Pascal Horton

Preliminary Slope Mass Movement Susceptibility Mapping Using DEM and LiDAR DEM

Hazard mapping in mountainous areas at the regional scale has greatly changed since the 1990s thanks to improved digital elevation models (DEM). It is now possible to model slope mass movement and floods with a high level of detail in order to improve geomorphologic mapping. We present examples of regional multi-hazard susceptibility mapping through two Swiss case studies, including landslides, rockfall, debris flows, snow avalanches and floods, in addition to several original methods and software tools. The aim of these recent developments is to take advantage of the availability of high resolution DEM (HRDEM) for better mass movement modeling. Our results indicate a good correspondence between inventories of hazardous zones based on historical events and model predictions. This paper demonstrates that by adapting tools and methods issued from modern technologies, it is possible to obtain reliable documents for land planning purposes over large areas.

Global Optimization of an Analog Method by Means of Genetic Algorithms

AbstractAnalog methods are based on a statistical relationship between synoptic meteorological variables (predictors) and local weather (predictand, to be predicted). This relationship is defined by several parameters, which are often calibrated by means of a semiautomatic sequential procedure. This calibration approach is fast, but has strong limitations. It proceeds through successive steps, and thus cannot handle all parameter dependencies. Furthermore, it cannot automatically optimize some parameters, such as the selection of pressure levels and temporal windows (hours of the day) at which the predictors are compared. To overcome these limitations, the global optimization technique of genetic algorithms is considered, which can jointly optimize all parameters of the method, and get closer to a global optimum, by taking into account the dependencies of the parameters. Moreover, it can objectively calibrate parameters that were previously assessed manually and can take into account new degrees of freedo...

Definition and mapping of potential rockfall source and propagation areas at a regional scale in Basilicata region (Southern Italy)

An overview of the more interesting results of the rockfall source areas and propagation obtained in different zones (Province of Potenza) of Basilicata Region is presented and discussed. Basilicata Region is considered one of the regions in the Mediterranean basin most subject to slope instability. In particular, rockfalls constitute a major hazard in numerous rock cuts in such mountainous area, giving rise to casualties, damages and injuries. For mapping of rockfalls susceptibility, it has been possible to calculate the source areas and the propagation. Slope Angle Distribution procedure (SAD) has been adopted to assess the potential rockfall source areas: it allows to show the characteristic of morphological units, such as rock cliffs, steep slopes, footslopes and plains. Potential rockfall source areas are identified by a threshold angle (above the morphological unit steep slopes). Then rockfalls spreading area is assessed using GIS and process-based software: Flow-R (Flow assessment at a Regional Scale). The limit of the applied method is due to the unavailability of high resolution DEM of the study area, nevertheless potential rockfall source areas are identified through the slope angle distribution deduced from geological and topographic maps GIS format.

The Analogue Method for Precipitation Forecasting: Finding Better Analogue Situations at a Sub-Daily Time Step

Analogue methods (AMs) predict local weather variables (predictands) such as precipitation by means of a statistical relationship with predictors at a synoptic scale. The analogy is generally assessed on gradients of geopotential heights first to sample days with a similar atmospheric circulation. Other predictors such as moisture variables can also be added in a successive level of analogy. The search for candidate situations similar to a given target day is usually undertaken by comparing the state of the atmosphere at fixed hours of the day for both the target day and the candidate analogues. This is a consequence of using standard daily precipitation time series, which are available over longer periods than sub-daily data. However, it is unlikely for the best analogy to occur at the exact same hour for the target and candidate situations. A better analogue situation may be found with a time shift of several hours since a better fit can occur at different times of the day. In order to assess the potential for finding better analogues at a different hour, a moving time window (MTW) has been introduced. The MTW resulted in a better analogy in terms of the atmospheric circulation and showed improved values of the analogy criterion on the entire distribution of the extracted analogue dates. The improvement was found to increase with the analogue rank due to an accumulation of better analogues in the selection. A seasonal effect has also been identified, with larger improvements shown in winter than in summer. This may be attributed to stronger diurnal cycles in summer that favour predictors taken at the same hour for the target and analogue days. The impact of the MTW on the precipitation prediction skill has been assessed by means of a sub-daily precipitation series transformed into moving 24 h totals at 12, 6, and 3 h time steps. The prediction skill was improved by the MTW, as was the reliability of the prediction. Moreover, the improvements were greater for days with heavy precipitation, which are generally related to more dynamic atmospheric situations in which the timing is more specific and for which fewer records are available in the meteorological archive. The improvements of the analogy criterion and the performance scores on precipitation were both found to be higher for MTWs with a smaller time step of 3 h. A 3 h MTW provides 8 times more candidate situations even though they are not fully independent. Since the MTW provides additional situations to the pool of possible analogues, it can be considered as an inflation of the meteorological archive. Because this technique is simple and easily applicable, it should be considered for several applications in different contexts, such as operational forecasting or climate-related studies.