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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 km 2 ) 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This study presents a summary of sixty years of air temperature and precipitation measurements at the Žabčice weather station, located in the southeastern Czech Republic and operated by Mendel University in Brno. An instrumental dataset spanning two climatological normal periods (1961– 1990 and newly established 1991–2020) is analyzed for long term linear trends with monthly data presented in full span in Appendices. In the new climate normal period, the mean annual temperature increased from 9.3 °C to 10.3 °C with growing trend of 0.34 °C/10 years (p < 0.001). Every calendar month of year is warmer, with the highest and fastest increase in August (+2.0 °C, 0.64 °C/10 years, p < 0.001) and the lowest in October (+0.2 °C). Annual precipitation sum increased negligibly (+11.1 mm), however, the quarterly distribution significantly changes towards drier second quarter (-22.9 mm, p < 0.05) and wetter third quarter (+37.1 mm, p < 0.05). Number of tropical days (maximum daily air temperature > 30 °C) significantly increased (+4.44/10 years, p < 0.001), whereas number of frost days is negligibly decreasing (-0.88/10 years). Temperature derived Huglin index for vineyards increased by 369 °C to a seasonal sum 2062 °C (+84 °C/10 years, p < 0.001). This study provides evidence of the rate of changing climate at this southern Moravia lowland site. [ABSTRACT FROM AUTHOR]

The present study analyses 61 years of phenological observations (1961–2021) of five herb, five shrub, four tree, and one bird species representing the prevalent spring species of floodplain forest ecosystems in the Czech Republic, central Europe. The in situ observations were conducted at the Vranovice site (48°48′ N, 16°46′ E, 170 m above mean sea level) representing the Plaček' forest National Reserve. The observed plants and bird species showed statistically significant (p < 0.05) shifts in phenological terms to an earlier date of the year, but the rate of the shift among the observed species differed. The most progressive shifts were detected for the herbs (14 days), followed by the shrubs (13 days), trees (9 days), and finally by the bird species (8 days). All the phenophases were significantly correlated with the daily maximum temperature (r = 0.72–0.91). The results also showed a decline in the correlation for species among the phenophases of the herbs and trees. The phenophases that were highly correlated in the past were less correlated and had higher variability in the last decades. We conclude that the phenological response of the ecosystem to warming in the spring resulted in higher variability and a lower correlation among the observed phenophases mainly caused by the most expressive phenological shifts of the early herbs. [ABSTRACT FROM AUTHOR]

In 1994, a network of small catchments (GEOMON) was established in the Czech Republic to determine input–output element fluxes in semi‐natural forest ecosystems recovering from anthropogenic acidification. The network consists from 16 catchments and the primary observations of elements fluxes were complemented by monitoring of biomass stock, element pools in soil and vegetation, and the main water balance components. Over last three decades, reductions of SO2, NOx and NH3 emissions were followed by sulphur (S) and nitrogen (N) deposition reductions of 75% and 30%, respectively. Steeper declines of strong acid anion concentrations compared to cations (Ca, Mg, Na, K, NH4) in precipitation resulted in precipitation pH increase from 4.5 to 5.2 in bulk precipitation and from 4.0 to 5.1 in spruce throughfall. Stream chemistry responded to changes in deposition: S leaching declined. However at majority of catchments soils acted as a net source of S to runoff, delaying recovery. Stream pH increased at acidic streams (pH < 6) and aluminium concentration decreased. Stream nitrate (NO3) concentration declined by 60%, considerably more than N deposition. Stream NO3 concentration was tightly positively related to stream total dissolved nitrogen to total phosphorus (P) ratio, suggesting the role of P availability on N retention. Trends in dissolved organic carbon fluxes responded to both acidification recovery and to runoff temporal variation. An exceptional drought occurred between 2014 and 2019. Over this recent period, streamflow decreased by ≈ 40% on average compared to 1990s, due to the increases of soil evaporation and vegetation transpiration by ≈ 30% and declines in precipitation by ≈ 15% on average across the elevational gradient. Sharp decreases of stream runoff at catchments <650 m a.s.l. corresponded to areas of recent forest decline caused by bark beetle infestation on drought stressed spruce forests. Understanding of the interactions among legacies of acidification and eutrophication, drought effects on the water cycle and forest disturbance dynamics is requisite for effective management of forested ecosystems under anthropogenic influence. [ABSTRACT FROM AUTHOR]

The awareness of drought and its impacts on Central Europe increased after the significant drought episodes in 2000, 2003, 2012 and 2015, which were all estimated to have caused over 500 million Euro in damage in the Czech Republic alone. These events indicated the need for timely and high‐resolution monitoring tools that would enable analysing, monitoring and forecasting of drought events. Monitoring soil water availability in near real time and at high‐resolution (up to 0.5 × 0.5 km for some products) helps farmers and water managers to mitigate impacts of these extreme events. The Czech Drought Monitor was developed between 2012 and 2014 and has since been operational as an online platform. It uses an operational modelling system that consists of four pillars: (a) weekly soil moisture estimates based on spaceborne Advanced Scatterometer sensor measurements; (b) the daily SoilClim soil moisture model, which runs based on high‐density network data from the Czech Hydrometeorological Institute with a 55‐year reference period; (c) weekly reports on vegetation condition, which is deduced from satellite‐based vegetation indices and early warnings of imminent drought impacts; and (d) weekly reports of soil moisture, especially after drought impacts, which are provided by dozens of experts. Since 2016 the drought forecast (+9 days) has been released daily based on an ensemble of five numerical weather prediction models combined with a weekly drought outlook (+2 months). The analysis of four recent episodes (2000, 2003, 2012 and 2015) clearly showed that both large‐scale and regionally restrained drought episodes posed serious risks in terms of their impacts and damage. Comparisons with historical droughts showed that these events, especially the 2000, 2003 and 2015 events, were among the top five drought episodes in the June–August period observed in the Czech Republic since 1961 in terms of spatial extent, magnitude and duration. [ABSTRACT FROM AUTHOR]

Floodplain forests are very complex, productive ecosystems, capable of storing huge amounts of soil carbon. With the increasing occurrence of extreme events, they are today among the most threatened ecosystems. Our study's main goal was to assess the productivity of a floodplain forest located at Lanžhot in the Czech Republic from two perspectives: carbon uptake (using an eddy covariance method) and stem radius variations (using dendrometers). We aimed to determine which conditions allow for high ecosystem production and what role drought plays in reducing such production potential. Additionally, we were interested to determine the relative soil water content threshold indicating the onset and duration of this event. We hypothesized that summer drought in 2018 had the most significant negative effects on the overall annual carbon and water budgets. In contrast with our original hypothesis, we found that an exceptionally warm spring in 2018 caused a positive gross primary production (GPP) and evapotranspiration (ET) anomaly that consequently led in 2018 to the highest seasonal total GPP and ET from all of the investigated years (2015–2018). The results showed ring-porous species to be the most drought resistant. Relative soil water content threshold of approximately 0.45 was determined as indicating the onset of drought stress. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'. [ABSTRACT FROM AUTHOR]

In order to understand the effect of phytotoxic tropospheric ozone (O3) on terrestrial vegetation, we quantified the impact of current O3 concentration ([O3]) on net ecosystem production (NEP) when compared to the conditions of the pre-industrial era. We compared and tested linear mixed-effects models based on [O3] and stomatal O3 flux (Fsto). The managed ryegrass–clover (Lolium perenne and Trifolium pratense) mixture was grown on arable land in the Czech Republic, Central Europe. Values of [O3] and Fsto were measured and calculated based on resistance analogy, respectively, while NEP was calculated from eddy covariance CO2 fluxes. We found the Fsto-based model more precise when compared to measured NEP. High Fsto was found even at low [O3], while broad summer maximum of [O3] was not necessarily followed by significant NEP decline, due to low soil water content leading to a low stomatal conductivity and Fsto. Comparing to low pre-industrial O3 conditions, current levels of O3 resulted in the reduction of cumulative NEP over the entire growing season, up to 29.7 and 13.5% when the [O3]-based and Fsto-based model was applied, respectively. During the growing season, an O3-induced reduction of NEP ranged between 13.1% in May and 26.2% in July when compared to pre-industrial Fsto levels. Looking to the future, high [O3] and Fsto may lead to the reduction of current NEP by approximately 13.3% on average during the growing season, but may increase by up to 61–86.6% in autumn, indicating further O3-induced acceleration of the senescence. These findings indicate the importance of Fsto and its inclusion into the models estimating O3 effects on terrestrial vegetation. The interaction between environmental factors and stomatal conductance is therefore discussed in detail. [ABSTRACT FROM AUTHOR]

Indicators based on evapotranspiration (ET) provide useful information about surface water status, response of vegetation to drought stress, and potential growth limitations. The capability of ET-based indicators, including actual ET and the evaporative stress index (ESI), to predict crop yields of spring barley and winter wheat was analyzed for 33 districts of the Czech Republic. In this study, the ET-based indicators were computed using two different approaches: (i) a prognostic model, SoilClim, which computes the water balance based on ground weather observations and information about soil and land cover; (ii) the diagnostic Atmosphere–Land Exchange Inverse (ALEXI) model based primarily on remotely sensed land surface temperature data. The capability of both sets of indicators to predict yields of spring barley and winter wheat was tested using artificial neural networks (ANNs) applied to the adjusting number and timeframe of inputs during the growing season. Yield predictions based on ANNs were computed for both crops for all districts together, as well as for individual districts. The root mean square error (RMSE) and coefficient of determination (R2) between observed and predicted yields varied with date within the growing season and with the number of ANN inputs used for yield prediction. The period with the highest predictive capability started from early-June to mid-June. This optimal period for yield prediction was identifiable already at the lower number of ANN inputs, nevertheless, the accuracy of the prediction improved as more inputs were included within ANNs.The RMSE values for individual districts varied between 0.4 and 0.7 t ha–1 while R2 reached values of 0.5–0.8 during the optimal period. Results of the study demonstrated that ET-based indicators can be used for yield prediction in real time during the growing season and therefore have great potential for decision making at regional and district levels. • Results of the study demonstrated that ET-based indicators can be used for yield prediction prior to harvest. • ET-based indicators can be employed as a useful tool for assessment of drought and its impact on agricultural crops. • ET-based indicators can be used in real time during the season and thus have great potential for decision making at regional and district levels. [ABSTRACT FROM AUTHOR]

Satisfactory requirements for the spatial resolution of climate and the influences of soil data in defining the starting points, endings, and the intensities of droughts have become matters of discussion in recent years. The overall inclusiveness of the modelling tools applied is also frequently discussed. In this light, five model setups (MSs) of the daily SoilClim water balance model were developed and tested for the Czech Republic (CR) in the 1961–2020 period. These included two versions of the SoilClim model, two sets of soil data, and two sets of climatic data at different spatial resolutions. MS1–MS4 were based on local, spatially-interpolated data from meteorological stations (500 × 500 m resolution), while MS5 was developed for global drought monitoring, based on the coarser ERA5-Land reanalysis (0.1° × 0.1°). During the 1961–2020 period, all the MSs indicated strong, statistically significant increases in the occurrence of 10th-percentile soil drought in the April–June season; however, trends remained largely non-significant for the remainder of the year. Variations among MS1–MS4 demonstrate that the range of soil property input data affects results to a lesser extent than different modelling schemes. The major simplification of the model grid in MS5 still led to an acceptable conformity of results, while the non-conformities disclosed may be explained by differences between meteorological inputs. Comparison with the Palmer Drought Severity Index (PDSI) confirmed that the SoilClim model depicts the variability of soil drought occurrence in greater detail, while PDSI tends to highlight the most severe events. The discussion arising out of the study centers around model uncertainties and the expression of soil drought episodes in different MSs. [ABSTRACT FROM AUTHOR]

Above canopy eddy covariance (EC) derived forest carbon fluxes might be biased due todecoupling and insufficient mixing between above and below canopy air masses andconsequently missing soil respiration components in the above canopy derived data. Themost common way to address insufficient mixing across the canopy is to filter theabove canopy derived fluxes at a certain u∗-threshold. However, at some sites likee.g. at the current study site Bílý Kříž (49˚ 30′N, 18˚ 32′E; 800–900 m a.s.l.)located in the Moravian-Silesian Beskydy Mountains, the Czech Republic, it isnot possible to identify a u∗-threshold due to the complexity of the surroundingterrain. The Bílý Kříž experimental forest is a ∼ 40 years old Norway spruce(Picea abies /L./, Karst) monoculture with a leaf area index of ∼ 9 m2 m−2 in 2016.Eddy covariance measurements of energy and trace gas fluxes have a more thandecade long tradition at this site. The EC tower is situated close to a ridge on a steeproughly south oriented planar slope with a regular inclination of 13˚. North of thesite, there is a W-E-oriented mountain crest with a shallow saddle. The ridge andslope force the flow above the canopy in two main regimes, namely upslope anddownslope. Recently, an additional below-canopy EC system was installed at the study site to supportthe interpretation of the above canopy derived EC data. Amongst others, such abelow-canopy system provides readings of the standard deviation of vertical wind(σw). The correlation of σw between above and below canopy EC measurementsremarkably differs for the cases of decoupling and the cases of full coupling betweenbelow and above canopy air masses. Thus, once an objective site-specific thresholdin this σw correlation is experimentally determined, it can be used as an EC fluxfiltering approach to improve the representativeness of the above canopy derivedfluxes. With this study we aim to assess decoupling with a set of two-level filtering approachesbased on 1 year (August 2017 – July 2018) of vertical wind measurements above and belowthe canopy: i) σw (described above), ii) telegraphic approximation (w) which identifiesperiods where the vertical wind above and below the canopy is directed in the samedirection and considers these periods as coupled, iii) cross correlation maximum(w) which is used as measure for maximum of below-above canopy coupling. Thevalue ranges and characteristics of these 3 measures throughout the seasons willbe given and ways to identify filtering thresholds will be discussed. We furtherevaluate the effect of these filtering approaches on the above canopy derived carbonfluxes. Finally, recommendations shall be derived how to treat carbon exchangeEC data at forested sites in complex terrain in the most proper way to minimizepotential biasing effects by decoupling on the above canopy derived carbon fluxes. [ABSTRACT FROM AUTHOR]

With the development of a standardized eddy covariance (EC) data processing software it is now possible to create a high-throughput post-processing chain that allows to assess various statistics extracted from the datasets. The effect of changes in quality checking (QC) procedures can be thus effectively analysed. It is still difficult to establish what constitutes an effective QC test or filter, in other words, how exactly to define such filtering efficiency. One of the main obstacles is the design of such filters that can focus on issues that span from very specific problems to general tests of basic assumptions of the EC method. Here we propose a framework to benchmark different QC schemes based on a combination of three main measures extracted from the dataset – 1) difference in the aggregated EC fluxes, 2) change in the aggregated uncertainty and 3) data exclusion fraction. It is clear that relaxing of QC cannot be justified simply by the effort to retain data coverage in case of frequent spurious records. However, inclusion of a filter that increases exclusion fraction while the post-processed data do not differ in aggregated fluxes and uncertainties can be hardly accepted. In order to push this topic forward it would be also beneficial to provide easily available and reliable QC tools for the EC community and collect the feedback. This was already accomplished by publishing the R package openeddy (https://github.com/lsigut/openeddy) and related workflows. The feedback can help to make the codes more robust and also draw attention to new QC related issues not addressed before. The software could be therefore a platform for an exchange of experience from EC measurements across different ecosystem types and environmental conditions. Such an overview is otherwise difficult to obtain as the QC benchmarking requires supplemental information typically not included in tower network databases. Here we present the QC benchmarking results for sites from the Czech Carbon Observation System (CzeCOS) covering different ecosystems that represent different QC challenges. We show that, even though most of the QC procedures are generally applicable, site specific adaptation of filters is useful in some cases.This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the CzeCOS program, grant number LM2015061, and within the National Sustainability Program I (NPU I), grant number LO1415. [ABSTRACT FROM AUTHOR]

The close relationship between the onset and severity of agricultural and hydrological drought is considered self-evident, yet relatively few studies have addressed the effects of applying agricultural drought adaptation to hydrological drought characteristics. The present study applies a model cascade capable of simultaneously considering the interactions between agricultural and hydrological droughts. The study area covers all river basins in the Czech Republic and includes the periods of 1956–2015 (baseline) and 2021–2080 (future). The model cascade was shown to explain 91% of the variability in the seasonal and annual accumulated runoff and allows for the analysis of increasing/maintaining/decreasing available water capacity (AWC) across the 133 defined basins with a total area of c. 78,000 km2. The study reports that the probability and extent of agricultural drought increased over the entire period with higher AWC scenario showing slower pace of such increase especially from April to June. The trends in the extent or severity of hydrological droughts were of low magnitude. The future climate has been projected through the use of ensembles of five global (CMIP5) and five regional (EURO-CORDEX) climate models. The results showed a significant increase in the duration of agricultural drought stress and in the area affected throughout the year, particularly in July–September. The hydrological drought response showed a marked difference between areas with a negative and positive climatic water balance, i.e., areas where long-term reference evapotranspiration exceeds long-term precipitation (negative climatic water balance) and where it does not (positive climatic water balance). The overall results indicate that increasing soil AWC would decrease the frequency and likely also impact of future agricultural droughts, especially during spring. This result would be especially true if the wetter winters predicted by some of the models materialized. Hydrological droughts at the country level are estimated to become more pronounced with increasing AWC, particularly in catchments with a negative climatic water balance. • We analyzed the past and projected agricultural and hydrological droughts in 133 basins in the Czech Republic. • The area and severity of the agricultural drought during the growing season has increased since 1956. • The runoff and hydrological droughts have increased insignificantly since 1956 except for June. • The increase in the water holding capacity decreases area and severity of agricultural droughts but exacerbates hydrological ones. • Adaptation studies have to consider drought impacts simultaneously to avoid maladaptation. [ABSTRACT FROM AUTHOR]

• Fuel aridity and high-risk fire weather have increased substantially since 1956 • The trends are more severe during April-June and linked to the climate change • Fuel aridity levels explain 70% of interannual variability in number of wildfires • Marked increase in wildfire-conducive conditions is expected by 2050 • Forested areas above 500 m asl. are expected to see largest increases The occurrence of major wildfires in countries such as Portugal, Italy and Spain (2017) and Sweden (2018) indicated that wildfires pose a risk across Europe. While Central Europe has not been at the center of such events, observed climate data and climate projections suggest a tendency toward more years with wet and warm winters and dry and hot summers as well as fuel accumulation, leading to more hazardous conditions. Although some existing studies analyzed the differences in wildfire occurrence in this territory based on terrain, soil or vegetation characteristics, the effects of climate change have not been properly appraised. To fill this knowledge gap, we used and tested an ensemble of nine fuel aridity metrics, including three dedicated fire danger rating indices, and evaluated their level of agreement with actual fire occurrence, their ability to explain the interannual variability in wildfire frequency, and their temporal trends. The analysis covered the entire territory of the Czech Republic at 500 m spatial resolution. Two periods were included based on observed (1956–2015) and projected (2020–2100) meteorological data using ensembles of five regional climate models (RCMs) and five global circulation models (GCMs) based on Euro-CORDEX and CMIP5 datasets. For the future, we considered Representative Concentration Pathway (RCP) 4.5. Our results showed that since 1956, most of the Czech territory has exhibited an increasing frequency of fire weather days (i.e., days with highly conducive wildfire conditions) and an increasing area affected by weather conducive to wildfire occurrence, with the trends accelerating after 2000. The annual variation in the fuel aridity levels (derived solely from meteorological data) explained more than 2/3 of the reported wildfire variability during 1991–2015 over the Czech Republic. The future projections based on the RCM or GCM ensembles indicated a significant increase in fuel aridity and an increase in the area under fire-conducive conditions. Recommendations derived from such robust results are provided for stakeholders seeking to implement adaptation measures. [Display omitted] [ABSTRACT FROM AUTHOR]