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 …

Soil water content (SWC) is a soil property that plays a crucial role in a large variety of
biophysical processes, such as seed germination, plant growth, and plant nutrition. SWC …

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 …

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 …

Preferential flow (PF) processes are governed by subsurface soil structures at various
scales. Still, model validation and mechanistic understanding of PF are very lacking. We …

Accurate and reliable monthly runoff forecasting is of great significance for water resource
optimization and management. A neoteric hybrid model based on variational mode …

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

In the Dry Andes of central Chile, summer water resources originate mostly from snowmelt
and ice melt. We use the physically based, spatially distributed hydrological model TOPKAPI …