Online Program Home
My Program

Abstract Details

Activity Number: 192 - Contributed Poster Presentations: Section on Statistics and the Environment
Type: Contributed
Date/Time: Monday, July 30, 2018 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and the Environment
Abstract #328842
Title: A Note on Managing Uncertainty About Source Release Height After an Accident
Author(s): Ali Gargowm*
Companies: United Arab Emirates Univ / College of Business & Economics
Keywords: Dispersion models; Puff models; Bayesian forecasting
Abstract:

One of the important pieces of information that are needed to inform very early decision-making immediately after a nuclear or chemical accident is how experts (plant designers and safety engineers) believe source emission will develop over time. To address this issue it is essential first to code as much expert opinion as possible about the types and profiles of release and secondly, to modify these opinions - which are often very uncertain- in the light of any observations which do become available. In this article we present a procedure that can be used to manage uncertainty about the height release at the emission source. This height is a key parameter in modelling the subsequent dispersal of contamination (e.g. the higher the release goes, the faster it spreads). When setting the initial parameters of the model, it is difficult to estimate the height of the release and this will obviously affects the consequences. The suggested procedure reduces the risk of setting an erroneous height value by running mixed models. That is, we include several models in our analysis, each with different release height. The Bayesian methodology assigns probabilities to each model representing.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2018 program