EFFICIENT ALGORITHMS FOR WILDLAND FIRE SIMULATION by VOLODYMYR Y. KONDRATENKO

In this dissertation, we develop the multiple-source shortest path algorithms and examine their application importance in real world problems, such as wildfire modeling. The theoretical basis and its implementation in the Weather Research Forecasting (WRF) model coupled with the fire spread code SFIRE (WRF-SFIRE model) are described. We present a data assimilation method that gives the fire spread model the ability to start the fire simulation from an observed fire perimeter instead of an ignition point. While the model is running, the fire state in the model changes in accordance with the new arriving data by data assimilation. As the fire state changes, the atmospheric state (which is strongly effected by heat flux) does not stay consistent with the fire state. The main difficulty of this methodology occurs in coupled fire-atmosphere models, because once the fire state is modified to match a given starting perimeter, the atmospheric circulation is no longer in sync with it. One of the possible solutions to this problem is a formation of the artificial time of ignition history from an earlier fire state, which is later used to replay the fire progression to the new perimeter with the proper heat fluxes fed into the atmosphere, so that the fire induced circulation is established. In this work, we develop efficient algorithms that start from the fire arrival times given at the set of points (called a perimeter) and create the artificial fire time of ignition and fire spread rate history. Different algorithms were developed in order to suit possible demands of the user, such as implementation in parallel programming,