In order to use environmental models effectively for management and decision-making, it is
vital to establish an appropriate level of confidence in their performance. This paper reviews …

Low flows are seasonal phenomena and an integral component of the flow regime of any
river. Because of increased competition between water uses, the demand for forecasts of …

Ensemble forecasting applied to the field of hydrology is currently an established area of
research embracing a broad spectrum of operational situations. This work catalogs the …

This paper traces two decades of neural network rainfall-runoff and streamflow modelling,
collectively termed 'river forecasting'. The field is now firmly established and the research …

Abstract Artificial Neural Networks (ANNs) are becoming more popular to model ocean
engineering problems. With the development of Artificial Intelligence, data-driven models …

Purpose Evaluating sediment fingerprinting source apportionments with artificial mixtures is
crucial for supporting decision-making and advancing modeling approaches. However …

Due to increasingly serious deterioration of surface water quality, effective water quality
prediction technique for real-time early warning is essential to guarantee the emergency …

Abstract The Artificial Neural Network (ANN) is a powerful data-driven model that can
capture and represent both linear and non-linear relationships between input and output …

A new hybrid model, the wavelet–bootstrap–ANN (WBANN), for daily discharge forecasting
is proposed in this study. The study explores the potential of wavelet and bootstrap** …

This paper proposes a new procedure for water level (or discharge) forecasting under
uncertainty using artificial neural networks: uncertainty is expressed in the form of a fuzzy …