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Observational data scarcity often limits the potential of rainfall-runoff modelling around the globe. In ungauged catchments, earth-observations or reanalysis products could be used to replace missing ground-based station data. However, performance of different datasets needs to be thoroughly tested, especially at finer temporal resolutions such as hourly time steps. This study evaluates the performance of ERA5-Land and COSMO-REA6 precipitation reanalysis products (PRPs) using 16 meso-scale catchments located in Slovenia, Europe. These two PRPs are firstly compared with a gridded precipitation dataset that was constructed based on ground observational data. Secondly, a comparison of the temperature data of these reanalysis products with station-based air temperature data is conducted. Thirdly, several data combinations are defined and used as input for the rainfall-runoff modelling using the GR4H model. A special focus is on the application of an additional snow module. Both tested PRPs underestimate, for at least 20 %, extreme rainfall events that are the driving force of natural hazards such as floods. In terms of air temperature both tested reanalysis products show similar deviations from the observational dataset that was catchment-specific. Additionally, air temperature deviations are smaller in winter compared to summer. In terms of rainfall-runoff modelling, the ERA5-Land yields slightly better performance than COSMO-REA6. If a re-calibration with PRP has been carried out, the performance is similar compared to the simulations where station-based data was used as input. Model recalibration proves to be essential in providing relatively sufficient rainfall-runoff modelling results. Hence, tested PRPs could be used as an alternative to the station-based based data in case that precipitation or air temperature data are lacking, but model calibration using discharge data would be needed to improve the performance.

The study deals with the composed landslide Urbas, located in the hinterland of the densely populated settlement in northwestern Slovenia at the foothills of the Karavanke mountain ridge. The Urbas landslide was recognized as the largest landslide among five other landslides that pose a direct danger to the underlying settlement of Koroška Bela. The Urbas landslide has a length of 500 m and a width of about 440 m. The landslide covers an area of 177,000 m2. The formation of the Urbas landslide is related to complex geological and tectonic conditions. It is defined as a rotational landslide and was formed at the tectonic contact between the Triassic carbonate and the Carboniferous clastic rocks, mainly composed of siltstone and claystone. To determine the characteristics and mechanism of the Urbas landslide, several investigations and monitoring projects have been carried out using data from the Global Navigation Satellite System (GNSS), a wire extensometer, unmanned aerial vehicle (UAV) photogrammetry and hydrometeorological sensing (groundwater table, precipitation). The results of this study show that the dynamics of the Urbas landslide exhibited different kinematic trends associated with different triggering mechanisms, depending on local geological and hydrogeological conditions. Consequently, certain parts of the landslide are at different evolutionary states and respond differently to the same external triggers.Reference: Peternel, T.; Janža, M.; Šegina, E.; Bezak, N.; Maček, M. Recognition of Landslide Triggering Mechanisms and Dynamics Using GNSS, UAV Photogrammetry and In Situ Monitoring Data. Remote Sens. 2022, 14, 3277. https://doi.org/10.3390/rs14143277Acknowledgments: This research was funded by Slovenian Research Agency through grants Z1-2638, P1- 0419, P2-0180 and J6-4628. Additional financial support was provided by the Ministry of Environment and Spatial Planning, and the Municipality of Jesenice.

High-resolution precipitation time series are required for numerous applications in hydrology. For data-scarce regions, precipitation reanalysis products (PRP) are a promising data source. We validated two PRP for Slovenia and identified biases, which disable a direct usage of the PRP. However, the PRP were used for the parameter estimation of a cascade model to disaggregate daily time series, which exist for long periods for the whole country. The so assimilated data benefits from the advantages from both datasets: the daily rainfall amounts from the observations and the high-resolution temporal structure from the PRP. The disaggregated time series show a superior representation of the observed high-resolution point and areal precipitation time series in comparison to the PRP themselves, and their usage is recommended instead. The developed concept can be transferred to other data-scarce regions.In more detail, from the latest PRP two are most promising due to their spatial and temporal resolution: ERA5-Land (raster width ~9 km width, temporal resolution of 1 h) and REA6 (6 km, 1 h). ERA5-Land and REA6 are evaluated in space and time by continuous and event-based characteristics as well as precipitation extreme values for five recording stations and 20 catchments in Slovenia. Both PRP show underestimations of dry spell duration, wet spell amount and average intensity, while wet spell duration is overestimated. For extreme values with 1 h duration both PRP lead to underestimations, whereby the bias increases with the return period. The identified biases are larger for ERA5-Land than for REA6. The PRP time series were used for the parameter estimation of a micro-canonical cascade model to disaggregate observed daily values to hourly values. The so estimated parameters differ from station-based estimations, e.g. probabilities for the generation of dry time steps (P(1/0), P(0/1)) are underestimated. Nevertheless, starting from observed daily rainfall amounts the disaggregated time series show a superior representation of the high-resolution precipitation characteristics in comparison to ERA5-Land and REA6. This conclusion is based on all studied precipitation characteristics.

Climate change is expected to affect the frequency, magnitude, and seasonality of several rainfall-related hazards, including flooding as one of the costliest hazards in Europe. Recent studies have shown that flood risk in Europe is both increasing and decreasing, with increases in most eastern and southern European countries, including Slovenia and Czechia. In addition, significant changes in the seasonal occurrence of floods have also been observed in Europe, thus challenging conventional approaches to flood risk management.As natural hazards have major impacts on infrastructure, human lives, and habitats, and cause large social and economic damages, it is clear that adaptation measures aimed at both prevention and mitigation of impacts must be considered to cope with climate change. To deal with the changing occurrence and characteristics of floods, different types of measures need to be adopted, including green, blue, and grey measures or combinations of these. Although their application is currently emphasized, purely green or blue-green measures in some cases may not be insufficient to cope with predicted future climate hazards. Additionally, implementation of such measures often encounter resistance in planning departments and among decision makers due to institutional path dependency related to the history of utilizing grey infrastructure measures. This is especially the case for some Central-Eastern European countries. An alternative are hybrid solutions that combine parts of grey and green infrastructure, since these kinds of measures can reflect the variety of environmental conditions. However, not much attention has been given to the documentation and evaluation of hybrid infrastructure in comparison to purely green measures. Hence, there are still several open questions related to the implementation and functioning of solutions combining elements of green and grey measures, so called hybrid solutions.The main objective of this contribution is to present the theoretical framework, research design and initial research steps of a newly launched international project focusing on: (i) enhancement of documentation and standardization related to hybrid solutions, (ii) development and testing of applicability and social acceptability of specific hybrid infrastructure in different environments and climate change scenarios, and (iii) environmental modelling and evaluation of effectiveness of different measures from the perspective of the flood risk management. Within the project, the effects of hybrid solutions on flood hazard and hydrological regime of the landscape will be modelled for selected small catchments in Slovenia and Czechia, but the standardization of hybrid solutions will enable to extrapolate our results beyond Central and Eastern Europe. Acknowledgment: The research was conducted within the project [Evaluation of hazard-mitigating hybrid infrastructure under climate change scenarios] co-granted by Slovenian Research Agency (J6-4628) and Czech Science Foundation (22-04520L).

As a vital element of public spaces, trees in urban settings are acclaimed to offer numerous social and environmental benefits, making them a quintessential nature-based solution for a more sustainable city. While carbon sequestration, air quality, and urban heat island mitigation benefits have long been acknowledged, less emphasis is directed to utilizing the hydrologic function of trees in terms of stormwater runoff reduction in the urban environment and this benefit is often underutilized. For urban areas with high proportions of impervious surfaces, increasing the percentage of tree canopy cover and green spaces is crucial in restoring the natural functioning of the ecosystem and water cycle. Within the framework of our ongoing research, we are investigating the positive impacts of trees (i.e., single tree elements, forests) as nature-based solutions on the urban water cycle using field measurements of rainfall partitioning, runoff, soil moisture, and infiltration from experimental catchments in the city of Ljubljana, Slovenia which started on August of 2021. Preliminary results revealed that open-grown birch (deciduous) and pine (coniferous) tree canopies intercepted a relative amount of gross rainfall with pine trees having a greater interception capacity. The following trees also modified the drop size distribution (e.g., drop number, diameter, fall velocity) of below-canopy rainfall before reaching the ground, thus attenuating the mean and maximum 10-minute rainfall intensities by 42-50% and 40-44%, respectively, depending on canopy phenoseasons. Such reduction in the intensity of rainfall has a significant effect on the peak water level of event runoff which could provide important information for understanding the runoff generation process. Moreover, this benefit with the root system of trees has a positive impact on the condition and structure of soils in urban areas promoting infiltration, preferential flow, and soil water recharge. In addition to this, tree canopies also dampen the average kinetic energies of rainfall to cause soil erosion by 34%. These initial findings suggest that the hydrological benefits of trees in the urban environment are adequate to warrant a further investigation into their potential to regulate the flow mechanisms of stormwater runoff and reduce urban pluvial flooding. Thus, it is also imperative to explore how the integration of trees interacts with other stormwater control measures and how this interaction could leverage their functions. This will deliver invaluable information to urban planners, landscape designers, stormwater management experts, and decision-makers on the need to expand the efforts of urban greening to address the associated adverse impacts of rapid urbanization and various environmental challenges. Acknowledgments: Results are part of the CELSA project entitled “Interception experimentation and modelling for enhanced impact analysis of nature-based solution” and research programmes and projects P2-0180, J6-4629, and N2-0313 financed by the Slovenian Research Agency (ARRS).

Ecohydrological cycle in addition to common hydrological components such as rainfall, runoff and evaporation, strongly focuses also on ecological elements, i.e. elements of the nature and their role in the water cycle. As such we have addressed the role of two natural elements in the water balance of the study plot: vegetation (trees) through rainfall interception process and the soil through water infiltration and soil moisture dynamics. The study plot covers small urban park in the city of Ljubljana, Slovenia and includes the opening with low-cut grass, group of birch trees and group of pine trees. There we are monitoring rainfall and its characteristics, as well as throughfall and stemflow under each group of trees since the year 2014. Additionally, in 2021 we have started to measure also soil moisture (volumetric water content; VWC) at three depths (16 cm, 51 cm and 74 cm) and at three locations: in the open, under the birch and under the pine trees. During the measurements of soil moisture, we have captured the distinctly dry period of spring and summer of 2022, as well as excess of rainfall amount according to the long-term average during September 2022. For the collected data set we have used statistical approaches to analyse influence of vegetation (rainfall interception) on values and response of soil moisture as well as influence of pre-event conditions on the response and dynamics of soil moisture.Acknowledgments: Results are part of the CELSA project entitled “Interception experimentation and modelling for enhanced impact analysis of nature-based solution” and research programmes and projects P2-0180, J6-4629, and N2-0313 financed by the Slovenian Research Agency (ARRS).

Rain-on-Grid (RoG) modelling offers an attractive alternative to more traditional routing methods. Currently, few publications are addressing the suitability of this approach to modelling a storm event, and fewer benchmark findings present its possible limitations. In the present study, it is verified whether RoG is able to replicate the 2007 flash flood event that occurred in the Selška Sora watershed, located in western Slovenia. The results are validated against a high-resolution benchmark run, and the flood footprint extracted from the field by the Slovenian Environment Agency. Results display a satisfactory description of the flood event using uniform station rainfall data as an input. The flood extent slightly exceeds the confines of the runup measured in the field. RoG offers a more realistic description of the downstream hydrograph, with a sharper initial peak, when antecedent soil moisture is lower. Keywords: Rain-on-Grid, Flash flood, Slovenia

Debris flows are one of the natural disasters that can occur in the alpine environment, cause large economic damage, and endanger human lives. This study presents an overview of recent research done in relation to the debris flow hazard assessment and conceptual mitigation at the Koroska Bela area in Slovenia. This includes fieldwork, lab experiments, modelling, and a conceptual design of hydro-technical measures to reduce the risk. The results indicate that multiple debris flows occurred in the past in the area but a relatively long period of more than 100 years without an extreme event led to urbanization and development of the area. Magnitudes of the most extreme events as the worst-case scenarios were estimated to be in the range between 100,000 and 400,000 m3, using debris flow modelling and geological information from research trenches. Based on the landslide volumes, such events could also potentially occur in the future in extreme conditions. Additionally, torrential floods could mobilize more than 15,000 m3 of material located along the stream network that can be regarded as potentially unstable. The existing check dam system does not have the capacity to capture this material. Thus, a new check dam and three flexible net barriers could help to reduce the risk due to torrential outbursts or debris flows.

In the paper, the determination of nitrate nitrogen (NO3-N) export regimes from the Kuzlovec catchment during rainfall events is presented employing various determination methods: the ratio of coefficient of variation of NO3-N concentration and discharge (CVC/CVQ), the slope of the regression line to the points of concentration and discharge logarithms (b), both mentioned indices together, and the relative change of the NO3-N concentration during the event (Crs). According to previous analyses, the amount of exported NO3-N during rainfall events comprises approx. 30% of the total export amount, while from a temporal point of view, rainfall events represent only 10% of the time. Export regimes were identified as chemostatic (concentration does not change with discharge) and chemodynamic (concentration changes with discharge). The latter were further divided into dilution and flushing regimes. 43 rainfall events from the period April 2018–April 2020 were included in the analysis. For these events, high-frequency data of 20-minute intervals were available for concentration and discharge. All applied indices showed that the catchment responds differently from a concentration-discharge perspective and that chemodynamic behaviour is predominant, with flushing most frequently prevalent. A possible seasonal connection with regime diversity was tested using the non-parametric, statistical Wilcoxon test. A statistically significant difference was not found for any of the indices. Nevertheless, a detailed analysis of CVC/CVQ revealed that the ratio is likely related to seasonal variability in rainfall characteristics and consequently to the hydrological conditions in the catchment. Hence, it would be of great importance to include data about rainfall and hydrological properties in future studies.

Design discharges are a key element for flood protection measures. Their determination is a continuing challenge, especially for sparely or even ungauged catchments. While hydrological modelling and subsequently derived flood frequency analysis is a possible solution for this issue, its reliability significantly depends on the quality of the input precipitation time series. Unfortunately, observed precipitation time series are often too short, their temporal resolution is not sufficient or the network density is too low.From the latest precipitation reanalysis products (PRP) three are most promising due to their spatial and temporal resolution for rainfall-runoff (r-r) modelling of small to mesoscale catchments: ERA5-Land (raster with ~9 km width), REA6 (6 km) and CFSv2 (22 km). These three PRP are able to cope with the dynamics of the r-r process due to their hourly resolution. The PRP are evaluated for Slovenia (Europe) with both, precipitation and runoff characteristics. For areal precipitation, continuous and event-based characteristics are evaluated as well as precipitation extreme values. Simple correction methods for identified biases are suggested and applied. It can be seen that although the PRP clearly differ from each other, there is no clear ‘favourite’ to use as input for the r-r modelling.For r-r modelling, continuous simulations are carried out with GR4H for 20 catchments in Slovenia (55 km²-480 km²). Models are re-calibrated for each PRP input based on KGE. Simulation results of calibration and validation period are evaluated by runoff extreme values, KGE, flow duration curve and intra-annual cycle. Interestingly, first results show that the deviations of some rainfall characteristics do not necessarily transfer to deviations in runoff characteristics, which can be explained by the high nonlinearity of the r-r process. PRP lead to better, at least similar results for runoff characteristics for catchments without rain gauges in their centre.

An adequate representation of the relationship between effective rainfall and rainfall losses is required in hydrological rainfall–runoff models to reduce the uncertainty of the modelling results. This study evaluates the performance of several hydrological rainfall loss methods using the experimental data obtained from a laboratory small-scale physical landslide model with variable slope inclination, homogenous material and no vegetation effects. Three different experiments were selected and five rainfall loss methods were tested to evaluate their performance in reproducing the experimental results from the perspective of the surface runoff formation on the experimental slope. Initial and calibrated parameters were used to test the performance of these hydrological rainfall loss methods. The results indicate that the initial parameters of the rainfall loss model can satisfactorily reproduce the experimental results in some cases. Despite the fact that the slope material characteristics used in the laboratory experiments were relatively homogenous, some well-known methods yielded inaccurate results. Hence, calibration of the rainfall loss model proved to be essential. It should also be noted that, in some cases, the calibrated model parameters were relatively different from the initial model parameters estimated from the literature. None of the tested hydrological rainfall loss methods proved to be superior to the others. Therefore, in the case of natural environments with heterogeneous soil characteristics, multiple rainfall loss methods should be tested and the most suitable method should be selected only after cross-validation or a similar evaluation of the tested methods.

Detecting the mechanism of landslides and evaluating their dynamics is challenging, especially concerning composite landslides. For this purpose, several investigation and monitoring techniques should be implemented to obtain reliable information on landslide characteristics (e.g., geological and hydrogeological conditions and type of landslide processes), kinematics (displacement rate), and potential triggering mechanisms (e.g., change in groundwater table and precipitation). The Urbas landslide in northwest Slovenia has been studied for decades through geological, geotechnical, geodetic, and remote sensing investigations. However, due to the complexity of the landslide and the short duration of continuous monitoring, no assessment of its dynamics has been made. To meet this need, this study analysed continuous and periodic monitoring of landslide displacements using data from the global navigation satellite system (GNSS), a wire extensometer, unmanned aerial vehicle (UAV) photogrammetry, and hydrometeorological sensing (groundwater table, precipitation). The results of this study show that the dynamics of the Urbas landslide differ along the landslide area, depending on local geological and hydrogeological conditions. Consequently, certain parts of the landslide are at different evolutionary states and respond differently to the same external triggers.

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.

Rainfall-induced landslides are one of the most frequent natural disasters. Detection of changes in the characteristics of the rainfall events that can be regarded as triggering factor is therefore of primary importance for policy-makers, practitioners, civil protection units and others. This study evaluated changes in the frequency and intensity of rainfall events above selected empirical rainfall thresholds at the pan-European level. For areas classified as at least moderately susceptible to landslides according to the ELSUS v2 map (i.e. around 1.8 * 106 km2; around 37% of the area), changes were evaluated for the 1961–2018 period. The regional rainfall reanalysis data was used as input. Four different empirical rainfall thresholds were selected and changes in the frequency of rainfall events above the thresholds and their characteristics were analysed. The results showed that, on average, 14% more rainfall events above the threshold were recorded in the 1991–2018 period compared to 1961–1990 at the European level according to the selected empirical rainfall threshold. Moreover, several regions were found where frequency and intensity of rainfall events above the four selected global empirical rainfall thresholds were positive and statistically significant. These regions were for example Italy, Carpathian Mountains, British Isles and some other parts of Europe. Some of these areas are also regions where landslides susceptibility is high or even very high and where multiple landslides were recorded in the past. On the other hand, there are also regions where frequency and intensity of events above the threshold were negative and statistically significant. These regions were parts of Central Europe, Alps and Pyrenees. Also, in these regions landslides frequently occur. According to different empirical thresholds, no significant change in the frequency of rainfall events above the thresholds could be detected for around 50% of the investigated area.

Karst springs and aquifers are important sources of drinking water, so knowledge about the dynamics of changes in the hydrological characteristics of karst springs is especially important. This paper presents a hydrological trend analysis conducted for 14 karst springs in Slovenia. The trends of low, mean, and high annual flows were analyzed for the period from 1961 to 2013. Additionally, changes in annual rainfall, air temperature, and water temperature were investigated. The relationship between precipitation and discharges was also examined, as well as that between water and air temperature. Results indicate that low and mean flows in the selected springs are decreasing. In the case of high flows, no significant decreasing or increasing trend could be detected. For air temperature, the trend results were positive and statistically significant with the selected significance level. Some precipitation stations showed a significant decrease in the annual rainfall. Because the relationship between annual precipitation and mean flows is relatively high, the rainfall decrease could be the main reason for the decrease in low and mean flows. Moreover, the retention times of karst springs are relatively short. Some of the investigated springs are located in the Mediterranean part of the country where issues with drinking water supply occur commonly in the summer. If a similar dynamic continues, water scarcity problems can be expected in the future. The climate change models also predict such dynamics.

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.

The review study conducted by Brychta et al. (2022) is very informative. It provides an excellent overview of the approaches that can be used for the spatio-temporal assessment of rainfall erosivity. The authors also emphasized the importance of applying regression equations to the physio-geographic conditions for which they were developed. However, the study’s authors incorrectly cited the source of one of the empirical equations shown in Table 1. In addition, only a portion of the original equations was presented. Consequently, applying this particular equation with insufficient information could result in estimations of rainfall erosivity that are erroneous or biased. Hence, researchers should always double-check the applied equations in the original sources.

Precipitation reanalysis products (PRP) are a promising data source for ungauged regions. Since observed time series are often i) too short, ii) their temporal resolution is not sufficient or iii) the network density is too low, they cannot be used as e.g. input for rainfall-runoff (r-r) modelling and derived flood frequency analysis. Reanalysis products as global simulation of the atmosphere over the last decades solve the aforementioned issues.From the latest PRP three are most promising due to their spatial and temporal resolution for r-r modelling of small to mesoscale catchments: ERA5-Land (raster with approx. 9 km width), REA6 (6 km) and CFSv2 (22 km). These three PRP are able to cope with the dynamics of the r-r process due to their hourly resolution. The PRP are evaluated for Slovenia (Europe) with both, precipitation characteristics in space and time, and runoff characteristics. For areal precipitation, continuous and event-based characteristics are evaluated as well as precipitation extreme values. Simple correction methods for identified biases are suggested and applied. It can be seen that although the PRP clearly differ from each other, there is no clear ‘favourite’ to use as input for the r-r modelling.To conclude about the suitability of the PRP for r-r modelling, continuous simulations are carried out with GR4H for 20 catchments in Slovenia (55 km²-480 km²). Models are re-calibrated for each PRP input based on KGE. Simulation results of calibration and validation period are evaluated by runoff extreme values, KGE, flow duration curve and intra-annual cycle. Interestingly, first results show that the deviations of some rainfall characteristics do not necessarily transfer to deviations in runoff characteristics, which can be explained by the high nonlinearity of the r-r process. PRP lead to better, at least similar results for runoff characteristics for catchments without rain gauges in their centre.

Rainfall erosivity is one of the main inputs for soil erosion modelling. Long high-resolution rainfall time series are needed for the estimation of rainfall erosivity but these are likely to be lacking at many locations around the globe. An alternative approach could be the generation of synthetic rainfall time series using stochastic rainfall models. In this study, four methods for estimating the rainfall erosivity were evaluated at ungauged sites:i) estimation from regionalised observed 5 minute rainfall time series,ii) direct regionalisation of the rainfall erosivity estimated from observations,iii) estimation from 5 minute rainfall time series disaggregated from daily observations,iv) estimation from rainfall time series generated by a regionalized stochastic rainfall model.Data from 159 stations from Lower Saxony, Germany, were used to evaluate the performance of different methods. All tests were performed using the leave-one-out cross validation method. Additionally, we also analysed the minimum time series length necessary to adequately estimate the rainfall erosivity.The results indicated that the direct regionalization of the mean annual rainfall erosivity yielded the best performance in terms of relative bias followed by the regionalization of the 5 minute rainfall data. However, the main advantage of the rainfall generators is that they can generate long synthetic time series and can also provide estimates of other rainfall erosivity characteristics such as number of erosive rainfall events, etc. Applying the alternating renewal model indicated that more than 60 years of data are needed to obtain a stable estimate of rainfall erosivity and that rainfall erosivity estimations using 5 years of data can lead to significant uncertainty. Moreover, it was also found that the rainfall erosivity calculations are sensitive to the resolution of the input data. Acknowledgment: The results of the study are part of the bilateral research project between Slovenia and Germany “Stochastic rainfall models for rainfall erosivity evaluation” (BI-DE/18-19-008).

Throughfall constitutes the majority of incident precipitation reaching the ground under any type of vegetation canopies. Its characteristics play a crucial role in understanding the sub-canopy hydrologic and erosional processes. The present study examines the drop size distribution (DSD) and erosivity of throughfall beneath the birch tree (Betula pendula Roth.) canopy during its leafed period using a Parsivel1 optical disdrometer installed in the experimental plot in the city of Ljubljana, Slovenia. The momentum and kinetic energy of throughfall drops were used to express the impact of the tree canopy on the potential erosive power of throughfall on a soil surface which was computed from the measured raindrop size and velocity. The microstructures of open rainfall and throughfall were measured simultaneously by an optical disdrometer during the two separate precipitation events that occurred on August and September 2021 with an accumulated amount of 34.4 mm in 7.3 hours and 87.6 mm in 7.6 hours, respectively. On an event basis, the preliminary results show that the throughfall DSD for both events exhibits two contrasting modes (i.e. bimodal peaks) while open rainfall has only one which is attributed to the influence of canopy interception and storage. The total number of throughfall drops is higher compared to the open field condition but are smaller in size, comprising nearly 89% of the recorded drops are below 1 mm while only 0.23% are greater than 2.4 mm. Additionally, the median-volume drop diameter (D50) of the throughfall is 1.31 mm for an extreme event (September 2021) and 0.98 mm for a medium-magnitude rainfall (August 2021) which is respectively, 70% and 79% lower than those in open precipitation. On the other hand, the raindrops from moderate and heavy precipitation have greater momentum to cause soil particle displacement with a corresponding value of 60.49 and107.83 kg m s-1 m-2 than the throughfall drops (40.99 and 87.49 kg m s-1 m-2). Similarly, a throughfall kinetic energy of 91.96 and 187.77 J m-2 is respectively 64% and 82% lower than the energy loads of raindrops in the open environment. Owing to the effects of the birch tree canopy, the distribution of throughfall reduces the erosive potential of raindrops by approximately 36% and 18% for the two selected rainfall events during the leafed period. These results accentuate the importance of understanding the different characteristics of throughfall from the open rainfall which is necessary for the prediction of soil erosion processes in areas where this tree species is abundant in nature. Acknowledgments: Results are part of the CELSA project entitled “Interception experimentation and modelling for enhanced impact analysis of nature-based solution” and research programme P2-0180 supported by the Slovenian Research Agency (ARRS).

The assessment of rainfall erosivity is one of the main inputs in determining soil erosion. To calculate mean annual rainfall erosivity (R), long-term high-resolution observed rainfall time series are required, which are often not available. To overcome the issue of limited data availability in space, four methods are employed: the direct regionalisation of R, the regionalisation of 5 minute rainfall, the disaggregation of daily rainfall into 5 minute timesteps, and the use of a regionalised stochastic rainfall model. In addition the minimum time series length necessary to adequately estimate R is investigated. The impact of station density is considered for each of the methods. The study is carried out using 159 recording and 150 non-recording (daily) rainfall stations in the federal state of Lower Saxony, Germany. Results show that the direct regionalisation of mean annual erosivity leads to the best results in terms of relative bias and relative root mean square error (RMSE). This is followed by the regionalisation of the 5 minute rainfall data, which yields better results than the rainfall generation models, namely an alternating renewal model (ARM) and a multiplicative cascade model (Disagg). However, a key advantage of using regionalised rainfall models is the generation of rainfall time series that can be used for the estimation of the erosive event characteristics, which is not possible through the direct regionalisation of R. Using the stochastic ARM it can be shown that in most cases more than 60 years of data is needed in order to obtain a stable estimate of the annual rainfall erosivity. Estimation of soil erosion based on only 5 or 10 years of data can lead to uncertain values. Such short time series are often used when regionalisation is applied. Moreover, it was also found that resolution of measuring device has a significant effect on the rainfall erosivity and coarser data resolution can lead to high relative bias.

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 1994-2017. Our aim was to identify (i) processes and models most frequently addressed in the literature, (ii) regions within which models are primarily applied, (iii) what regions 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 merged the knowledge of a group of 66 soil-erosion scientists from 67 research institutions and 25 countries. The resulting database ‘Global Applications of Soil Erosion Modelling Tracker (GASEMT)’ includes 3,030 individual modelling records from 126 counties encompassing all continents (except Antarctica). Out of 8,471 articles identified as potentially relevant, we reviewed 1,697 articles and transferred relevant information from each into the database. For each record reported in the GASEMT database, 42 attributes were evaluated. The GASEMT database provides insights into the state-of-the-art of soil- erosion models and model applications worldwide. The database is also intended to support the upcoming country-based United Nations global soil-erosion assessment. This database may help inform soil erosion research priorities in that it builds a foundation for future targeted in-depth analyses. GASEMT is an open-source database that anyone can use to develop research, rectify errors, and expand.

Despite the widespread concerns of increasing precipitation extremes caused by climate change, the application of urban trees as a nature-based solution against pluvial flooding are still often overlooked and undervalued due to its limited practical value in case of extreme rainfall occurrences. Hence, this study investigated the rainfall interception performance of open-grown birch (Betula pendula Roth.) and pine (Pinus nigra Arnold) trees in an urban park of Ljubljana, Slovenia (Europe) on an event basis using disdrometer data. In addition, we closely analysed the rainfall microstructure under both types of trees during the extreme storm event on September 29, 2021 and compared it to average values from the past. During this single storm event with a cumulative rainfall of 87.6 mm within 7.6 hours, birch trees intercepted 19.5% of the gross rainfall, which is lower than its average interception of 35.9% during the period of 2014-2017. On the other hand, the canopy of pine trees was able to intercept 47.0% of rainfall – higher than its average retention capacity of 37.1% during extreme events in the past (>40 mm). The total number of raindrops recorded for this event under the birch tree crown is 362,556 with a largest diameter of 13 mm, where the throughfall from birch and pine trees constitute 75% and 53% of the rainfall, respectively. For small to moderate rainfall events that occurred from August to October 2021 with an average number of 167,329 raindrops, the amount of rainfall intercepted by birch and pine tree canopies corresponds to 23.8% and 55.7%, respectively. The results show that on an event basis, both types of trees perform effectively in intercepting low to medium magnitudes of precipitation. Results also reveal that pine trees can intercept substantially more rainfall even during the high-magnitude events, which emphasizes the importance of proper selection of trees species with higher rainfall interception capacity to leverage its benefits in an urban setting during extreme conditions.Acknowledgments: Results are part of the CELSA project entitled “Interception experimentation and modelling for enhanced impact analysis of nature-based solution” and research programme P2-0180 supported by the Slovenian Research Agency (ARRS).

International audience; The major event that hit Europe in summer 2021 reminds society that floods are recurrent and among the costliest and deadliest natural hazards. The long-term flood risk management (FRM) efforts preferring sole technical measures to prevent and mitigate floods have shown to be not sufficiently effective and sensitive to the environment. Nature-Based Solutions (NBS) mark a recent paradigm shift of FRM towards solutions that use nature-derived features, processes and management options to improve water retention and mitigate floods. Yet, the empirical evidence on the effects of NBS across various settings remains fragmented and their implementation faces a series of institutional barriers. In this paper, we adopt a community expert perspective drawing upon LAND4FLOOD Natural flood retention on private land network (https://www.land4flood.eu) in order to identify a set of barriers and their cascading and compound interactions relevant to individual NBS. The experts identified a comprehensive set of 17 barriers affecting the implementation of 12 groups of NBS in both urban and rural settings in five European regional environmental domains (i.e., Boreal, Atlantic, Continental, Alpine-Carpathian, and Mediterranean). Based on the results, we define avenues for further research, connecting hydrology and soil science, on the one hand, and land use planning, social geography and economics, on the other. Our suggestions ultimately call for a transdisciplinary turn in the research of NBS in FRM.

Morphodynamic changes in the riverbed may be accelerated by the climate change-induced effects, mostly through the increase of the frequency of extreme climatic events such as floods. This can lead to scouring of the riverbed around the bridge substructure and consequently reduces its overall stability. In order to better understand hydromorphological processes at the local scale, the influence of floods on bridge scour requires a detailed analysis of several interacting flood hydrograph characteristics. This paper presents a multivariate analysis of the annual maximum (AM) flood discharge data at four gauging stations on the Drava and Sava Rivers in Croatia (Europe). As part of the hydrograph analysis, multiple baseflow separation methods were tested. Flood volumes and durations were derived after extracting the baseflow from measured discharge data. Suitable marginal distribution functions were fitted to the peak discharge (Q), flood volume (V) and duration (D) data. Bivariate copula analyses were conducted for the next pairs: peak discharge and volume (Q–V), hydrograph volume and duration (V–D) and peak discharge and hydrograph duration (Q–D). The results of the bivariate copula analyses were used to derive joint return periods for different flood variable combinations, which may serve as a preliminary analysis for the pilot bridges of the R3PEAT project where the aim is to investigate the influences on the riverbed erosion around bridges with installed scour countermeasures. Hence, a design hydrograph was derived that could be used as input data in the hydraulic model for the investigation of the bridge scour dynamics within the project and a preliminary methodology is proposed to be applied. The results indicate that bivariate frequency analysis can be very sensitive to the selected baseflow separation methodology. Therefore, future studies should test multiple baseflow separation methods and visually inspect the performance.