In this study, we compare infinite slope and the three-dimensional stability analysis performed by SCOOPS 3D (software to analyze three-dimensional slope stability throughout a digital landscape). SCOOPS 3D is a model proposed by the U. S. Geological Survey (USGS), the potentialities of which have still not been investigated sufficiently. The comparison between infinite slope and 3D slope stability analysis is carried out using the same hydrological analysis, which is performed with TRIGRS (transient rainfall infiltration and grid-based regional slope-stability model)—another model proposed by USGS. The SCOOPS 3D model requires definition of a series of numerical parameters that can have a significant impact on its own performance, for a given set of physical properties. In the study, we calibrate these numerical parameters through a multi-objective optimization based on genetic algorithms to maximize the model predictability performance in terms of statistics of the receiver operating characteristics (ROC) confusion matrix. This comparison is carried out through an application on a real case study, a catchment in the Oltrepò Pavese (Italy), in which the areas of triggered landslides were accurately monitored during an extreme rainfall on 27–28 April 2009. Results show that the SCOOPS 3D model performs better than the 1D infinite slope stability analysis, as the ROC True Skill Statistic increases from 0.09 to 0.37. In comparison to other studies, we find the 1D model performs worse, likely for the availability of less detailed geological data. On the other side, for the 3D model we find even better results than the two other studies present to date in the scientific literature. This is to be attributed to the optimization process we proposed, which allows to have a greater gain of performance passing from the 1D to the 3D simulation, in comparison to the above-mentioned studies, where no optimization has been applied. Thus, our study contributes to improving the performances of landslide models, which still remain subject to many uncertainty factors.

The proactive approach to drought management is based on measures devised and implemented before, during, and after the drought event, according to a planning strategy rather than within an emergency framework. The measures taken before the initiation of a drought event consist of long-term measures oriented to improve the reliability of the water supply system to meet future demands under drought conditions. The measures taken after a drought is forecasted or starts are short-term measures that try to mitigate the impacts of the particular drought on the basis of a contingency plan. Selection of the preferable mix of long-term and short-term measures can be accomplished through multicriteria decision analysis (MCDA), which enables the comparison of alternatives on the basis of appropriate quantitative and/or qualitative assessment criteria. In this paper, a methodology for the assessment of drought mitigation measures based on a combined use of simulation models and MCDA is applied to a water supply syst...

In recent years, several drought monitoring indexes have found application to describe and compare droughts among different time periods and regions as well as to forecast the evolution of ongoing droughts, in order to select appropriate mitigation measures and policies for water resources management under shortage risk conditions. However, limited efforts have been made to investigate the possibilities of using information conveyed by large-scale climatic indexes to improve the forecasting ability of drought indexes, provided they exert some influence on the climatic variability in a region. The aim of the paper is to develop models for forecasting Palmer Hydrological Drought Index series in Sicily (Italy) based on artificial neural networks, and to extend such models in order to include information from large-scale climatic indexes. First, the influence of North Atlantic Oscillation (NAO) and European Blocking (EB) indexes on Palmer index series, computed on areal monthly precipitation from 1955 until 1...