Reliability of fire danger forecasts for Czech agricultural and forestry landscapes

Reliability of fire danger forecasts for Czech agricultural and forestry landscapes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Reliability of fire danger forecasts for Czech agricultural and forestry landscapes Lucie Kudláčková, Rostislav Linda, Jan Balek, Petr Štěpánek, Pavel Zahradníček, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5273235/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 08 Apr, 2025 Read the published version in Fire Ecology → Version 1 posted 4 You are reading this latest preprint version Abstract Background : The 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. Results : We 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. Conclusions : This 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 Republic fire danger FFDI fire occurrence FWI number of wildfires prediction weather forecast Full Text Cite Share Download PDF Status: Published Journal Publication published 08 Apr, 2025 Read the published version in Fire Ecology → Version 1 posted Reviewers agreed at journal 19 Nov, 2024 Reviewers invited by journal 06 Nov, 2024 Editor assigned by journal 22 Oct, 2024 First submitted to journal 21 Oct, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5273235","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":375032377,"identity":"9a68921b-2417-461e-9391-ef011a9c77ce","order_by":0,"name":"Lucie 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