water resources. Three nonlinear time …

Numerical groundwater flow and solute transport models are usually subject to model
structural error due to simplification and/or misrepresentation of the real system, which …