Groundwater is a crucial resource across agricultural, civil, and industrial sectors. The
prediction of groundwater pollution due to various chemical components is vital for planning …

River flow (Q flow) is a hydrological process that considerably impacts the management and
sustainability of water resources. The literature has shown great potential for nature-inspired …

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 …

Reliable and accurate streamflow forecasting is vital for water resource management. Many
streamflow prediction studies have demonstrated the excellent prediction ability of …

Modelling and forecasting the stock price constitute an important area of financial research
for both academics and practitioners. This study seeks to determine whether improvements …

Monthly streamflow prediction can offer important information for optimal management of
water resources, flood mitigation, and drought warning. The semi-humid and semi-arid Wei …

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

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 …

This study compares LSTM neural network and wavelet neural network (WNN) for spatio-
temporal prediction of rainfall and runoff time-series trends in scarcely gauged hydrologic …

Predicting river runoff accurately is of substantial significance for flood control, water
resource allocation, and basin ecological dispatching. To explore the reasonable and …