This study presents investigations on rainfall microphysical processes and ground-based rainfall instrument measurements through laboratory rainfall simulations with careful considerations for in-situ observations and validations.  Controlled laboratory rainfall experimentation has a pivotal role in systematic investigations to deepen our understanding of rainfall microphysical processes and the development, calibration, and assessment of rainfall instruments.  In the rainfall and related investigations in the PI’s laboratory over the past nearly two decades, we have utilized a variety of laboratory rainfall simulation setups, each featuring customized drop generators for the application, that were designed to address the specific aspects and objectives of the targeted research.  Here we will present our select experimental investigations on raindrop morphodynamics (shape and fall speed) and collisions as well as assessments of the OTT Parsivel² disdrometer and OTT Pluvio² rain gauge measurements.  Raindrop morphodynamics and collisions are of importance for various applications, including radar rainfall retrievals and hydrological modeling.  Parsivel² and Pluvio² are widely used ground-based instruments to monitor various precipitation quantities (e.g. raindrop size distribution, fall speed, and rainfall intensity, amount, and kinetic energy) that are of importance for a variety of rainfall- and water resources-related applications, including ground validation and soil erosion studies.  This material is based upon work supported by the National Science Foundation under Grants No. AGS-1741250 to the first author (FYT).

How to cite: Testik, F. Y., Saha, R., and Rahman, K.: Rainfall Microphysics and Instrument Measurement Assessments via Rainfall Simulators, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8198, https://doi.org/10.5194/egusphere-egu24-8198, 2024.

Non-Catching Gauges (NCGs) are instruments used to measure precipitation without the need to collect the equivalent water volume in a reservoir. They sense each hydrometeor individually, often using a contactless approach, providing measurements of the relevant microphysical properties of precipitation. These gauges offer several advantages over traditional catching gauges, making them an invaluable source of data for numerous research applications. However, NCGs, like catching-type gauges, are susceptible to measurement biases from both instrumental and environmental sources. To assess instrumental biases, rigorous testing and calibration are required, which can be more challenging than for catching gauges. In fact, to provide reference precipitation, it is necessary to carefully reproduce hydrometeor characteristics such as particle size, shape, fall velocity, and density. Calibration is therefore typically delegated to manufacturers, who may use undisclosed procedures that cannot be traced to the international standards (see Lanza et al. 2021 for a review).

In this work, we use an existing precision raindrop generator, as detailed in the work of Baire et al. (2022), to verify the performance of optical NCGs that employ two different measuring principles. During laboratory tests, drops ranging from 0.6 to 5 mm in diameter were released from a height of 1.2 m over the instrument sensing area. At least 50 drops were generated for each combination of drop diameter and gauge tested. The generator independently measured the diameter and fall velocity of each released drop using a photogrammetric approach, providing a traceable reference for the calibration. The percentage errors for both the measured drop size and fall velocity were computed by comparing gauge measurements against the reference drop, either drop by drop (when the gauge provides the raw data) or in terms of Particle Size and Velocity Distribution (PSVD) matrix (for all gauges). Additionally, by assuming a literature Drop Size Distribution (DSD) and integrating measured and reference microphysical properties over the range of drop diameters tested, the percentage error for rainfall intensity measurements was also computed. The gauges tested show significant biases in both microphysical and integral properties, with the latter being larger than what is generally expected from traditional catching gauges.

The development of the precision raindrop generator was funded as part of the activities of the EURAMET project 18NRM03 “INCIPIT Calibration and Accuracy of Non-Catching Instruments to measure liquid/solid atmospheric precipitation”. The project INCIPIT has received funding from the EMPIR programme co-financed by the Participating States and from the European Union’s Horizon 2020 research and innovation programme. Laboratory testing of NCGs was carried out in the framework of the Italian national project PRIN2022MYTKP4 “Fostering innovation in precipitation measurements: from drop size to hydrological and climatic scales”.

References:

Lanza L.G. and co-authors, 2021: Calibration of non-catching precipitation measurement instruments: a review. J. Meteorological Applications, 28.3(2021):e2002.

Baire, Q and co-authors, 2022: Calibration uncertainty of non-catching precipitation gauges. Sensors, 22(17), 6413.

How to cite: Chinchella, E., Cauteruccio, A., and Lanza, L. G.: Laboratory calibration of non-catching rain gauges using a precision raindrop generator, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11487, https://doi.org/10.5194/egusphere-egu24-11487, 2024.

Rainfall simulators are essential tools for geoscientific and hydrological research, e.g. water erosion processes, throughfall phenomenon, interception etc. They allow the creation of suitable and reproducible experimental conditions providing a large amount of information. However, in certain situations, e.g. the soil splash phenomenon, other research methods are needed to study the basic processes and mechanisms on a smaller scale, i.e. concerning the interaction of single drops. In such a case, single drop measurements used with raindrop generators can be a good complementary tool for rainfall simulators. They provide complete understanding and description of the investigated phenomenon.

The aim of this study was to present selected measurement methods based on the single drop methodology which are used to investigate splash erosion and surface deformation, interaction of drops with leaves or conifers, and microorganism transportation. These include: a) a set of high-speed cameras with PTV (Particle Tracking Velocimetry) software used to identify, track, and characterize the splashed particles and water droplets; b) splash cup measurements for the determination of the mass ratio of splashed particles during the raindrop splash phenomenon; c) a 3D surface scanner and microtomography for the description of surface deformation after the drop impact; d) a laser diffraction method and light microscopy for the determination of the size of splashed particles; e) IRMS (Isotope-ratio mass spectrometry), i.e., deuterium-labelled water used to the define the origin of the splashed water.

This work was partly financed from the National Science Centre, Poland; project no. 2022/45/B/NZ9/00605.

References:

Beczek M., Ryżak M., Sochan A., Mazur R., Polakowski C., Hess D., Bieganowski A.: Methodological aspects of using high-speed cameras to quantify soil splash phenomenon. GEODERMA 378, 2020

Mazur R., Ryżak M., Sochan A., Beczek M., Polakowski C., Przysucha B., Bieganowski A.: Soil deformation after one water-drop impact – The effect of texture and soil moisture content. GEODERMA 417, 2022

Ryżak M., Beczek M., Mazur R., Sochan A., Gibała K., Polakowski C., Bieganowski A.: The splash of a single water drop on selected coniferous plants. Forest Ecology and Management 541, 121065, 2023

How to cite: Beczek, M., Ryżak, M., Gibała, K., Mazur, R., Sochan, A., Polakowski, C., Beczek, T., and Bieganowski, A.: Supplementing rainfall simulator studies with single drop measurements, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-338, https://doi.org/10.5194/egusphere-egu24-338, 2024.

The estimation of sheet flow velocities is crucial to understanding and modelling the dynamics of surface flow processes. When direct flow velocity measurements are not feasible, the use of velocity tracers can be a valuable tool. Recent studies have shown that fluorescent quinine-based tracer can be used to estimate sheet flow surface velocities over various soil and urban surfaces under low luminosity conditions, when exposed to ultraviolet light. In this study, a quinine solution was used to test the applicability of this tracer to estimating the velocity of sheet flow disturbed by rainfall with different intensities. For this purpose, a series of laboratory experiments using a soil flume and a rainfall simulator were conducted to study flows under simulated rainfall. Several hydraulic conditions were explored. The rainfall simulator included a downward-oriented full-cone nozzle from Spraying Systems Co. The nozzle was positioned at an average height of 2.5 m from the geometric centre of the flume’s soil surface, with a spray angle of 90°. The working pressure on the nozzles was kept approximately constant at 50 kPa, producing rainfall at a maximum intensity of 150 mm h^-1 just below the nozzle, with average drop sizes of approximately 1.7 mm. Flow velocities were estimated by injecting a quinine solution into the sheet flow. By tracking the leading-edge of the tracer plume and calculating the travel distance of the tracer’s leading edge over a certain time lapse, the surface velocity of the flow was evaluated. The results show that for high rainfall intensities, the disturbance of the water surface by the rainfall drops affected the visibility of the tracer and, thus, the ability to accurately estimate flow velocities using this tracer technique.

How to cite: P. de Lima, I., Zehsaz, S., and L.M.P. de Lima, J.: Testing the use of a fluorescent quinine-based tracer for estimating velocities of sheet flow under simulated rainfall: laboratory experiments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13300, https://doi.org/10.5194/egusphere-egu24-13300, 2024.

Rainfall simulators have been used for research of soil erosion by water for many years. Scientific teams around the world own a variety of different devices. In the case of comparing the results of several teams, the problem is the rainfall characteristics of different devices and therefore different input parameters. In this contribution, 3 devices were compared: a small rainfall simulator of the CTU, a small rainfall simulator of Tubingen University, and a laboratory rainfall simulator of the CTU. A laser diffractometer (Thies Clima Laser Precipitation Monitor 5.4110) was used to determine the kinetic energy (KE) and rainfall intensity and splash cups filled with sand (Tubingen Splash Cups, designed by Scholten et al., 2011) were used to compare the methods of the kinetic energy measurement. On each device, measurements were made on a plot with area 1 x 1 metre at nine positions with a rainfall intensity set at 60 mm h^-1.

Significant differences among the devices were observed using the laser disdrometer. Small rainfall simulator of Tubingen University achieving a KE of approximately 2.5 J m^-2 mm^-1, small simulator of the CTU a KE of approximately 5.5 J m^-2 mm^-1, and the laboratory simulator of the CTU a KE of approximately 8 J m^-2 mm^-1. The kinetic energies obtained by the splash cups did not reach the values produced by the laser diffractometer. During the experiments, local irregularities in rainfall were observed associated with different types of nozzles and different simulator constructions. The splash cups (46 mm in size) allowed one to measure exact locations proving that locally KE can reach much higher values.

The experiments proved that the differences among different simulator constructions can greatly affect the results of the experiments performed, and the method of assessing the rainfall characteristics can help to understand the real functioning of each device.

This research was supported by the research projects QK22010261, Mobility 8J23DE006, and by the Grant Agency of the CTU in Prague SGS23/155/OHK1/3T/11.

How to cite: Neumann, M., Seitz, S., Krasa, J., Falcao, R., and Dostal, T.: Comparison of Kinetic Energies of Different Spraying Systems, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16564, https://doi.org/10.5194/egusphere-egu24-16564, 2024.

Our aim is to compile a methodology for verifying the soil protection effect of various crop cultivation technologies directly in operating conditions and to design and verify such methods of anti erosion protection together with farmers. The methods should be effective, environmentally friendly, and should not endanger the competitiveness of Czech agriculture. The CTU in Prague, together with the Research Institute for Soil and Water Conservation, has been using a rainfall simulator of 8m plot length (16 m²) for soil loss ratio and C-factor estimation since 2015, putting together a database of several hundreds of representative measurements (Stasek et al., 2023).

To be able to test different technologies directly at fields in different field conditions, the simulator construction was modified to portable construction of 1m² plot size. During 2023 both simulators were compared in the field, especially in cultivated fallow conditions, but also for initial crop stages. Technically to be able to operate in field and use limited amount of water while reaching high enough kinetic energy and rainfall uniformity, the construction uses overflow box capturing and recycling water that would be sprayed outside of the measured plot (Kavka et al., 2018). One of the advantages of the 8m plot length was that several nozzles with overlapping spraying cones still reach higher kinetic energies than a single-nozzle construction. What we investigated is that rill evolution is visible in 8 m long plot in fallow conditions, while for 1 m plot length, mostly only interril erosion is prevailing.  For 1 mm.minute^-1 rainfall intensity both constructions reach similar runoff rates after ca 10 minutes of the simulation when starting with fully saturated conditions (0.9 litre per minute for large simulator, 0.85 litre per minute for small simulator using the same nozzle type). On the other hand, the sediment transport values at smaller plot size reach only 63% on average (0.0110 versus 0.0175 kg.minute^-1). As expected, the variability of sediment transport is higher in between replications on the smaller plot size, due to the greater influence of small surface irregularities, or due to the greater influence of preferential pathways in both surface runoff and infiltration. The contribution presents ways of standardising smaller rainfall simulator data using previous datasets obtained by larger-scale simulations.

Data were obtained from the NAZV QK22010261, Mobility 8J23DE006, H2020Tudi No 101000224, and by the CTU Grant Agency in Prague No. SGS23/155/OHK1/3T/11.

How to cite: Krasa, J., Dostal, T., Neumann, M., and Mistr, M.: Using Rainfall Simulators to Assess New Soil Protection Technologies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20712, https://doi.org/10.5194/egusphere-egu24-20712, 2024.

Over the past years studies (e.g., Hänsel et al. 2016 or Yang et al. 2021) have shown the feasibility of camera-based soil erosion assessment. This cost-efficient and non-invasive photogrammetric approach is a valuable tool to meassure soil surface changes (Balaguer-Puig et al., 2018). A challenging aspect nevertheless represents the masking of the sediment yield by surface lowering processes such as soil consolidation and compaction (Ehrhardt et al. 2022). Based on the camera elevation changes and measured field observations, we developed an approach to estimate these masking effects in the beginning of rainfall events and approximate a correction function.

We conducted ten rainfall simulations at plots with 3 m length and 1 m width on agricultural slopes. The runoff and sediment concentration were measured at the plots outlet, while a time-lapse camera system surrounding the plot took images every few seconds. We furthermore collected data on soil bulk density, soil moisture, grain size distribution, total organic carbon, slope steepness, surface cover and surface roughness. To describe the changes of the soil surface at the beginning of the rainfall events, dominated by the masking effects, S-shaped curves were fitted via non-linear regression for each rainfall experiment. We then used the variables of those functions as well as the field observations as input values for an adjustment to estimate masking effects at the beginning of rainfall simulations as functions of soil and plot characteristics.

The best results were achieved using four observations: grain size distribution, slope, bulk density and total carbon content. Our approach shows the potential to disentangle soil surface changes due to erosion and non-erosion processes at the onset of rainfall events. While the model worked well for most of the rainfall simulations, predictions were challenging for those events with strongly varying field observations. Especially difficult were those simulations conducted on freshly tilled soils. They showed high elevation changes at the beginning of the event that had great potential for soil consolidation and thus the mixed signals regarding the different processes were not separable by our approach. Nevertheless our study showed potential to increase the informative value of camera-based soil erosion measurements on agricultural fields.

References

Balaguer-Puig, M.; Marqués-Mateu, Á.; Lerma, J.L.; Ibáñez-Asensio, S. Quantifying small-magnitude soil erosion: Geomorphic change detection at plot scale. Land Degrad Dev 2018, 29, 825-834, doi:10.1002/ldr.2826.

Ehrhardt, A.; Deumlich, D.; Gerke, H.H. Soil Surface Micro-Topography by Structure-from-Motion Photogrammetry for Monitoring Density and Erosion Dynamics. Front. Environ. Sci. 2022, 9, doi:10.3389/fenvs.2021.737702.

Hänsel, P.; Schindewolf, M.; Eltner, A.; Kaiser, A.; Schmidt, J. Feasibility of High-Resolution Soil Erosion Measurements by Means of Rainfall Simulations and SfM Photogrammetry. Hydrol 2016, 3, 38, doi:10.3390/hydrology3040038.

Yang, Y.; Shi, Y.; Liang, X.; Huang, T.; Fu, S.; Liu, B. Evaluation of structure from motion (SfM) photogrammetry on the measurement of rill and interrill erosion in a typical loess. Geomorphology 2021, 385, 107734, doi:10.1016/j.geomorph.2021.107734.

How to cite: Epple, L., Grothum, O., Bienert, A., and Eltner, A.: An empirical approach to separate camera-based elevation change measurements due to sediment yield from other soil erosion masking processes  , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8795, https://doi.org/10.5194/egusphere-egu24-8795, 2024.

Measuring runoff formation on soil surfaces by rainfall simulators predominantly provide lumped values without spatiotemporal information in regard to water dynamics (e.g., water ponding timing and connectivity).  Understating spatial and temporal variations of water storage on soil surface is key to assess hydrological connectivity and runoff generation. Furthermore, it is very relevant for erosion studies. Computer vision and deep learning has presented state-of-the-art results in environmental sciences, for instance to segment water using cameras as gauges or performing flood mapping with remote sensing images. However, automatic mapping of water forming on soil surfaces due to rainfall is very challenging because the water area is considerably smaller and water ponds present complex shapes and similar color characteristics to the soil itself, which is a challenge for deep learning models. The aim of this study is to assess the potential of computer vision and deep learning to estimate water ponding timing, connectivity and runoff formation behavior during rainfall simulations, with emphasis on data imbalance and label uncertainty.

We conducted rainfall simulations at three different soil erosion plots with different soil and tillage caracteristics. Runoff was measured at the plot outlet. We collected time lapse images from the plot surface. And ground control points for model scaling were measured with a total station. To train the deep learning models, we manually labeled a selected set of images from all the plot images to derive binary masks (i.e., water and background). We trained three different convolution neural networks (CNN) and further considered techniques that take class imbalance and label uncertainty into account. Eventually, we assess the performance of ensemble models. We applied the best model on the whole set of time lapse images and measured the water pixel area and pond connectivity in terms of connected components. 

Our findings suggest that considering class imbalance and label uncertainty is key to reach satisfactory segmentation performance, being more important than the model architecture. Furthermore, ensemble models result in better performance when compared to single models. By comparing the measured discharge and the water area derived from the best deep learning model, we can observe different characteristics of the runoff formation related to distinct ponding and intensity of ponding and connectivity. Our approach presents an innovative visual and automatic observation option to quantify the water pond formation and its spatial temporal development. It is a step towards a better understanding of the runoff generation.

How to cite: Zamboni, P., Lenz, J., Wöhling, T., and Eltner, A.: Water ponding timing, spatial distribution, and connectivity on soil surfaces measured by time-lapse imagery processed with deep learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13931, https://doi.org/10.5194/egusphere-egu24-13931, 2024.

Small-scale field rainfall simulators provide scientists with a tool to investigate complex interconnections between landcover and soil erosion experimentally. In particular, specific effects of vegetation such as plant structure or traits on sediment translocation are of key interest in erosion studies. A main feature of portable rainfall simulators is the formation of repeatable precipitation patterns with a kinetic energy corresponding to natural rainfall events at different locations in the field. Despite not measuring the whole process chain of water erosion, they assist to shed light on individual influences on sediment transport with an enhanced number of replications and thus adding to field measurements under natural rainfall.

In this context, the Tübingen Rainfall Simulator (TRS, single-nozzle, <1-2 m²) has been used in the last two decades to investigate the effect of plant diversity, individual plant species as well as fauna on soil erosion in different forest and agricultural ecosystems. Results show among others, that higher forest vegetation does often not show an erosion-reducing effect and the kinetic energy of rainfall in young forest plantations can exceed freefall kinetic energy several fold. Impacts on sediment transport are strongly species-specific and depending on individual plant traits such as plant height, height of the first branch, branch angles or leaf sizes and shapes. Therefore, surface-near soil covering vegetation layers and contained mesofauna play a larger role than expected. Important reducing impacts can be initiated by biological soil crusts as a pioneer stage after vegetation disturbances, which also show severe impacts on water fluxes and infiltration in woodlands. Furthermore, these results from forestry are transferable to crop production and agriculture, where a positive impact of modern organic farming systems with short fallow periods and reduced soil-turning techniques on soil erosion control can be underlined.

In summary, portable simulator systems have proven reliable even under difficult operating conditions and could be successfully used to gather data sets with a high number of data points and to supplement large-scale erosion studies. They therefore help answering fundamental questions on the principal effects of vegetation on sediment translocation. For a better comparability of different studies and to further widen existing data sets, a harmonization of different field measurement approaches would be desirable.

How to cite: Seitz, S., Gall, C., Riveras-Muñoz, N., Song, Z., and Scholten, T.: Investigating effects of different vegetation layers on soil erosion with a portable rainfall simulator, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3431, https://doi.org/10.5194/egusphere-egu24-3431, 2024.