Improving the fire weather index system for peatlands using peat-specific hydrological input data

Jonas Mortelmans*, Anne Felsberg, Gabriëlle J.M. De Lannoy, Sander Veraverbeke, Robert D. Field, Niels Andela, Michel Bechtold

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

The Canadian Fire Weather Index (FWI) system, even though originally developed and calibrated for an upland Jack pine forest, is used globally to estimate fire danger for any fire environment. However, for some environments, such as peatlands, the applicability of the FWI in its current form, is often questioned. In this study, we replaced the original moisture codes of the FWI with hydrological estimates resulting from the assimilation of satellite-based L-band passive microwave observations into a peatland-specific land surface model. In a conservative approach that maintains the integrity of the original FWI structure, the distributions of the hydrological estimates were first matched to those of the corresponding original moisture codes before replacement. The resulting adapted FWI, hereafter called FWIpeat, was evaluated using satellite-based information on fire presence over boreal peatlands from 2010 through 2018. Adapting the FWI with model- and satellite-based hydrological information was found to be beneficial in estimating fire danger, especially when replacing the deeper moisture codes of the FWI. For late-season fires, further adaptations of the fine fuel moisture code show even more improvement due to the fact that late-season fires are more hydrologically driven. The proposed FWIpeat should enable improved monitoring of fire risk in boreal peatlands.

Original languageEnglish
Pages (from-to)445-464
Number of pages20
JournalNatural Hazards and Earth System Sciences
Volume24
Issue number2
Early online date9 Feb 2024
DOIs
Publication statusPublished - 2024

Bibliographical note

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Funding

This research has been supported by the Research Foundation – Flanders (FWO) (FWO.G095720N). The computer resources and services used in this work were provided by the High-Performance Computing system of the Vlaams Supercomputer Center, funded by the Research Foundation – Flanders (FWO) and the Flemish Government. It was further supported by the Dutch Research Council (Vidi grant 016.Vidi.189.070) and European Research Council through a Consolidator Grant under the European Union's Horizon 2020 research and innovation program (grant agreement no. 101000987).

FundersFunder number
Vlaamse regering
Fonds Wetenschappelijk Onderzoek
European Research Council
Horizon 2020
Horizon 2020 Framework Programme101000987
Nederlandse Organisatie voor Wetenschappelijk Onderzoek016

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