Developing accurate soft computing methods for groundwater level (GWL) forecasting is
essential for enhancing the planning and management of water resources. Over the past two …

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 …

Groundwater potential maps are one of the most important tools for the management of
groundwater storage resources. In this study, we proposed four ensemble soft computing …

The groundwater resources are the essential sources for irrigation and agriculture
management. Forecasting groundwater levels (GWL) for the current and future periods is an …

This study proposes two techniques: Deep Learning (DL) and Ensemble Deep Learning
(EDL) to predict groundwater level (GWL) for five wells in Malaysia. Two scenarios were …

Nature-inspired optimization is an active area of research in the artificial intelligence (AI)
field and has recently been adopted in hydrology for the calibration (training) of both process …

Predicting groundwater levels is pivotal in curbing overexploitation and ensuring effective
water resource governance. However, groundwater level prediction is intricate, driven by …

This study presents a new strategy to predict the monthly groundwater level with short-and
long-lead times over the Rafsanjan aquifer in Iran using an ensemble machine learning …

With the effects of climate change such as increasing heat, higher rainfall, and more
recurrent extreme weather events including storms and floods, a unique approach to …

The main aim of this study is to assess groundwater potential of the DakNong province,
Vietnam, using an advanced ensemble machine learning model (RABANN) that integrates …