Hydrological models often have issues during droughts. We used the distributed Continuum model over the Po river basin and independent datasets of streamflow (Q), evapotranspiration (ET), and storage. Continuum simulated Q well during wet years and moderate droughts. Performances declined for a severe drought and we explained this drop with an increased uncertainty in ET anomalies in human-affected croplands. These findings provide guidelines for assessments of model robustness during droughts.

This work shows advances in high-resolution satellite data for hydrology. We performed hydrological simulations for the Po River basin using various satellite products, including precipitation, evaporation, soil moisture, and snow depth. Evaporation and snow depth improved a simulation based on high-quality ground observations. Interestingly, a model calibration relying on satellite data skillfully reproduces observed discharges, paving the way to satellite-driven hydrological applications.

We have analyzed the spatial dependence of rainfall extremes upon elevation and morphology in Italy. Regression analyses show that previous rainfall–elevation relations at national scale can be substantially improved with new data, both using topography attributes and constraining the analysis within areas stemming from geomorphological zonation. Short-duration mean rainfall depths can then be estimated, all over Italy, using different parameters in each area of the geomorphological subdivision.

The dissimilarity methods use basins' descriptors to translate their hydrologic data. The methods use selective basin parameters for the prediction. We coupled dissimilarity model with nearest neighbor algorithm to constitute a model space for the predictions of the flow data. Afterwards, based on the orientation of nearest neighbors of ungauged basin in descriptor space __ the prediction is improved by swapping the model space with the other available models provided the set criteria are met.

The paper provides an easy-to-use implementation of the UNCODE framework, which allows one to estimate the design flood value by directly accounting for sample uncertainty. Other than a design tool, this methodology is also a practical way to quantify the value of data in the design process.

The flow duration curve is a widely used tool to support water resources management, planning of hydropower plants and many other problems in hydrological engineering. This paper describe a procedure to estimate the flow duration curve in river sections where no data are available by exploiting observations from other gauged river basins. The procedure also allows one to include information about existing water intakes that alter the natural flow in the river.