Abstract Randomized quasi-Monte Carlo methods have enjoyed increasing popularity in
applications due to their faster convergence rate than Monte Carlo, and the existence of …

Wildfires are an essential part of a healthy ecosystem, yet the expansion of the wildland-
urban interface, combined with climatic changes and other anthropogenic activities, have …

Wildfire behavior predictions typically suffer from significant uncertainty. However, wildfire
modeling uncertainties remain largely unquantified in the literature, mainly due to computing …

Geospatial fire behaviour and fire hazard simulators, fire effects models and smoke emission
software commonly use standard fuel models in order to simplify data collection and the …

Wildfires could pose a significant danger to electrical transmission lines and cause
considerable losses to the power grids and residents nearby. Previous studies of preventing …

Computational models for natural hazards usually require a large number of input
parameters that affect the model outcome in a complex manner. The sensitivity of the input …

Shapley effects are attracting increasing attention as sensitivity measures. When the value
function is the conditional variance, they account for the individual and higher order effects …

Background Advances in fire modeling help quantify and map various components and
characterizations of wildfire risk and furthermore help evaluate the ability of fuel treatments …

Predicting wildfire spread is a challenging task fraught with uncertainties.'Perfect'predictions
are unfeasible since uncertainties will always be present. Improving fire spread predictions …

Environmental models involve inherent uncertainties, the understanding of which is required
for use by practitioners. One method of uncertainty quantification is global sensitivity …