Rainfall erosivity estimation over the Tibetan plateau based on high spatial-temporal resolution rainfall records

The Tibetan Plateau (TP) in China has been experiencing severe water erosion because of climate warming. The rapid development of weather station network provides an opportunity to improve our understanding of rainfall erosivity in the TP. In this study, 1-min precipitation data obtained from 1226 weather stations during 2018–2019 were used to estimate rainfall erosivity, and subsequently the spatial-temporal patterns of rainfall erosivity in the TP were identified. The mean annual erosive rainfall was 295 mm, which accounted for 53% of the annual rainfall. An average of 14 erosive events occurred yearly per weather station, with the erosive events in the wet season being more likely to extend beyond midnight. In these cases, the precipitation amounts of the erosive events were found to be higher than those of the daily precipitations, which may result in implicit bias as the daily precipitation data were used for estimating the rainfall erosivity. The mean annual rainfall erosivity in the TP was 528 MJ mm·ha^?1·h^?1, with a broader range of 0–3402 MJ mm·ha^?1·h^?1, indicating a significant spatial variability. Regions with the highest mean annual rainfall erosivity were located in the forest zones, followed by steppe and desert zones. Finally, the precipitation phase records obtained from 140 weather stations showed that snowfall events slightly impacted the accuracy of rainfall erosivity calculation, but attention should be paid to the erosion process of snowmelt in the inner part of the TP. These results can be used as the reference data for soil erosion prediction in normal precipitation years.     

Development of an appropriate procedure for estimation of RUSLE EI30 index and preparation of erosivity maps for Pulau Penang in Peninsular Malaysia

Pluviographic data at 15 min interval from 6 stations in Pulau Penang of Peninsular Malaysia were used to compute rainfall erosivity factor (R) for the revised universal soil loss equation (RUSLE). Three different modelling procedures were applied for the estimation of monthly rainfall erosivity (EI₃₀) values. While storm rainfall (P) and duration (D) data were used in the first approach, the second approach used monthly rainfall for days with rainfall ≥ 10 mm (rain₁₀) and monthly number of days with rainfall ≥ 10 (days₁₀). The third approach however used the Fournier index as the independent variable. Based on the root mean squared error (RMSE) and the percentage error (PE) criteria, models developed using the Fournier index approach was adjudged the best with an average PE value of 0.92 and an average RMSE value of 164.6. Further, this approach was extended to the development of a regional model. Using data from additional sixteen stations and the Fournier index based regional model, EI₃₀ values were computed for each month. ArcView GIS was used to generate monthly maps of EI₃₀ values and also annual rainfall erosivity (R). The rainfall erosivity factor (R) in the region was estimated to vary from 9000 to 14,000 MJ mm ha^− 1 h^− 1 year^− 1.     

Soil loss and runoff obtained with customized precipitation patterns simulated by InfiAsper

Applying constant precipitation intensity, which does not occur in natural events, is one of the main limitations concerning rainfall simulators in soil erosion studies. The present work evaluated the InfiAsper rainfall simulator operating with a new control panel to program rainfalls with different precipitation intensities (PI). Infiltration rates and soil and water losses were evaluated in a Distrophic Acrisol (clay loam texture) with simulated rainfalls of 30 mm and duration of 40 min, considering advanced (AD), intermediate (IN), delayed (DE), and inverted intermediate (II) patterns, all with PI peaks of 110 mm h^?1, and a constant (CT) pattern. The experimental design was in randomized blocks with five treatments (rainfall patterns) and experimental units measuring 2.5 × 2.5 m. The simulator worked satisfactorily, applying the rainfall according to the preconfigured programs. The simulated rainfall with the CT and II patterns did not promote runoff nor soil loss. Infiltration and runoff rates varied according to the applied rainfall pattern, reaching 97.8 and 27.3 mm h^?1 (AD), 82.1 and 39.5 mm h^?1 (IN), and 76.2 and 49.7 mm h^?1 (DE), respectively. Soil loss and surface runoff totaled each 4.77 g m^?2 and 3.9 mm (AD), 6.70 g m^?2 and 6.8 mm (IN), and 6.03 g m^?2 and 7.0 mm (DE). The InfiAsper simulator modified enables varying precipitation intensity besides obtaining satisfactory results in the field and information consistent with the expected characteristics of natural rainfall patterns. In the intermediate and delayed rainfall patterns, soil and water losses are higher than in the advanced.     

1951-2018年韶关不同量级降雨侵蚀力变化

降雨是引起土壤水蚀的主要动力因子之一,为探讨韶关市不同量级降雨对土壤水蚀特征造成的影响,选取1951—2018年韶关市逐日降雨量数据,采用日降雨侵蚀力模型计算降雨侵蚀力,利用变异系数、趋势系数分析不同时间尺度各量级降雨侵蚀力的变化.结果表明:(1)68年来韶关市年均降雨侵蚀力为9314(MJ·mm)/(hm2·h·a)...     

Rainfall erosivity map for Brazil

Rainfall erosivity is the potential ability for rainfall to cause soil loss. Erosivity can be quantified by means of the R factor calculation of the universal soil loss equation (USLE). The purpose of this study was to investigate the spatial distribution of annual rainfall erosivity in Brazil. For each of eight Brazilian regions covering the whole of the territory of Brazil, one adapted equation was applied using pluviometric records obtained from 1600 weather stations. A geographic information system (GIS) was used to interpolate the values and to generate a map showing spatial variations of erosivity. The annual values of erosivity ranged from 3116 to 20,035 MJ mm ha⁻¹ h⁻¹ year⁻¹. The region with highest annual values was the extreme northwestern, while the northeastern region showed the lowest annual values of erosivity. For the most part of the Brazilian territory, December and January revealed the highest erosivity values, while the lowest values were observed from June to September.     

Residue cover and rainfall intensity effects on runoff soil organic carbon losses

Soil cover and rainfall intensity (RI) are recognized to have severe impacts on soil erosion and an interaction exists between them. This study investigates the effect of rainfall intensity (RI) and soil surface cover on losses of sediment and the selective enrichment of soil organic carbon (SOC) in the sediment by surface runoff. A field rainfall simulator was used in the laboratory to produce 90 min rainfall events of three rainfall intensities (65, 85 and 105 mm h^− 1) and four cover percentages (0%, 25%, 50% and 75%) on soil material at 9% slope. A strong negative exponential relation was observed between cover percentage and RI on sediment loss under 85 and 105 mm h^− 1 of rain, while under RI of 65 mm h^− 1, the highest sediment loss was observed under 25% cover. Overall, higher RI and lower cover produced higher sediment and consequently higher nutrient loss, but resulted in a lower SOC enrichment ratio (ER_SOC) in the sediment. The amount of runoff sediment rather than the ER_SOC in the sediment was the determinant factor for the amount of nutrients lost. The values of ER_SOC were high and positively correlated with the ER values of particles smaller than 20 µm (p < 0.01). Although the sediment contained substantially more fine fractions (fine silt and clay, < 20 µm), the original soil and runoff sediment were still of the same texture class, i.e. silt clay loam.     

An improved rainfall erosivity index obtained from experimental interrill soil losses in soils with a Mediterranean climate

The most common index to predict rainfall erosivity is based on the kinetic energy (KE) and the maximum intensity in a 30-min period. However, rainfalls recorded in the Mediterranean climate are, in most cases, the short duration (<30 min) and the high intensity. The goal of this work was to improve rainfall erosivity indices for the Mediterranean conditions from experimental interrill soil losses measured in natural conditions in 1-m² plots. The plots were located in three vineyard fields, whose soils are classified as Typic Calcixerept, Typic Xerofluvent and Typic Xerorthent, and ploughed at the same time as the vineyards. Soil losses and runoff were collected after each rainfall event during 1 year and rainfall data were obtained from bucket gauges installed at the same places. Mean intensity of the storms was less than 10 mm h⁻¹, but maximum intensities in short periods were as high as 103 mm h⁻¹. Kinetic energy was calculated using different expressions proposed in the literature and improved with our data obtained with a disdrometer type Joss Waldvogel. Soil losses were related to kinetic energy and to different combinations of kinetic energy and maximum intensity for different time intervals. The best correlation was that obtained between soil losses and the product of kinetic energy by Sempere Torres and the maximum intensity in 5-min intervals (I₅), which explained more than 80% of the variability. When a surface crust was formed quickly there was no significant relation between soil loss and rainfall parameters.     

DECADAL MODELLING OF RAINFALL EROSIVITY IN BELGIUM

Hydrological extremes are major weather related disasters, but little is known about their long‐term patterns in the context of environmental change. Better understanding of damaging rainfall (e.g. rainfall‐erosivity events) occurring at different time‐scales has important implications for hydrological and land degradation management. The study of the interdecadal variations may help in understanding some of the consequences of abrupt environmental changes over long time periods. Thus, a decadal‐scale rainfall erosivity model (DREM), comparable with the Revised Universal Soil Loss Equation (RUSLE), was developed based on a parsimonious interpretation of rain aggressiveness (95th percentile of rainfalls). The DREM was parameterised to capture interdecadal erosivity variability at the Ukkel station (Belgium), which has the longest RUSLE‐based rain‐erosivity series in Europe (1898–2007). The DREM performed well against decadal RUSLE data, with a coefficient of determination (R²) of 0·72 and a Nash–Sutcliffe efficiency index of 0·71. The model outperformed three well‐established models used in this study (R² ~ 0·4). For a spatial evaluation of the DREM, a pattern of decadal rainfall erosivity was provided for an area around Ukkel, which includes the western part of Germany bordering Belgium, and was compared with maps from the RUSLE approach for 1961–1990. The 95th percentile of June–September rainfalls proved to be a better predictor of decadal rainfall erosivity than yearly based precipitation amount. These results lay the foundation for estimating decadal erosivity in the surrounding areas of Ukkle as well as for historical reconstructions where detailed hydrological data are unavailable, and assumptions cannot be met, for physically based models. Copyright © 2012 John Wiley & Sons, Ltd.     

嘉陵江流域降雨侵蚀力时空变化分析

降雨侵蚀力是降雨引起土壤侵蚀的潜在能力,对预测土壤侵蚀量具有重要意义。对嘉陵江流域12个气象站的日降雨量资料,利用章文波日降雨侵蚀力模型估算流域的降雨侵蚀力。结果表明:嘉陵江流域降雨侵蚀力的空间变异与降雨量的空间分布趋势基本一致,由东南向西北递减,变化于800～9 000MJ.mm/(hm2.h.a)之间;流域内降雨侵蚀力年际变率Cv在0.346～0.493之间,除平武站呈显著减少外并无显著变化趋势;年内降雨侵蚀力随季节变化,夏秋季降雨侵蚀力较大,冬春季降雨侵蚀力较小。降雨侵蚀力年内集中度高,6—9月份的降雨侵蚀力占全年降雨侵蚀力的80%以上。近50a降雨侵蚀力存在35a,21a的主周期变化,且对应不同的丰枯状态。研究结果表明,虽然年降雨侵蚀力无明显变化,但年内却相对集中于夏秋两季,因此仍要做好汛期的水土流失等灾害的防治。     

Evaluation of rainfall kinetic energy and erosivity in northern Taiwan using kriging with climate characteristics

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 (KE_mm) and the unit time‐specific kinetic energy (KE_time) 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 KE_time, 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.     

Soil erosion caused by extreme rainfall events: mapping and quantification in agricultural plots from very detailed digital elevation models

This paper presents a method that can be used to quantify and map soil losses at field scale produced by extreme rainfall events. The amounts of sediment produced by overland flow and concentrated overland flow (inter-rill, rill and gully erosion) at the agricultural plot scale are evaluated from elevation differences computed from very high resolution digital elevation models (DEMs), from before and just after an extreme rainfall event. Geographical Information Systems (GIS) techniques are used to analyse the multi-temporal spatial data. The research case study presented makes reference to a mechanised vineyard plot located in the Alt Penedès–Anoia region (Catalonia, Spain). The rainfall event, which occurred in June 2000, registered 215 mm, 205 mm of which fell in 2 h 15 min. The average intensity of the downpour was 91.8 mm h⁻¹, with a maximum intensity in 30-min periods of up to 170 mm h⁻¹. The erosivity index R reached a value of 11,756 MJ ha⁻² mm h⁻¹, 10 times greater than the annual value for this area. The volume of soil detached by the rainfall, as measured by the proposed method, was 828±19 m³. About 57% of those materials were deposited in other parts within the same plot. The balance was negative, with a total 352±36 m³ of soil loss from the plot, which represented a rate of 207±21 Mg ha⁻¹. The paper analyses the characteristics of the rainfall event in relation to historical data and discusses the proposed method for soil erosion mapping at plot scales in relation to other measurement methods.     

Effects of rainfall intensity and slope gradient on the dynamics of interrill erosion during soil surface sealing

Soil erosion during rainfall is strongly affected by runoff and slope steepness. Runoff production is drastically increased when a seal is formed at the soil surface during rainfall. Therefore, a complex interaction exists between soil erosion and surface sealing. In this study, the dynamics of interrill erosion during seal formation is studied under different simulated rainfall and slope conditions. A sandy soil was exposed to 70 mm of rainfall at two intensities, 24 mm h^− 1 and 60 mm h^− 1, and five slope gradients, from 5% to 25%. Infiltration, runoff and soil loss rates were monitored during rainfall. Final infiltration rates increased with slope gradient at both rainfall intensities, this effect being stronger for the higher intensity. Cumulative runoff at the end of the rainfall event was lower as slopes were steeper, while an opposite trend was obtained for soil loss. For the 5% and the 9% slopes, the sediment concentration in runoff reached quickly a stable value during the whole rainfall event, while it reached a peak value before declining for the higher slopes. The peak value and its timing were rainfall intensity dependent. Soil erodibility during seal formation was evaluated using two empirical multiplication-of-factors type models. It seems that slope and rainfall erosivity are accounted for only partly in these models. For mild slope gradients below 9%, the value of K_i estimated by means of the two expressions becomes practically constant shortly after runoff apparition. Consequently, the estimates resulting from this type of expressions remain valuable from the practical point of view.     

基于降雨量和降雨时间的月降雨侵蚀力简易算法——以陕北黄土丘陵沟壑区为例

 降雨侵蚀力简易算法是较大尺度应用USLE/RUSLE进行土壤侵蚀评价研究的必要内容。基于降雨量和降雨时间建立月降雨侵蚀力计算模型,并以陕北黄土丘陵沟壑区为例,进行模型的拟合。结果表明:随着自变量中降雨量和降雨时间表示方式的改变,模型的拟合优度表现出明显的差异;对于不同因变量而言,以ΣEI30(或lg(ΣEI30))和以ΣEI10(或lg(ΣEI10))为因变量的模型拟合优度在整体上比较接近甚至相同,而以ΣE60I10(或lg(ΣE60I10))为因变量的模型拟合优度在整体上略低;就尺度效应而言,在时间尺度上,整个汛期的模型拟合优度低于1个月份或多个月份模型的拟合优度,在空间尺度上,区域模型中的拟合优度低于至少1个流域的模型拟合优度;在实际应用中,可以选择以ΣEI30为因变量的月降雨侵蚀力公式对该区域进行土壤侵蚀评价。     

西部黄土丘陵区不同草地土壤侵蚀对侵蚀性降雨的响应

[目的]研究西部黄土丘陵区人工和天然草地对不同类型侵蚀性降雨的响应,为该区植被建设和水土流失防治提供指导。[方法]利用甘肃省定西市安家沟径流场2007—2015年的观测数据,分析侵蚀性降雨因素对坡度为20°的人工草地和天然草地土壤侵蚀的影响。[结果]西部黄土丘陵区的侵蚀性降雨分布在5—9月,其中7—8月的侵蚀性雨量较大,其侵蚀量占年均侵蚀的70%以上。两种不同类型的草地侵蚀量均与PI10相关性最好。该区域侵蚀性降雨主要是中雨和大雨,造成的草地侵蚀量占年均侵蚀的86%。中、高雨强型降雨的侵蚀量分别占人工、天然草地总量的90.8%和91.2%,其侵蚀量与PI10,PI30呈较好的幂函数关系。大于300 MJ·mm/(hm2·h)的高侵蚀力型降雨引起的侵蚀量最大,分别占人工、天然草地总侵蚀量的32.3%和33.4%;50~100MJ·mm/(hm2·h)的中侵蚀力型降雨次数最多,而引起人工、天然草地的侵蚀占相应总量的26.0%和29.1%。[结论]人工草地(盖度75%~82%)和天然草地(盖度80%)的侵蚀性降雨量标准分别为11.3和11.9mm,最大I10标准分别为10.4和11.7mm/h。天然草地比人工草地具有更好的水土保持效果。     

辽河流域降雨侵蚀力的时空变化分析

降雨侵蚀力是反映流域降雨侵蚀能力的综合指标之一。根据辽河流域10个气象站的日降雨量资料,利用日降雨侵蚀力模型估算辽河流域的降雨侵蚀力。结果表明：辽河流域降雨侵蚀力的空间变异与降雨量的空间分布趋势基本一致,由东南向西北递减,变化于1000—3800MJ·mm／（hm^2·h·a）之间;降雨侵蚀力年内集中度高,6—8月3个月约占全年的80％;降雨侵蚀力年际变化大,年际变率Cv在0．367—0．649之间,采用时序系列的Mann—Kendall检验表明,降雨侵蚀力并无显著变化趋势;特别是在流域水土流失严重的西辽河地区,年降雨侵蚀力较小,但年内集中程度大,年际变化更突出。     

渭河流域降雨侵蚀力时空分布特征

[目的]揭示渭河流域降雨侵蚀力的时空变化特征,为区域水土保持规划提供依据。[方法]根据渭河流域及其周边范围30个气象站点1957—2014年逐日降雨资料,采用章文波日降雨量侵蚀模型计算各站点的降雨侵蚀力,分析其空间分布规律和年内分布特征。[结果]渭河流域多年平均降雨侵蚀力值分布范围为806.25~3 510.81 MJ·mm/(hm2·h),平均值1 798.97 MJ·mm/(hm2·h),与多年平均侵蚀性降雨的空间分布基本一致,总体呈现西北低东南高的趋势。渭河流域降雨侵蚀力年内变化呈单峰型,主要集中在7—9月,占全年降雨侵蚀力的63.91%。北部黄土高原地区和关中平原发生水土流失的时期集中在7—9月,而秦岭北麓地区5—10月均有可能发生较大的水土流域,侵蚀风险由西北向东南递增。流域降雨侵蚀力年际波动较大,年际变率Cv值在34%~56%之间,整体而言,流域西北部地区的降雨侵蚀力年际变化幅度大于东南部地区。除洛川、长武、环县、平凉4个站点降雨侵蚀力在研究时段内有所增大外,其余地区降雨侵蚀侵蚀力呈不同速率的减小趋势。[结论]渭河流域降雨侵蚀力时空分布差异显著,尽管流域降雨侵蚀力呈减弱趋势,由于流域地处黄土高原,水土保持与水源涵养工作仍需高度重视。     

赣南九曲水流域降雨侵蚀力变化规律及其影响因素

为有效防治流域土壤侵蚀、维护生态安全,基于九曲水流域1982—2019年逐日降雨数据,运用小波分析、交叉小波变换等方法分析了中雨、大雨、暴雨及年降雨侵蚀力的年际变化规律,并探讨了太阳黑子、厄尔尼诺—南方涛动（ENSO）、北极涛动（AO）及太平洋年代际涛动（PDO）对它们的影响。结果表明：（1）中雨、大雨、暴雨及年降雨侵蚀力的年际变化趋势均不显著（p>0.05）,其变异系数（C_V）分别为0.24,0.31,0.64,0.26,均属于中等变异。（2）不同量级降雨侵蚀力的周期变化差异明显,年降雨侵蚀力与暴雨侵蚀力均存在15~23年周期变化和19年主周期,二者联系更紧密。（3）年降雨侵蚀力和暴雨侵蚀力与太阳黑子、ENSO、AO、PDO均分别存在9~11,10~11,10~11,9~10年的显著共振周期,暴雨侵蚀力受太阳黑子、ENSO、PDO的影响大于中雨、大雨侵蚀力,大雨侵蚀力受AO的影响大于中雨、暴雨侵蚀力。研究成果可为赣南乃至我国土壤侵蚀预测预报与防治提供科学依据。     

大同市降雨侵蚀力时间变化特征分析

 为适时地采取侵蚀的预防措施,采用基于日降雨量的半月降雨侵蚀力计算方法、气候趋势系数法、降雨集聚指数法等,对大同市年降雨侵蚀力的变化特征、年内降雨侵蚀力变化特征进行分析。结果显示:大同市年降雨侵蚀力具有周期波动特征,趋势系数显示大同市区每10年降雨侵蚀力上升21.8MJ.mm.hm-2.h-1,其他县区每10年降雨侵蚀力具有不同程度的减少趋势。年内分析结果显示,大同市降雨侵蚀力主要分布在6—9月,集聚指数介于20.85～23.67之间,均大于均匀分布时8.3的水平。     

A detailed reconstruction of changes in the factors and parameters of soil erosion over the past 250 years in the forest zone of European Russia (Moscow region)

Accelerated soil erosion is a major threat to soil, and there are great variations in the rate of soil erosion over time due to natural and human-induced factors. The temperate forest zone of Russia is characterized by complex stages of land-use history (i.e. active urbanization, agricultural development, land abandonment, etc.). We have for the first time estimated the rates of soil erosion by the WaTEM/SEDEM model (rainfall erosion) and by a regional model (snowmelt erosion) over the past 250 years (from 1780 to 2019) for a 100-km² study site in the Moscow region of Russia. The calculations were made on the basis of a detailed historical reconstruction of the following factors: the location of the arable land, crop rotation, the rain erosivity factor, and the maximum snow water equivalent. The area of arable land has decreased more than 3.5-fold over the past 250 years. At the end of the 20th century, the rates of gross erosion had declined more than 5.5-fold (from 28 × 10³ to 5 × 10³ t?ha^?1?yr^?1) in comparison with the end of the 18th century. Changes in the boundaries of arable land and also the relief features had led to a significant intra-slope accumulation of sediments. As a result of sediment redeposition within the arable land, the variation in net soil erosion was significantly lower than the variation in gross soil erosion. The changes in arable land area and in crop composition are the factors that have to the greatest extent determined the changes in soil erosion in this territory.