Reliability of fire danger forecasts for Czech agricultural and forestry landscapes

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652079%3A_____%2F25%3A00619059" target="_blank" >RIV/86652079:_____/25:00619059 - isvavai.cz</a>

Alternative codes found

RIV/62156489:43210/25:43926880 RIV/00020702:_____/25:N0000092 RIV/00020699:_____/25:N0000072

Result on the web

<a href="https://fireecology.springeropen.com/articles/10.1186/s42408-025-00362-7" target="_blank" >https://fireecology.springeropen.com/articles/10.1186/s42408-025-00362-7</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1186/s42408-025-00362-7" target="_blank" >10.1186/s42408-025-00362-7</a>

Result language

angličtina

Original language name

Reliability of fire danger forecasts for Czech agricultural and forestry landscapes

Original language description

BackgroundThe increasing threat of fire caused by ongoing climate change requires accurate and timely prediction for the effective management of extreme fire situations. The limited research on the connection between fire danger metrics and the occurrence of wildfires in the forested and agricultural landscapes of the Czech Republic underscores the need to better understand how to properly quantify fire danger in the context of Central Europe. This study focused on assessing the accuracy of fire danger prediction with respect to the number of wildfires in different geographic regions of the Czech Republic and provided new insights into central European fire ecology.ResultsWe found that the fire season in the Czech Republic has two peaks, in spring and summer, with regional differences in the total number of wildfires. Analyses of fire danger via the Canadian Fire Weather Index (FWI) and Australian Forest Fire Danger Index (FFDI) for the years 2018-2022 revealed that the IFS numerical weather prediction model is the most suitable for conditions in the Czech Republic. A linear regression model showed a high predictive capability for the total number of wildfires in the Czech Republic, with an observed R-squared value of 0.81 and a mean absolute error (MAE) of 5.19 wildfires with a 95% confidence interval (CI) of 4.94-5.44. Additionally, the second model, which utilized a linear model with random effects to account for regional variability, had an R-squared value of 0.34 and an MAE of 1 wildfire (95% CI +/- 3), indicating that the inclusion of regional correction coefficients (random effects) enhanced the prediction accuracy.ConclusionsThis study provides key insights into fire danger prediction in relation to the number of wildfires. With this model, it is possible to predict how many wildfires may occur at specific values of the FWI and FFDI in individual regions (NUTS 3) of the Czech Republic. This information can be used for more effective readiness planning for human resources and fire equipment while also contributing to the enhancement of general knowledge in the field of fire science in the context of central Europe.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10618 - Ecology

Project

<a href="/en/project/EH22_008%2F0004635" target="_blank" >EH22_008/0004635: AdAgriF - Advanced methods of greenhouse gases emission reduction and sequestration in agriculture and forest landscape for climate change mitigation</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

FIRE ECOLOGY

ISSN

1933-9747

e-ISSN

1933-9747

Volume of the periodical

21

Issue of the periodical within the volume

1

Country of publishing house

US - UNITED STATES

Number of pages

21

Pages from-to

20

UT code for WoS article

001462059700001

EID of the result in the Scopus database

2-s2.0-105002885682