The quantification of uncertainty in the ensemble-based predictions of climate change and
the corresponding hydrological impact is necessary for the development of robust climate …

The objective of this study is to evaluate the relative potential of spatially distributed surface
and root zone soil moisture estimates in calibration of Soil and Water Assessment Tool …

Parameter optimization is an essential step in hydrological simulations, especially for
solving practical problems. However, parameter optimization is usually intractable for …

This historical review addresses the issues of the evaluation and testing of hydrological
models, with a focus on rainfall–runoff models. After a discussion of the general …

Mountain regions in arid and semi-arid climates, such as California, are considered
particularly sensitive to climate change because global warming is expected to alter …

Climate change significantly impacts the natural systems, accelerating the global water
cycle, and impacting various ecosystem services. However, the expected effects of climate …

The SWAT model is a semi-distributed hydrological watershed model with an explicit
physical mechanism, which is widely applied in areas characterized by a wide variety of …

The physical-based and machine learning (ML) models are two distinctive tools for
predicting soil salt content (SSC). However, few studies have compared their performances …

Most hydrological studies rely on a model calibrated using discharge alone. However,
judging the model reliability based on such calibration is problematic, as it does not …

Optimizing empirical baseflow filters using environmental tracers (eg, specific electrical
conductance (SEC), turbidity) is an effective and efficient way to quantify the contribution of …