Uncertainty propagation in puff-based dispersion models using polynomial chaos


Konda, U., Singh, T., Singla, P., and Scott, P.


Environmental Modelling and Software .


Atmospheric dispersion is a complex nonlinear physical process with numerous uncertainties in model parameters, inputs, source parameters, initial and boundary conditions. Accurate propagation of these uncertainties through the dispersion models is crucial for a reliable prediction of the probability distribution of the states and assessment of risk. A simple three-dimensional Gaussian puff-based dispersion model is used as a testcase to study the effect of uncertainties in the model parameters and initial conditions on the output concentration. A polynomial chaos based approach is used to numerically investigate the evolution of the model output uncertainties due to initial condition and parametric uncertainties. The polynomial chaos solution is found to be anaccurate approximation to ground truth, established by Monte Carlo simulation, while offering an efficient computational approach for large nonlinear systems with a relatively small number of uncertainties.

   Author = {U. Konda, T. Singh, P. Singla and P. Scott},
   Journal = {Environmental Modelling and Software},
   Month = {December},
   Title = {Uncertainty propagation in puff-based dispersion models using polynomial chaos},
   Volume = {25},
   Number = {12},
   Pages = {1608--1618},
   Year = {2010}