Estimation of rainfall erosivity using 5- to 60-minute fixed-interval rainfall data from China

The 30-min rainfall erosivity index (EI₃₀) is commonly used in the Universal Soil Loss Equation for predicting soil loss from agricultural hillslopes. EI₃₀ is calculated from the total kinetic energy and the maximum 30-min rainfall intensity of a storm. Normally, EI₃₀ values are calculated from breakpoint rainfall information taken from continuous recording rain gauge charts, however, in many places in China and other parts of the world the detailed chart-recorded rain gauge data relative to storm intensities are not readily available, while hourly rainfall is readily available. The objective of this study was to assess the accuracy of EI₃₀ estimations based on 5-, 10-, 15-, 30-, and 60-min time-resolution rainfall data as compared to EI₃₀ estimations from breakpoint rainfall information. 456 storm events from five soil conservation stations in eastern China were used. The values of EI₃₀ based on the fixed-time-interval data were less than those calculated from breakpoint data. The average conversion factors (ratio of values calculated from the breakpoint data to those from the fixed-interval data) for the five stations decreased from 1.105 to 1.009 for the estimation of E values, from 1.668 to 1.007 for I₃₀ values, and from 1.730 to 1.014 for EI₃₀ values as the time resolution increased from 60 to 5 min. The maximum 30-min rainfall intensity was the major source of error in estimating EI₃₀ for 60-min fixed-interval data, while storm kinetic energy played a proportionately more significant role as the fixed-interval data decreased from 60 to 5 min.     

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.     

黔西高原地区降雨侵蚀力的简易算法

[目的]对黔西高原地区侵蚀性降雨特性进行分析并探索降雨侵蚀力的简易算法,为该区土壤侵蚀预报模型的建立提供理论依据。[方法]利用径流小区观测法,基于毕节小区2012—2014年53次降雨过程资料进行分析。[结果](1)降雨量(P)和最大60min降雨动能(E60)是影响坡面产流、产沙的两个主要因子。坡面产流、产沙与最大60min雨强(I_(60))显著相关;(2)坡面产流产沙与二元复合因子的相关系数显示,EI_(60),PI_(60)和I30I_(60)是影响坡面产流、产沙的3类主要降雨复合指标,EI30和EI_(60)与坡面产流产沙的相关系数间相差较小;(3)基于坡面产流、产沙与降雨单指标和降雨复合指标的相关关系,确定了简易算法的参数。[结论]基于可比性,以R=EI30作为参照值对3种简易算法的结果进行决定系数和偏差率比较后,得到研究区便捷、快速的降雨侵蚀力简易算法为:R=0.344(PI_(60))。     

基于IMERG反演降水数据估算广东省降雨侵蚀力

近年来遥感反演降水产品的时空分辨率不断提高，为估算区域尺度上具有空间连续性的降雨侵蚀力提供了新的可能。但以往研究在应用遥感降水产品估算降雨侵蚀力时多忽略了其与站点观测数据间的差异和对其纠偏的可能性。该研究以广东省86个气象站2001—2020年的逐时降水资料估算的降雨侵蚀力为观测值，评估两套IMERG（integrated multi-satellite retrievals for GPM）遥感降水产品-GPM_3IMERGHH（0.1°，逐30-min）和GPM_3IMERGDF（0.1°，逐日）对广东省降雨侵蚀力的估算精度并量化偏差，再结合拟合纠偏确定基于遥感反演降水数据估算广东省降雨侵蚀力的最优方法。结果表明：这两套产品均不适宜直接估算降雨侵蚀力指标，不同时间尺度、不同方法直接应用时精度均较低，克林-古普塔效率系数（Kling-Gupta efficiency, KGE）小于等于0.51。但多年平均和极端次事件降雨侵蚀力与对应观测值间具有强相关性（皮尔逊相关系数大于等于0.78），具备纠偏的潜力。因此，本研究发展线性模型对IMERG估算结果进行纠偏，交叉验证结果表明纠偏后GPM_3IMERGHH估算多年平均降雨侵蚀力（R因子）的KGE可达0.79，10年一遇EI₃₀的KGE可达0.64，优于采用站点日降水估算降雨侵蚀力并插值的精度（KGE分别为0.60和0.59），与采用站点小时降水估算降雨侵蚀力并插值的精度相近（KGE分别为0.77和0.66）。当前研究结果充分展示了遥感反演降水在土壤水蚀领域的应用潜力和前景。     

Effect of time resolution of rainfall measurements on the erosivity factor in the USLE in China

Rainfall erosivity, one of the factors in the Universal Soil Loss Equation, quantifies the effect of rainfall and runoff on soil erosion. High-resolution data are required to compute rainfall erosivity, but are not widely available in many parts of the world. As the temporal resolution of rainfall measurement decreases, computed rainfall erosivity decreases. The objective of the paper is to derive a series of conversion factors as a function of the time interval to compute rainfall erosivity so that the R factor computed using data at different time intervals could be converted to that computed using 1-min data. Rainfall data at 1-min intervals from 62 stations over China were collected to first compute the ‘true’ R factor values. Underestimation of the R factor was systematically evaluated using data aggregated at 5, 6, 10, 15, 20, 30, and 60-min to develop conversion factors for the R factor and the 1-in-10-year storm EI₃₀ values. Compared with true values, the relative error in R factor using data at fixed intervals of ≤10min was <10% for at least 44 out of 62 stations. Errors increased rapidly when the time interval of the rainfall data exceeded 15 min. Relative errors were >10% using 15-min data for 66.1% of stations and >20% using 30-min data for 61.3% of stations. The conversion factors for the R factor, ranging from 1.051 to 1.871 for 5 to 60-min data, are higher than those for the 1-in-10-years storm EI₃₀, ranging from 1.034 to 1.489 for the 62 stations.     

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。     

北约旦地区降水侵蚀因子的近似估算研究

Despite being in arid and semi-arid areas, erosion is largely a result of infrequent but heavy rainfall events; therefore, rainfall erosivity data can be used as an indicator of potential erosion risks. The purpose of this study was to investigate the spatial distribution of annual rainfall erosivity in North Jordan. A simplified procedure was used to correlate erosivity factor R values in both the universal soil loss equation (USLE) and the revised universal soil loss equation (RUSLE) with annual rainfall amount or modified Fournier index (F_mod). Pluviometric data recorded at 18 weather stations covering North Jordan were used to predict R values. The annual values of erosivity ranged between 86-779 MJ mm ha^-1 h^-1 year^-1. The northwest regions of Jordan showed the highest annual erosivity values, while the northeastern regions showed the lowest annual erosivity values.     

Effects of slope length on runoff from alfisols in Western Nigeria

The effects of 5, 10, 15 and 20 m slope lengths were investigated on runoff for natural slope gradients of about 1, 5, 10 and 15%. These studies were conducted on field runoff plots on natural slopes and under natural rainfall conditions at Ibadan in western Nigeria. The runoff, based on individual rainfall events, was not significantly correlated with either of three erosivity indices (EI₃₀, KE > 1, AI_m) and only a maximum of 36% of variability in runoff could be attributed to rainfall erosivity. Runoff per unit area decreased with increase in slope length. The mean annual runoff was of the order of 100, 87, 80 and 69 for 1977 and 100, 66, 49 and 35 for 1978 for 5, 10, 15 and 20 m slope lengths, respectively. Regression analyses indicated that the annual runoff was related to slope length according to the regression equation W = 773 L^?0?53, where W is annual runoff in mm and L is slope length in meters. When fitted to data from all plots on a given slope steepness, for individual years the numerical value of length exponent b ranged from 0.153 to ?0.865.     

Magnitude and Occurrence Probability of Soil Loss: A Risk Analytical Approach for the Plot Scale For Two Sites in Lower Austria

Long‐term contribution of soil loss events depends on both – the magnitude and the occurrence probability – but oftentimes, a limited observation period impedes the assessment of the temporal soil loss distribution. In this research, the event‐based soil loss from two plot locations in Lower Austria (Mistelbach and Pixendorf) was linked with the event‐based rainfall erosivity (EI₃₀) to assess the temporal soil loss distribution using long‐term rainfall data from two meteorological stations in Lower Austria. For both plot locations, a risk analysis was performed to (i) assess the long‐term average annual soil loss and to (ii) evaluate the contribution of incremental erosion events according to different event return periods. The risk analysis showed that in Pixendorf the events <20 years return period dominatingly contribute to long‐term soil loss, because the contribution of the events >20 years return period is progressively reduced through the low occurrence probability. On the contrary, in Mistelbach the soil loss magnitudes of the extreme events overcome the effect of the low occurrence probability, and consequently, the contribution of the extreme events (>20 years return period) is dominant. The spatially variable contribution of the erosion events reveals the need for spatially customized soil conservation strategies. A risk analytical approach may help to allocate the driving events and thus to define proper event design magnitudes for local soil conservation planning. Copyright © 2014 John Wiley & Sons, Ltd.     

Soil erosion on Alfisols in Western Nigeria: III. Effects of rainfall characteristics

The applicability of various erosivity indices was tested for runoff and soil loss from plowed bare-fallow field runoff plots of 25 × 4 m established on an Alfisol with natural slopes of 1, 5, 10 and 15%. The correlation coefficients of percent runoff from individual rainstorms with various indices such as kinetic energy (E), EI₃₀, KE > 1, rainfall amount (A), maximum intensity (I_m), and AI_m, were generally low. The correlation coefficients of all these indices with soil loss per storm were high and did not differ significantly from one another. The use of an empirical relation (kinetic energy = 916 + 331 log₁₀, I is in inches/h) may underestimate the kinetic energy of tropical rainstorms. The kinetic energy of tropical rainstorms may be significantly influenced by other factors such as wind velocity, drop size distribution and high rainfall intensity. The index AI_m has the advantage of simplicity of computation, and it incorporates one of the most important factors, peak intensity (I_m). Further improvements can be made in this index by incorporating a factor which accounts for the kinetic energy of a rainstorm. In the meantime, the index, AI_m, may be used to prepare an “iso-erodant” map, i.e. places with equal erosion potential. There also exists a linear correlation between rainfall amount per storm and AI_m. Such a relationship may be useful in estimating AI_m for regions where data from recording rain gauges are not available.     

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.     

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.     

Natural disaster in the mountainous region of Rio de Janeiro state,Brazil: Assessment of the daily rainfall erosivity as an early warning index

Rainfall erosivity is defined as the potential of rain to cause erosion. It has great potential for application in studies related to natural disasters, in addition to water erosion. The objectives of this study were: i) to model the R_day using a seasonal model for the Mountainous Region of the State of Rio de Janeiro (MRRJ); ii) to adjust thresholds of the R_day index based on catastrophic events which occurred in the last two decades; and iii) to map the maximum daily rainfall erosivity (R_maxday) to assess the region's susceptibility to rainfall hazards according to the established R_day limits. The fitted R_day model presented a satisfactory result, thereby enabling its application as a R_day estimate in MRRJ. Events that resulted in R_day > 1500 MJ ha^?1.mm.h^?1. day^?1 were those with the highest number of fatalities. The spatial distribution of R_maxday showed that the entire MRRJ has presented values that can cause major rainfall. The R_day index proved to be a promising indicator of rainfall disasters, which is more effective than those normally used that are only based on quantity (mm) and/or intensity (mm.h^?1) of the rain.     

红壤区裸露坡地不同类型次降雨的产流产沙规律

为探究红壤区裸露坡地在不同类型次降雨下的产流产沙规律,研究收集长汀县水土保持科教园红壤裸露坡地径流小区2013年1月至2020年12月共388场降雨—径流—土壤侵蚀观测资料,采用K-means将降雨划分为4类进行分析。结果表明:(1)主要降雨类型有A(短历时、大雨强、小雨量、低频次)、B(长历时、小雨强、大雨量、中频次)、C(中等历时、小雨强、小雨量、高频次)3类,B、C为研究区主要产流产沙来源,贡献85%以上的径流和土壤侵蚀量。(2)次降雨径流深及土壤侵蚀量与降雨量(P)、最大30 min雨强(I₃₀)和降雨动能(E)呈线性正相关,与降雨侵蚀力(EI₃₀)呈幂函数关系。但降雨特征对产流产沙的总解释度小于65%,且随着降雨历时的增加而减小。(3)降雨特征与产流产沙存在3种约束关系,其约束线表明降雨特征对次降雨潜在最大产流产沙的影响。其中,潜在最大径流深主要由P和E决定,潜在最大土壤侵蚀量的上限为800~900 t/hm²。从降雨特征单因子影响、综合影响和约束效应3个方面分析了红壤裸露坡地的产流产沙特征,为红壤区水土流失防治提供了数据基础。     

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。     

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。     

北京市降雨侵蚀力及其空间分布

 通过对北京地区20个气象站雨量资料的回归分析,发现可用公式R=5.2562F1.3057F来估算北京的降雨侵蚀力,其中FF是由逐月雨量计算而来的一种指标。用此公式计算了北京113个站点的R值,绘制了降雨侵蚀力等值线图,发现北京的R值变化于2144.0～6682.7MJ·mm·hm-22·h-1·a-1。由北部和西部山地所组成的弧形山脉R值最高,并呈现向西北、东南方向递减的趋势。研究结果可为北京的水土保持规划和评价提供依据。     

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.     

沂河流域1961-2010年降雨侵蚀力时空分布特征

[目的]分析沂河流域近50 a的降雨量和降雨侵蚀力的时空变化特征,为流域水土流失防治及土地利用合理规划等工作提供参考.[方法]利用沂河流域及周边12个气象站1961-2010年的日降雨数据,基于日降雨信息的月降雨侵蚀力模型计算流域多年平均降雨侵蚀力,采用Mann-Kendall非参数检验法及析取Kriging内插法分析流域降雨量和降雨侵蚀力的时空变化特征.[结果]沂河流域降雨量和降雨侵蚀力空间分布上呈现出由西南向北逐级递减的变化趋势.多年平均降雨量为789.41 mm,多年平均降雨侵蚀力为2 626.09(MJ·mm)/(hm2·h·a),两者都在1965年产生突变;降雨量和降雨侵蚀力年内分布主要集中在夏季(6-8月),分别占全年比例的63.02％和71.22％,二者最大值都出现在7月,且秋季对流域多年降雨量的减少趋势贡献最多,夏季的降雨侵蚀力上升幅度最大.[结论]沂河流域的降雨量和降雨侵蚀力空间分布趋势相似,不同月份的降雨量与降雨侵蚀力差异不同.