TY  - JOUR
PY  - 2015//
TI  - Parametric uncertainty quantification in the Rothermel model with randomised quasi-Monte Carlo methods
JO  - International journal of wildland fire
A1  - Liu, Yaning
A1  - Jimenez, Edwin
A1  - Hussaini, M. Yousuff
A1  - Ökten, Giray
A1  - Goodrick, Scott
SP  - 307
EP  - 316
VL  - 24
IS  - 3
N2  - Rothermel's wildland surface fire model is a popular model used in wildland fire management. The original model has a large number of parameters, making uncertainty quantification challenging. In this paper, we use variance-based global sensitivity analysis to reduce the number of model parameters, and apply randomised quasi-Monte Carlo methods to quantify parametric uncertainties for the reduced model. The Monte Carlo estimator used in these calculations is based on a control variate approach applied to the sensitivity derivative enhanced sampling. The chaparral fuel model, selected from Rothermel's 11 original fuel models, is studied as an example. We obtain numerical results that improve the crude Monte Carlo sampling by factors as high as three orders of magnitude.<p /> <p>Language: en</p>
LA  - en
SN  - 1049-8001
UR  - http://dx.doi.org/10.1071/WF13097
ID  - ref1
ER  -