A pressing problem facing coastal decision makers is the conversion of "high level" but plausible climate change assessments into an effective basis for climate change adaptation at the local scale. Here, we describe a web-based, geospatial decision-support tool (DST) that provides an assessment of the potential flood risk for populated coastal lowlands arising from future sea-level rise, coastal storms and high river flows.

We investigate the use of landslide failure forecast models by exploiting near-real-time monitoring data. Starting from the inverse velocity theory, we analyze landslide surface displacements on different temporal windows, and apply straightforward statistical methods to obtain confidence intervals on the estimated time of failure. Here we describe the main concepts of our method, and show an example of application to a real emergency scenario, the La Saxe rockslide, Aosta Valley region, northern Italy.