Hydrology is a mature physical science based on application of first principles. However, the
water system is complex and its study requires analysis of increasingly large data available …

For accurate estimation of streamflow of a mountainous river basin, a novel hybrid method is
developed in this study, where gradient-based optimization (GBO) algorithm is employed to …

Floods and droughts are environmental phenomena that occur in Peninsular Malaysia due
to extreme values of streamflow (SF). Due to this, the study of SF prediction is highly …

Long-term streamflow forecasting is a critical step when planning and managing water
resources. Advanced techniques in deep learning have been proposed for forecasting …

This study compares the ability of Long Short-Term Memory (LSTM) tuned with Grey Wolf
Optimization (GWO) and machine learning models, artificial neural network (ANN), Adaptive …

This paper proposes runoff models based on machine learning to estimate daily streamflows
in Oued Sebaou watershed, a Mediterranean coastal basin located in northern Algeria …

Forecasting river flow is crucial for optimal planning, management, and sustainability using
freshwater resources. Many machine learning (ML) approaches have been enhanced to …

Streamflow forecasting is vital for managing water resources, such as flood control,
agriculture planning, hydropower generation, environmental management, drought …

This study investigates the application of the Gaussian Radial Basis Function Neural
Network (GRNN), Gaussian Process Regression (GPR), and Multilayer Perceptron …

Streamflow prediction is an important matter for the water resources management and the
design of hydraulic structures that can be built on rivers. Recently, it has become a widely …