Time and Date: 10:15 - 11:55 on 3rd June 2015
Chair: Alexander Boukhanovsky
|728|| Computational uncertainty management for coastal flood prevention system [abstract]
Abstract: Multivariate and progressive uncertainty is the main factor of accuracy in simulation systems. It can be a critical issue for systems that forecast and prevent extreme events and related risks. To deal with this problem, computational uncertainty management strategies should be used. This paper aims to demonstrate an adaptation of the computational uncertainty management strategy in the framework of a system for prediction and prevention of such natural disasters as coastal floods. The main goal of the chosen strategy is to highlight the most significant ways of uncertainty propagation and to collocate blocks of action with procedures for reduction or evaluation of uncertainty in a way that catches the major part of model error. Blocks of action involve several procedures: calibration of models, data assimilation, ensemble forecasts, and various techniques for residual uncertainty evaluation (including risk evaluation). The strategy described in this paper was tested and proved based on a case study of the coastal flood prevention system in St. Petersburg.
|Anna Kalyuzhnaya, Alexander Boukhanovsky|
|731|| Computational uncertainty management for coastal flood prevention system. Part II: Diversity analysis [abstract]
Abstract: Surge floods in Saint-Petersburg are related to extreme natural phenomena of rare repeatability. A lot of works were devoted to the problems appeared during maintenance of the flood prevention facility complex in Saint-Petersburg. However a lot of investigation issues connected with similar extreme events in Baltic Sea are remained opened. In this work, for surge flood of rare repeatability reconstruction need combination of two approaches based on the statistical multidimensional extremum analysis and on the synthetic surge floods was made. Synthetic storm model, taking multidimensional probability distributions from Reanalysis was developed and synthetic cyclone generation for its implementation was proposed.
|Anna Kalyuzhnaya, Denis Nasonov, Alexander Visheratin, Alexey Dudko and Alexander Boukhanovsky|
|517|| SIM-CITY: an e-Science framework for urban assisted decision support [abstract]
Abstract: Urban areas are characterised by high population densities and the resulting complex social dynamics. For urban planners to evaluate, analyse, and predict complex urban dynamics, a lot of scenarios and a large parameter space must be explored. In urban disasters, complex situations must be assessed in short notice. We propose the concept of an assisted decision support system to aid in these situations. The system interactively runs a scenario exploration, which evaluates scenarios and optimize for desired properties. We introduce the SIM-CITY architecture to run such interactive scenario explorations and highlight a use case for the architecture, an urban fire emergency response simulation in Bangalore.
|Joris Borgdorff, Harsha Krishna, Michael H. Lees|
|297|| Towards a general definition of Urgent Computing [abstract]
Abstract: Numerical simulations of urgent events, e.g. tsunamis, storms and flash floods, must be completed within a stipulated deadline. The simulation results are needed by relevant authorities in making timely educated decisions to mitigate financial losses, manage affected areas and reduce casualties. The existing definition of urgent computing is too usage context specific and thus restricts the identification of urgent use cases and the general application of urgent computing. We aim to extend and refine the existing definition and provide a comprehensive general definition of urgent computing. This general definition will aid in the identification of urgent computing's unique challenges and thus demonstrates the need for innovative multi-disciplinary solutions to address these challenges.
|Siew Hoon Leong, Dieter Kranzlmüller|
|375|| Combining Data-driven Methods with Finite Element Analysis for Flood Early Warning Systems [abstract]
Abstract: We developed a robust approach for real-time levee condition monitoring based on combination of data-driven methods (one-side classification) and finite element analysis. It was implemented within a flood early warning system and validated on a series of full-scale levee failure experiments organised by the IJkdijk consortium in August-September 2012 in the Netherlands. Our approach has detected anomalies and predicted levee failures several days before the actual collapse. This approach was used in the UrbanFlood decision support system for routine levee quality assessment and for critical situations of a potential levee breach and inundation. In case of emergency, the system generates an alarm, warns dike managers and city authorities, and launches advanced urgent simulations of levee stability and flood dynamics, thus helping to make informed decisions on preventive measures, to evaluate the risks and to alleviate adverse effects of a flood.
|A.L. Pyayt, D.V. Shevchenko, A.P. Kozionov, I.I. Mokhov, B. Lang, V.V. Krzhizhanovskaya, P.M.A. Sloot|