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 …

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 …

Calculations of risk from natural disasters may require ensembles of hundreds of thousands
of simulations to accurately quantify the complex relationships between the outcome of a …

Every year natural hazards such as wildfires cause massive destruction of physical
infrastructure and loss of lives. A wide range of activities is carried out at different stages of a …

With the goal to facilitate evaluation and mitigation of the risks from natural hazards, the
Natural Hazards Engineering Research Infrastructure's Computational Modeling, and …

Scenario analysis and improved decision-making for wildfires often require a large number
of simulations to be run on state-of-the-art modeling systems, which can be both …

Computational natural wildfire simulation is a computing-intensive process. The process is
also challenging because of the need to integrate data with wide spatial and temporal …

Forest fires cause every year damages to biodiversity, atmosphere, and economy activities.
Forest fire simulation have improved significantly, but input data describing fire scenarios …

This thesis describes a methodology for time response and quality assessment in natural
hazards evolution prediction. This work has been focused on the specific case of forest fires …

The accurate modeling of bushfires is not only complex and contextual but also a
computationally intensive task. Ensemble predictions, involving several thousands to …