A new analytical model describes how the amount and grain size of sediment transported by rivers influences bedrock channel width, which can be used to predict where rivers will widen or narrow.
Including diverse observations of exchange fluxes, tracer concentrations and residence times in groundwater model calibration results in more robust predictions than using only classical observations.
Most representations of the water cycle are flawed, researchers found by analyzing over 450 diagrams: The effects of humans, seasonal changes, and different biomes are often neglected.
A new study presents a framework for finding the best optimization algorithm.
Hydrological models are usually calibrated using observations of streamflow, but a new method uses remotely sensed land surface temperature for this purpose.
How can scientists make a hydrology model that can predict water flow in an uncertain future climate?