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 …

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

Stable isotopes in water (oxygen-18 and deuterium) are hydrologic tracers, which have
been embedded into both analytical mass balance and physically based continuous …

In marine ecosystems, both living and non-living organisms depend on “good” water quality.
It depends on a number of factors, and one of the most important is the quality of the water …

Abstract Study region Lai Giang River basin, Central Vietnam Study focus The Digital
Elevation Models (DEM) is essential in hydrological modeling and water cycle …

Abstract Model calibration is the procedure of finding model settings such that simulated
model outputs best match the observed data. Model calibration is necessary when the …

Abstract Machine learning methodology has recently been considered a smart and reliable
way to monitor water quality parameters in aquatic environments like reservoirs and lakes …

Despite the advances in methods of statistical and mathematical modeling, there is
considerable lack of focus on improving how to judge models' quality. Coefficient of …

A deep learning model designed for time series predictions, the long short-term memory
(LSTM) architecture, is regularly producing reliable results in local and regional rainfall …

This study examines the overall performance of the Noah with multiparameterization (Noah‐
MP) land surface model in simulating key land‐atmosphere variables at a global scale and …