Sensitivity analysis (SA) aims to identify the key parameters that affect model performance
and it plays important roles in model parameterization, calibration, optimization, and …

Water resources in Mediterranean regions are under increasing pressure due to climate
change, economic development, and population growth. Many Mediterranean rivers have …

This paper investigates the degree of complexity required in a snow accounting routine to
ultimately simulate flows at the catchment outlet. We present a simple, parsimonious and …

Physically based models provide insights into key hydrologic processes but are associated
with uncertainties due to deficiencies in forcing data, model parameters, and model …

In structural reliability analysis, Kriging-based adaptive analysis approaches considerably
improve the analysis's efficiency by utilizing proper learning strategies. However, the time …

Formal and informal Bayesian approaches have found widespread implementation and use
in environmental modeling to summarize parameter and predictive uncertainty. Successful …

The transferability of conceptual hydrologic models in time is often limited by both their
structural deficiencies and adopted parameterizations. Adopting a stationary set of model …

Several satellite-based snow products are assimilated, both separately and jointly, into the
Noah land surface model for improving snow prediction in Alaska. These include the …

In snow‐dominated regions, a key source of uncertainty in hydrologic prediction and
forecasting is the magnitude and distribution of snow water equivalent (SWE). With …

Uncertainty plays a key role in hydrological modeling and forecasting, which can have
tremendous environmental, economic, and social impacts. Therefore, it is crucial to …