The FLaIR model has been developed for the simulation and the forecast
ing of landslide movements activated by rainfall. It is composed of tw
o modules. The first, rainfall-landslide module, correlates precipitat
ion and landslide occurrence. The second, stochastic rainfall module,
provides synthetic generation of rainfalls, giving a probabilistic rep
resentation of future precipitations. A mobility function, schematised
as convolution of the rainfall intensity and a filter function, is re
lated to the probability of landslide occurrence. The forecasting cons
ists of the estimation at time tau of the value that the mobility func
tion may attain to, at time t. Such a value depends on both the observ
ed rainfall intensity, measured before tau, and the estimated one, der
ived from the stochastic rainfall module in the interval]tau, t]. Then
the mobility function is composed of a deterministic and a stochastic
part. In the paper a parameter, variance index, is introduced in orde
r to describe the roles of the two components. For two very general cl
asses of filters the analytical form of the variance index is determin
ed providing an easy evaluation of the weights of the two components.
The behaviour of different types of landslides is finally emphasised b
y two case studies.