ABSTRACT
Objective To construct a rapid prediction system to improve the accuracy and efficiency of evaluation of the consequences of nuclear accidents at a field scale. Methods Base on a diagnostic wind field model and Lagrangian particle diffusion, we established a rapid prediction method for wind field and pollutant dispersion around complex underlying surfaces within a field scale, in a way of visual discrimination of buildings and vegetation distribution. With data simulation and the use of a real urban field example, the simulated results were compared with wind tunnel test measurements and computational fluid dynamics results to study the influence of complex underlying surfaces on wind field and pollutant transport in the region. Results The rapid prediction system could clearly simulate the high-resolution wind field and pollutant concentration distribution of the region in about five minutes. It could interface with geographic information software and couple with a mesoscale weather prediction model. In terms of accuracy, the system performed well in wind field simulation, with the fractional deviations of wind speed and wind direction being 0.33 and −0.08, respectively. Concentration field simulation was greatly affected by the wind field, and the ratios of simulated concentrations to observed concentrations were between 0.05 and 3.4, except for a few low concentration points. Conclusion The rapid prediction system can effectively simulate the distribution characteristics of the flow field and improve calculation efficiency when ensuring calculation accuracy, which provides an important reference for emergency response to nuclear accidents.