Catani, Filippo

Fanti, Riccardo

Martelloni, Gianluca

Segoni, Samuele

English

Florence Research

Geophysical Research AbstractsVol. 13, EGU2011-3322-1, 2011EGU General Assembly 2011© Author(s) 2011Snow melt modeling calibrated through simplex flexible algorithm:application to rainfall thresholds for landslides forecastingGianluca Martelloni (1,2), Samuele Segoni (1), Filippo Catani (1), and Riccardo Fanti (1)(1) Earth Sciences Department, University of Firenze, Italy (gianluca.martelloni@unifi.it), (2) Dipartimento di Energetica,University of Firenze, ItalyIn temperate or cold climate regions a not negligible part of precipitation may be withhold in a snow cover until atemperature change that triggers a sudden water input in the ground. The study area, Northern Apennines of Italy,is no exception to this rule as demonstrated by the recent seasonal event of last decade in which several shallowlandslides have been triggered by a rapid snow melt in Tuscany and Emilia-Romagna regions.In order to integrate snow precipitation within existing statistical models for landslide prediction, a simple greydynamic model for the snow melting, is proposed: it takes into account the buildup and melting of the snow coverin time. This model is based on two equations: the conservation of mass (input-output balance) and an empiricalequation for modeling the snow density variation. From the conservation of mass a differential equation of snowcover depth can be obtained: in the proposed model the latter is a function of snow cover density, temperature ofthe air and rainfall (if present). The second equation is an empirical function for the density variation in time anddepends on the snow cover depth (gravity effect) and the temperature of the air. Then to take into account the snowmelt phenomena we use an empirical functional based on chemical kinetics depending on the air temperature,depth and density of snow cover and rainfall (other effects like for example wind, air humidity and radiation, asdata are not available, cannot be considered). In the present form, this model depends on 13 empirical parametersincluding a threshold temperature between snowfall and rainfall and the density of newly fallen snow. In order tothe modeling identification, employing empirical data of depth of snow cover obtained through sensors in the studyarea, we use an optimization algorithm (simplex flexible) to deduce the optimal values of the model parametersto reduce the errors between experimental measures and output of the model. The static and dynamic sensitivityanalysis show a good resilience of the model. The final objective of the work is to increase the predictive capacityof the statistical models for landslide prediction based on rainfall thresholds. In the study area an improvementwas achieved: several landslides, caused by melting, are correctly detected and then in an integrated system forlandslides prediction false alarms are reduced due to re-distribution of water input in the ground.

Snow melt modeling calibrated through simplex flexible algorithm:application to rainfall thresholds for landslides forecasting

https://flore.unifi.it/bitstream/2158/431012/1/Martelloni%20et%20al%20GRA%20vol%2013%20p%203322%20EGU%202011.pdf

Snow melt modeling calibrated through simplex flexible algorithm:application to rainfall thresholds for landslides forecasting

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