Published online by Cambridge University Press: 16 September 2010
Within the EURANOS project data assimilation (DA) approaches have been successfullyapplied in two areas to improve the predictive power of simulation models used in theRODOS and ARGOS decision support systems. For the areas of atmospheric dispersionmodelling and of modelling the fate of radio-nuclides in urban areas the results ofdemonstration exercises are presented here. With the data assimilation module of theRIMPUFF dispersion code, predictions of the gamma dose rate are corrected with simulatedreadings of fixed detector stations. Using the DA capabilities of the IAMM package formapping the radioactive contamination in inhabited areas, predictions of a large scaledeposition model have been combined with hypothetical measurements on a local scale. Inboth examples the accuracy of the model predictions has been improved and theuncertainties have been reduced.