Uncertainty propagation in puff-based dispersion models using polynomial chaos |
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| Authors: | Umamaheswara Konda Tarunraj Singh Puneet Singla Peter Scott |
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| Affiliation: | 1. Department of MAE, University at Buffalo, Buffalo, NY, USA;2. Department of CSE, University at Buffalo, Buffalo, NY, USA;1. Centre for Hydrogeology and Geothermics (CHYN), University of Neuchâtel, Rue Emile Argand 11, 2000 Neuchâtel, Switzerland;2. Terreplus Sàrl, Chemin de Closel 9, 2022 Bevaix, Switzerland;3. ANDRA, 1-7 rue Jean Monnet, 92298 Châtenay-Malabry Cedex, France;1. PIMENT, EA 4518, Université de La Réunion, FST, 15 Avenue René Cassin, 97715 Saint-Denis, Réunion, France;2. Université de Strasbourg, CNRS, ENGEES, LHyGeS UMR 7517, F-67000 Strasbourg, France;3. IRD, UMR LISAH, F-92761 Montpellier, France;4. LMHE, Ecole Nationale d''Ingénieurs de Tunis, Tunisia;1. Department of Agricultural and Biological Engineering, University of Florida, 281 Frazier Rogers Hall, Gainesville, FL, 32611-0570, USA;2. Projects and Rural Engineering Department, Public University of Navarre, Ed. Los Olivos, Pamplona, Spain;3. Geography Department, University of Florida, Gainesville, FL, USA;1. Ven Te Chow Hydrosystems Laboratory, Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA;2. Nebland Software, LLC, Green Bay, WI, USA;1. Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan S4S 0A2, Canada;2. School of Environment, Beijing Normal University, Beijing 100875, China;3. Department of Civil Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada;4. Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2, Canada;5. State Key Laboratory of Hydrology–Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China;6. State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China;1. Institute of Earth and Environmental Sciences, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany;2. Econometrics and Applied Statistics Unit, Joint Research Centre, Ispra, Italy |
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| Abstract: | 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 test case 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 an accurate 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. |
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