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International audience; The geophysical and hydrological processes governing river flow formation exhibit persistence at several timescales, which may manifest itself with the presence of positive seasonal correlation of streamflow at several different time lags. We investigate here how persistence propagates along subsequent seasons and affects low and high flows. We define the high-flow season (HFS) and the low-flow season (LFS) as the 3-month and the 1-month periods which usually exhibit the higher and lower river flows, respectively. A dataset of 224 rivers from six European countries spanning more than 50 years of daily flow data is exploited. We compute the lagged seasonal correlation between selected river flow signatures, in HFS and LFS, and the average river flow in the antecedent months. Signatures are peak and average river flow for HFS and LFS, respectively. We investigate the links between seasonal streamflow correlation and various physiographic catchment characteristics and hydro-climatic properties. We find persistence to be more intense for LFS signatures than HFS. To exploit the seasonal correlation in the frequency estimation of high and low flows, we fit a bi-variate meta-Gaussian probability distribution to the selected flow signatures and average flow in the antecedent months in order to condition the distribution of high and low flows in the HFS and LFS, respectively, upon river flow observations in the previous months. The benefit of the suggested methodology is demonstrated by updating the frequency distribution of high and low flows one season in advance in a real-world case. Our findings suggest that there is a traceable physical basis for river memory which, in turn, can be statistically assimilated into high- and low-flow frequency estimation to reduce uncertainty and improve predictions for technical purposes.

[Departement_IRSTEA]Eaux [TR1_IRSTEA]ARCEAU; International audience; This study asses changes in snowline elevation during snowmelt runoff floods in selected basins from Austria, France, Norway, Slovakia, Slovenia, Sweden, Switzerland and Turkey. The main research question is to investigate the spatial and temporal differences in regional snowline elevation (RSLE) and to discuss the factors which control its change in Europe. The RSLE is estimated from daily MODIS snow cover data (MOD10A1) by using the methodology of Krajcí et al., (2014). The changes in RSLE are analysed for selected flood events in the period 2000-2015. The snowmelt runoff events are extracted from Catalogue of identified flood peaks from GRDC dataset (FLOOD TYPE experiment) available at http://www.water-switch-on.eu/sip-webclient/byod/#/resource/12056. The results will be discussed in terms of: (a) availability and potential of MODIS snow cover data for identifying RSLE changes during snowmelt runoff events, (b) spatial and temporal patterns of RSLE changes across Europe and (c) factor controlling the RSLE change. The analysis is performed as an experiment in Virtual Water Science Laboratory of SWITCH-ON Project (http://www.water-switch-on.eu/). All data, tools and results of the analysis will be open and accessible through the Spatial Information Platform of the Project (http://www.water-switch-on.eu/sip-webclient/byod/). We believe that such strategy will allow to improve and forward comparative research and cooperation between different partners in hydrology (Ceola et al., 2015).

International audience; The various geophysical and hydrological processes involved in the river flow generating process exhibit persistence at several distinct timescales which propagates into the river flow behavior and manifests itself as river memory. We investigate the latter at two seasonal periods of interest, i.e. 3-month High Flow Seasons (HFS) and 1-month Dry Months (DM), by exploiting a dataset of 224 European rivers spanning more than 50 years of daily flow data. We compute the lagged seasonal correlation for the peak flows in the HFS and the average flows in the DM both against the average flows in the antecedent months. We link correlation magnitude to various geophysical catchment characteristics e.g. basin size, presence of lakes, glaciers etc., as well as rainfall-related properties such as seasonality. To exploit the river memory in flood forecasting, we fit a bivariate Meta-Gaussian probability distribution model between peak HFS flow and average pre-HFS flow in order to condition the peak flow distribution in the HFS upon observance of a higher-than-usual (e.g. 95th quantile) flow in the pre-HFS month. The benefit of the suggested methodology is demonstrated by updating a season in advance the flood frequency distribution in real-world applications. Our findings suggest that there is a traceable physical basis for river memory which in turn can be statistically assimilated into flood frequency estimation to improve predictions for technical purposes.

International audience; We investigate the long memory properties of 224 european rivers spanning more than 50 years of daily flow data. For this purpose, we identify two periods of interest; High Flow Seasons (HFS) as 3-month periods receiving the maximum occurrences of peaks-over-threshold flows and Dry Months (DM) as 1-month periods with the minimum average flow.

The SedAlp project contributes to an integrated management of sediment transport in Alpine basins. It is directed to an effective reduction of sediment-related risk while promoting the enhancement of riverine ecosystems and reducing the impacts of hydropower plants (balancing the implementation of EU Directives and national law e.g. RES, WFD, NGP etc.). SedAlp includes pilot actions in various representative Alpine river basins of five countries and contributes in particular to monitor sediment and wood transfer in a large set of Alpine catchments. A major goal of the project was to understand spatial and temporal variability of processes and to provide planning, warning and predictive tools but also sediment and wood management recommendations for protecting people. Furthermore the project includes strategy policy development and implementation actions for the improvement of sediment continuity in Alpine river basins. SedAlp regards the geological and climatic variability across the Alps that generate complex patterns of sediment transfer, whereas management conflicts are similar. To reach the ambitious goals of the project, it is essential to understand the key processes of sediment and wood transport. Workpackage 5 with the title "sediment transport monitoring" was focused to enhance the knowledge about these transport processes by conducting the first standardized transnational monitoring of sediment and wood transport in Alpine basins. WP5 concentrated on monitoring and assessing fluxes of sediment and wood at the local scale. Measured fluxes are strongly depending on the supply from the catchment and on the connectivity to source areas, analysed in WP4. The output of WP5 feeds WP6 which studied the interferences between structures and sediment/wood fluxes and forms the basis for WP7 which linked the catchment with channel processes. Finally, the results of WP5 contribute to policy recommendations in WP8. Within WP5, monitoring activities on 28 different pilot sites in Austria, Germany, France, Italy and Slovenia have been conducted between 2012 and 2015. The monitored transport processes covered woody debris, debris flow, bedload and suspended load. The different pilot sites showed a great diversity in catchment size, channel slope and hydraulic parameters and covered the whole bandwidth from small, high alpine catchments (e.g. Strimm: 5 km² catchment size, 2427 m elevation a.s.l) to large catchments in the alpine valleys (e.g. Drau/Dellach: 2131 km² catchment size, 600 m elevation a.s.l). With the results of the monitoring activities, a database using different parameters regarding the transport process has been established and reflects the big diversity of the different pilot sites. The coordinated sediment transport monitoring outlined the links between the various processes responsible for sediment delivery at catchment scale and stresses out the need for a closer integration between the monitoring of various sediment transport processes in Alpine headwaters. Due to the wide range of different measurement methods used within the project, one focus of this work package was to standardize the measurement procedures and harmonize data analysis. This led to the 1st milestone "Protocol on standardized data collection methods in sediment transport monitoring for transboundary exchange". These protocols were intended to describe the used monitoring techniques and data processing methods for debris flows, wood transport and bedload transport. Furthermore, the protocols work also as guidelines to assist in choosing the appropriate monitoring method for supporting prospective monitoring efforts. 4 An important aspect of the project was to understand spatial and temporal variability of the monitored processes. The observed appearance of clockwise and counter clockwise hysteresis effects between sediment and discharge, showed the significant role of the location of the active sediment source in the temporal variability of sediment transport. Analysis of the spatial distribution showed an evolvement of the bedload transport width with increasing discharge which provides vital information for an improved planning of river related measures. To determine these process related variability, the use of appropriate monitoring methods as well as their right application is of great importance. Indirect monitoring methods (e.g. geophone devices) pointed out their potential in the automatic and continuous detection of these transport processes. The presented data reflect a high spatial and temporal variability in the occurrence of bedload, suspended load debris flow and wood transport and reveal significant consequences for the practical usage of monitoring methods, data and application. Many river engineering tasks require detailed information about the extent of sediment transport and wood mobility, which are provided by sediment and wood transport relations and equations. The 3rd milestone "First set of practically applicable bedload/wood transport relations and models" gives an overview about the most common transport relations and formulas. Furthermore it presents the difficulties and challenges in the application of these relations and shows the last developments in improving transport equations. The comparison between measured and calculated specific bedload transport rates showed substantial differences in the derived results. For the practical use of these relations it is strongly recommended to select, calibrate and validate the sediment and wood transport equations using monitored field data. The evaluation of river restoration projects showed the need of an improved process understanding between sediment transport an engineering measures. The functionality and sustainability of river restoration measures are, beside the hydrologic and hydraulic conditions, mainly depending on the superior sediment regime and thus the sediment input into the reach. By increase or decrease of the mean sediment input, the hydraulic and thus morphological conditions of the reach need to rearrange to the given input by e.g. lateral and vertical adjustments of the river bed or by changing the river type.

To gain a better understanding of the global application of soil erosion prediction models, we comprehensivelyreviewed relevant peer-reviewed research literature on soil-erosion modelling published between 1994 and2017. We aimed to identify (i) the processes and models most frequently addressed in the literature, (ii) the re-gions within which models are primarily applied, (iii) the regions which remain unaddressed and why, and (iv)how frequently studies are conducted to validate/evaluate model outcomes relative to measured data. To per-form this task, we combined the collective knowledge of 67 soil-erosion scientists from 25 countries. Theresulting database, named‘Global Applications of Soil Erosion Modelling Tracker (GASEMT)’, includes 3030 indi-vidual modelling records from 126 countries, encompassing all continents (except Antarctica). Out of the 8471articles identified as potentially relevant, we reviewed 1697 appropriate articles and systematically evaluatedand transferred 42 relevant attributes into the database. This GASEMT database provides comprehensive insightsinto the state-of-the-art of soil- erosion models and model applications worldwide. This database intends to sup-port the upcoming country-based United Nations global soil-erosion assessment in addition to helping to informsoil erosion research priorities by building a foundation for future targeted, in-depth analyses. GASEMT is anopen-source database available to the entire user-community to develop research, rectify errors, andmakefutureexpansions

Soil erosion can present a major threat to agriculture due to loss of soil, nutrients, and organic carbon. Therefore, soil erosion modelling is one of the steps used to plan suitable soil protection measures and detect erosion hotspots. A bibliometric analysis of this topic can reveal research patterns and soil erosion modelling characteristics that can help identify steps needed to enhance the research conducted in this field. Therefore, a detailed bibliometric analysis, including investigation of collaboration networks and citation patterns, should be conducted. The updated version of the Global Applications of Soil Erosion Modelling Tracker (GASEMT) database contains information about citation characteristics and publication type. Here, we investigated the impact of the number of authors, the publication type and the selected journal on the number of citations. Generalized boosted regression tree (BRT) modelling was used to evaluate the most relevant variables related to soil erosion modelling. Additionally, bibliometric networks were analysed and visualized. This study revealed that the selection of the soil erosion model has the largest impact on the number of publication citations, followed by the modelling scale and the publication's CiteScore. Some of the other GASEMT database attributes such as model calibration and validation have negligible influence on the number of citations according to the BRT model. Although it is true that studies that conduct calibration, on average, received around 30% more citations, than studies where calibration was not performed. Moreover, the bibliographic coupling and citation networks show a clear continental pattern, although the co-authorship network does not show the same characteristics. Therefore, soil erosion modellers should conduct even more comprehensive review of past studies and focus not just on the research conducted in the same country or continent. Moreover, when evaluating soil erosion models, an additional focus should be given to field measurements, model calibration, performance assessment and uncertainty of modelling results. The results of this study indicate that these GASEMT database attributes had smaller impact on the number of citations, according to the BRT model, than anticipated, which could suggest that these attributes should be given additional attention by the soil erosion modelling community. This study provides a kind of bibliographic benchmark for soil erosion modelling research papers as modellers can estimate the influence of their paper.

Flash floods, debris flows and shallow landslides are all induced by intensive rainfall events, where antecedent precipitation conditions can play an important role in triggering these kinds of natural catastrophic events. This study presents the methodology used for the construction of the intensity-duration-frequency (IDF) relationship using the Frank copula function and the evaluation of the different empirical rainfall threshold curves for several extreme events, which happened in Slovenia in the last 25 years and caused 17 casualties and about 500 million Euros of economic losses. The results show that different empirical rainfall threshold curves should be included in the early warning system where measuring rainfall network should have an adequate spatial resolution. The differences in estimated return periods with the use of classical and copula approaches can be significant, however differences can also be the result of relatively short series. The results demonstrate that in case of shorter data series the classical univariate methodology should be preferred.

The erosive force of rainfall (rainfall erosivity) is a major driver of soil, nutrient losses worldwide and an important input for soil erosion assessments models. Here, we present a comprehensive set of future erosivity projections at a 30 arc-second (∼1 km2) spatial scale using 19 downscaled General Circulation Models (GCMs) simulating three Representative Concentration Pathways (RCPs) for the periods 2041–2060 and 2061–2080. The future rainfall erosivity projections were obtained based on a Gaussian Process Regression (GPR) approach relating rainfall depth to rainfall erosivity through a series of (bio)climatic covariates. Compared to the 2010 Global Rainfall erosivity baseline, we estimate a potential average increase in global rainfall erosivity between 26.2 and 28.8% for 2050 and 27–34.3% for 2070. Therefore, climate change and the consequential increase in rainfall erosivity is the main driver of the projected + 30–66% increase in soil erosion rates by 2070. Our results were successfully compared with 20 regional studies addressing the rainfall erosivity projections. We release the whole dataset of future rainfall erosivity projections composed of 102 simulation scenarios, with the aim to support further research activities on soil erosion, soil conservation and climate change communities. We expect these datasets to address the needs of both the Earth system modeling community and policy makers. In addition, we introduce a modeling approach to estimate future erosivity and make further assessments at global and continental scales.

Despite recent developments in modeling global soil erosion by water, to date, no substantial progress has been made towards more dynamic inter- and intra-annual assessments. In this regard, the main challenge is still represented by the limited availability of high temporal resolution rainfall data needed to estimate rainfall erosivity. As the availability of high temporal resolution rainfall data will most likely not increase in future decades since the monitoring networks have been declining since the 1980s, the suitability of alternative approaches to estimate global rainfall erosivity using satellite-based rainfall data was explored in this study. For this purpose, we used the high spatial and temporal resolution global precipitation estimates obtained with the National Oceanic and Atmospheric Administration (NOAA) Climate Data Record (CDR) Climate Prediction Center MORPHing (CMORPH) technique. Such high spatial and temporal (30 min) resolution data have not yet been used for the estimation of rainfall erosivity on a global scale. Alternatively, the erosivity density (ED) concept was also used to estimate global rainfall erosivity. The obtained global estimates of rainfall erosivity were validated against the pluviograph data included in the Global Rainfall Erosivity Database (GloREDa). Overall, results indicated that the CMORPH estimates have a marked tendency to underestimate rainfall erosivity when compared to the GloREDa estimates. The most substantial underestimations were observed in areas with the highest rainfall erosivity values. At the continental level, the best agreement between annual CMORPH and interpolated GloREDa rainfall erosivity maps was observed in Europe, while the worst agreement was detected in Africa and South America. Further analyses conducted at the monthly scale for Europe revealed seasonal misalignments, with the occurrence of underestimation of the CMORPH estimates in the summer period and overestimation in the winter period compared to GloREDa. The best agreement between the two approaches to estimate rainfall erosivity was found for fall, especially in central and eastern Europe. Conducted analysis suggested that satellite-based approaches for estimation of rainfall erosivity appear to be more suitable for low-erosivity regions, while in high-erosivity regions (> 1000–2000 MJ mm ha−1 h−1 yr−1) and seasons (> 150–250 MJ mm ha−1 h−1 month−1), the agreement with estimates obtained from pluviographs (GloREDa) is lower. Concerning the ED estimates, this second approach to estimate rainfall erosivity yielded better agreement with GloREDa estimates compared to CMORPH, which could be regarded as an expected result since this approach indirectly uses the GloREDa data. The application of a simple-linear function correction of the CMORPH data was applied to provide a better fit to GloREDa and correct systematic underestimation. This correction improved the performance of CMORPH, but in areas with the highest rainfall erosivity rates, the underestimation was still observed. A preliminary trend analysis of the CMORPH rainfall erosivity estimates was also performed for the 1998–2019 period to investigate possible changes in the rainfall erosivity at a global scale, which has not yet been conducted using high-frequency data such as CMORPH. According to this trend analysis, an increasing and statistically significant trend was more frequently observed than a decreasing trend.

16 Pags.- 12 Figs.- 8 Tabls., Soil erosion can present a major threat to agriculture due to loss of soil, nutrients, and organic carbon. Therefore, soil erosion modelling is one of the steps used to plan suitable soil protection measures and detect erosion hotspots. A bibliometric analysis of this topic can reveal research patterns and soil erosion modelling characteristics that can help identify steps needed to enhance the research conducted in this field. Therefore, a detailed bibliometric analysis, including investigation of collaboration networks and citation patterns, should be conducted. The updated version of the Global Applications of Soil Erosion Modelling Tracker (GASEMT) database contains information about citation characteristics and publication type. Here, we investigated the impact of the number of authors, the publication type and the selected journal on the number of citations. Generalized boosted regression tree (BRT) modelling was used to evaluate the most relevant variables related to soil erosion modelling. Additionally, bibliometric networks were analysed and visualized. This study revealed that the selection of the soil erosion model has the largest impact on the number of publication citations, followed by the modelling scale and the publication's CiteScore. Some of the other GASEMT database attributes such as model calibration and validation have negligible influence on the number of citations according to the BRT model. Although it is true that studies that conduct calibration, on average, received around 30% more citations, than studies where calibration was not performed. Moreover, the bibliographic coupling and citation networks show a clear continental pattern, although the co-authorship network does not show the same characteristics. Therefore, soil erosion modellers should conduct even more comprehensive review of past studies and focus not just on the research conducted in the same country or continent. Moreover, when evaluating soil erosion models, an additional focus should be given to field measurements, model calibration, performance assessment and uncertainty of modelling results. The results of this study indicate that these GASEMT database attributes had smaller impact on the number of citations, according to the BRT model, than anticipated, which could suggest that these attributes should be given additional attention by the soil erosion modelling community. This study provides a kind of bibliographic benchmark for soil erosion modelling research papers as modellers can estimate the influence of their paper., Nejc Bezak and Matjaž Mikoš would like to acknowledge the support of the Slovenian Research Agency through grant P2-0180. Diana Vieira is funded by national funds (OE), through FCT – Fundação para a Ciência e a Tecnologia, I.P., in the scope of the framework contract foreseen - DL57/2016 (CDL-CTTRI-97-ARH/2018 - REF.191-97-ARH/2018), and acknowledges CESAM financial support of through (UIDP/50017/2020+UIDB/50017/2020). Jae E. Yang and Pasquale Borrelli are funded by the EcoSSSoil Project, Korea Environmental Industry & Technology Institute (KEITI), Korea (Grant No. 2019002820004). Walter Chen is funded by the Ministry of Science and Technology (Taiwan) Research Project (Grant Number MOST 109-2121-M-027-001).

40 Pags.- 10 Figs.- 2 Tabls.- Suppl. Informat. The definitive version is available at: https://www.sciencedirect.com/science/journal/00489697, To gain a better understanding of the global application of soil erosion prediction models, we comprehensively reviewed relevant peer-reviewed research literature on soil-erosion modelling published between 1994 and 2017. We aimed to identify (i) the processes and models most frequently addressed in the literature, (ii) the regions within which models are primarily applied, (iii) the regions which remain unaddressed and why, and (iv) how frequently studies are conducted to validate/evaluate model outcomes relative to measured data. To perform this task, we combined the collective knowledge of 67 soil-erosion scientists from 25 countries. The resulting database, named ‘Global Applications of Soil Erosion Modelling Tracker (GASEMT)’, includes 3030 individual modelling records from 126 countries, encompassing all continents (except Antarctica). Out of the 8471 articles identified as potentially relevant, we reviewed 1697 appropriate articles and systematically evaluated and transferred 42 relevant attributes into the database. This GASEMT database provides comprehensive insights into the state-of-the-art of soil- erosion models and model applications worldwide. This database intends to support the upcoming country-based United Nations global soil-erosion assessment in addition to helping to inform soil erosion research priorities by building a foundation for future targeted, in-depth analyses. GASEMT is an open-source database available to the entire user-community to develop research, rectify errors, and make future expansions., Jae E. Yang and Pasquale Borrelli are funded by the EcoSSSoil Project, Korea Environmental Industry & Technology Institute (KEITI), Korea (Grant No. 2019002820004). Diana Vieira is funded by national funds (OE), through FCT – Fundação para a Ciência e a Tecnologia, I.P., in the scope of the framework contract foreseen - DL57/2016 (CDL-CTTRI-97-ARH/2018 - REF.191-97-ARH/2018), and acknowledges CESAM financial support of through (UIDP/50017/2020+UIDB/50017/2020). Walter Chen is funded by the Ministry of Science and Technology (Taiwan) Research Project (Grant Number MOST 109-2121-M-027-001). Nejc Bezak and Matjaž Mikoš would like to acknowledge the support of the Slovenian Research Agency through grant P2-0180.

Soil loss by water erosion is a major land degradation processes that can locally reduce crop productivity and cause off-site negative effects such as siltation, eutrophication of waterways, flooding and terrestrial and aquatic biodiversity loss. The major driver of water erosion is the erosive power of rainfall. Using the detailed erosive events of the Rainfall Erosivity Database at European Scale (REDES), we study the characteristics and patterns of rainfall erosivity in Europe introducing the Rainfall Erosivity Synchrony Scale (Rsync). Rsync expresses the maximum radius in kilometers around a given meteorological station within which at least half of the other meteorological stations in the database also detect an erosive event. In this study we correlate the Rsync and the annual erosivity with annual number of thunderstorm days, convective and large-scale precipitation and multiple geo-morphological features such as topographic position index and terrain ruggedness index. Our analysis shows an inverse relationship between the Rsync and rainfall erosivity values in Europe. Different spatial patterns of synchrony scale are detected in Europe, which enables us to delineate areas where severe soil erosion can simultaneously occur at larger scales, e.g., large sectors of Italy, Spain, Croatia and Slovenia. Furthermore, we observe a tendency of the Rsync to decrease with convective precipitation, annual number of thunderstorm days and increase with the large-scale precipitation. On the contrary, annual rainfall erosivity increases with convective precipitation and annual number of thunderstorm days and decreases with large-scale precipitation.

Back in the 1930s, the aphorism “publish or perish” first appeared in an academic context. Today, this phrase is becoming a harsh reality in several academic environments, and scientists are giving increasing attention to publishing and disseminating their scientific work. Soil erosion modelers make no exception. With the introduction of the bibliometric field, the evaluation of the impact of a piece of scientific work becomes more articulated. The post-publication impact of the research became an important aspect too. In this study, we analyse the outreach and the impact of the literature on soil erosion modelling using the altmetric database, i.e., Altmetric. In our analysis, we use only a small fraction (around 15%) of Global Applications of Soil Erosion Modelling Tracker (GASEMT) papers because only 257 papers out of 1697 had an Altmetric Score (AS) larger than 0. We observed that media and policy documents mentioned more frequently literature dealing with global-scale assessments and future projection studies than local-scale ones. Papers that are frequently cited by researchers do not necessarily also yield high media and policy outreach. The GASEMT papers that had an AS larger than 0 were, on average, mentioned by one policy document and five Twitter users and had 100 Mendeley readers. Only around 5% and 9% of papers with AS > 0 appeared in news articles and blogs, respectively. However, this percentage was around 45% for Twitter and policy mentions. The top GASEMT paper’s upper bound was around 1 million Twitter followers, while this number was around 10,000 for the 10th ranked GASEMT paper. The exponentially increasing trend for erosion modelling papers having an AS has been confirmed, as during the last 3 years (2014–2017), we estimated that the number of entries had doubled compared to 2011–2014 and quadrupled if we compare it with 2008–2011.

Heavy rainstorms play a central role in the water-driving soil erosion processes. An in-depth knowledge about temporal and spatial erosivity of rainfall events is required to gain a better understanding of soil erosion processes and optimize soil protection measures efficiency. In this study, the spatiotemporal distribution of more than 300,000 erosive events measured at 1181 locations, part of the Rainfall Erosivity Database at European Scale (REDES) database, is studied to shed some new light on the rainfall erosivity in Europe. Rainfall erosive events are statistically investigated through the Lorenz curve and derived coefficients such as the Gini coefficient (G). Additionally, seasonal characteristics of the most and the less erosive events are compared to investigate seasonal characteristics of rainstorms across Europe. The G shows largest values of inequality of the inter-annual temporal distribution of the rainfall erosive events in the Alpine region, mostly due to the large number of rainfall events with smaller rainfall erosivity. While for other parts of Europe, the inequality described by the G is mostly due to a small number of high erosive events. The G slightly decreases from south to north while no clear regional patterns can be detected. Additionally, in Europe, on average 11% (ranging from 1 to 24%) of all erosive events contribute to form 50% of the total rainfall erosivity. Furthermore, higher erosive rainfall events tend to occur later in the year compared to less erosive events that take place earlier. To our knowledge, this study is the first one addressing event scale rainfall erosivity distribution using more than 300,000 rainfall erosivity events and covering almost a whole continent. Scientifically our findings represent a major step towards large-scale process-based erosion modelling while, practically, they provide new elements that can support national and local soil erosion monitoring programs.

Rainfall erosivity is the driving force of soil erosion and it is characterized by a large variability in space and time. In order to obtain robust estimates of rainfall erosivity, long series of high-frequency rainfall data are needed, which are often not available for large study areas. In this study we reconstructed past rainfall erosivity in Europe for the period 1961–2018, with the aim to investigate temporal changes in rainfall erosivity. As input data, we used the Rainfall Erosivity Database at European Scale (REDES) and Uncertainties in Ensembles of Regional Reanalyses (UERRA) rainfall data. Using a set of regression models, which we derived with the application of the k-fold cross-validation approach, we computed the annual rainfall erosivity for the 1675 stations forming the REDES database. Based on the reconstructed data, we derived a rainfall erosivity trend map for Europe where the results were qualitatively validated. Among the stations showing a statistically significant trend, we observed a tendency towards more positive (15%) than negative trends (7%). In addition, we also observed an increasing tendency of the frequency of years with maximum erosivity values. Geographically, large parts of regions such as Eastern Europe, Scandinavia, Baltic countries, Great Britain and Ireland, part of the Balkan Peninsula, most of Italy, Benelux countries, northern part of Germany, part of France, among others, are characterized by a positive trend in rainfall erosivity. By contrast, negative trends in annual rainfall erosivity could be observed for most of the Iberian Peninsula, part of France, most of the Alpine area, Southern Germany, and part of the Balkan Peninsula, among others. The new dataset of rainfall erosivity trends reported in this study scientifically provides new information to better understand the impacts of the ongoing erosivity trends on soil erosion across Europe, while, from a policy perspective, the gained findings provide new knowledge to support the development of soil erosion indicators aiming at promoting mitigation measures at regional and pan-European level.