Floods are among the most destructive natural disasters, which are highly complex to model.
The research on the advancement of flood prediction models contributed to risk reduction …

The estimation of sediment yield concentration is crucial for the development of stream
ventures, watershed management, toxins estimation, soil disintegration, floods, and so on. In …

Rainfall is one of the most significant parameters in a hydrological model. Several models
have been developed to analyze and predict the rainfall forecast. In recent years, wavelet …

In this study, a new method of stand-alone short-term spring snowmelt river flood forecasting
was developed based on wavelet and cross-wavelet analysis. Wavelet and cross-wavelet …

The current study demonstrates the potential use of wavelet neural network (WNN) for river
flow modeling by developing a rainfall-runoff model for Malaprabha basin in India. Daily …

In this research, a new wavelet artificial neural network (WANN) model was proposed for
daily suspended sediment load (SSL) prediction in rivers. In the developed model, wavelet …

Accurate suspended sediment prediction is an integral component of sustainable water
resources and environmental systems. This study considered artificial neural network (ANN) …

Skilful short-term streamflow forecasting is a challenging task, but useful for addressing a
variety of issues associated with water resources planning and management. This study …

In this study, short‐term river flood forecasting models based on wavelet and cross‐wavelet
constituent components were developed and evaluated for forecasting daily stream flows …

Floods are natural phenomena that invade different parts of the globe annually, leaving
severe adverse effects on the natural landscape, particularly in areas where humans …