Dedicated Lectures in Natural Hazard and Risk Research

Dr. Odin Marc,Junior Researcher at CNRS, will give a lecture titled:

What do we need to better constrain spatial and temporal occurrence of rainfall induced landslides?

The seminar will be on the 1st of June from 10:00 - 12:00.

The venue is at:

Room 1.15

Haus 1, Room 1.22

Universität Potsdam

Karl-Liebknecht-Str. 24/25

14476 Potsdam

Abstract:

Storm-induced landsliding is a global and recurrent hazard, likely to increase with the strengthening of extreme precipitation events associated with current climate change. Risks associated with landslide hazard could be mitigated, for example with early warning systems or forecasting procedures. However, these approaches require to have constrained a tight relation between rainfall characteristics and the occurrence of landsliding. A traditional approach has been to derive such relationships from the failure of individual landslides, but the development of landslide mapping from satellite imagery allows now to constrain large landslide inventories triggered by single storm. Thus, at regional scale, forecasting the region of occurrence of a widespread landsliding event may be easier than forecasting the failure of individual slopes. First, I will start by illustrating the importance of not only considering rainfall during the triggering storms but also past extreme rainfall in the area to understand the pattern of triggered landsliding during a large typhoons in Japan. Then I will show how this approach can be used in data-poor areas by defining and computing rainfall anomaly from rainfall products derived by satellites products, with global applications for 20 landslide events. Using 20 years of data from these satellite products over regional area I discuss how the spatial pattern of intense anomaly corresponds to the landslide pattern, and if years without reported landslides have low level of anomalies. Upon improvement and validation, this approach may also be extended towards nowcasting and potentially forecasting based on meteorological models. These results apply to landslide datasets associated to well identified, relatively short-lived storms, where the long-term dynamic of soil moisture accumulation is not a major control. It cannot be applied in persistently rainy areas, with almost constant clouds, or with heavy continuous rainfall, as for the Himalayan monsoon. Thus, in a second time, I will present a new methods using Sentinel-1 satellite radar amplitude time-series data to time (within one week) the occurrence of landslides. After demonstrating the potential of the methods for well constrained rainfall or earthquake events, I will show the resulting dates for a several seasonal catalogs of monsoon-induced landslides and discuss their relation to the gorkha earthquake and to rainfall measurements. Last, I will show that, in various settings, large, deep-seated landslides departs from the behaviour of the shallower landslides. Based on literature and preliminary results I will discuss how the characterization of antecedent deformation could perhaps be a way forward to better predicts these large landslides with a key impact on hazard and erosion.