Technical Note: An operational landslide early warning system at regional scale based on space–time-variable rainfall thresholds

Abstract

Abstract.We set up an early warning system for rainfallinduced landslides in Tuscany (23 000 km 2 ). The system is based on a set of state-of-the-art intensity-duration rainfall thresholds (Segoni et al., 2014b) and makes use of LAMI (Limited Area Model Italy) rainfall forecasts and real-time rainfall data provided by an automated network of more than 300 rain gauges.The system was implemented in a WebGIS to ease the operational use in civil protection procedures: it is simple and intuitive to consult, and it provides different outputs. When switching among different views, the system is able to focus both on monitoring of real-time data and on forecasting at different lead times up to 48 h. Moreover, the system can switch between a basic data view where a synoptic scenario of the hazard can be shown all over the region and a more in-depth view were the rainfall path of rain gauges can be displayed and constantly compared with rainfall thresholds.To better account for the variability of the geomorphological and meteorological settings encountered in Tuscany, the region is subdivided into 25 alert zones, each provided with a specific threshold. The warning system reflects this subdivision: using a network of more than 300 rain gauges, it allows for the monitoring of each alert zone separately so that warnings can be issued independently.An important feature of the warning system is that the visualization of the thresholds in the WebGIS interface may vary in time depending on when the starting time of the rainfall event is set. The starting time of the rainfall event is considered as a variable by the early warning system: whenever new rainfall data are available, a recursive algorithm identifies the starting time for which the rainfall path is closest to or overcomes the threshold. This is considered the most hazardous condition, and it is displayed by the WebGIS interface.The early warning system is used to forecast and monitor the landslide hazard in the whole region, providing specific alert levels for 25 distinct alert zones. In addition, the system can be used to gather, analyze, display, explore, interpret and store rainfall data, thus representing a potential support to both decision makers and scientists.

Basic features of the predictive tools of early warning systems for water-related natural hazards: examples for shallow landslides

“…This is due to the intrinsic difficulty of finding historical data sets of rainstorms and corresponding landslides occurring in a small area, with enough data to allow reliable estimation of the probability of landslide triggering during extreme (and thus rare) rainfall events. Usually, only a few landslides occur at a site during an observation period of typically some decades, so that probabilistic landslide initiation thresholds are mostly defined at regional scale, so as to have a rich data set of observed landslides (e.g., Terlien, 1998;Guzzetti et al, 2007;Jakob et al, 2012;Ponziani et al, 2012;Segoni et al, 2015;Iadanza et al, 2016). The use of physically based models of infiltration and slope stability can help in the prediction of slope response under conditions different from those actually encountered during the observation period, thus allowing the definition of site-specific landslide initiation thresholds (e.g., Arnone et al, 2011;Ruiz-Villanueva et al, 2011;Tarolli et al, 2011;Papa et al, 2013;Peres and Cancelliere, 2014;Posner and Georgakakos, 2015;Greco and Bogaard, 2016), which can be useful for carrying out stochastic predictions.…”

Intensity–duration–frequency curves from remote sensing rainfall estimates: comparing satellite and weather radar over the eastern Mediterranean

“…First, early warning systems, e.g. for flash floods (Borga et al, 2011Villarini et al, 2010), urban floods (Yang et al, 2016), landslides/debris flows (Tiranti et al, 2014;Borga et al, 2014;Segoni et al, 2015), or heavy rain (Panziera et al, 2016), need to operate in real time and rely on shortlatency remote sensing measurements. In these situations, calculating the frequency of near-real-time estimates using IDF curves derived from gauge-adjusted data could provide misleading results.…”

Detailed and large-scale cost/benefit analyses of landslide prevention vs. post-event actions

“…This methodology can also provide an economic point of view for the global landslide issue, giving authorities the appropriate tool to face this ever-growing problem. To this end, new-generation early warning systems should be developed for monitoring and preventing instabilities on local and regional scales (Manconi et al, 2015;Segoni et al, 2015); thanks to the new availability of free data from spaceborne sensors and of WebGIS low-cost solutions, such systems represent reliable and costefficient tools to reduce landslide risk (Stähli et al, 2015). Afterwards, prevention is effectively possible from the economic point of view to the architectural one and could represent an efficient way to defend every defenseless territory.…”