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Rainfall interception process is an important part of the biohydrological cycle, in which vegetation plays an important role by regulating the amount and dynamics of rainfall reaching the ground. In this paper, an event-based analysis is performed to discuss the influence of vegetation on dynamic of temporal response of soil volumetric water content (VWC) in the upper soil layer during rainfall events. More specifically, six events that occurred between 19 November 2021 and 30 June 2022, characterized by different hydro-meteorological and vegetation conditions, are analyzed based on continuous measurements of VWC in the open and below groups of two deciduous (Betula pendula Roth.) and two coniferous trees (Pinus nigra Arnold), as well as rainfall in the open and throughfall on an urban experimental plot in Ljubljana, Slovenia. VWC values at the upper depth (16 cm) were the highest under the birch tree, followed by the location in the open and under the pine tree. However, in the lowest depth (74 cm) VWC values were the lowest under the birch tree. VWC responses to rainfall and throughfall showed seasonal patterns related to the pre-event wetness conditions, with a faster occurrence of maximum VWC values in the leafless period. Additionally, rainfall amount and its dynamics during the event significantly affect the response, as VWC in general reaches its peak after the occurrence of more intense rainfall. Such an event-based analysis, offering an insight into the dynamics of the event development, is crucial and very beneficial for understanding of the biohydrological processes.

General weather conditions may have a strong influence on the individual elements of the hydrological cycle, an important part of which is rainfall interception. The influence of general weather conditions on this process was analysed, evaluating separately the influence of various variables on throughfall, stemflow, and rainfall interception for a wet (2014), a dry (2015), and an average (2016) year. The analysed data were measured for the case of birch and pine trees at a study site in the city of Ljubljana, Slovenia. The relationship between the components of rainfall partitioning and the influential variables for the selected years was estimated using two statistical models, namely boosted regression trees and random forest. The results of both implemented models complemented each other well, as both indicated the rainfall amount and the number of raindrops as the most influential variables. During the wet year 2014 rainfall duration seems to play an important role, correlating with the previously observed influence of the variables during the wetter leafless period. Similarly, during the dry year 2015, rainfall intensity had a significant influence on rainfall partitioning by the birch tree, again corresponding to the influences observed during the drier leafed period.

Substantial evidence shows that the frequency of hydrological extremes has been changing and is likely to continue to change in the near future. Non-stationary models for flood frequency analyses are one method of accounting for these changes in estimating design values. The objective of the present study is to compare four models in terms of goodness of fit, their uncertainties, the parameter estimation methods and the implications for estimating flood quantiles. Stationary and non-stationary models using the GEV distribution were considered, with parameters dependent on time and on annual precipitation. Furthermore, in order to study the influence of the parameter estimation approach on the results, the maximum likelihood (MLE) and Bayesian Monte Carlo Markov chain (MCMC) methods were compared. The methods were tested for two gauging stations in Slovenia that exhibit significantly increasing trends in annual maximum (AM) discharge series. The comparison of the models suggests that the stationary model tends to underestimate flood quantiles relative to the non-stationary models in recent years. The model with annual precipitation as a covariate exhibits the best goodness-of-fit performance. For a 10% increase in annual precipitation, the 10-year flood increases by 8%. Use of the model for design purposes requires scenarios of future annual precipitation. It is argued that these may be obtained more reliably than scenarios of extreme event precipitation which makes the proposed model more practically useful than alternative models.

A thorough understanding of the hydrologic mechanisms that control the movement of water through the soil is essential for developing effective stormwater management strategies. Infiltration is critical for determining the amount of water entering the soil and controlling surface runoff. Spatial and temporal variations in soil properties strongly affect infiltration rates, which underscores the importance of evaluating field-specific values for hydraulic conductivity, which are also highly dependent on the chosen measurement and evaluation methods. The objective of this study is to determine and compare soil hydraulic conductivity under dry conditions using two field measurement techniques, namely the double-ring infiltrometer (DRI) and the mini-disk infiltrometer (MDI). The results demonstrate the importance of performing multiple replicates of infiltration tests, especially during the dry season, as the initial dry surface caused deviations in hydraulic conductivity estimates for both methods used (DRI and MDI). Significant spatial variability was observed within the radius of the test replicates over short distances (<1 m). In addition, experimental infiltration curves for a selected site were used to evaluate and compare soil hydraulic parameters through infiltration modeling. In general, the Philip, Green-Ampt, and Smith-Parlange theoretical models showed a better fit to the experimental DRI data than the semi-empirical Horton model. [ABSTRACT FROM AUTHOR]

The detailed analysis of individual flood event elements, including peak discharge (Q), flood event volume (V), and flood event duration (D), is an important step for improving our understanding of complex hydrological processes. More than 2,500 flood events were defined based on the annual maximum (AM) peak discharge from 50 Slovenian gauging stations with catchment areas of between 10 and 10,000 km2. After baseflow separation, the stations were clustered into homogeneous groups and the relationships between the flood event elements and several catchment characteristics were assessed. Different types of flood events were characteristic of different groups. The flashiness of the stream is significantly connected with mean annual precipitation and location of the station. The results indicate that some climatic factors like mean annual precipitation and catchment related attributes as for example catchment area have notable influence on the flood event elements. When assessing the dependency between the pairs of flood event elements (Q, V, D), the highest correlation coefficients were obtained for the Q-V pair. The smallest correlations or no correlations were observed between the Q and D variables.

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 (41–460 km 2) 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. 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 recalibration with PRP has been carried out, the performance is similar compared to the simulations where station-based data were 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 data in case precipitation or air temperature data are lacking, but model calibration using discharge data would be needed to improve the performance. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Compound events occur when multiple drivers or hazards occur in the same region or on the same time scale, hence amplifying their impacts. Compound events can cause large economic damage or endanger human lives. Thus, a better understanding of the characteristics of these events is needed in order to protect human lives. This study investigates the drivers and characteristics of floods in Europe and North America from the compound event perspective. More than 100 catchments across Europe and North America were selected as case study examples in order to investigate characteristics of floods during a 1979–2019 period. Air temperature, precipitation, snow thickness, snow liquid water equivalent, wind speed, vapour pressure, and soil moisture content were used as potential drivers. Annual maximum floods were classified into several flood types. Predefined flood types were snowmelt floods, rain-on-snow floods, short precipitation floods and long precipitation floods that were further classified into two sub-categories (i.e., wet and dry initial conditions). The results of this study show that snowmelt floods were often the dominant flood type in the selected catchments, especially at higher latitudes. Moreover, snow-related floods were slightly less frequent for high altitude catchments compared to low- and medium-elevation catchments. These high-altitude areas often experience intense summer rainstorms that generate the highest annual discharges. On the other hand, snowmelt-driven floods were the predominant flood type for the lower elevation catchments. Moreover, wet initial conditions were more frequent than the dry initial conditions, indicating the importance of the soil moisture for flood generation. Hence, these findings can be used for flood risk management and modelling. [ABSTRACT FROM AUTHOR]

Regional flood frequency analysis (RFFA) is a powerful method for interrogating hydrological series since it combines observational time series from several sites within a region to estimate risk-relevant statistical parameters with higher accuracy than from single-site series. Since RFFA extreme value estimates depend on the shape of the selected distribution of the data-generating stochastic process, there is need for a suitable goodness-of-distributional-fit measure in order to optimally utilize given data. Here we present a novel, least-squares-based measure to select the optimal fit from a set of five distributions, namely Generalized Extreme Value (GEV), Generalized Logistic, Gumbel, Log-Normal Type III and Log-Pearson Type III. The fit metric is applied to annual maximum discharge series from six hydrological stations along the Sava River in South-eastern Europe, spanning the years 1961 to 2020. Results reveal that (1) the Sava River basin can be assessed as hydrologically homogeneous and (2) the GEV distribution provides typically the best fit. We offer hydrological-meteorological insights into the differences among the six stations. For the period studied, almost all stations exhibit statistically insignificant trends, which renders the conclusions about flood risk as relevant for hydrological sciences and the design of regional flood protection infrastructure. [ABSTRACT FROM AUTHOR]

The article presents the results of the analysis of low flows at 5 gauging stations on the Vipava River, which has a Dinaric pluvial-nival regime (catchment area of 590 km2). The low-flow statistics show that the gauging station Vipava stands out with the lowest values. Baseflow index (BFI) values are comparable among the considered stations and are around 0.40. Relatively low BFI values indicate low soil permeability. A high similarity between the mean annual minimum 7-day flow (MAM7) and the 95th percentile exceedance discharge (Q95) at all gauging stations indicates a temperate climate. The highest flows values occur in spring and autumn, and the lowest in summer. In wet years there are relatively large fluctuations in flow, while in dry years the flow consists mainly of baseflow. This is also confirmed with the flow duration curves analysis. The seasonality analysis shows a predominant summer regime with low flows. [ABSTRACT FROM AUTHOR]

Floods are one of the most devastating natural disasters that can cause large economic damage and endanger human lives. Flood forecasting is one of the flood risk mitigation measures serving to protect human lives and social estate. The Danube River Basin (DRB) is the world's most international river basin, flowing through the territory of 19 countries, covering more than 800,000 km2. The frequency of floods in the DRB increased in the last decades, urging the need for a more effective and harmonized regional and cross‐border cooperation in the field of flood forecasting. Reliable and comprehensive hydrologic data are the basis of flood forecasting. This paper provides an overview of the national flood forecasting systems in the DRB. Detailed information about meteorological and hydrological measurements, flood modelling, forecasting, and flood warnings is provided for 12 countries that cover almost 95% of the total DRB area. Notably, significant differences exist among the countries in terms of the measuring network density, the models used as well as forecasting and warnings methodology. These differences can be attributed to the geographical and climatological setting, political situation, historical forecasting development, etc. It can be seen that there is still much room left for improvements of measurement networks (e.g., density, measured parameters) and models used that could be improved to enhance the flood forecasting in the DRB. [ABSTRACT FROM AUTHOR]

Rain-on-snow (ROS) floods can cause economic damage and endanger human lives due to the compound effect of rainfall and snowmelt, especially under climate change. In this study, possible future changes of seasonality, magnitude and frequency characteristics of ROS floods were investigated for the selected catchments in Slovenia, Europe. For this purpose, five global/regional climate models (GCM/RCM) combinations were applied using the RCP4.5 climate scenario for the period 1981–2100. To determine ROS floods' characteristics in the future, a lumped conceptual hydrological model Génie Rural à 6 paramètres Journalier (GR6J) with snow module CemaNeige was applied. The results indicate that the number of ROS floods could increase in the future. Moreover, also the magnitudes of extreme ROS floods could increase, while a slight decrease in the median values of ROS flood magnitudes was observed. The strength of seasonality for a high-altitude catchment could decrease in the future. A slight shift in the average ROS floods' timing could be expected. Furthermore, a catchment located in a temperate continental climate could have a different response to the climate change impact in comparison to a catchment located in a mountain climate with alpine characteristics. Additionally, differences among investigated climate models show a large variability. [ABSTRACT FROM AUTHOR]

In the case of ungauged catchments, different procedures can be used to derive the design hydrograph and design peak discharge, which are crucial input data for the design of different hydrotechnical engineering structures, or the production of flood hazard maps. One of the possible approaches involves using a hydrological model where one can calculate the design hydrograph through the design of a rainfall event. This study investigates the impact of the design rainfall on the combined one-dimensional/two-dimensional (1D/2D) hydraulic modelling results. The Glinšˇcica Stream catchment located in Slovenia (central Europe) is used as a case study. Ten different design rainfall events were compared for 10 and 100-year return periods, where we used Huff curves for the design rainfall event definition. The results indicate that the selection of the design rainfall event should be regarded as an important step, since the hydraulic modelling results for different scenarios differ significantly. In the presented experimental case study, the maximum flooded area extent was twice as large as the minimum one, and the maximum water velocity over flooded areas was more than 10 times larger than the minimum one. This can lead to the production of very different flood hazard maps, and consequently planning very different flood protection schemes. [ABSTRACT FROM AUTHOR]

Part of precipitation is intercepted by forest canopies, while the rest reaches the ground as throughfall or stemflow. This process is influenced by various meteorological variables, of which we have mainly focused on drop diameter and velocity. Rainfall in the open and throughfall under birch and pine trees have both been measured since 2014 in Ljubljana, Slovenia. The results demonstrate that the total throughfall during 3.5 years was 73% and 53% of rainfall under birch and pine trees, respectively. During the 236 analysed events, the median volume diameter was 1.8 mm (1.7 mm), and kinetic energy between 0.01 mJ/cm² and 23.3 mJ/cm² was recorded. We closely analysed the effect of rainfall microstructure on throughfall under pine and birch trees during three specific rainfall events. The increase in drop diameter and fall velocity during a rainfall event instantaneously increased throughfall under pine trees between 25% and 47%, whereas no such changes were observed under birch trees. This may be the consequence of different tree properties of the two species. Additionally, in the case of a saturated canopy, throughfall under pine trees exceeded rainfall in the open after an onset of larger and faster drops. [ABSTRACT FROM AUTHOR]

Suspended sediment load (SSL) observations are usually less frequent than precipitation and river discharge measurements; therefore a reliable procedure is needed for the estimation of SSL. One year of precipitation, SSL, and discharge measurements at 20-min intervals were performed at the Kuzlovec torrent in Slovenia. The Frank copula was selected to construct an event-based model using the following variables: precipitation sum (P), peak discharge (Q), and SSL. The idea was to estimate the SSL based on the measured P and Q. The proposed model was additionally tested using the daily data from the Gornja Radgona station on the Mura River, for which 29 years of data were available and where Khoudraji-Liebscher copulas were used. The estimated SSL values using the copula were compared with different regression models. The proposed copula model yielded meaningful SSL estimates. Some performance criteria and tests indicated that the copula model gives a better fit to the measured data than other tested methods. [ABSTRACT FROM AUTHOR]

Suspended solids are present in every river, but high quantities can worsen the ecological conditions of streams; therefore, effective monitoring and analysis of this hydrological variable are necessary. Frequency, seasonality, inter-correlation, extreme events, trends and lag analyses were carried out for peaks of suspended sediment concentration (SSC) and discharge (Q) data from Slovenian streams using officially monitored data from 1955 to 2006 that were made available by the Slovenian Environment Agency. In total more than 500 station-years of daily Q and SSC data were used. No uniform (positive or negative) trend was found in the SSC series; however, all the statistically significant trends were decreasing. No generalization is possible for the best fit distribution function. A seasonality analysis showed that most of the SSC peaks occurred in the summer (short-term intense convective precipitation produced by thunderstorms) and in the autumn (prolonged frontal precipitation). Correlations between Q and SSC values were generally relatively small (Pearson correlation coefficient values from 0.05 to 0.59), which means that the often applied Q–SSC curves should be used with caution when estimating annual suspended sediment loads. On average, flood peak Q occurred after the corresponding SSC peak (clockwise-positive hysteresis loops), but the average lag time was rather small (less than 1 day). Editor M.C. Acreman; Associate editor Y. Gyasi-Agyei [ABSTRACT FROM AUTHOR]

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Drought is a complex phenomenon with high spatial and temporal variability. Water scarcity has become a growing problem in Slovenia in recent decades. Therefore, the spatial and temporal variability of hydrological drought was investigated in this study by analysing the Standardized Streamflow Index (SSI). Monthly discharge data series from 46 gauging stations for the period 1961–2016 were used to calculate SSI values at five different time scales (1, 3, 6, 12, and 24 months). The results indicate that the frequency and intensity of droughts in Slovenia has increased in recent decades at most of the analysed gauging stations and at all time scales considered. Spring and summer periods were identified as critical in terms of water deficit. SSI values vary independently from the location of the gauging station, confirming that drought is a regional phenomenon, even in a small country such as Slovenia. However, SSI values vary considerably depending on the time scale chosen. This was also confirmed by the results of the hierarchical clustering of the number of extreme droughts, as various time scales resulted in a different distribution of gauging stations by individual groups. [ABSTRACT FROM AUTHOR]

A distributed-framework hydrologic modeling system (DF-HMS) is a primary and significant component of a distributed-framework basin modeling system (DFBMS), which simulates the hydrological processes and responses after rainfall at the basin scale, especially for non-homogenous basins. The DFBMS consists of 11 hydrological feature units (HFUs) involving vertical and horizontal geographic areas in a basin. Appropriate hydrologic or hydraulic methods are adopted for different HFUs to simulate corresponding hydrological processes. The digital basin generation model is first developed to determine the essential information for hydrologic and hydraulic simulation. This paper mainly describes two significant HFUs contained in the DF-HMS for hydrologic modeling: Hilly sub-watershed and plain overland flow HFUs. A typical hilly area application case study in the Three Gorges area is introduced, which demonstrates DF-HMS's good performance in comparison with the observed streamflow at catchment outlets. [ABSTRACT FROM AUTHOR]

To better simulate the river basin hydrological cycle and to solve practical engineering application issues, this paper describes the distributed-framework basin modeling system (DFBMS), which concatenate a professional hydrological model system, a geographical integrated system, and a database management system. DFBMS has two cores, which are the distributed-frame professional modeling system (DF-PMS) and the double-object sharing structure (DOSS). An area/region that has the same mechanism of runoff generation and/or movement is defined as one type of hydrological feature unit (HFU). DF-PMS adopts different kinds of HFUs to simulate the whole watershed hydrological cycle. The HFUs concept is the most important component of DF-PMS, enabling the model to simulate the hydrological process with empirical equations or physical-based submodules. Based on the underlying source code, the sharing uniform data structure, named DOSS, is proposed to accomplish the integration of a hydrological model and geographical information system (GIS), which is a new way of exploring temporal GIS. DFBMS has different numerical schemes including conceptual and distributed models. The feasibility and practicability of DFBMS are proven through its application in different study areas. [ABSTRACT FROM AUTHOR]

A distributed-framework basin modeling system (DFBMS) was developed to simulate the runoff generation and movement on a basin scale. This study is part of a series of papers on DFBMS that focuses on the hydraulic calculation methods in runoff concentration on underlying surfaces and flow movement in river networks and lakes. This paper introduces the distributed-framework river modeling system (DF-RMS) that is a professional modeling system for hydraulic modeling. The DF-RMS contains different hydrological feature units (HFUs) to simulate the runoff movement through a system of rivers, storage units, lakes, and hydraulic structures. The river network simulations were categorized into different types, including one-dimensional river branch, dendritic river network, loop river network, and intersecting river network. The DF-RMS was applied to the middle and downstream portions of the Huai River Plain in China using different HFUs for river networks and lakes. The simulation results showed great consistency with the observed data, which proves that DF-RMS is a reliable system to simulate the flow movement in river networks and lakes. [ABSTRACT FROM AUTHOR]

This paper presents the application of a distributed-framework basin modeling system (DFBMS) in Taihu Basin, China. The concepts of professional modeling systems and system integration/coupling have been summarized in the first three series papers. This study builds a hydrologic and hydrodynamic model for Taihu Basin, which is in the lowland plain areas with numerous polder areas. Digital underlying surface area data agree with the survey results from the water resource development and utilization. The runoff generated in each cell was calculated with the model based on the digital underlying surface data. According to the hydrological feature units (HFU) concept from the DFBMS, Taihu Basin was conceptualized into six different HFUs. The basic data of rainfall, evaporation, water surface elevation (WSE), discharge, tide level, and water resources for consumption and discharge in 2000 were used to calibrate the model. The simulated results of WSE and discharge matched the observed data well. The observed data of 1998, 1999, 2002, and 2003 were used to validate the model, with good agreement with the simulation results. Finally, the basic data from 2003 were used to simulate and evaluate the management scheme of water diversion from the Yangtze River to Taihu Lake. Overall, the DFBMS application in Taihu Basin showed good performance and proved that the proposed structure for DFBMS was effective and reliable. [ABSTRACT FROM AUTHOR]

Conceptual rainfall-runoff models besides precipitation and discharge data generally require estimates of the mean daily air temperature as input data. For the estimation of the mean daily air temperature, there are different methods available. The paper presents an evaluation of the impact of the mean daily air temperature calculation on the rainfall-runoff modelling results. Additionally, other measured variables and rating curve uncertainty were assessed. Differences in the mean daily air temperature values were evaluated for the 33 meteorological stations in Slovenia and additional investigations were conducted for four selected meso-scale catchments located in different climates. The results of the application of four equations for the mean air temperature calculation yielded the mean absolute error values between 0.56–0.80 °C. However, the results of rainfall-runoff modelling showed that these differences had an almost negligible impact on the model results. Differences in the mean simulated discharge values were no larger than 1%, while differences in the maximum discharge values were a bit larger, but did not exceed 5%. A somewhat larger impact on the model results was observed when precipitation and water level measurements' uncertainty was included. However, among all analysed input data uncertainties, the rating curve uncertainty can be regarded as the most influential with differences in the simulated mean discharge values in the range of 3% and differences in the maximum discharge values up to 14%. [ABSTRACT FROM AUTHOR]

Rainfall-runoff modeling is nowadays applied for water resources management, water system design, real-time forecasting, flood design and can be carried out by using different types of hydrological models. In this study, we focused on lumped conceptual hydrological models and their performance in diverse sub-catchments of the Sava River in Slovenia, related to their size and non-homogeneity. We evaluated the difference between modeled and measured discharges of selected discharge gauging stations, using different model performance criteria that are usually applied in hydrology, connecting the results to geospatial analysis of geological and hydrogeological characteristics, land use, runoff potential, proportion of agglomeration and various meteorological variables. Better model performance was obtained for catchments with a higher runoff potential and with less variations in meteorological variables. Regarding the number of used parameters, the results indicated that the tested Genie Rural 6-parameter Journalier (GR6J) model with 6 parameters performed better than the Genie Rural 4-parameter Journalier (GR4J) model with 4 parameters, especially in the case of larger sub-catchments. These results illustrate the comprehensive nature of lumped models. Thus, they yield good performance in case of the catchments with indistinguishable characteristics. [ABSTRACT FROM AUTHOR]

Urban trees play an important role in the built environment, reducing the rainfall reaching the ground by rainfall interception. The amount of intercepted rainfall depends on the meteorological and vegetation characteristics. By applying the multiple correspondence analysis (MCA), we analysed the influence of rainfall amount, intensity and duration, the number of raindrops, the mean volume diameter (MVD), wind speed and direction on rainfall interception. The analysis was based on data from 176 events collected over more than three years of observations. Measurements were taken under birch (Betula pendula Roth.) and pine (Pinus nigra Arnold) trees located in an urban park in the city of Ljubljana, Slovenia. The results indicate that rainfall interception is influenced the most by rainfall amount and the number of raindrops. In general, the ratio of rainfall interception to gross rainfall decreases with longer and more intense rainfall events. The influence of the raindrop number depends also on their size (MVD), which is evident especially for the pine tree. For example, pine tree interception increases with smaller raindrops regardless of their number. In addition, MCA gives a new insight into the influence of wind characteristics, which was not visible using previous methods of data analysis (regression analysis, correlation matrices, regression trees, boosted regression trees). According to the nearby buildings, a wind corridor is sometimes created, decreasing rainfall interception by both tree species. [ABSTRACT FROM AUTHOR]

Urbanization changes the natural environment, alters land use, and affects the hydrological cycle. Due to decreased infiltration, runoff appears faster with higher flow peaks. A nature‐based solution is to plant trees because they intercept precipitation and help to reduce water reaching the ground, forming surface runoff. Rainfall partitioning for birch (Betula pendula Roth.) and pine (Pinus nigra Arnold) trees is measured in the city of Ljubljana, Slovenia, during 2014 and 2015. The measured values for two consecutive years are used to estimate potential surface runoff reduction due to planting of the trees at a parking lot. The results demonstrate that birch and pine trees intercepted 23 and 45% of gross rainfall, respectively. Both tree species intercept more rainfall in the leafed period. Additionally, rainfall interception during wet (2014) and dry (2015) years has been compared. In 2014 rainfall interception is highly influenced by rainfall intensity, while it has a negligible impact on rainfall interception in 2015, when air temperature is more influential. The scenario of covering 10% of the parking lot area with the trees results in runoff reduction of up to 7.3% per year. In general, runoff reduction is higher in a wet rather than a dry year. The new findings about the performance of different tree species in different climate conditions can offer valuable information for the decision makers and landscape designers about the benefits of trees in urban areas. [ABSTRACT FROM AUTHOR]

Soil hydraulic conductivity has a direct influence on infiltration rate, which is of great importance for modelling and design of surface runoff and stormwater control measures. In this study, three measuring techniques for determination of soil hydraulic conductivity were compared in an urban catchment in Ljubljana, Slovenia. Double ring (DRI) and dual head infiltrometer (DHI) were applied to measure saturated hydraulic conductivity (Ks) and mini disk infiltrometer (MDI) was applied to measure unsaturated hydraulic conductivity (K), which was recalculated in Ks in order to compare the results. Results showed significant differences between investigated techniques, namely DHI showed 6.8 times higher values of Ks in comparison to DRI. On the other hand, Ks values obtained by MDI and DRI exhibited the lowest difference. MDI measurements in 12 locations of the small plot pointed to the spatial variability of K ranging between 73%–89% as well as to temporal variability within a single location of 27%–99%. Additionally, a reduction of K caused by the effect of drought-induced water repellency was observed. Moreover, results indicate that hydrological models could be enhanced using different scenarios by employing a range of K values based on soil conditions. [ABSTRACT FROM AUTHOR]