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.     

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.     

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。     

黑龙江省降雨侵蚀力空间分布规律

利用黑龙江省16个国家级气象站,1960-2000年日降雨量资料,分析黑龙江省侵蚀性降雨和降雨侵蚀力的空间分布规律。在16个气象站中,日降雨量达到侵蚀性标准（≥12mm／d）的降雨时间为9～15d／a,最大值同最小值之间相差近0．7倍;日降雨量达到侵蚀性标准的年降雨量为192～387mm,最大值同最小值之间相差l倍。16个气象站年降雨侵蚀力多年平均值为794～2144MJ·mm／（hm^2·h·a）,最大值同最小值之间相差近2倍。降雨侵蚀力空间分布从西北到中南部逐渐升高,东部低于中部,年降雨侵蚀力空间分布基本与年降雨量空间分布相似。年内降雨侵蚀力分布主要集中在6—9月,7月份下半月或8月份上半月达到最高值,6—9月降雨侵蚀力占全年比率为88％～95％,其中西部比东部略高。     

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.     

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。     

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。     

Effect of land management on runoff and soil losses from two small watersheds in St Lucia

The influence of land use on runoff and soil loss was assessed on two small watersheds in the Eastern Caribbean island of St Lucia, under contrasting land management regimes. The data generated from these watersheds revealed that the soil losses from an intensively cultivated agricultural watershed were 20‐times higher in magnitude than that of a forested watershed both for peak rainfall event and for total duration of analysis. This was due to higher surface runoff rates and exposure of soil to direct raindrop impact within cultivated areas. Whereas the forest canopy cover in combination with higher infiltration capacities of the forested land reduced the erosive runoff from the forest watershed and thus the soil loss. Moreover, the energy intensities of large storms in excess of 40 mm were estimated and found to range between 400 MJ mm ha⁻¹ h⁻¹ and 1834 MJ mm ha⁻¹ h⁻¹. 1

1 Megajoules‐millimeters per hectare‐hour.

Soil loss from the agricultural watershed was strongly correlated (R² = 0·85) to storm energy‐intensity (EI₃₀). However, the correlation of soil loss with the EI₃₀ (R² = 0·71) was poor for the forest watershed due to the effect of canopy vegetation, which significantly reduced the energy of raindrop impact. Over the study period, cumulative soil losses were 10·0 t ha⁻¹ for the agricultural site and 0·5 t ha⁻¹ for the forest site. 2

2 Metric tons per hectare.

The largest storm observed during the study period resulted in erosion losses of 3·78 t ha⁻¹ and 0·2 t ha⁻¹ from the agricultural and forest sites respectively. The regression models were developed using the measured data for prediction of runoff and soil loss over the watersheds of St Lucia under similar conditions. This study contributed towards efficient watershed management planning and implementation of suitable water conservation measures in St Lucia. Copyright © 2005 John Wiley & Sons, Ltd.     

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。     

基于GIS的白洋淀流域降雨侵蚀力时空分布特征分析

为分析白洋淀流域降雨侵蚀力的时空分布特征,利用白洋淀流域及周边64个气象站点2003—2018年的日雨量资料,采用日雨量模型、线性逐步回归、倾向率、Mann-Kendall突变检验以及克里金插值等方法进行了研究。结果表明：(1)白洋淀流域年均降雨侵蚀力为2 284.54 (MJ·mm)/(hm²·h),西南阜平县和东北霞云岭降雨侵蚀力较大,在东南—西北方向上呈先增后降趋势。(2)气象站点降雨侵蚀力与经纬度、海拔的关系为：降雨侵蚀力=-0.115×纬度+0.414×经度-0.235×海拔,降雨侵蚀力与纬度、海拔呈负相关,与经度呈正相关。(3)降雨侵蚀力年内分布中,夏季较大,平均1 826.75 (MJ·mm)/(hm²·h),冬季较小,平均1.77 (MJ·mm)/(hm²·h);降雨侵蚀力年际分布中,2011—2014年较大,平均2 584.82 (MJ·mm)/(hm²·h);2003—2006年较小,平均2 053.79 (MJ·mm)/(hm²·h)。(4)降雨侵蚀力时间...     

黄土高原降雨侵蚀力时空分布

降雨侵蚀力时空分布规律定量研究是进行土壤侵蚀预报的基础。利用231个气象站多年平均年雨量资料估算了黄土高原地区多年平均降雨侵蚀力,并绘制了等值线图。利用17个气象站日雨量和日雨强资料估算了半月降雨侵蚀力及其年内分配特征。全区降雨侵蚀力变化于327~4416MJ.mm/(hm2.h.a)之间,等值线图显示降雨侵蚀力的空间分布与年降水量的空间分布规律十分相似,大致从东南向西北递减。半月降雨侵蚀力占年侵蚀力的累积频率表,为估算土壤侵蚀方程中土壤可蚀性因子和植被覆盖—管理因子提供了基础。侵蚀力年内分配集中度指标反映出黄土高原R值年内分配集中度很高,且多集中在6—9月,集中度最大的达96.4%,最小的也有66.9%。     

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.     

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.     

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。     

1980-2009年闽东南地区降雨侵蚀力的时空分布特征

[目的]揭示闽东南地区降雨侵蚀力的时空变异特征,为区域水土流失防治及水土保持规划提供依据。[方法]基于闽东南地区1980—2009年26个雨量站的逐日降雨数据,运用福建省降雨侵蚀力简易算法。[结果]闽东南地区降雨侵蚀力年内分布集中于5—8月,呈现双峰式分布;降雨侵蚀力年际间变化幅度较大。1982年年降雨侵蚀力(R值)低至253.82(MJ·mm)/(hm2·h),2006年R值高达725.39(MJ·mm)/(hm2·h),极值比为2.86;30a内的闽东南地区的降雨侵蚀力并未出现明显的突变现象。[结论]研究区内降雨侵蚀力R值空间分布不均匀,总体上呈现沿海向内陆增加,西南高东北低的趋势。     

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。     

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。     

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.     

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9 314(MJ·mm)/(hm~2·h·a),变异系数为0.29,属于中等变异;(2)年降雨量、降雨日数、侵蚀性降雨量和降雨日数均呈上升趋势,而非侵蚀性降雨量和降雨日数则呈下降趋势,且暴雨量和暴雨侵蚀力呈较明显上升趋势,说明韶关市降雨更为集中,降雨侵蚀力增加;(3)大雨以上量级的降雨日数和降雨量占总降雨日数和总降雨量的比例分别为43.91%,51.15%,而其引起的降雨侵蚀力占总降雨侵蚀力比例却高达77.05%。研究结果为韶关市的土壤侵蚀的监测和水土保持工作提供参考。