Observed and estimated consequences of climate change for the fire weather regime in the moist-temperate climate of the Czech Republic

Trnka, Miroslav; Možný, Martin; Jurečka, František; Bálek, Jan; Semerádová, Daniela; Hlavinka, Petr; Štěpánek, Petr; Farda, Aleš; Skalák, Petr; Cienciala, Emil; Čermák, Petr; Chuchma, Filip; Zahradníček, Pavel; Janouš, Dalibor; Fischer, Milan; Žalud, Zdeněk; Brázdil, Rudolf

doi:10.1016/j.agrformet.2021.108583

Cited by 14 publications

(8 citation statements)

References 59 publications

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“…In total, eight remote sensing data predictors were used. The high density of ground-based climate and precipitation stations was used to run the national soil moisture model [14]. In total, 25 agrometeorological characteristics and characteristics based on water balance model simulations were applied in the study.…”

Section: Yield Loss Predictorsmentioning

confidence: 99%

Estimating Drought-Induced Crop Yield Losses at the Cadastral Area Level in the Czech Republic

et al. 2023

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In the Czech Republic, soil moisture content during the growing season has been decreasing over the past six decades, and drought events have become significantly more frequent. In 2003, 2015, 2018 and 2019, drought affected almost the entire country, with droughts in 2000, 2004, 2007, 2012, 2014 and 2017 having smaller extents but still severe intensities in some regions. The current methods of visiting cadastral areas (approximately 13,000) to allocate compensation funds for the crop yield losses caused by drought or aggregating the losses to district areas (approximately 1000 km2) based on proxy data are both inappropriate. The former due to the required time and resources, the later due to low resolution, which leads to many falsely negative and falsely positive results. Therefore, the study presents a new method to combine ground survey, remotely sensed and model data for determining crop yield losses. The study shows that it is possible to estimate them at the cadastral area level in the Czech Republic and attribute those losses to drought. This can be done with remotely sensed vegetation, water stress and soil moisture conditions with modeled soil moisture anomalies coupled with near-real-time feedback from reporters and with crop status surveys. The newly developed approach allowed the achievement of a proportion of falsely positive errors of less than 10% (e.g., oat 2%, 8%; spring barley 4%, 3%; sugar beets 2%, 21%; and winter wheat 2%, 6% in years 2017, resp. 2018) and allowed for cutting the loss assessment time from eight months in 2017 to eight weeks in 2018.

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Section: Yield Loss Predictorsmentioning

confidence: 99%

Estimating Drought-Induced Crop Yield Losses at the Cadastral Area Level in the Czech Republic

et al. 2023

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“…As inputs for the study, long-term measurements of daily meteorological data from 268 climatological and 787 precipitation measuring stations of the Czech Hydrometeorological Institute were used. This dataset consists of all relevant weather variables, such as daily average, 1400 maximum and minimum temperature ( • C); daily average relative humidity (%); precipitation (mm•day −1 ); global solar radiation (MJ-m −2 •day −1 ) and wind speed (m•s −1 ), from the national drought monitoring system (www.intersucho.cz: last access 20 February 2023), available for the entire Czech Republic with daily weather data interpolated into 500 × 500 m grids [34]. Daily data are interpolated by kriging regression, which uses geographic coordinates, elevation and other terrain characteristics as predictors.…”

Section: Observed Climate Datamentioning

confidence: 99%

Estimating Heat Stress Effects on the Sustainability of Traditional Freshwater Pond Fishery Systems under Climate Change

Orság

Meitner

Fischer

et al. 2023

Water

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Freshwater fish production is significantly correlated with water temperature, which is expected to increase under climate change. This study evaluated changes in water temperature and their impact on productive ponds at fisheries in the Czech Republic. A model was developed to calculate surface water temperature based on the five-day mean of the air temperature and was then tested in several ponds in three major Czech fish production areas. The output of the surface water temperature model was compared with independently measured data (r = 0.79–0.96), and the verified model was then applied to predict climate change conditions. The results were evaluated with regard to the thresholds characterizing the water temperature requirements of fish species and indicated that the limitation of Czech fish farming results from (i) an increased number of continuous periods during which given fish species are threatened by high water temperatures and (ii) the extension of continuous periods with stressful water temperatures. For Czech fisheries, the model suggests a sharp increase in unprecedented temperature regimes, which will pose critical challenges to traditional forms of common carp farming within several decades. Although reducing the level of eutrophication and loading them with organic substances might alleviate expected threads, farming current fish species in deeper and colder ponds at higher elevations might be inevitable.

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“…However, the frequency of forest fire increased by 70% during the periods from 1971 to 1990 and from 1991 to 2015, probably due to the increasingly hot and dry weather [40]. The danger of forest fire is expected to further increase not only due to increasingly conducive fire weather [41], but also due to intensifying human activity at the wildland-urban interface; growing numbers of visitors in the forests; and the increased fire danger associated with elevated forest mortality induced by drought, insects, and diseases. Large-scale forest mortality due to bark-beetle (Coleoptera: Curculionidae: Scolytinae) infestations in Central Europe [42] is of particular concern due to the large amounts of fuels that accumulate [43,44].…”

Section: Introductionmentioning

confidence: 99%

“…We aimed to identify drivers of forest fire ignition in the Czech Republic (Central Europe) in the period 2006 to 2015, placing equal emphasis on landscape, social, and climatic drivers. Contrary to most previous studies, which mainly addressed the effect of climate [41,46], we sought to reach more profound insights by considering factors such as population density, tourism, and wildland-urban interface, which are hypothesized to be associated with fire ignition and spread in the region. This information will allow for a more robust fire danger assessment and forecasts by considering the coupled effects of climate change and ongoing socio-ecological transformations.…”

Section: Introductionmentioning

confidence: 99%

A Combination of Human Activity and Climate Drives Forest Fire Occurrence in Central Europe: The Case of the Czech Republic

Berčák,

Holuša,

Trombik

et al. 2024

Fire

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Central Europe is not a typical wildfire region; however, an increasingly warm and dry climate and model-based projections indicate that the number of forest fires are increasing. This study provides new insights into the drivers of forest fire occurrence in the Czech Republic, during the period 2006 to 2015, by focusing on climate, land cover, and human activity factors. The average annual number of forest fires during the study period was 728, with a median burned area of 0.01 ha. Forest fire incidence showed distinct spring (April) and summer (July to August) peaks, with median burned areas of 0.04 ha and 0.005 ha, respectively. Relationships between the predictors (climate data, forest-related data, socioeconomic data, and landscape-context data) and the number of forest fires in individual municipality districts were analyzed using Generalized Additive Models (GAM) on three time scales (annually, monthly, and during the summer season). The constructed GAMs explained 48.7 and 53.8% of forest fire variability when fire occurrence was analyzed on a monthly scale and during the summer season, respectively. On an annual scale, the models explained 71.4% of the observed forest fire variability. The number of forest fires was related to the number of residents and overnight tourists in the area. The effect of climate was manifested on monthly and summer season scales only, with warmer and drier conditions associated with higher forest fire frequency. A higher proportion of conifers and the length of the wildland–urban interface were also positively associated with forest fire occurrence. Forest fire occurrence was influenced by a combination of climatic, forest-related, and social activity factors. The effect of climate was most pronounced on a monthly scale, corresponding with the presence of two distinct seasonal peaks of forest fire occurrence. The significant effect of factors related to human activity suggests that measures to increase public awareness about fire risk and targeted activity regulation are essential in controlling the risk of fire occurrence in Central Europe. An increasing frequency of fire-conducive weather, forest structure transformations due to excessive tree mortality, and changing patterns of human activity on the landscape require permanent monitoring and assessment of possible shifts in forest fire risk.

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Observed and estimated consequences of climate change for the fire weather regime in the moist-temperate climate of the Czech Republic

Cited by 14 publications

References 59 publications

Estimating Drought-Induced Crop Yield Losses at the Cadastral Area Level in the Czech Republic

Estimating Drought-Induced Crop Yield Losses at the Cadastral Area Level in the Czech Republic

Estimating Heat Stress Effects on the Sustainability of Traditional Freshwater Pond Fishery Systems under Climate Change

A Combination of Human Activity and Climate Drives Forest Fire Occurrence in Central Europe: The Case of the Czech Republic

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