We used remote sensing data to define new rainfall thresholds for the possible occurrence of landslides in Marche and Umbria regions, central Italy. Remote sensing data are provided by NASA and the estimated rainfall is cumulated every three hours in a regular grid of 0.25° × 0.25°. We exploited a catalogue of temporal and spatial information on landslides triggered by rainfall in the study area in the period 2002-2010. For each slope failure in the catalogue, we calculated the cumulated rainfall E (mm) and the duration D (h) of each rainfall event that triggered one or more landslide, using both remote sensing data and measurements obtained from a rain-gauge network. The rain-gauge network in the study area includes 123 stations and the rainfall is cumulated every hour. Finally, we obtained two data sets of empirical rainfall conditions (D, E) that triggered landslides and we defined the corresponding rainfall thresholds for remote sensing data and for rain gauge data. We used a Frequentist method and assumed that the threshold curve is a power law E = ? × D^?, where ? is a scaling constant (the intercept) and ? is the shape parameter that defines the slope of the power law curve. This method allows to define rainfall threshold corresponding to different exceedance probabilities. We observed that the threshold for remote sensing data is permanently lower than the threshold obtained with rain-gauge measurements. Finally, we found a relationship between the two thresholds. This is important because it permits the use of sensing precipitation data to obtain rainfall thresholds for the possible occurrence of landslides in those areas where rain gauge measurements are insufficient, or inexistent.
Rainfall thresholds for the initiation of landslides in central Italy using remote sensing precipitation data
Luciani S;Rossi M;Guzzetti F
2011
Abstract
We used remote sensing data to define new rainfall thresholds for the possible occurrence of landslides in Marche and Umbria regions, central Italy. Remote sensing data are provided by NASA and the estimated rainfall is cumulated every three hours in a regular grid of 0.25° × 0.25°. We exploited a catalogue of temporal and spatial information on landslides triggered by rainfall in the study area in the period 2002-2010. For each slope failure in the catalogue, we calculated the cumulated rainfall E (mm) and the duration D (h) of each rainfall event that triggered one or more landslide, using both remote sensing data and measurements obtained from a rain-gauge network. The rain-gauge network in the study area includes 123 stations and the rainfall is cumulated every hour. Finally, we obtained two data sets of empirical rainfall conditions (D, E) that triggered landslides and we defined the corresponding rainfall thresholds for remote sensing data and for rain gauge data. We used a Frequentist method and assumed that the threshold curve is a power law E = ? × D^?, where ? is a scaling constant (the intercept) and ? is the shape parameter that defines the slope of the power law curve. This method allows to define rainfall threshold corresponding to different exceedance probabilities. We observed that the threshold for remote sensing data is permanently lower than the threshold obtained with rain-gauge measurements. Finally, we found a relationship between the two thresholds. This is important because it permits the use of sensing precipitation data to obtain rainfall thresholds for the possible occurrence of landslides in those areas where rain gauge measurements are insufficient, or inexistent.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
