River‐groundwater interactions are at the core of a wide range of major contemporary
challenges, including the provision of high‐quality drinking water in sufficient quantities, the …

Accurate and reliable short-term runoff prediction is of great significance to the management
of water resources optimization and reservoir flood operation. In order to improve the …

In recent years, applications of convolutional neural networks (CNNs) to runoff prediction
have received some attention due to their excellent feature extraction capabilities. However …

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 …

Baseflow plays a vital role in protecting the environment and ensuring a stable water supply
for farming. There are still gaps in the current understanding of baseflow convergence rates …

It is of great significance for operation, planning and dispatching of hydropower station to
predict monthly streamflow accurately. Therefore, the main goal of this study is to investigate …

In recent years, deep Recurrent Neural Network (RNN) has been applied to predict daily
runoff, as its wonderful ability of dealing with the high nonlinear interactions among the …

Abstract The Colorado River has been identified as the most overallocated river in the world.
Considering predicted future imbalances between water supply and demand and the …

Deep neural network (DNN) models have become increasingly popular in the hydrology
community. However, most studies are related to (rainfall-) runoff simulation and …

Baseflow is the slowly varying portion of streamflow, and it is essential for sustaining river
flows. Several methods have been developed for separating baseflow from streamflow …