Rainfall Kinetic Energy Research Articles

Seasonal Variations in the Rainfall Kinetic Energy Estimation and the Dual-Polarization Radar Quantitative Precipitation Estimation Under Different Rainfall Types in the Tianshan Mountains, China

Seasonal Variations in the Rainfall Kinetic Energy Estimation and the Dual-Polarization Radar Quantitative Precipitation Estimation Under Different Rainfall Types in the Tianshan Mountains, China

Measurement and modelling of kinetic energy and erosivity of rainfall and throughfall in a tropical semiarid region

Empirical relationships have been widely used to estimate kinetic energy of rainfall (KE) and its erosivity potential (EI30) due to scarcity of direct and continuous measurements. Two disdrometers were installed − one in an open field and another under the canopy − in a fragment of Tropical Dry Forest (TDF) in a semiarid region, Northeast of Brazil, to quantify the role of the canopy on attenuating rain kinetic energy and erosivity potential, for all events and at the seasonal scale. The data was also used to test available KE and EI30 models, as well as to recalibrate the models for the study area. Data were collected from December/2019 to July/2021, totaling 95 events. Rainfall (R) was higher than throughfall (TF) due to canopy interception, but rainfall duration and the total number of drops were higher under the canopy. The TDF canopy reduces rainfall kinetic energy by 30% and its erosivity potential by 39%, with higher KE and EI30 attenuation being observed during the high leaf density stage, which highlights the major seasonal role of this vegetation in protecting the soil surface from the impact of raindrops and, consequently, against erosion. The relationship between KE and mean intensity of R and TF is best expressed as a function of time (J m−2 h−1), by a linear model (r2 > 0.98 – p-value = 0.000). The Wischmeier and Smith-WS model for KE and EI30 was recalibrated for the semiarid region, underestimating KE of open field rainfall by 2% and overestimated TF KE by 1%, against underestimations of 24% and 20% of the original model for R and TF, respectively. The results presented here contribute to understanding the role of dry forests in attenuating the erosivity potential of the rainfall in semiarid environments, as well as to improving the capacity on predicting rainfall and throughfall erosivity under such conditions.

Wind and rainfall erosion energy in large sediment generating and coarse sediment class areas of the middle Yellow river

Joint action by strong winds and high-intensive rainfall leads to serious soil erosion problems in large sediment generating and coarse sediment class areas of the middle Yellow River. Investigating the variation of trend and alternating wind and rainfall energy is an important prerequisite for controlling regional sediment transport problems. We calculated the wind and rainfall erosion energies by using the aerodynamic energy and rainfall kinetic energy formulas. The Mann-Kendall (MK) trend test and Theil-Sen approach were used to analyze the spatial-temporal variation and alternation of joint erosion energy during the last 40 years (1979–2018). The results show the following. 1) Wind erosion energy increased and rainfall erosion energy decreased. However, the former is larger than the latter. 2) The dominant erosive energy varies for different seasons. Wind erosive energy dominates in spring, and rainfall erosive energy dominates in summer. 3) There is a regular wind-rainfall-wind alternation of erosive energy. The wind-rainfall energies were alternately distributed in May–July and the rainfall-wind energies were alternately distributed in September–December. Furthermore, the dominant time of rainfall erosive energy decreased when wind erosive energy increased. The results can help decision makers to develop soil erosion control strategies to reduce soil erosion when it occurs in wind and water staggered areas.

Advances in a measurement method of rainfall kinetic power and momentum affecting soil erosion processes

AbstractRainfall is one of the factors affecting soil erosion, and rainfall kinetic energy or momentum is used to represent the capability of the precipitation to erode soil, named rainfall erosivity. Accurate measurements of rainfall erosivity are useful for a reliable prediction of soil loss. Rainfall momentum and kinetic energy, both calculated per unit time and area, can be obtained using terminal raindrop velocity and the drop size distribution (DSD) measured by disdrometers, which are instruments expensive and not suitable for large scale use. An innovative patented method to measure the rainfall energy is based on the estimation of DSD by simultaneous detection, in a given time interval, of the rainfall intensity I and the number N of raindrops that hit a specific piezoelectric surface. In this paper, advances of this method are presented. In particular, two new theoretical procedures to estimate the parameters μ and Λ of Ulbrich's distribution, that allow for the calculation of the rainfall kinetic energy and momentum, are proposed. Both procedures (Scenario 1 and 2) are based on the frequency distribution of the momentum M(D) of raindrops detected in a sampling time interval. Specifically, in the Scenario 1, μ and Λ are estimated by using I, N and the standard deviation, s(D), of the drop diameters obtained from the measured momentum distribution. In the Scenario 2 the parameters are estimated using I, N and the mean value, m(D), of the drop diameters deriving from the momentum distribution. The reliability of the proposed procedures was tested using DSD measurements recorded in three different experimental sites. The developed analysis demonstrated that Scenario 2 is the best method to estimate μ and Λ, and to reproduce the DSD, accordingly. The proposed method, associated with a patented device, not yet build, will allow the direct measurement of the rainfall energy characteristics, which are usually roughly estimated from rainfall intensity. The possibility to easily measure these energy variables can support the development of research in the field of soil erosion and, in general, of hydrogeological instability. In particular, the proposed measurement method and the construction of the device could stimulate the scientific community to deepen the study of the effect of the rainfall energy on soil erosion for improving the predictive capability of water erosion models.

Impacts of Rainfall Characteristics and Slope on Splash Detachment and Transport of Loess Soil

To identify the key parameters and develop accurate experimental models of detachment and transport, splash detachment and transport of loess soil were investigated in relation to the rainfall characteristics and slope. The experiment was conducted under 25 combinations of five rainfall intensities (60, 84, 108, 132 and 156 mm h−1) and five slope gradients (0°, 5°, 10°, 15° and 20°), using a custom splash pan. Raindrop characteristics (diameter, velocity and kinetics) and splash mass were measured in downslope and upslope. The results indicated that rainfall intensity and slope contributed 94.77% and 0.46%, respectively, to the detachment rate, and 24.39% and 67.82%, respectively, to the transport rate. From a holistic viewpoint, the positive effect of slope became more visible on the detachment rate when the rainfall intensity exceeded 108 mm h−1, and on the transport rate when the slope exceeded 15°. Based on the rainfall simulator in this study, the rainfall kinetic energy (KE, J), raindrop median particle size (D50, mm) and raindrop terminal velocity (V, m s−1) all increased with increasing rainfall intensity (I) within the 60~108 mm h−1 range but decreased with increasing rainfall intensity within the 132~156 mm h−1 range. The rainfall intensity and raindrop characteristics (D50/V/KE) are the key parameters of splash detachment (Dr, g·m−2 min−1), and three detachment models were developed: (1) Dr = 0.1153 I1.09D500.79 (R2 = 0.99, NSE = 0.98, p < 0.01); (2) Dr = 0.0162 I1.11V1.22 (R2 = 0.99, NSE = 0.99, p < 0.01); and (3) Dr = 0.0813 I1.10KE0.18 (R2 = 0.99, NSE = 0.99, p < 0.01). The rainfall intensity and slope are the key parameters for splash transport (Tr, g·m−2 min−1), and the developed transport models could be expressed as: (1) Tr = 0.00657 I1.343S0.116 (R2 = 0.914, NSE = 0.874, p < 0.01) (slopes of 0°, 5° and 10°) and (2) Tr = 0.00218 I1.165S1.033 (R2 = 0.986, NSE = 0.986, p < 0.01) (slopes of 15° and 20°). The results of this study could enhance the understanding of soil splash detachment and transport on loess slopes.

Evaluating and modeling a rainfall kinetic energy and erosivity: a case study of a humid watershed in the Ethiopian highlands

Evaluating and modeling a rainfall kinetic energy and erosivity: a case study of a humid watershed in the Ethiopian highlands

Optical Precipitation Gauge in the Rainfall Kinetic Energy Measurements

A brief overview of the tasks that require information about the rainfall kinetic energy is presented. The possibilities of methods for obtaining such information using different techniques are shown. The influence of various microstructural parameters of raindrops on the kinetic energy is analyzed. This technique is illustrated by the data of measuring the characteristics of a heavy rain on July 22, 2023 in Tomsk. The measurements were carried out using the optical precipitation gauge OPTIOS. The OPTIOS measurement results are compared with the results of simplified estimates. It is concluded that the optical precipitation gauge is successfully used in solving problems requiring an accurate measurement of rainfall kinetic energy

SOIL EROSION RISK IN RELATION TO RAINFALL EROSIVITY IN GUNUNG ALAB AND INOBONG OF CROCKER RANGE PARK IN SABAH, MALAYSIA

The rainfall ability to erode and detach soil particles, resulting in soil erosion, is referred to as rainfall erosivity (R). This research aims to estimate the risk of soil erosion from rainfall intensity in Gunung Alab and Inobong of Crocker Range Park, Sabah. Daily rainfall data from 2017 and 2020 where an observed mild La Nina were extracted. The 30-minute Maximum Rainfall Intensity (I30) and Rainfall Kinetic Energy (E) were determined for estimating the R Factor. ROSE Index was then referred to in classifying the soil erosion risk. The estimated monthly R Factor in Gunung Alab ranged from 15282.2 to 32029.2 MJ.mm (ha.h)-1 in 2017 and from 16069.5 to 35401.6 MJ.mm (ha.h)-1 in 2020. Gunung Alab was rated as having an “extremely high” and “critical” risk of soil erosion 80% of the time in 2017 and 50% in 2020. At the Inobong substation, the monthly R Factor in 2017 (16069.5 to 58348.0 MJ.mm (ha.h)-1) and 2020 (16863.6 to 36246.4 MJ.mm (ha.h)-1) translates to an erosion risk (extremely high-critical) throughout 67% and 92% of the time, respectively. Given the possibility of landslides, rainfall erosivity is useful information in assessing soil erosion risk and could be used in soil and land management

Microphysics-based rainfall energy estimation using remote sensing and reanalysis data

Rainfall plays a critical role in soil erosion by detaching and transporting soil particles, making it a key factor in soil erosion models. Its potential effect on soil erosion is reflected by rainfall erosivity, which considers the interaction between raindrops and soil, primarily driven by the kinetic energy carried by raindrops. Traditional approaches rely on empirical relationships between rainfall rate and kinetic energy, but they often overlook regional differences in rainfall microphysical characteristics. This study aims to compare the performance of conventional fixed and disdrometer-derived local microphysics-based unit rainfall kinetic energy–rain rate (KE–I) relationships for estimating rainfall energy using the IMERG and ERA5-land precipitation datasets. The findings reveal that conventional method using the fixed KE–I relationship do not account for regional differences in rainfall microphysical characteristics and tend to overestimate KE values for high rainfall intensities in the UK. Disdrometer-derived microphysics-based KE–I relationships improve estimation correlations, with the fully fitting formula exhibiting the highest correlation coefficient. The findings highlight the need to consider local rainfall characteristics for improved estimation accuracy and demonstrate that ERA5-land exhibits higher correlation and lower error compared to IMERG for estimating rainfall energy, but it generally underestimates rainfall intensity. This study will provide valuable insights into the applicability of using gridded precipitation datasets for large-scale soil erosion estimation and emphasizes the significance of accounting for regional variations in rainfall characteristics.

Splash erosion-induced soil aggregate turnover and associated organic carbon dynamics

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.

The response of organic carbon fractions in sediment to rainfall characteristics and slope lengths: Based on four-years on-site monitoring data

The effect of soil erosion processes on the properties of sediment and organic carbon fractions is not well understood under complex erosion environments, such as various rainfall characteristics and transport distances, which leads to a gap in knowledge regarding the role of soil erosion in the global carbon cycle. This study investigated the impact of different rainfall characteristics (patterns and parameters) and slope lengths (5 m ∼ 20 m) on the sediment yield, particle size distribution (PSD) and properties of organic carbon fractions on China’s Loess Plateau. The results show that runoff was highest under rainfall pattern A (extreme rainfall), while the sediment concentration peaked under rainfall pattern B (heavy rainfall), with significant correlation with slope length, rainfall intensity, kinetic energy, rainfall erosivity and precipitation (p less than 0.05). Silt- and clay-sized fractions were transported as primary particles and enriched under rainfall patterns B and C with no differences between slope lengths. The enrichment ratio (ER) of sediment, effective and ultimate particles were primarily influenced by rainfall intensity-related parameters. In contrast, the aggregation ratio (AR) tended to be influenced by rainfall kinetic energy. The content and loss of organic carbon fractions correlated to rainfall parameters and slope length, although no significant difference was observed between different rainfall patterns and slope lengths. Lost organic carbon fractions were predominantly Mineral-associated organic carbon (MOC), with great enrichment under rainfall pattern C and rapid depletion as the slope length increased. Structural equation models (SEM) indicated the effect of rainfall characteristics and slope length on organic carbon loss was mainly due to the regulation of soil loss and particle size distribution of sediment in selective transport erosion processes. We highlighted the need to consider the effect of soil erosion and particle size distribution comprehensively on the carbon cycle from the perspective of organic carbon fractions to describe the potential effects of soil erosion on the carbon budget quantitatively, especially in complex environmental conditions with consideration of scale effect.

Radar remote sensing reveals potential underestimation of rainfall erosivity at the global scale.

Rainfall kinetic energy (RKE) constitutes one of the most critical factors that drive rainfall erosivity on surface soil. Direct measurements of RKE are limited, relying instead on the empirical relations between kinetic energy and rainfall intensity (KE-I relation), which have not been well regionalized for data-scarce regions. Here, we present the first global rainfall microphysics-based RKE (RKEMPH) flux retrieved from radar reflectivity at different frequencies. The results suggest that RKEMPH flux outperforms the RKE estimates derived from a widely used empirical KE-I relation (RKEKE-I) validated using ground disdrometers. We found a potentially widespread underestimation of RKEKE-I, which is especially prominent in some low-income countries with ~20% underestimation of RKE and the resultant rainfall erosivity. Given the evidence that these countries are subject to greater rainfall-induced soil erosion, these underestimations would mislead conservation practices for sustainable development of terrestrial ecosystems.

The size distribution metrics and kinetic energy of raindrops above and below an isolated tree canopy in urban environment

Raindrop impact on bare soils is the initial phase of rainfall-induced soil erosion which is altered under any type of vegetation due to the interactions of rainfall with the canopies. This study examines the drop size distribution (DSD) and kinetic energy (KE) of raindrops above and below the birch tree (Betula pendula Roth.) canopy in a research plot in the city of Ljubljana, Slovenia using a one-year observation of 63 rainfall events and the effect of meteorological variables under moderate continental climate. Simultaneous measurement of the microstructures of open rainfall and throughfall was carried out using an optical disdrometer. The result of our analysis revealed that throughfall DSD showed two distinct major peaks (bimodal) occurring primarily on smaller drop sizes while open rainfall has only one. The cumulative drop number, median drop-volume diameter (D50), and drop fall velocity of throughfall were 16.4%, 26.6%, and 5.0% lower than those of open rainfall, respectively. Also, the relative volume percentage of raindrops > 1.5 mm is 1.5 times higher than those observed in throughfall drops which indicates that the presence of the canopy caused the fractionation of larger drops into smaller droplets. These reductions significantly differ depending on the phenoseasons of the canopy with the leafed state being higher than the leafless state. Similarly, the Kruskal-Wallis H test result revealed that birch tree elicits a statistically significant change in the kinetic energy of open rainfall, thus weakening the mean rainfall KE by 33.7%. On the other hand, KE is positively affected by the phenological condition of the canopy with higher attenuation being observed during its leafed state. Also, the correlation analysis demonstrated that vapor pressure deficit, air temperature, and relative humidity have stronger associations with throughfall kinetic energy among meteorological variables considered. These findings underscore the necessity of an optimized selection of tree species for afforestation programs.

Assessment of OTT Parsivel2 Raindrop Fall Speed Measurements

Abstract This study was to assess the raindrop fall speed measurement capabilities of OTT Parsivel2 disdrometer through comparisons with measurements of a collocated High-speed Optical Disdrometer (HOD). Raindrop fall speed is often assumed to be terminal in relevant hydrological and meteorological applications, and generally predicted using terminal speed–raindrop size relationships obtained from laboratory observations. Nevertheless, recent field studies have revealed that other factors (e.g., wind, turbulence, raindrop oscillations, and collisions) significantly influence raindrop fall speed, necessitating accurate fall speed measurements for many applications instead of reliance on laboratory-based terminal speed predictions. Field observations in this study covered rainfall events with a variety of environmental conditions, including light, moderate, and heavy rainfall events. This study also involved rigorous laboratory experiments to faithfully identify the internal filtering and calculation algorithm of OTT Parsivel2. Our assessments revealed that, for the smaller diameter bins, Parsivel2 filters out many of the observed raindrops that fall faster than predicted terminal speeds, bringing down the mean fall speed for those size bins without observational evidence. Furthermore, Parsivel2 fall speed measurements exhibited notable artificial bell-shaped deviations from the predicted terminal speeds toward subterminal fall starting at around 1 mm diameter raindrops with peak deviations around 1.625 mm diameter bin. Such bell-shaped fall speed deviation patterns were not present in collocated HOD measurements. Assessment results along with the faithfully identified Parsivel2 algorithm are presented with discussions on implications on reported raindrop size distributions (DSD) and rainfall kinetic energy.

Measuring Rainfall Kinetic Power in Two Sicilian Experimental Areas by Drop-Size Distribution Data

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.

Evaluation of Numerous Kinetic Energy-Rainfall Intensity Equations Using Disdrometer Data

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.

Interactive effects of rainfall intensity, kinetic energy and antecedent soil moisture regime on splash erosion in the Ultisol region of South China

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 (θa) 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.

An assessment of rainfall kinetic energy functional relationships with GPM DPR

The kinetic energy (KE) of rainfall is an important parameter in estimating the rainfall erosivity factor, an essential parameter in the soil erosion equation. The global precipitation measurement dual-frequency precipitation radar (GPM DPR) can provide radar reflectivity at Ku- and Ka-band frequencies (Zku and Zka), rainfall rate (I, mm h−1), and drop size distribution parameters (mass-weighed mean diameter: Dm in mm and normalized intercept parameter: log10Nw, Nw in m−3 mm−1). The empirical relations between rainfallKEand GPM DPR parameters (KEtime–I, KEmm–Dm, KEtime–Zku, and KEtime–Zka relations) can allow us to estimate the KE at the locations where there are no ground-based measurements. In the present work, long-term measurements of impact type disdrometers located at three different locations (Zhongli, Feitsui, and Hsiayun) in north Taiwan are used to collect the raindrop size distribution (RSD) information of six seasons (spring, mei-yu, summer, autumn, winter, and typhoon). Measured RSDs in six seasons are used to estimate the rainfall intensity, mass-weighted mean diameter, rainfall KE flux (KEtime, J m–2 h−1), KE content (KEmm, J m−2 mm−1), radar reflectivity at Ku- and Ka-band frequencies. For the first time, present study establish and validate the rainfall KE functional relationships with GPM DPR data products (KEtime–I, KEmm–Dm, KEtime–Zku, and KEtime–Zka relations). The empirical relations between rainfall KE and GPM DPR parameters (I, Dm, Zku, and Zka) are established for six seasons of each disdrometer location. Derived KE relations did not show any spatial disparity for a given season, especially the KEmm–Dm, KEtime–Zku, and KEtime–Zka relations. On the other hand, a clear seasonal differences in the rainfall KE relations are noticed at each observational site. The established relations showed reasonable agreement in estimating the KE from the GPM DPR. However, in determining the KE, the KEmm–Dm relation showed outperformance over the remaining three relations (KEtime–I, KEtime–Zku, and KEtime–Zka relations).

PHOTOGRAMMETRIC TECHNIQUE FOR ANALYZING RAINDROP SIZE DISTRIBUTION

Rainfall erosivity and rainfall kinetic energy are predominantly affected by the rainfall droplet size distribution characteristics. This study aims to determine the raindrop size distribution with different rainfall intensities in East Malaysia using photographic method and MATLAB image processing tools. A total of five natural rainfall intensities of different ranges were analyzed: 5.51 mm hr-1, 14.20 mm hr-1, 28.80 mm hr-1, 32.41 mm hr-1 and 58.11 mm hr-1. A digital camera with fast capturing mode was used to capture falling raindrops and the droplets were then processed in MATLAB to determine the raindrop size distribution. It was found that the captured raindrop diameters were within the range of 0.1 mm and 5.0 mm, and a higher portion of the raindrops fell between 0.1 mm and 1.0 mm. The results also showed that higher rainfall intensities would promote the formation of larger raindrop sizes, i.e., from 1.0 mm to 5.0 mm, and lower rainfall intensities tended result in higher drop counts in smaller raindrop sizes of &lt;1.0 mm. The modified image processing tools of MATLAB had proved a shorter analysis duration and higher accuracy of the raindrop size determination than the human visual system. The novelty of this study contributes to the understanding of the equatorial rainfall properties. This enhances the study of the rainfall kinetic energy and soil erosion rate estimation. The findings demonstrate the capability of photogrammetric techniques for determination of raindrop size distribution.

Microphysical characteristics of seasonal rainfall observed by a Parsivel disdrometer in the Tianshan Mountains, China

Raindrop size distribution (DSD) is critical for understanding rainfall microphysical processes. Correlated DSD relationships, including the radar reflectivity factor-rainfall rate (Z–R), shape factor-slope parameter (μ–∧), and the rainfall kinetic energy-R (mass-weighted average diameter) (KE–R (Dm)) are significant in many fields such as quantitative precipitation estimation, parameterization schemes in weather forecast models, and assessing rainfall kinetic energy; however, the collective scientific understanding of DSD in arid regions remains insufficient. Here, 2020–2021 DSD data from the Tianshan Mountains, China, were collected to assess various corresponding characteristics for a typical arid region in China across different seasons, rainfall types, and rainfall rate classes. Rainfall in the fall (summer) had the most (least) small raindrops (diameter < 1 mm), the least (most) mid-size raindrops (1 ≤ diameter ≤ 3 mm), and large raindrops (diameter > 3 mm). Mean Dm was the largest (smallest) in the summer (fall) at 1.059 mm (0.876 mm), while the mean generalized intercept parameter was the largest (smallest) in the fall (winter) at 3.738 (3.505). For stratiform rainfall, fall (summer) had the most (least) small raindrops, as well as the least (most) mid-size and large raindrops, whereas, for convective rainfall, summer displayed fewer small and mid-size raindrops compared to spring. Regarding the rainfall rate classes, the concentration of mid- and large-size raindrops in spring changed from a minimum at C1 (0.1 ≤ R < 0.5 mm·h−1; notably comparable to fall rates) to C4 (2 ≤ R < 5 mm·h−1; comparable to summer), before peaking beyond summer rates at C5 (R ≥ 5 mm·h−1). The localized Z-R, μ–∧, KEtime–R, and KEmm–Dm relationships also exhibited marked seasonal characteristics, which ultimately impact estimates of regional radar quantitative precipitation and rainfall kinetic energy, as well as efforts aimed at improving model parameterization schemes. Additionally, the more abundant water vapor, the more frequent cold rain process, and the stronger warm–dry atmospheric vertical environment in summer appeared as the most important influencing factors leading to the fewest small-, and greatest mid- and large-size raindrops.