The Danjiangkou hydropower station is a water source project for the middle line of the
South-to-North Water Transfer Project in China. The dam is composed of riverbed concrete …

Physically-based hydrologic models can accurately simulate flow discharge in natural
environment, but they cannot precisely consider the anthropogenic disturbance caused by …

This study coupled the ensemble learning method with residual error (RE) correction to
propose a more accurate hydrologic model for the time-series prediction of the reservoir …

In recent years, deep learning (DL) approaches have been proven effective in addressing
high nonlinear relationships within complex systems. Although various scientific studies …

Hydropower remains the largest source of renewable electricity while most hydropower
plants, especially commercial hydropower plants, require accurate future energy or reservoir …

Flash flood forecasting is a challenging task for hydrological modelers due to its complexity,
which often poses obstacles to physics-based models. Given the fast-dynamic nature of …

Accurate forecasting of the available energy portion that corresponds to the reservoir inflow
of the month (s) ahead provides important decision support for hydropower plants in energy …

Seepage is a critical problem in earthfill dams which threatens the dam's stability and safety
owing to extreme shifts in climate change with the rise in water intake in dams. To cope with …

Via the framework of this research, a Bayesian Neural Network (BNN) machine learning
model integrated with atmospheric teleconnection patterns was employed to predict the …

The present study aims to evaluate the potentiality of Bidirectional Long Short-Term Memory
(Bi-LSTM), Convolutional Neural Networks (CNNs), eXtreme Gradient Boosting (XGBoost) …