As one of nature's most destructive calamities, floods cause fatalities, property destruction,
and infrastructure damage, affecting millions of people worldwide. Due to its ability to …

Predictions of floods, droughts, and fast drought‐flood transitions are required at different
time scales to develop management strategies targeted at minimizing negative societal and …

Predictions of hydrologic variables across the entire water cycle have significant value for
water resources management as well as downstream applications such as ecosystem and …

Abstract Model calibration and validation are critical in hydrological model robustness
assessment. Unfortunately, the commonly used split‐sample test (SST) framework for data …

While deep learning (DL) models exhibit superior simulation accuracy over traditional
distributed hydrological models (DHMs), their main limitations lie in opacity and the absence …

Taylor diagram has been frequently used to evaluate climate or hydrology models 4 or data.
A Taylor diagram summarizes three frequently used metrics including correlation 5 …

Floods cause substantial damage across the world every year. Accurate and timely
prediction of floods can significantly minimize the loss of life and property. Recently …

Twelve actual evaporation datasets are evaluated for their ability to improve the
performance of the fully distributed mesoscale Hydrologic Model (mHM). The datasets …

A companion paper in this Special Issue reviewed the development of a hydrological model
of the Silala River basin, using long‐term data (1969–1992) to determine the basin's water …

This study evaluates the ability of different gridded rainfall datasets to plausibly represent the
spatiotemporal patterns of multiple hydrological processes (ie streamflow, actual …