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.

A new comprehensive dataset of annual maximum rainfall depths recorded in 1 to 24 consecutive hours in Italy is presented. More than 4500 stations are considered, spanning the period between 1916 and 2014. For the first time, a national dataset of annual maxima allows for an updated characterization of rainstorms in Italy, getting rid of the regional borders. The spatio-temporal analyses of the highest rainstorms represent a robust starting point for the assessment of the extreme rainfall risk.

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.

We provide the results of the joint analysis of the main climate variables and spatiotemporal distribution of 41 rockfalls that occurred in the Italian Alps between 1997 and 2013 in the absence of an evident trigger. We compared the meteorological conditions preceding the failures with the historical datasets, to determine if rockfall initiation was associated with some climatic anomaly. We found out that temperature anomalies were associated with rockfall occurrence in 83 % of our case studies.

This paper analyses the evolution in space and time of human presence in terms of settlements and associated economic activities along the Eastern Alpine river network in Austria and Italy by using high-resolution satellite images. To this aim, nocturnal artificial luminosity images and the geographical location of streams and rivers are employed. Our results reveal a significant increase of nighttime lights, and thus of human presence.