Although numerical and non-numerical models of groundwater flow and transport have
separately been reviewed in several studies, they have not hitherto been reviewed …

Climate, groundwater extraction, and surface water flows have complex nonlinear
relationships with groundwater level in agricultural regions. To better understand the relative …

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 …

The potential of multiple linear regression (MLR) and artificial neural network (ANN)
techniques in predicting transient water levels over a groundwater basin were compared …

In view of worldwide concern for the sustainability of groundwater resources, basin-wide
modeling of groundwater flow is essential for the efficient planning and management of …

The objective of the present study was to assess the impacts of climate change on irrigation
cost in a groundwater dependent irrigated region in northwest Bangladesh. An ensemble of …

Pum** optimization of coastal aquifers involves complex numerical models. In problems
with many decision variables, the computational burden for reaching the optimal solution …

In this study, a novel surrogate model assisted multiobjective memetic algorithm (SMOMA) is
developed for optimal pum** strategies of large-scale coastal groundwater problems. The …

Comprehensive national estimates of groundwater storage loss (GSL) are needed for better
management of natural resources. This is especially important for data scarce regions with …

Considering true values cannot be available at every time step in an online learning
algorithm for multi-step-ahead (MSA) forecasts, a MSA reinforced real-time recurrent …