Final Sediment Outcome from Meteorological Flood Events: A Multimodelling Approach Coastal areas are more and more exposed to the effects of climatic change. Intense local rainfalls increases the frequency of flash floods andor flowlike subaerial and afterward submarine landslides. The overall phenomenon of flash flood is complex and involves different phases strongly connected: heavy precipitations in a short period of time, soil erosion, fan deltas forming at mouth and hyperpycnal flows andor landslides occurrence. Such interrelated phases were separately modelled for simulation purposes by different computational models: Partial Differential Equations methods for weather forecasts and sediment production estimation and Cellular Automata for soil erosion by rainfall and subaerial sediment transport and deposit. Our aim is to complete the model for the last phase of final sediment outcome. This research starts from the results of the previous models and introduces the processes concerning the demolition of fan deltas by sea waves during a seastorm and the subsequent transport of and sediments in suspension by current at the seastorm end and their deposition and eventual flowing on the sea bed. A first reduced implementation of the new model SCIDDICAss2wu0026c1 was applied on the partial reconstruction of the 2016 Bagnara case regarding the meteorological conditions and the flattening of Sfalassaxe2x80x99s fan delta.

A new geometrical approach for fast prediction of front propagation Abstract   The challenge to predict the future is the very reason why we developed sophisticated methods to integrate data, whatever the domain of application. In the context of the subsurface flow characterisation, the 4D seismic data reflecting the reservoir timelapsed changes as a result of production, requires detailed processing before derived valuable information is incorporated in a subsurface model update. This is a highly uncertain timeconsuming process with embedded uncertainty, which is still a challenge in data assimilation procedure. In this study, we propose a new way to the problem of forecasting. A new framework is proposed to extract a proxy model for front prediction directly from timelapse seismic data. Multiple timelapsed seismic surveys present the evolution of processes happening in the subsurface. These, therefore can provide information on the propagation of saturation fronts. This paper is based on the simple idea that, different snapshots in time should be able to determine a velocity propagation of fronts and from this velocity, we can then predict their future unknown positions. This work applies a modified version of the Eikonal equation and a modified version of the fastmarching method. This new approach of forecasting a front position is a fast track prediction of fronts evolution. Also, this approach is more strongly based on selected information within the data. To test this approach, we used a water injection scenario from a North Sea reservoir, from which we generated the synthetic seismic data. We compared the results from our algorithm with results from the simulation model, showing that with few data inputs (only two fronts) and a short computing time of 90xc2xa0s, this method is able to give a good approximation of the waterflood front evolution. It functions as a rapid solution for front prediction based directly on seismic data, irrespective of the shape of the front (isolated blobs), with the only prerequisite being that the sequence of measured fronts is monotonic.