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Tasks which require information about energy characteristics of rains and methods for acquiring this information are briefly reviewed. A technique is suggested for estimating the kinetic energy transferred by hydrometeors based on microstructural characteristics of rainfall obtained with an OPTIOS optical precipitation gage. The technique is tested with measurement data received during a heavy rainfall occurred in Tomsk on July 22, 2023. The influence of different microstructural parameters on the amount of kinetic energy brought by raindrops to the underlying surface is analyzed. The results are compared with the values obtained by simplified methods. It is concluded that the capabilities of the optical precipitation gage make it a useful tool for solving tasks where accurate assessments of rainfall energy characteristics are required. [ABSTRACT FROM AUTHOR]

[Objective] To investigate the influence of rainfall energy and initial moisture content on the mechanism of soil aggregate splashing erosion. [Methods] The typical cultivated black soil in northeast China was selected as the research object. Artificial simulated rainfall experiments were conducted to explore the splashing erosion characteristics of soil aggregates with varying initial moisture content, rainfall energy, and initial particle size of aggregates. [Results] (1) The splash erosion of the four kinds of black soil aggregates with initial particle size was highest when the initial soil moisture level was 4%, and the splash erosion of the aggregates with an initial particle size

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The rainfall kinetic energy, which affects soil erosion processes, can be calculated by the drop-size distribution (DSD) and falling velocity. This study presents the outcomes derived by the DSDs recorded with the same optical disdrometer in two experimental areas, located in Sicily (southern Italy). Specifically, the DSDs were recorded from March 2017 to December 2019 at Sparacia and from June 2006 to April 2014 at Palermo. The aims of this paper are both to compare the DSDs for the two sites and to evaluate the applicability of Gamma theoretical distribution. Moreover, the relations of rainfall kinetic power vs. rainfall intensity are assessed. Differences in DSDs, especially for rainfall intensity I lower than 100 mm h−1, are detected, while they are less evident for the highest I values. The kinetic power per unit volume of rainfall varies between the two sites and can be considered roughly coincident only for I higher than 100 mm h−1. The observed kinetic power-rainfall intensity relations are not well described by the equations by Wischmeier and Smith and Brown and Foster. Finally, the reliability of a theoretical relationship for estimating the kinetic power by I and the median volume diameter D0 is positively tested for the Palermo dataset, while it is found to be reliable only for D0 greater than 0.17 cm for the Sparacia dataset. [ABSTRACT FROM AUTHOR]

Calculating rainfall erosivity, which is the capacity of rainfall to dislodge soil particles and cause erosion, requires the measurement of the rainfall kinetic energy (KE). Direct measurement of KE has its own challenges, owing to the high cost and complexity of the measuring instruments involved. Consequently, the KE is often approximated using empirical equations derived from rainfall intensity (Ir) inputs in the absence of such instruments. However, the KE–Ir equations strongly depend on local climate patterns and measurement methods. Therefore, this study aims to compare and evaluate the efficacy of 27 KE–Ir equations with observed data. Based on a re-analysis, we also propose an exponential KE–Ir equation for the entire Korean site, and the spatial distribution of its parameter in the equation is also discussed. In this investigation, we used an optical disdrometer (OTT Parsivel2) to gather data in Sangju City (Korea) between June 2020 and December 2021. The outputs of this study are shown as follows: (1) The statistically most accurate estimates of KE expenditure and KE content in Sangju City are obtained using power-law equations given by Sanchez-Moreno et al. and exponential equations published by Lee and Won, respectively. (2) The suggested KE–Ir equation applied to the entire Korean site exhibits a comparable general correlation with the observed data. The parameter maps indicate a high variance in geography. [ABSTRACT FROM AUTHOR]

Rain simulation is a method widely used in detecting hydrological and erosional processes. Most portable samples have inconvenient and challenging transport, high water consumption, and energy supply. The objective of this study was to design and test a rainfall simulator characterized by the following innovative features: 1) The simulator is easy to be transported and assembled in the field, thereby allowing the necessary experimental replicates, 2) Applicability on different slopes. The first calibration step regarded the spatial distribution of rainfall, the stability of the rainfall intensity, and the reproducibility of the rainfall intensities over time (among successive experiments). Next, the drop size distribution (DSD) and the related rainfall characteristics (median volumetric drop diameter D50 and mean kinetic energy per unit area and unit depth) were evaluated by the flour pellet method. A fluorescent tracer method is used to measure the velocity of falling drops. According to the findings, the Christiansen uniformity coefficient (Cu) of this rainfall simulator varies from 77-87% for rainfall intensities of 35-75 mmh-1. The best rainfall distribution has been achieved for rainfall intensities of 55 and 75 mmh-1, with rain droplet sizes ranging from 0.6 to 3.8 mm. The raindrop velocity was also measured by photo-shooting and revealed a velocity rate of 2.7-5.7 ms-1. The system allows rainfall simulation on the fields and under laboratory conditions. Moreover, erosion, runoff, and sediment production under natural and intact soil conditions can also be examined with the highest possible accuracy

When raindrops collide with the topsoil surface, they cause soil detachment, which can be estimated by measuring the kinetic energy (KE) of the raindrops. Considering their direct measurements on terrestrial surfaces are challenging, empirical equations are commonly utilized for estimating the KE from rainfall intensity (Ir), which has a great influence on soil loss and can be easily obtained. However, establishing the optimal relationship between KE and Ir is difficult. In this study, we used a laser-based instrument (OTT Parsivel2 Optical disdrometer) to collect datasets in Sangju City (South Korea) between June 2020 and December 2021 to examine the characteristics of KE–Ir relationships. We derived two different expressions for KE–Ir: KE expenditure (KEexp; J m−2h−1) and KE content (KEcon; J m−2mm−1), using 37 rainfall events. Subsequently, the 37 rainfall events were categorized into three groups based on the magnitude of the mean rainfall intensity of each event. Overall, the KE values estimated through the equations derived based on 37 events were higher than those estimated by the equations derived based on the three rainfall event groups. Our findings should facilitate the development of more suitable physics-based soil erosion models at event scales.

The summer season raindrop size distribution (DSD) characteristics and their important applications, based on a PARSIVEL2 disdrometer installed in Zhaosu over the western Tianshan Mountains, China, in 2020–2021 are studied. Our analysis reveals that, for total rainfall and different rainfall types, the DSD in Zhaosu follows the normalized gamma distribution model, and convective rainfall has a higher raindrop concentration than stratiform rainfall at all diameters. For stratiform rainfall, the mean value of mass-weighted mean diameter (Dm) is lower than that of convective DSD, while the mean value of normalized intercept parameter (log10 Nw) is higher than that of convective DSD, and the summer season convective rainfall in Zhaosu is continental convective rainfall according to the conventional classification, which is characterized by relatively larger Dm and lower log10 Nw values. The derived µ–∧ relation in Zhaosu exhibits some differences from those reported in eastern, southern, and northern China and the Tibetan Plateau. Furthermore, derived Z–R relations for stratiform and convective rainfall in Zhaosu are compared with those from other regions. Analysis shows that the empirical relation of Z = 300R1.4 (widely used), strongly overestimates the R of convective precipitation in Zhaosu. The C-band polarimetric radar rainfall estimation relations are derived, and the R(Zh,Zdr) and R(Kdp,Zdr) relations perform the best in quantitative precipitation estimation. Moreover, the empirical Dm–Zku and Dm–Zka relations are derived, which are beneficial to the improvement of rainfall retrieval algorithms of the GPM DPR. Lastly, rainfall kinetic energy relations proposed in this study can be used to better assess rainfall erosivity. The empirical relationships of DSD evaluated in this study provide an opportunity to (1) improve rainfall retrieval algorithms for both ground-based and remote sensing radars and to (2) enhance rainfall kinetic energy estimates in rainfall erosivity studies based on disdrometer and GPM DPR. [ABSTRACT FROM AUTHOR]

Precipitation is a key driver of leading-edge erosion of wind turbine blades, which leads to a loss in annual energy production and high cost for repair of wind turbines. Precipitation type, drop size and their frequency are relevant parameters, but not easily available. Reflectivity-Rain Rate (Z‑R) relationships as well as annual sums of rainfall amount and rainfall kinetic energy potentially could be used to estimate leading-edge erosion. Although Z‑R relationships and amounts are known for several places, their spatial variation and dependence on weather types is unknown in the North Sea and Baltic Sea area. We analysed time series of multiple disdrometers located on the coast of the North Sea and Baltic Sea to characterize the variation and weather-type dependence of the Z‑R relationship, precipitation type, rainfall amount and kinetic energy.The Z‑R relationship as indication for the mean drop-size distribution showed small variations within different locations, but had a large variability for specific, but rare weather types. Only the precipitation types snow and hail showed some tendencies of weather-type dependence. Rainfall amount and rainfall kinetic energy were higher for stations in the eastern part of the North Sea compared to the western part and the Baltic Sea. Highest values were related to advection from the West. Overall, variations with location and weather type were found. These results will need to be considered in leading-edge erosion modelling and site assessment.

Herein, the raindrop size distribution (DSD) and rainfall microphysics characteristics are investigated at multiple stations within the Yangtze River Delta (YRD) under two air pollution conditions. Raindrop data from 14 Thies Clima Laser Precipitation Monitor disdrometers spanning approximately 2 years were employed together with corresponding air pollution data. Rain gauge data and several types of meteorological data were also used. The DSD characteristics were found to vary across the YRD; thus, we compiled DSD‐based demarcations between convective rain and stratiform rain at each site. During summer, the average mass‐weighted mean drop diameter parameter value was higher by a mean 20%, and the average normalized intercept parameter value was lower by a mean 12% in polluted atmosphere conditions for both convective rain and stratiform rain, as well as for different rainfall intensity classes. The differences in atmospheric conditions between clear and polluted air conditions partially account for the uncertainties in the DSD characteristics. Air pollution resulted in uncertainty in the shape parameter‐slope parameter relationship and in the rainfall kinetic energy‐rainfall intensity (KE‐R) relationship. The air pollution index can be integrated into the KE‐R relationship to improve the KE simulation accuracy. In addition, air pollution causes some uncertainty in the radar reflectivity‐rainfall intensity (Z‐R) relationship, while the acceptable deviation of the Z‐R relationship did not significantly impact the accuracy of rainfall simulations. This study improves our understanding of DSD and provides a comprehensive overview of the relationship between air pollution and rainfall microphysics for a typical urban agglomeration area. Plain Language Summary: This study investigates the relationship between air pollution and rainfall microphysics at several stations within the Yangtze River Delta (YRD). Rainfall microphysics were found to vary across the YRD. Moreover, summer raindrop characteristics differ between low and high air pollution conditions. That is, compared with a clean atmosphere, a polluted atmosphere results in larger average raindrop size and lower average raindrop concentration. Air pollution results in slight uncertainty in radar rainfall estimation, while causing significant uncertainty when calculating rainfall erosivity. This study provides a comprehensive understanding of rainfall microphysics in a typical urban agglomeration area. Key Points: The characteristics of rainfall microphysics across the Yangtze River Delta are relatively uncertainLarger average raindrops and lower average number concentrations are observed during high pollution in summerAir pollution causes high uncertainty of rainfall kinetic energy calculations and low uncertainty of radar rainfall simulations [ABSTRACT FROM AUTHOR]

The rainfall kinetic energy, which affects soil erosion processes, can be calculated by the drop-size distribution (DSD) and falling velocity. This study presents the outcomes derived by the DSDs recorded with the same optical disdrometer in two experimental areas, located in Sicily (southern Italy). Specifically, the DSDs were recorded from March 2017 to December 2019 at Sparacia and from June 2006 to April 2014 at Palermo. The aims of this paper are both to compare the DSDs for the two sites and to evaluate the applicability of Gamma theoretical distribution. Moreover, the relations of rainfall kinetic power vs. rainfall intensity are assessed. Differences in DSDs, especially for rainfall intensity I lower than 100 mm h−1, are detected, while they are less evident for the highest I values. The kinetic power per unit volume of rainfall varies between the two sites and can be considered roughly coincident only for I higher than 100 mm h−1. The observed kinetic power-rainfall intensity relations are not well described by the equations by Wischmeier and Smith and Brown and Foster. Finally, the reliability of a theoretical relationship for estimating the kinetic power by I and the median volume diameter D0 is positively tested for the Palermo dataset, while it is found to be reliable only for D0 greater than 0.17 cm for the Sparacia dataset.

Calculating rainfall erosivity, which is the capacity of rainfall to dislodge soil particles and cause erosion, requires the measurement of the rainfall kinetic energy (KE). Direct measurement of KE has its own challenges, owing to the high cost and complexity of the measuring instruments involved. Consequently, the KE is often approximated using empirical equations derived from rainfall intensity (Ir) inputs in the absence of such instruments. However, the KE–Ir equations strongly depend on local climate patterns and measurement methods. Therefore, this study aims to compare and evaluate the efficacy of 27 KE–Ir equations with observed data. Based on a re-analysis, we also propose an exponential KE–Ir equation for the entire Korean site, and the spatial distribution of its parameter in the equation is also discussed. In this investigation, we used an optical disdrometer (OTT Parsivel2) to gather data in Sangju City (Korea) between June 2020 and December 2021. The outputs of this study are shown as follows: (1) The statistically most accurate estimates of KE expenditure and KE content in Sangju City are obtained using power-law equations given by Sanchez-Moreno et al. and exponential equations published by Lee and Won, respectively. (2) The suggested KE–Ir equation applied to the entire Korean site exhibits a comparable general correlation with the observed data. The parameter maps indicate a high variance in geography.

The summer season raindrop size distribution (DSD) characteristics and their important applications, based on a PARSIVEL2 disdrometer installed in Zhaosu over the western Tianshan Mountains, China, in 2020–2021 are studied. Our analysis reveals that, for total rainfall and different rainfall types, the DSD in Zhaosu follows the normalized gamma distribution model, and convective rainfall has a higher raindrop concentration than stratiform rainfall at all diameters. For stratiform rainfall, the mean value of mass-weighted mean diameter (Dm) is lower than that of convective DSD, while the mean value of normalized intercept parameter (log10 Nw) is higher than that of convective DSD, and the summer season convective rainfall in Zhaosu is continental convective rainfall according to the conventional classification, which is characterized by relatively larger Dm and lower log10 Nw values. The derived µ–∧ relation in Zhaosu exhibits some differences from those reported in eastern, southern, and northern China and the Tibetan Plateau. Furthermore, derived Z–R relations for stratiform and convective rainfall in Zhaosu are compared with those from other regions. Analysis shows that the empirical relation of Z = 300R1.4 (widely used), strongly overestimates the R of convective precipitation in Zhaosu. The C-band polarimetric radar rainfall estimation relations are derived, and the R(Zh,Zdr) and R(Kdp,Zdr) relations perform the best in quantitative precipitation estimation. Moreover, the empirical Dm–Zku and Dm–Zka relations are derived, which are beneficial to the improvement of rainfall retrieval algorithms of the GPM DPR. Lastly, rainfall kinetic energy relations proposed in this study can be used to better assess rainfall erosivity. The empirical relationships of DSD evaluated in this study provide an opportunity to (1) improve rainfall retrieval algorithms for both ground-based and remote sensing radars and to (2) enhance rainfall kinetic energy estimates in rainfall erosivity studies based on disdrometer and GPM DPR.

Abstract The understanding of large‐scale rainfall microphysical characteristics plays a significant role in meteorology, hydrology and natural hazards managements. Traditional instruments for estimating raindrop size distribution (DSD), including disdrometers and ground dual‐polarization radars, are available only in limited areas. However, the development of space‐based radars and mesoscale numerical weather prediction models would allow for DSD estimation on a large scale. This study investigated the performance of the weather research and forecasting (WRF) model and the global precipitation measurement mission (GPM) dual‐frequency precipitation radar for DSD retrieval under different conditions. The DSD parameters (Dm and Nw), rain rate (R), rainfall kinetic energy (KE) and radar reflectivity (Z) were estimated in Chilbolton, United Kingdom, by using long‐term disdrometer observations for validation. The rainfall kinetic energy–rain rate (KE–R) and radar reflectivity–rain rate (Z–R) relationships were explored using a disdrometer, the WRF model and GPM. It was found that the DSD parameter distribution trends of the three approaches are similar although the WRF model has larger Dm and smaller Nw values. In terms of the rainfall microphysical relationship, GPM performs better when both Ku‐ and Ka‐band precipitation radars (KuPR and KaPR) observe precipitation simultaneously (R > 0.5 mm h−1), while the WRF model shows high accuracy in light rain (R

The understanding of large‐scale rainfall microphysical characteristics plays a significant role in meteorology, hydrology and natural hazards managements. Traditional instruments for estimating raindrop size distribution (DSD), including disdrometers and ground dual‐polarization radars, are available only in limited areas. However, the development of space‐based radars and mesoscale numerical weather prediction models would allow for DSD estimation on a large scale. This study investigated the performance of the weather research and forecasting (WRF) model and the global precipitation measurement mission (GPM) dual‐frequency precipitation radar for DSD retrieval under different conditions. The DSD parameters (Dm and Nw), rain rate (R), rainfall kinetic energy (KE) and radar reflectivity (Z) were estimated in Chilbolton, United Kingdom, by using long‐term disdrometer observations for validation. The rainfall kinetic energy–rain rate (KE–R) and radar reflectivity–rain rate (Z–R) relationships were explored using a disdrometer, the WRF model and GPM. It was found that the DSD parameter distribution trends of the three approaches are similar although the WRF model has larger Dm and smaller Nw values. In terms of the rainfall microphysical relationship, GPM performs better when both Ku‐ and Ka‐band precipitation radars (KuPR and KaPR) observe precipitation simultaneously (R > 0.5 mm h−1), while the WRF model shows high accuracy in light rain (R < 0.5 mm h−1). The fusion of GPM and WRF model is recommended for the improved understanding of rainfall microphysical characteristics in ungauged areas. [ABSTRACT FROM AUTHOR]

Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The microphysical features of the typhoon (TY) and non-typhoon (NTY) rainfall in summer seasons are analyzed using long-term (2004 to 2016) data from the impact disdrometer installed in north Taiwan. The RSD stratified based on rainfall rate showed distinct RSD characteristics between TY and NTY rainfall. More (less) number of small (big) size raindrops are noticed in TY rainfall than NTY rainfall. RSD features in terms of gamma parameters are studied for these two weather regimes. The mass-weighted mean diameter (Dm) values are higher in NTY than TY rainfall, and an inverse behavior is observed for the normalized intercept parameter (Nw). Even after separating the rainfall regimes into convective and stratiform type, a large Dm is found in NTY compared to TY precipitation. Distinct variations in Z -R, Dm-R, Nw- R, KE-R, and KE-Dm relations are noticed between TY and NTY rainfall. Possible mechanisms responsible for the RSD variations between TY and NTY are discussed using reanalysis, remote13 sensing, and ground-based radar datasets. [ABSTRACT FROM AUTHOR]

Optical disdrometers can be used to estimate rainfall erosivity; however, the relative accuracy of different disdrometers is unclear. This study compared three types of optical laser-based disdrometers to quantify differences in measured rainfall characteristics and to develop correction factors for kinetic energy (KE). Two identical PWS100 (Campbell Scientific), one Laser Precipitation Monitor (Thies Clima) and a first-generation Parsivel (OTT) were collocated with a weighing rain gauge (OTT Pluvio2) at a site in Austria. All disdrometers underestimated total rainfall compared to the rain gauge with relative biases from 2% to 29%. Differences in drop size distribution and velocity resulted in different KE estimates. By applying a linear regression to the KE–intensity relationship of each disdrometer, a correction factor for KE between the disdrometers was developed. This factor ranged from 1.15 to 1.36 and allowed comparison of KE between different disdrometer types despite differences in measured drop size and velocity. [ABSTRACT FROM AUTHOR]

A localized rainfall kinetic energy (E) equation and an erosivity map were developed, and the suitability of the universal soil loss equation (USLE) for assessing the soil erosion of a non‐US region was investigated. After accurately measuring and gathering data regarding raindrop size using disdrometers in four northern Taiwan locations, this study investigated the drop size distribution under different conditions by categorizing the rainfall patterns to develop regression equations for estimating the unit volume‐specific kinetic energy (KEmm) and the unit time‐specific kinetic energy (KEtime) of northern Taiwan. Climate zoning, which is not considered in currently used designs, was then implemented along with two‐stage cluster analysis to construct a rainfall erosivity (R) distribution map using the kriging model. The binary polynomial regression function of KEtime, which had the highest correlation (R2 = 0.98), was suggested to estimate E in northern Taiwan. It was found that the pattern and intensity (I) of rainfall will slightly affect E. The climatic influence on the root mean square of the semivariogram was significant, which suggests that climate zoning can help estimate the rainfall erosivity (R). The outcomes were extended to estimate R in areas without rainfall stations. [ABSTRACT FROM AUTHOR]

The splash erosion-induced soil aggregate turnover is important to understand the mechanisms of soil degradation and soil organic carbon (SOC) cycling. However, the relationship between aggregate turnover and rainfall impact has not been explored directly because of methodological difficulties. The soil samples, developed from Quaternary red clay, were adopted from three land use types: natural forest (NF), garden/shrubs (AS), and abandoned meadow (AM). By using rare earth oxides to trace the transformation in soil aggregates of four size-fractions (>2 mm, large macroaggregate; 0.25–2 mm, small macroaggregate; 0.053–0.25 mm, microaggregate; <0.053 mm, silt and clay fraction), we investigated aggregate turnover based on splash experiments at four different rainfall kinetic energies (501.95, 326.00, 252.50 and 153.39 J·m−2·h−1). After splash erosion, the rare earth oxides concentrations and SOC content in different soil aggregate fractions were measured. Our results indicated that the soil aggregates mainly followed the direction of breakdown, with higher cumulative breakdown rates than formation rates. Specifically, with the rainfall kinetic energy increased to 501.95 J·m−2·h−1, the three soil samples (NF, AS, AM) exhibited the highest breakdown rates of 48.35%, 31.95% and 39.29% in large macroaggregates, respectively. Meanwhile, the formation pathway was mainly in the direction of forming small macroaggregates. Compared to soil aggregate from NF, AS and AM aggregates had higher proportion of silt and clay fraction transformed into larger aggregates. Moreover, the changes of SOC varied in aggregates during splash process. With the increase of rainfall kinetic energy, the organic matter content gradually decreased in large aggregates and microaggregates in AM and AS (P < 0.05), in contrast to a trend of first increasing and then decreasing (P < 0.05) in their small aggregates. In the clay particles, with the increase of rainfall kinetic energy, the SOC content gradually decreased in NF (P < 0.05) and fluctuated in AS, with both their organic matter content lower than before the splash test (P < 0.05). The loss of SOC in total soil was linearly related to the net breakdown rate of soil aggregates (P < 0.05, R2 =0.635). Therefore, we proposed a framework to highlight the quantitative relationship between aggregate turnover and SOC degradation under splash, which may enrich the mechanisms of soil erosion and soil degradation in the positions where erosion takes place. • Aggregate turnover is significantly accelerated by splash erosion. • Aggregate turnover rate depends on aggregate size and rainfall kinetic energy. • Soil carbon dynamics within aggregates are tightly related to aggregate breakdown. [ABSTRACT FROM AUTHOR]

Disdrometer observations obtained by an OTT Parsivel2 during the 2017 Great Hunan Flood from 1:00 a.m. LST 23 June 2017 to 4:00 a.m. LST 2 July 2017 in Changsha, Hunan Province, southern China, are analyzed to diagnose characteristics of raindrop size distribution (DSD). This event was characterized by a large number of small- to medium-sized raindrops (diameters smaller than 1.5 mm) and the mean median volume diameter (D0) is about 1.04 mm. The median values of rain rate R (1.57 mm h−1), liquid water content W (0.10 g m−3), and radar reflectivity Z (25.7 dBZ) are smaller than that of the 2013 Great Colorado Flood. This event was composed of two intense rainfall periods and a stratiform period, and notable distinctions of rainfall microphysics among the three rainfall episodes are observed. Two intense rainfall periods were characterized by widespread and intense convection rains with a surface reflectivity of 48.8~56.7 dBZ. A maximum diameter of raindrops up to 7.5 mm was observed, as well as high concentrations of small and midsize drops, resulting in large rainfall amounts during the two intense rainfall episodes. The mean radar reflectivity of 22.6 dBZ, total rainfall of 17.85 mm and the maximum raindrop of approximately 4.25 mm were observed during the stratiform rainfall episode. The composite DSD for each rainfall episode peaked at 0.56 mm but higher concentrations of raindrops appeared in the two intense rainfall episodes. The Z-R relationships derived from the disdrometer measurements reflect the unusual characteristics of DSD during the flood. As a result, the standard NEXRAD Z-R relationship (Z = 300R1.4) strongly underestimated hourly rainfall by up to 27.5%. In addition, the empirical relations between rainfall kinetic energy (KE) versus rainfall intensity (R) and mean mass diameter (Dm) are also derived using DSDs to further investigate the impacts of raindrop properties on the rainfall erosivity.

The current study summarizes the raindrop size distributions (RSDs) characteristic of the North Indian Ocean (NIO) tropical cyclones (TCs) measured with ground-based disdrometers installed at the coastal (Thiruvananthapuram, 8.5335°N, 76.9047°E) and inland (Kadapa, 14.4742°N, 78.7098°E) stations in south India. The NIO TCs observed at the coastal station showed more mid- and large-size drops (>1 mm) than the inland station. On the other hand, for both inland and coastal stations, small and mid-size drops (

A portable rainfall simulator was built for assessing runoff and soil erosion processes at interrill scale. Within this study, requirements and constraints of the rainfall simulator are identified and discussed. The focus lies on the calibration of the simulator with regard to spatial rainfall homogeneity, rainfall intensity, drop size, drop fall velocity and rainfall kinetic energy. These parameters were obtained using different methods including a Laser Precipitation Monitor. A detailed presentation of the operational characteristics is given. The presented rainfall simulator setup featured a rainfall intensity of 45.4 mm·h-1 with a spatial homogeneity of 80.4% based on a plot area of 0.64 m². Because of the comparatively low drop height (2 m), the diameter-dependent terminal fall velocity (1.87 m·s-1) was lower than benchmark values for natural rainfall. This conditioned also a reduced rainfall kinetic energy (4.6 J·m-2·mm-1) compared to natural rainfall with same intensity. These shortfalls, a common phenomenon concerning portable rainfall simulators, represented the best possible trade-off between all relevant rainfall parameters obtained with the given simulator setup. Field experiments proved that the rainfall erosivity was constant and replicable.

Soil crusts and surface roughness are properties which are highly dynamic in both space and time that change in response to biotic processes, meteorological conditions and farming operations. These factors, however, are difficult to quantify and are usually described using simplified expert-based classes. This hampers a clear identification of the controlling factors and their relation to soil erosion and sediment generation processes. The availability of new small portable multispectral cameras offers the potential to study soil surface dynamics at a high spatial and temporal resolution. The objective of this study was to analyse the relationship between soil crusting, represented by cumulative rainfall kinetic energy, and soil surface reflectance, as derived from vis-NIR multispectral imaging. We designed a series of rainfall-soil surface experiments to disentangle the effects of soil crusting on spectral reflectance factors from those related to surface micro-scale roughness. Partial least squared regression (PLSR) models were developed to predict both kinetic energy and roughness from multispectral images. We evaluated different roughness removal methods which were based on the transformation of reflectance through standard normal variate (SNV) and roughness thresholding using high resolution digital elevation models. Furthermore, we assigned the light scattering effect related to roughness in the multispectral spatial domain by calculating the inter-quantile range of the reflectance values in a kernel. Our experiments and workflow demonstrate that it is possible to model crust development, using rainfall kinetic energy as a proxy, from vis-NIR based multispectral imaging.

Abstract Splash erosion is recognized as an important process of water erosion on agricultural land, but evaluating and modelling splash detachment capacity on steep slopes using loessial soil were not fully studied. The objectives of this study are: (1) to evaluate the effects of slope gradient (S) and rainfall intensity (I) on splash detachment capacity (SDr), (2) to select the key rainfall physical parameters and hydraulic parameters affecting splash detachment capacity, (3) to establish new and more accurate experimental models between splash detachment capacity (SDr) and these key parameters on steep slopes for loess regions. The experiment was conducted at slopes of 12.23%, 17.63%, 26.8%, 36.4%, 40.4% and 46.63% under rainfall intensities of 48, 60, 90, 120, 138 and 150 mm h−1, respectively, using simulated rainfall. Results showed that the equation between splash detachment capacity (SDr) with both parameters of rainfall intensity (I) and slope gradient (S) (i.e. SDr = 0.000126 ln (0.36 S −0.3 I 1.3 − 14)) could predict SDr well with R2 = 0.85 and Nash–Sutcliffe model efficiency (NSE) = 0.71. SDr was more sensitive to rainfall intensity than to slope gradient. The rainfall kinetic energy (KE) was the key rainfall physical parameter and the mean flow depth (h) was the key hydraulic parameter affecting SDr. The equation between SDr with both parameters of KE and h (i.e. SDr = 0.000164 ln (0.0031 KE 1.13 h −0.3 − 4.5)) could satisfactorily predict SDr with R2 = 0.85 and Nash–Sutcliffe model efficiency (NSE) = 0.81. The new equations (i.e. SDr = 0.000126 ln (0.36 S −0.3 I 1.3 − 14) and SDr = 0.000164 ln (0.0031 KE 1.13 h −0.3 − 4.5)) could help in controlling water erosion in the loess region of China. Highlights • The experiments were conducted under six rainfall intensities and six slope gradients using loessial soil samples. • The key rainfall physical parameter for evaluating splash detachment capacity was revealed. • The key hydraulic parameter for evaluating splash detachment capacity was revealed. • Two reliable equations were derived for predicting splash detachment capacity. [ABSTRACT FROM AUTHOR]

Highlights • Another method was provided to determine T c of raindrop-impacted interrill flow. • T c can be calculated using power function equation of slope gradient and rainfall intensity. • Stream power together with rainfall kinetic energy can best describe T c. Abstract Interrill erosion processes typically involve such scientific issues as detachment-limited and transport-limited erosion behaviour. An accurate estimation of the sediment transport capacity ( T c ) by raindrop-impacted overland flow is critical for interrill erosion modelling and for evaluating sediment budgets under erosion-limiting conditions. Simulated rainfall experiments with rainfall intensities from 0.8 to 2.5 mm min−1 over a three-area soil pan with slope gradients from 12.7% to 46.6% were conducted to identify the transport-limited cases and determine T c by raindrop-impacted overland flow within the transport-limited systems of interrill erosion processes. Results indicated that T c increased as a power function of rainfall intensity and slope gradient ( R2 = 0.84, NSE = 0.75), and T c was more sensitive to rainfall intensity than to slope gradient. In terms of R2 and NSE , stream power was the key hydraulic parameter that influenced T c among flow velocity ( R2 = 0.64, NSE = 0.39), shear stress ( R2 = 0.53, NSE = 0.23), stream power ( R2 = 0.76, NSE = 0.52) and unit stream power ( R2 = 0.49, NSE = 0.16). The addition of rainfall physical parameters in response equations of T c in addition to hydraulic parameter, could improve an accuracy of T c modelling. Stream power combined with rainfall kinetic energy can best describe the T c of raindrop-impacted overland flow within the transport-limited system of interrill erosion processes by a power-exponent function ( R2 = 0.90, NSE = 0.72). Rainfall kinetic energy can reduce the Darcy-Weisbach resistance coefficient of raindrop-impacted overland flow and thus benefit sediment transporting. This study provides another method for directly identifying the T c of raindrop-impacted overland flow in interrill erosion processes on steep loess slopes, and points out that rainfall impacts should be particularly considered when studying T c by raindrop-impacted overland flow. [ABSTRACT FROM AUTHOR]

Abstract For bare soil conditions, the most important process driving and initiating splash and interrill erosion is the detachment of soil particles via raindrop impact. The kinetic energy of a rainfall event is controlled by the drop size and fall velocity distribution, which is often directly or indirectly implemented in erosion models. Therefore, numerous theoretical functions have been developed for the estimation of rainfall kinetic energy from available rainfall intensity measurements. The aim of this study is to assess differences inherent in a wide number of kinetic energy-rainfall intensity (KE-I) relations and their role in soil erosion modelling. Therefore, 32 KE-I relations are compared against measured rainfall energies based on optical distrometer measurements carried out at five stations of two substantially different rainfall regimes. These allow for continuous high-resolution (1-min) direct measurements of rainfall kinetic energies from a detailed spectrum of measured drop sizes and corresponding fall velocities. To quantify the effect of different KE-I relations on sediment delivery, we apply the erosion model WATEM/SEDEM in an experimental setup to four catchments of NE-Germany. The distrometer data shows substantial differences between measured and theoretical models of drop size and fall velocity distributions. For low intensities the number of small drops is overestimated by the Marshall and Palmer (1948; MP) drop size distribution, while for high intensities the proportion of large drops is overestimated by the MP distribution. The distrometer measurements show a considerable proportion of large drops falling at slower velocities than predicted by the Gunn and Kinzer (1949) terminal velocity model. For almost all rainfall events at all stations, the KE-I relations predicted higher cumulative kinetic energy sums compared to the direct measurements of the optical distrometers. The different KE-I relations show individual characteristics over the course of rainfall intensity levels. Our results indicate a high sensitivity (up to a range from 10 to 27 t ha−1) of the simulated sediment delivery related to different KE-I relations. Hence, the uncertainty associated with KE-I relations for soil erosion modelling is of critical importance. Highlights • Thirteen years of optical disdrometer measurements from five stations to derive rainfall kinetic energy • Analysis of short-term dynamics of rainfall kinetic energy during storm events of different intensity • Comparison of measured versus derived kinetic energy based on 32 rainfall kinetic energy-intensity relations • Analysis of the uncertainty in modelled soil erosion using the measured versus the derived daily/yearly rainfall erosivity [ABSTRACT FROM AUTHOR]

Soil erosion by water is affected by the rainfall erosivity, which controls the initial detachment and mobilization of soil particles. Rainfall erosivity is expressed through the rainfall intensity (I) and the rainfall kinetic energy (KE). KE–I relationships are an important tool for rainfall erosivity estimation, when direct measurement of KE is not possible. However, the rainfall erosivity estimation varies depending on the chosen KE–I relationship, as the development of KE–I relationships is affected by the measurement method, geographical rainfall patterns and data handling. This study investigated how the development of KE–I relationships and rainfall erosivity estimation is affected by the use of different disdrometer types. Rainfall data were collected in 1-min intervals from six optical disdrometers at three measurement sites in Austria, one site in Czech Republic and one site in New Zealand. The disdrometers included two disdrometers of each of the following types: the PWS100 Present Weather Sensor from Campbell Scientific, the Laser Precipitation Monitor from Thies Clima and the first generation Parsivel from OTT Hydromet. The fit of KE–I relationships from the literature varied among disdrometers and sites. Drop size and velocity distributions and developed KE–I relationships were device-specific and showed similarities for disdrometers of the same type across measurement sites. This hindered direct comparison of results from different types of disdrometers, even when placed at the same site. Thus, to discern spatial differences in rainfall characteristics the same type of measurement instrument should be used.

Soil internal forces, including electrostatic, hydration and van der Waals, play critical roles in aggregate stability, erosion, and other processes related to soil and water. However, the extent to which soil internal forces influence splash erosion during rainfall remains unclear. In the present study, we used cationic-saturated soil samples to quantitatively separate the effects of soil internal and raindrop impact forces (external) on splash erosion through simulated rainfall experiments. An electrolyte solution was employed as rainfall material to represent the combined effects of soil internal and external forces on splash erosion. Ethanol was used to simulate the sole effect of soil external force on splash erosion. The soil splash erosion rate increased with increasing rainfall kinetic energy in experiments with electrolyte solution and ethanol and was also greatly influenced by soil internal forces. Moreover, the soil splash erosion rate increased first (from 1 to 10 −2  mol L −1 ) then leveled off (from 10 −2 to 10 −4  mol L −1 ) with decreasing electrolyte concentration in the bulk solution. This finding was in agreement with the theoretical analysis of soil internal forces. The contribution rate of soil internal forces on splash erosion was >65% at a low electrolyte concentration (<10 −2  mol L −1 ) and only 3%–25% at an electrolyte concentration of 1 mol L −1 . Even though the electrolyte concentration of the soil bulk solution reached 10 −1  mol L −1 , the contribution rate of soil internal forces to splash erosion was >50%. Hence, soil internal forces exerted higher contribution to rainfall splash erosion than raindrop impact force under most field conditions. This work provides new understanding of the mechanism of soil splash erosion and establishes the possibility of controlling splash erosion by jointly regulating the soil internal and external forces. [ABSTRACT FROM AUTHOR]

This note describes the technical characteristics and the preliminary setup and calibration of a nozzle-type rainfall simulator installed at the University of Perugia's Masse experimental station. This simulator includes some innovative features, usually not present in similar low-cost instruments employed in field experiments: 1) both single and multi-nozzle operation are feasible, thus enabling the possibility to simulate variable-intensity rainfall events; 2) events are simultaneously reproduced in two identical plots (width 1 m, length 0.92 m, and slope 16%), thus obtaining two replications for each experiment; 3) the runoff volume coming from the micro-plots and the water volume falling outside the plots are both collected and conveyed to separate outlets, thus allowing an easy calculation of the infiltrated volumes and of the system efficiency. The first step of the calibration regarded the spatial distribution of rainfall, the stability of the rainfall intensity over time (within the experiment), and the reproducibility of the rainfall intensities both in space (between the two plots) and over time (among successive experiments). Next, the drop size distribution (DSD) and the related rainfall characteristics (median volumetric drop diameter D50 and mean kinetic energy per unit area and unit depth) were evaluated by the oil method for the single and some multi-nozzle applications. An effective automatic drop recognition procedure by the Fiji open-source software is proposed and illustrated. Results indicate a high uniformity of rainfall (Christiansen uniformity coefficient > 92%) in both single and multi-nozzle operation for both plots. The reproducibility of experiments over short time intervals and under similar environmental conditions is satisfactory (coefficient of variation of mean intensity < 3%). Comparing initial and final rainfall intensity values, a slight decrease was observed within each experiment (about 2% on average). Some systematic differences in rainfall intensity were also detected between the plots. The analysis of both the intensity and the DSD in the multi-nozzle operation indicated the presence of some interference among the individual sprays when larger nozzles are simultaneously activated. Moreover, in agreement with the literature, it was confirmed that this type of rainfall simulator always produces kinetic energy values lower than those associated with natural rainfall of similar intensity. [ABSTRACT FROM AUTHOR]

Kinetic energy and intensity of rainfall are commonly used factors to predict soil erosion by water. The difficulty in measuring these parameters triggers the scientific community to use the kinetic energy-intensity relationship to compute soil erosion. Six kinetic energy-intensity relationships (three exponential, one linear, one logarithmic and one power law) were used to compute and compare rainfall erosivity of Eastern Ghats Highland region of India. The result showed that when the rainfall intensity was < 6 mm h−1, there was a significant difference among the kinetic energy values computed using Brown and Foster, McGregor and Hudson relationships; however, no significant difference was observed for the values computed with van Dijk and Wischmeier and Smith. On the other hand, there was no significant difference in kinetic energy values computed with the different equations for rainfall intensity greater than 30 mm h−1. Highest and lowest rainfall erosivity was computed for Meshesha (6633.0 MJ ha−1 mm h−1 y−1) and Hudson (5503.2 MJ ha−1 mm h−1 y−1) equations, respectively. On an average, annual rainfall erosivity value was observed to be 23.4% lower when computed using I60 than that of I30. Therefore, use of I60 in place of I30 for the study area cannot be suggested. Instead of that, proper calculation of I30 is more important than choosing right kinetic energy-intensity relationship equation. [ABSTRACT FROM AUTHOR]

Typhoons episodically trigger landslides and export large quantities of particulate and dissolved organic carbon (POC and DOC) to the ocean from high-standing islands of the western North Pacific. On landslide scars, new soils are forming and organic carbon (OC) re-accumulates; however, these young soils may remain vulnerable to recurrent erosion. Here, we examined soil aggregate breakdown and concomitant release of OC from soils on recovering landslide scars in Taiwan. We calculated the kinetic energies of falling raindrops during two past typhoon events that hit Taiwan, i.e. Morakot (2009) and Fanapi (2010), at 137 kJ m −2 and 21 kJ m −2 , respectively. Soils from a chronosequence of recovering landslide scars (6 to 41 yrs) in the Central Mountain Range of Taiwan were subjected to ultrasonic vibrations simulating those typhoon energies. The younger soils of the chronosequence (<12 yrs) displayed little aggregate stability. Our results show that it may take several decades before soil aggregate stability significantly improves to withstand energy inputs corresponding to more frequent, moderate typhoons such as Fanapi; however, even the soils from an undisturbed reference site showed almost complete aggregate breakdown when subjected to the simulated energy of a rare but severe typhoon such as Morakot. With increasing recovery age and vegetation change towards forest cover, OC was increasingly accumulated in the soil aggregates and efficiently protected against disruption by lower simulated typhoon energy; however, upon increased aggregate breakdown induced by high simulated typhoon energy, significantly more DOC and POC was released. In light of increasing frequency of typhoon events with global climate change, active reforestation can stabilize soil structure and thus enhance protection against recurrent erosion of the newly forming soils. [ABSTRACT FROM AUTHOR]

The information of aggregate disintegration mechanisms during splash erosion is scant. This study was conducted to quantify contributions of the mechanisms of aggregate disintegration to splash erosion. Six soils with five soil textures were used. Soil aggregate stability was determined by the Le Bissonnais (LB) method. Deionized water was used to simulate the combined effect of slaking and mechanical disaggregation, while ethanol was used to estimate the sole contribution of the mechanical breakdown. Simulated rainfall with intensity of 60 mm h −1 was applied at five fall heights (0.5 m, 1 m, 1.5 m, 2 m and 2.5 m) to achieve different levels of rainfall kinetic energy. The results indicated that slaking caused the most severe aggregate breakdown, and followed by mechanical breakdown, while chemical dispersion in slow wetting with deionized water was the weakest breakdown mechanism. The splash erosion rates due to the effects of slaking and mechanical breakdown increased with an increase in rainfall kinetic energy. The contributions of the slaking (mechanical breakdown) to splash erosion decreased (increased) as rainfall kinetic energy increased. The contribution of mechanical breakdown had a power function relation with rainfall kinetic energy, and had the most significant correlation with RSI (relative slaking index)/ RMI (relative mechanical breakdown index). A power and a linear function could be used to describe the relationships between the contributions of mechanical breakdown with rainfall kinetic energy and RSI / RMI , respectively, which could be used to estimate the contribution of mechanical breakdown. The results of this research would be helpful to improving the soil erosion prediction models. [ABSTRACT FROM AUTHOR]

Rainfall intensity-duration (I-D) characteristics are widely used to study landslide triggering. Recent studies also propose that rainfall kinetic energy ( e k) can be used to quantify the rate of soil erosion induced by strong precipitation events. In the present study, the Joss-Waldvogel Disdrometers (JWD) was utilized to measure e k data, and the relationship between rainfall kinetic energy and rainfall intensity was determined as the regression results of e k N = 32.19 × (1–0.725 e (− 0.029I) ) for northern Taiwan and e k S = 32.23 × (1–0.643 e (− 0.022I) ) for southern Taiwan. Additionally, by examining data from 76 landslide events from the landslide inventory for the period of 2006–2012, the study established an empirical power law I-D relationship, which is crucial for determining the rainfall threshold needed in forecasting landslides. Two rainfall thresholds, i.e., functions of rainfall intensity (I) and rainfall duration (D), were established for study areas in northern and southern Taiwan to be I N = 13.81 D − 0.31 and I S = 66.44 D − 0.57 respectively. Landslides in northern Taiwan usually occurred when D was over 10 h and such events in southern Taiwan took place in two different D groups whose gap was between 16 h and 20 h. Two mechanisms were operative in triggering landslides in the two areas—water infiltration and high rainfall intensity. However, e k also proved to be an important rainfall parameter, and the present study further established that not only rainfall intensity-duration but also kinetic energy can provoke landslide triggering, thus allowing the compiling of more comprehensive information for more accurate landslide forecasting. [ABSTRACT FROM AUTHOR]

Raindrop-impact-induced erosion starts when detachment of soil particles from the surface results from an expenditure of raindrop energy. Hence, rain kinetic energy is a widely used indicator of the potential ability of rain to detach soil. Although it is widely recognized that knowledge of rain kinetic energy plays a fundamental role in soil erosion studies, its direct evaluation is not straightforward. Commonly, this issue is overcome through indirect estimation using another widely measured hydrological variable, namely, rainfall intensity. However, it has been challenging to establish the best expression to relate kinetic energy to rainfall intensity. In this study, first, kinetic energy values were determined from measurements of an optical disdrometer. Measured kinetic energy values were then used to assess the applicability of the rainfall intensity relationship proposed for central Italy and those used in the major equations employed to estimate the mean annual soil loss, that is, the Universal Soil Loss Equation (USLE) and its two revised versions (RUSLE and RUSLE2). Then, a new theoretical relationship was developed and its performance was compared with equations found in the literature.

In arable land, topsoil is exposed to structural changes during each growing season due to agricultural management, climate, the kinetic energy of rainfall, crop and root growth. The shape, size, and spatial distributions of soil aggregates are considerably altered during the season and thus affect water infiltration and the soil moisture regime. Agricultural topsoils are prone to soil compaction and surface sealing which result in soil structure degradation and disconnection of preferential pathways. To study topsoil infiltration properties over time, near-saturated hydraulic conductivity of topsoil was repeatedly assessed in a catchment in central Bohemia (Czech Republic) during three consecutive growing seasons, using a recently developed automated tension minidisk infiltrometer (MultiDisk). Seasonal variability of soil bulk density and saturated water content was observed as topsoil consolidated between seedbed preparations. Topsoil unsaturated hydraulic conductivity was lower in spring and increased in the summer months during two seasons, and the opposite trend was observed during one season. Temporal unsaturated hydraulic conductivity variability was higher than spatial variability. Cumulative kinetic energy of rainfall, causing a seasonal decrease in soil macroporosity and unsaturated hydraulic conductivity, was not a statistically significant predictor.

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• Differences in splash erosion between 50 and 100 mm h−1 were attributed to surface seals. • Quantified the key factors affecting splash erosion before and after runoff occurrence. • Rainfall intensity and its energy exhibit higher contributions on splash erosion whether runoff occurs. • Identified the critical ratio of flow depth and raindrop diameter (h/D) at 100 mm h−1. Splash erosion has been acknowledged as a key process of water erosion, depending on multiple factors including rainfall and soil properties, antecedent soil moisture, and surface runoff. Previous studies mostly focused on the effect of simple factors on splash erosion, but the interactive effects of multiple factors on splash erosion are still obscure. Therefore, we investigated the characteristics of splash erosion under simulated rainfall and quantified the interactive effects of multiple factors on splash erosion using a modified splash pan for measuring directional splash erosion. The results showed that total splash erosion (summation of four directional splash erosion) and net splash erosion (downslope minus upslope splash erosion) ranged from 14.4 to 804.8 g m−2 and 2.0 to 186.5 g m−2, respectively, and both increased with rainfall intensity and rainfall kinetic energy. The splash erosion rates in the dry run were greater than those in the wet run at the earlier stage, whereas after runoff occurred, the splash erosion rates in the dry run were lower than those in the wet run. Furthermore, the calculated variance contributions indicated that before runoff occurrence, rainfall kinetic energy (KE) and antecedent soil moisture (θ a) were the dominant factors affecting splash erosion, accounting for 25.3 % and 15.0 % of variance contributions, respectively. After runoff occurrence, the main factors affecting splash erosion were rainfall intensity (RI), rainfall kinetic energy (KE) and their interactions, explaining 98.2 % of the total splash and 95.7 % of the net splash for all variance contributions. In addition, the effect of shallow flow on splash erosion was dependent on the ratio of flow depth and raindrop diameter (h/D). The thresholds of h/D seemingly ranged from 0.63 to 0.86 and 0.77 to 1.02 for the dry and wet runs under 100 mm h−1 rainfall intensity. This study provides a basis for understanding splash erosion mechanisms and improving process-based erosion models. [ABSTRACT FROM AUTHOR]

Devido aos prejuízos provocados pela erosão sobre sistemas agrários e urbanos, foi desenvolvido este artigo para que se possa estabelecer relação entre a erosão e o selamento formado pelo impacto das gotas de chuva. Para avaliar as perdas de solo e as características físicas e micromorfólogicas das crostas desenvolvidas pelo impacto das gotas de água, foi realizado experimento, utilizando simulador de chuvas, num esquema fatorial 5 x 6, sendo cinco solos (Argissolo Vermelho, Argissolo Vermelho-Amarelo, Latossolo Vermelho-Amarelo, Neossolo Flúvico e Neossolo Quartzarênico) e seis energias cinéticas de chuva simulada (0; 525; 1.051; 2.102; 3.153 e 4.204 J m-2), com três repetições. As perdas de solo foram determinadas por amostragem do volume total de escoamento superficial e as características físicas e micromorfológicas da crosta, tais como distribuição e continuidade dos poros, por meio de técnicas de micromorfometria. Em todos os solos avaliados, as perdas de solo aumentaram progressivamente com a energia cinética aplicada, sendo essas perdas menos acentuadas nos solos com textura grossa ou argilosos com estrutura microgranular. Foi evidenciada a formação de crostas estruturais e erosionais, e suas características apresentaram variação temporal dependente da energia cinética da chuva e da tensão cisalhante do escoamento superficial.Due to the damage caused by erosions in land and urban systems, this article has been developed to establish the relation between soil losses and superficial sealing formed by rain drop impact. In order to evaluate soil losses and physical and micromorphological characteristics of soil crusts developed by water drop impact, an experiment was carried out using a rainfall simulator in a factorial scheme of 5 x 6. Five soils (Red Ultisol, Red-Yellow Ultisol, Red-Yellow Oxisol, Fluvic Entisol and Arenic Entisol) and six rainfall kinetic energy (0; 525; 1,051; 2,102; 3,153 and 4,204 J m-2) with three repetitions were used. Soil losses were determined by the total runoff volume samples and the physical and micromorphological characteristics of the crust, such as pores distribution and continuity, using micromorphometrics techniques. In all evaluated soils there was a progressive increase of soil losses with the kinetic energy applied. These losses were less accentuated in sandy or loamy texture soils with microgranular structure. Crust characteristics presented temporal variation, which were dependent of rainfall kinetic energy and runoff shear stress that induce structural and erosional crusts formation.