TY - JOUR
T1 - Analysis of historical landslide time series in the Emilia-Romagna region, northern Italy
AU - Rossi, Mauro
AU - Witt, Annette
AU - Guzzetti, Fausto
AU - Malamud, Bruce D.
AU - Peruccacci, Silvia
PY - 2010/8
Y1 - 2010/8
N2 - A catalogue of historical landslides, 1951–2002, for three provinces in the Emilia-Romagna region of northern Italy is presented and its statistical properties studied. The catalogue consists of 2255 reported landslides and is based on historical archives and chronicles. We use two measures for the intensity of landsliding over time: (i) the number of reported landslides in a day (DL) and (ii) the number of reported landslides in an event (Sevent), where an event is one or more consecutive days with landsliding. From 1951–2002 in our study area there were 1057 days with 1 ≤ DL ≤?45 landslides per day, and 596 events with 1 ≤ Sevent ≤ 129 landslides per event. In the first set of analyses, we find that the probability density of landslide intensities in the time series are power-law distributed over at least two-orders of magnitude, with exponent of about −2·0. Although our data is a proxy for landsliding built from newspaper reports, it is the first tentative evidence that the frequency-size of triggered landslide events over time (not just the landslides in a given triggered event), like earthquakes, scale as a power-law or other heavy-tailed distributions. If confirmed, this could have important implications for risk assessment and erosion modelling in a given area. In our second set of analyses, we find that for short antecedent rainfall periods, the minimum amount of rainfall necessary to trigger landslides varies considerably with the intensity of the landsliding (DL and Sevent); whereas for long antecedent periods the magnitude is largely independent of the cumulative amount of rainfall, and the largest values of landslide intensity are always preceded by abundant rainfall. Further, the analysis of the rainfall trend suggests that the trigger of landslides in the study area is related to seasonal rainfall.
AB - A catalogue of historical landslides, 1951–2002, for three provinces in the Emilia-Romagna region of northern Italy is presented and its statistical properties studied. The catalogue consists of 2255 reported landslides and is based on historical archives and chronicles. We use two measures for the intensity of landsliding over time: (i) the number of reported landslides in a day (DL) and (ii) the number of reported landslides in an event (Sevent), where an event is one or more consecutive days with landsliding. From 1951–2002 in our study area there were 1057 days with 1 ≤ DL ≤?45 landslides per day, and 596 events with 1 ≤ Sevent ≤ 129 landslides per event. In the first set of analyses, we find that the probability density of landslide intensities in the time series are power-law distributed over at least two-orders of magnitude, with exponent of about −2·0. Although our data is a proxy for landsliding built from newspaper reports, it is the first tentative evidence that the frequency-size of triggered landslide events over time (not just the landslides in a given triggered event), like earthquakes, scale as a power-law or other heavy-tailed distributions. If confirmed, this could have important implications for risk assessment and erosion modelling in a given area. In our second set of analyses, we find that for short antecedent rainfall periods, the minimum amount of rainfall necessary to trigger landslides varies considerably with the intensity of the landsliding (DL and Sevent); whereas for long antecedent periods the magnitude is largely independent of the cumulative amount of rainfall, and the largest values of landslide intensity are always preceded by abundant rainfall. Further, the analysis of the rainfall trend suggests that the trigger of landslides in the study area is related to seasonal rainfall.
U2 - 10.1002/esp.1858
DO - 10.1002/esp.1858
M3 - Article
SN - 1096-9837
VL - 35
SP - 1123
EP - 1137
JO - EARTH SURFACE PROCESSES AND LANDFORMS
JF - EARTH SURFACE PROCESSES AND LANDFORMS
IS - 10
ER -