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| Titel |
Forecasting wind-driven wildfires using an inverse modelling approach |
| VerfasserIn |
O. Rios, W. Jahn, G. Rein |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Sciences ; 14, no. 6 ; Nr. 14, no. 6 (2014-06-13), S.1491-1503 |
| Datensatznummer |
250118498
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| Publikation (Nr.) |
 copernicus.org/nhess-14-1491-2014.pdf |
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| Zusammenfassung |
| A technology able to rapidly forecast wildfire dynamics would lead to a paradigm shift in the
response to emergencies, providing the Fire Service with essential information about the ongoing
fire. This paper presents and explores a novel methodology to forecast wildfire dynamics
in wind-driven conditions, using real-time data assimilation and inverse modelling. The
forecasting algorithm combines Rothermel's rate of spread theory with a perimeter expansion model
based on Huygens principle and solves the optimisation problem with a tangent linear approach and
forward automatic differentiation. Its potential is investigated using synthetic data
and
evaluated in different wildfire scenarios. The results show the capacity of the method to
quickly predict the location of the fire front with a positive lead time (ahead of the
event) in the order of 10 min for a spatial scale of 100 m. The greatest strengths of our
method are lightness, speed and flexibility. We specifically tailor the forecast to be efficient and
computationally cheap so it can be used in mobile systems for field deployment and operativeness.
Thus, we put emphasis on producing a positive lead time and the means to maximise it. |
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