Structure and management of the information required to predict the results of human interventions for environmental restoration after nuclear accidents

CIEMAT, Departamento de Impacto Ambiental de la Energia, Avd. Complutense 22, 28040 Madrid, Spain

Abstract

The decision about the best strategy to restore environments contaminated after nuclear accidents requires to assess accurately the effects of the contamination and the subsequent intervention. A Decision Support System, funded by the EU, has been developed in TEMAS project to analyse and optimise the intervention in complex scenarios. The evaluation methodology breaks down the scenario into basic units for which models describing the radionuclides behaviour and the intervention response are well established. It distinguishes among urban, agricultural and forest environments. Each one is divided into primary compartments (IE) attending to a hierarchical arrangement. This categorization leads to a database with relationships among the information groups (climate, uses, soil, crops and food chain, urban and forest configuration, population data...) through the attributes defining them. In this way, only a few inputs are necessary and the system selects and estimates the rest of parameters. Each IE is associated to different applicable countermeasures characterised in the database. The decision methodology calculates for each intervention cost, residual individual doses and averted collective dose. Finally, it selects the best strategy restricting the maximum annual individual dose and applying cost-effectiveness criteria to the collective averted dose. In this work the type and structure of the information managed in the evaluation module is presented as well as the schematic review of the decision module.