Changing climate both increases and decreases European river floods

Climate change has led to concerns about increasing river floods resulting from the greater water-holding capacity of a warmer atmosphere. These concerns are reinforced by evidence of increasing economic losses associated with flooding in many parts of the world, including Europe. Any changes in river floods would have lasting implications for the design of flood protection measures and flood risk zoning. However, existing studies have been unable to identify a consistent continental-scale climatic-change signal in flood discharge observations in Europe, because of the limited spatial coverage and number of hydrometric stations. Here we demonstrate clear regional patterns of both increases and decreases in observed river flood discharges in the past five decades in Europe, which are manifestations of a changing climate. Our results—arising from the most complete database of European flooding so far—suggest that: increasing autumn and winter rainfall has resulted in increasing floods in northwestern Europe; decreasing precipitation and increasing evaporation have led to decreasing floods in medium and large catchments in southern Europe; and decreasing snow cover and snowmelt, resulting from warmer temperatures, have led to decreasing floods in eastern Europe. Regional flood discharge trends in Europe range from an increase of about 11 per cent per decade to a decrease of 23 per cent. Notwithstanding the spatial and temporal heterogeneity of the observational record, the flood changes identified here are broadly consistent with climate model projections for the next century, suggesting that climate-driven changes are already happening and supporting calls for the consideration of climate change in flood risk management

Changing climate shifts timing of European floods

A warming climate is expected to have an impact on the magnitude and timing of river floods; however, no consistent large-scale climate change signal in observed flood magnitudes has been identified so far. We analyzed the timing of river floods in Europe over the past five decades, using a pan-European database from 4262 observational hydrometric stations, and found clear patterns of change in flood timing. Warmer temperatures have led to earlier spring snowmelt floods throughout northeastern Europe; delayed winter storms associated with polar warming have led to later winter floods around the North Sea and some sectors of the Mediterranean coast; and earlier soil moisture maxima have led to earlier winter floods in western Europe. Our results highlight the existence of a clear climate signal in flood observations at the continental scale

Megafloods in Europe can be anticipated from observations in hydrologically similar catchments

Megafloods that far exceed previously observed records often take citizens and experts by surprise, resulting in extremely severe damage and loss of life. Existing methods based on local and regional information rarely go beyond national borders and cannot predict these floods well because of limited data on megafloods, and because flood generation processes of extremes differ from those of smaller, more frequently observed events. Here we analyse river discharge observations from over 8,000 gauging stations across Europe and show that recent megafloods could have been anticipated from those previously observed in other places in Europe. Almost all observed megafloods (95.5%) fall within the envelope values estimated from previous floods in other similar places on the continent, implying that local surprises are not surprising at the continental scale. This holds also for older events, indicating that megafloods have not changed much in time relative to their spatial variability. The underlying concept of the study is that catchments with similar flood generation processes produce similar outliers. It is thus essential to transcend national boundaries and learn from other places across the continent to avoid surprises and save lives

Batch orographic interpolation of monthly precipitation based on free-of-charge geostatistical tools

The effects of possible climate change on water resources in prescribed areas (e.g. river basins) are intensively studied in hydrology. These resources are highly dependent on precipitation totals. When focusing on long-term changes in climate variables, one has to rely on station measurements. However, hydrologists need the information on spatial distribution of precipitation over the areas. For this purpose, the spatial interpolation techniques must be employed. In Czechia, where the addition of elevation co-variables proved to be a good choice, several GIS tools exist that are able to produce time series necessary for climate change analyses. Nevertheless, these tools are exclusively based on commercial software and there is a lack of free-of-charge tools that could be used by everyone. Here, selected free-of-charge geostatistical tools were utilized in order to produce monthly precipitation time series representing six river basins in the Ore Mountains located in NW Bohemia, Czechia and SE Saxony, Germany. The produced series span from January 1961 to December 2012. Rain-gauge data from both Czechia and Germany were used. The universal kriging technique was employed where a multiple linear regression (based on elevation and coordinates) residuals were interpolated. The final time series seem to be homogeneous

Freely available mean daily discharge series from Czechia: what can be inferred from them?

Most hydrometeorological data from Czechia are still provided for a fee. This especially applies to time series with a finer step than monthly. The fact that the data must be paid with respect to an expert’s appraisement and that the proper licence agreement ratification has to be performed causes a considerable delay in the data transfer to potential customers, unfortunately including scientists as well. Naturally, this time-consuming process is unpleasant to the experts on both sides. Due to a substantial rise of university students’ requests for data, the Czech Hydrometeorological Institute’s hydrologists launched a website from which long mean daily discharge series representing ten selected water-gauging stations can be downloaded. Besides other assessments, the series may play an important role when studying climate change impacts on water resources in Czechia. Therefore, the objective here was to extract from these series some preliminary information on long-term changes such as abrupt and gradual trends caused either by the construction of reservoirs or by climate variability itself. The main tool used was nonparametric trend analysis. Mainly different months were of interest so as to determine if there have been recorded some changes in seasonality. The results may be easily expanded by students

Freely available daily hydrometeorological data from Czechia: further insights

Quite recently, freely available mean daily discharge series representing the territory of Czechia were complemented by ten daily series of nine climate variables, spanning usually from 1961 to the present. Their length thus allows the analyses similar to those conducted approximately a year ago in relation to the long series of discharge. Besides this possibility, the current paper goes further and shows how these long series (including discharge) can be used in order to assess the presence of the so-called Hurst phenomenon. Using a wavelet-based approach, several important differences in the wavelet spectra and values of the Hurst exponent (as well as the uncertainty in their estimation) were found when focusing on discharge, air temperature and precipitation. Furthermore, using the stationarity and unit root tests, it was revealed that, unlike precipitation, air temperature and discharge series may be characterized by long-memory processes in many cases. Finally, as the paper is devoted mainly to students, a short R script is presented in Appendix that makes it easier to work with the online files offered by Czech climatologists

Changing Low Flow and Streamflow Drought Seasonality in Central European Headwaters

In the context of the ongoing climate warming in Europe, the seasonality and magnitudes of low flows and streamflow droughts are expected to change in the future. Increasing temperature and evaporation rates, stagnating precipitation amounts and decreasing snow cover will probably further intensify the summer streamflow deficits. This study analyzed the long-term variability and seasonality of low flows and streamflow droughts in fifteen headwater catchments of three regions within Central Europe. To quantify the changes in the low flow regime of selected catchments during the 1968–2019 period, we applied the R package lfstat for computing the seasonality ratio (SR), the seasonality index (SI), mean annual minima, as well as for the detection of streamflow drought events along with deficit volumes. Trend analysis of summer minimum discharges was performed using the Mann–Kendall test. Our results showed a substantial increase in the proportion of summer low flows during the analyzed period, accompanied with an apparent shift in the average date of low flow occurrence towards the start of the year. The most pronounced seasonality shifts were found predominantly in catchments with the mean altitude 800–1000 m.a.s.l. in all study regions. In contrast, the regime of low flows in catchments with terrain above 1000 m.a.s.l. remained nearly stable throughout the 1968–2019 period. Moreover, the analysis of mean summer minimum discharges indicated a much-diversified pattern in behavior of long-term trends than it might have been expected. The findings of this study may help identify the potentially most vulnerable near-natural headwater catchments facing worsening summer water scarcity

Attempts to establish a regional probabilistic model of intense rainfall for the Upper and Middle Oder River basin

The main scope of this study was to present the possibility of developing a heavy rainfall regional model, based on a probabilistic approach. Following the methods and conclusions of the scientific and technical work of the research team in the Upper and Middle Oder basin, carried out on rainfall data between 1961 and 2010, it was found that the generalized exponential distribution enables a satisfactory probabilistic description of heavy rainfall, and the results of the models constructed on its basis are obtained in an accessible and not time-consuming way. The regional model presented in the article sufficiently describes the empirical heavy rainfall at eight analyzed meteorological stations, especially in the range of rainfall amounts occurring most frequently from a statistical point of view, i.e. with the p-value from 0.3 to 1.0

Bacterial community associated with worker honeybees (Apis mellifera) affected by European foulbrood

Background Melissococcus plutonius is an entomopathogenic bacterium that causes European foulbrood (EFB), a honeybee (Apis mellifera L.) disease that necessitates quarantine in some countries. In Czechia, positive evidence of EFB was absent for almost 40 years, until an outbreak in the Krkonose Mountains National Park in 2015. This occurrence of EFB gave us the opportunity to study the epizootiology of EFB by focusing on the microbiome of honeybee workers, which act as vectors of honeybee diseases within and between colonies. Methods The study included worker bees collected from brood combs of colonies (i) with no signs of EFB (EFB0), (ii) without clinical symptoms but located at an apiary showing clinical signs of EFB (EFB1), and (iii) with clinical symptoms of EFB (EFB2). In total, 49 samples from 27 honeybee colonies were included in the dataset evaluated in this study. Each biological sample consisted of 10 surface-sterilized worker bees processed for DNA extraction. All subjects were analyzed using conventional PCR and by metabarcoding analysis based on the 16S rRNA gene V1–V3 region, as performed through Illumina MiSeq amplicon sequencing. Results The bees from EFB2 colonies with clinical symptoms exhibited a 75-fold-higher incidence of M. plutonius than those from EFB1 asymptomatic colonies. Melissococcus plutonius was identified in all EFB1 colonies as well as in some of the control colonies. The proportions of Fructobacillus fructosus, Lactobacillus kunkeei, Gilliamella apicola, Frischella perrara, and Bifidobacterium coryneforme were higher in EFB2 than in EFB1, whereas Lactobacillus mellis was significantly higher in EFB2 than in EFB0. Snodgrassella alvi and L. melliventris, L. helsingborgensis and, L. kullabergensis exhibited higher proportion in EFB1 than in EFB2 and EFB0. The occurrence of Bartonella apis and Commensalibacter intestini were higher in EFB0 than in EFB2 and EFB1. Enterococcus faecalis incidence was highest in EFB2. Conclusions High-throughput Illumina sequencing permitted a semi-quantitative analysis of the presence of M. plutonius within the honeybee worker microbiome. The results of this study indicate that worker bees from EFB-diseased colonies are capable of transmitting M. plutonius due to the greatly increased incidence of the pathogen. The presence of M. plutonius sequences in control colonies supports the hypothesis that this pathogen exists in an enzootic state. The bacterial groups synergic to both the colonies with clinical signs of EFB and the EFB-asymptomatic colonies could be candidates for probiotics. This study confirms that E. faecalis is a secondary invader to M. plutonius; however, other putative secondary invaders were not identified in this study

Megafloods in Europe can be anticipated from observations in hydrologically similar catchments

Megafoods that far exceed previously observed records often take citizensand experts by surprise, resulting in extremely severe damage and loss oflife. Existing methods based on local and regional information rarely gobeyond national borders and cannot predict these foods well because oflimited data on megafoods, and because food generation processes ofextremes difer from those of smaller, more frequently observed events.Here we analyse river discharge observations from over 8,000 gaugingstations across Europe and show that recent megafoods could have beenanticipated from those previously observed in other places in Europe.Almost all observed megafoods (95.5%) fall within the envelope valuesestimated from previous foods in other similar places on the continent,implying that local surprises are not surprising at the continental scale. Thisholds also for older events, indicating that megafoods have not changedmuch in time relative to their spatial variability. The underlying conceptof the study is that catchments with similar food generation processesproduce similar outliers. It is thus essential to transcend national boundariesand learn from other places across the continent to avoid surprises andsave lives.</p