Over the past few years, Deep Learning (DL) methods have garnered substantial
recognition within the field of hydrology and water resources applications. Beginning with a …

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 …

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 …

Flood susceptibility projections relying on standalone models, with one-time train-test data
splitting for model calibration, yields biased results. This study proposed novel integrative …

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

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 …

Efficient simulation of rainfall-runoff relationships is one of the most complex problems owing
to the high number of interrelated hydrological processes. It is well-known that machine …

Groundwater level (GWL) forecasting is crucial for irrigation scheduling, water supply and
land development. Machine learning (ML)(eg, artificial neural networks) has been …

The demand for water resources has increased due to rapid increase of metropolitan areas
brought on by growth in population and industrialisation. In addition, the groundwater …

Many recent studies propose wavelet-based hydrological and water resources forecasting
models that have been incorrectly developed and that cannot properly be used for real …