Water | Free Full-Text | Review: Sources of Hydrological Model Uncertainties and Advances
in Their Analysis Next Article in Journal Assessing the Influence of Compounding Factors to …

The hydrologic community has experienced a surge in interest in machine learning in recent
years. This interest is primarily driven by rapidly growing hydrologic data repositories, as …

The spatially and temporally variable parameters and inputs to complex groundwater
models typically result in long runtimes which hinder comprehensive calibration, sensitivity …

The rapid growth of data in water resources has created new opportunities to accelerate
knowledge discovery with the use of advanced deep learning tools. Hybrid models that …

The overexploitation of groundwater resource and its delicacy management has gained
increasing attentions in recent years worldwide because of causing a series of serious …

North China Plain (NCP) is one of the most important agricultural production regions in
China. A severe water shortage, due to intensive irrigation, exists in the plain. In NCP, crop …

“Structural noise” is a term often used to describe model‐to‐measurement misfit that cannot
be ascribed to measurement noise and therefore must be ascribed to the imperfect nature of …

Decision making relative to groundwater resources requires the characterization, modeling
and prediction of complex and dynamical systems with many degrees of freedom …

Although numerical and non-numerical models of groundwater flow and transport have
separately been reviewed in several studies, they have not hitherto been reviewed …

Numerical groundwater flow and solute transport models are usually subject to model
structural error due to simplification and/or misrepresentation of the real system, which …