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.     

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 and erosivity density through rainfall synthetic series for São Paulo State,Brazil: Assessment,regionalization and modeling

Rainfall is the main cause of erosion of Brazilian soils, which makes assessing the rainfall erosivity factor (RE) and the erosivity density (ED) fundamental for soil and water conservation. Therefore, the objectives of this study were: i) to estimate the RE and ED for São Paulo State, Brazil, using synthetic series of pluviographic data; ii) to define homogeneous regions regarding rainfall erosivity; and iii) to generate regression models for rainfall erosivity estimates in each of the homogeneous regions. Synthetic series of pluviographic data were initially obtained on a sub-daily scale from the daily rainfall records of 696 rainfall gauges. The RE values were then estimated from the synthetic rainfall data, and ED was calculated from the relationship between erosivity and rainfall amounts. Monthly and annual maps for RE and ED were obtained. Hierarchical clustering analysis was used to define homogeneous regions in terms of rainfall erosivity, and regionalized regression models for estimating RE were generated. The results demonstrate high spatial variability of RE in São Paulo, where the highest annual values were observed in the coastal region. December to March concentrate approximately 60% of the intra-annual erosivity. The highest values of annual ED were observed in regions with intense agricultural activity. The definition of five homogeneous regions concerning the rainfall erosive potential evidenced distinct seasonal patterns of the spatial distribution of erosivity. Finally, the high predictive accuracy of the regionalized models obtained characterizes them as essential tools for reliable estimates of rainfall erosivity, and contribute to better soil conservation planning.     

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。     

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%。     

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.     

基于重心模型的西南山区降雨侵蚀力年内变化分析

降雨-植被耦合特征是决定土壤侵蚀的关键性要素,研究降雨侵蚀力的年内变化特征对于揭示不同区域降雨-植被的耦合特征、判定土壤侵蚀的危险期具有重要意义。该文利用中国西南山区439个气象站、水文站的逐日降雨量资料,估算了每个台站逐月降雨侵蚀力,并应用重心模型分析了西南山区降雨侵蚀力的年内变化特征。研究结果表明:西南山区春、夏、秋、季四季降雨侵蚀力变化明显,夏季最高,冬季最低。各季节的降雨侵蚀力空间分布与降水量相似,都表现出东南向西北逐渐递减的趋势。降雨侵蚀力年内分配曲线主要有"单峰型"和"双峰型"2种,绝大多数地区降雨侵蚀力年内分配曲线是"单峰型",峰值出现在6月、7月或8月份,青藏高原区域降雨侵蚀力年内分配曲线是"双峰型",有6月和9月2个峰值。从东南部向西北部,降雨侵蚀力峰值出现的月份不断推后。西南山区降雨侵蚀力重心年内先向北迁移,然后向南迁移,形成一个循环,这展示了季风气候影响下的西南山区降雨侵蚀力年内变化特征。     

The WEELS model: methods, results and limitations

Within the European Union (EU)-funded Project ‘Wind Erosion on European Light Soils’ (WEELS), a model was designed and implemented with the aim of predicting the long-term spatial distribution of wind erosion risks in terms of erosion hours and wind-induced soil loss. In order to ensure wide applicability, the model structure consists of a modular combination of different approaches and algorithms, running on available or easily collected topographic and climatological data input. Whereas the ‘WIND’, ‘WIND EROSIVITY’ and ‘SOIL MOISTURE’ modules combine factors that contribute to the temporal variations of climatic erosivity, the ‘SOIL ERODIBILITY’, ‘SURFACE ROUGHNESS’ and ‘LAND USE’ modules predict the temporal soil and vegetation cover variables that control soil erodibility. Preliminary simulations over a 29-year period for the Barnham site (UK) (1970–1998) and a 13-year period for the Grönheim site (Germany) (1981–1993) generally resulted in a higher erosion risk for the English test site, where the total mean soil loss was estimated at 1.56 t ha⁻¹ year⁻¹ and mean maximum soil loss at about 15.5 t ha⁻¹ year⁻¹. The highest rates exceeded 3 t ha⁻¹ in March, September and November. On the northern German test site, the total mean soil loss was 0.43 t ha⁻¹ year⁻¹. The highest erosion rates were predicted in April when they can exceed 2.5 t ha⁻¹. The total mean maximum soil loss at this site of about 10.0 t ha⁻¹ year⁻¹ corresponds to a loss of about 0.65 mm. Predictions based on a land use scenario for the German site revealed that the erosion risk could be reduced significantly by changing land use strategies.     

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.     

试验研究三峡库区大宁河流域降雨侵蚀力的时空变化

[目的]分析流域降雨侵蚀力时空变化规律,为水土流失预报及水土保持措施科学配置提供依据。[方法]以三峡库区大宁河流域内13个雨量站41 a 日降雨资料为基础,采用侵蚀力简易模型,分析了该流域降雨侵蚀力的年内分配和年际变化规律,并在软件 ArcGIS 10．2支持下,探讨流域降雨侵蚀力时空变化特征。[结果]大宁河流域年均降雨侵蚀力为7245．55 MJ ? mm／（hm2? h ? a）,它在空间上与流域降雨分布特征基本一致,呈现由东、西向流域中部逐渐减小的趋势,而南北差异较小;最大和最小降雨侵蚀力分别位于流域西北部的建楼站和南部的巫山站;降雨侵蚀力多年变化范围为3619．55～11109．14 MJ ? mm／（hm2? h ? a）。降雨侵蚀力的年内分布呈双峰型,集中程度高,4—10月占全年的95％。[结论]大宁河流域降雨侵蚀力和降雨变化年内分配一致,侵蚀力时空特征除与流域降雨量分布密切相关外,还与区域降雨格局及地形地貌等因素有关。     

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.     

基于日降雨的沂蒙山区降雨侵蚀力时空变化研究

降雨侵蚀力是水土流失最为重要的外部驱动力,是土壤侵蚀相关领域的研究重点。以沂蒙山区及周边38个气象台站1971—2008年逐日降雨量资料为数据源,利用基于日降雨信息的月降雨侵蚀力模型,估算了研究区多年月、年降雨侵蚀力,并初步分析了降雨侵蚀力的时空分布规律。结果表明:沂蒙山区降雨侵蚀力总体趋势为西北、中南高,北部低,泗水县、曲阜市东部一带是研究区降雨侵蚀力的高值中心;R值与年降雨量和年侵蚀性降雨量的年际变化趋势基本一致,但也有部分异常年份;沂蒙山区降雨侵蚀力年内主要集中分布在6—9月份,占全年的97.07%,其中最大月降雨侵蚀力出现在7月份,占年降雨侵蚀力的51%。研究结果可为该区域水土流失预报、农业面源污染状况预报等提供理论依据。     

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。     

Factors affecting runoff and erosion under simulated rainfall in Mediterranean vineyards

Data on surface runoff and soil loss on gentle slopes with vineyards are analysed. Using a rainfall simulator, 22 rainstorms with varied intensities from 30 to 117.5 mm h⁻¹ and return periods from 2 to 127 years were reproduced. The experimental plots were installed on vineyards planted in straight rows and oriented with the slope direction having a mean gradient of 3.8°. The texture of soils was loamy, with a very heterogeneous surface gravel cover. Values of measured surface runoff varied from 7.2 mm h⁻¹ for low rainfall intensities (30 mm h⁻¹) and short return periods (2 years) to 41.9 mm h⁻¹ with simulation experiments of higher rainfall intensity (104 mm h⁻¹) and long return periods (68 years). Runoff increased linearly with rainfall intensity resulting in soil losses that also increased with rainfall intensity (18.2 g m⁻² h⁻¹ with storms of 30 mm h⁻¹, and 93.2 g m⁻² h⁻¹ with storms of 104 mm h⁻¹); however, r² explains only 36% of the variance. It was necessary to add other factors to improve the coefficient of determination (0.74; p = 0.001) and the predictive function of the equation. These variables were rainfall intensity, kinetic energy of the storm, runoff, soil resistance to drop detachment, surface gravel cover, and gradient. The equation obtained was validated with the USLE-M. In comparison with similar experiments in other regions, the results obtained for soil loss were very moderate, especially those caused by rainstorms of intermediate and low intensity.     

日照市降雨侵蚀力时空分布特征

为掌握山东省日照市降雨侵蚀力时空分布特征,提高日照市水土保持规划与决策的科学性,利用日照市水利局雨量遥测系统61个雨量站点2005-2014年日降雨资料计算降雨侵蚀力,并运用Excel 2013、ArcGIS 10等工具分析日照市降雨侵蚀力的时空分布特征.结果表明:1)从年度变化来看,日照市站均年度降雨侵蚀力最大值(2008年)是最小值(2014年)的2.90倍,站均汛期降雨侵蚀力最大值(2007年)是最小值(2014年)的3.74倍.从月度变化来看,降雨侵蚀力主要集中在5-9月,尤其集中在7-8月.2)从空间分布来看,各站点年均降雨侵蚀力、汛期降雨侵蚀力呈现东南沿海地区较高、内陆地区较低、中部地区最低的特征,变化范围分别在2 942.07 ～4 921.45、2 694.36～3 921.78 MJ· mm/(hm2·h·a)之间,分区县看,岚山区最高,东港区次之,莒县和五莲县较低;各月的降雨侵蚀力重点也不尽相同.3)从时间变异来看,站均年度降雨侵蚀力变化范围在1 831.55 ～5 306.12 MJ·mm/(hm2·h·a)之间,均值、中值分别为3 826.01、4 053.62 MJ·mm/(hm2·h·a),标准差1 089.46MJ·mm/(hm2·h·a),变异系数28.48％;站均月度降雨侵蚀力变化范围在1.23 ～1 171.93 MJ·mm/(hm2·h·a)之间,均值、中值分别为318.83、61.51 MJ·mm/(hm2·h·a),标准差397.99 MJ· mm/(hm2·h·a),变异系数124.83％.4)从空间变异来看,各站年均降雨侵蚀力变化范围在2 755.23 ～5 061.15 MJ·mm/(hm2·h·a)之间,均值、中值分别为3 826.01、3 730.97 MJ·mm/(hm2·h·a),标准差512.81 MJ·mm/(hm2·h·a),变异系数13.40％.本研究结果可为日照市水土保持规划与决策、土壤侵蚀预报等提供参考.     

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。     

基于不同模型的黄河中游降雨侵蚀力时空变化分析

[目的] 基于不同模型探究黄河中游地区降雨侵蚀力的时空演变特征,为该地区水土流失危害评估、水土保持措施规划提供参考依据。[方法] 采用黄河中游1981—2020年日降雨量数据集,基于两种降雨侵蚀力模型探究了降雨和降雨侵蚀性的时空变化特征。 [结果] 黄河中游年均降雨量为349.90～699.90 mm,空间上自东南向西北呈波浪形递减趋势,时间上呈多峰状不显著的波动上升趋势特征,存在2 a主周期变化特征。黄河中游两种模型的降雨侵蚀力年际变化趋势特征和周期性相似,但降雨量越大的地区,两模型估算的降雨侵蚀力结果相差越大。谢云模型估算的降雨侵蚀力结果与降雨量相对更拟合。黄河中游年均降雨侵蚀力为767.00～3 003.40 MJ·mm/(hm²·h),具有高度月度集中性,集中于7—8月,呈单峰型。 [结论] 黄河中游年均降雨侵蚀力具有显著的垂直空间差异,且在地形和地貌影响下空间差异会发生变化,高海拔地区的变化系数通常高于低海拔地区。在东南部秦岭山区和关中平原等地区,随海拔升高,降雨侵蚀力迅速减少,在西北部黄土高原区,随海拔升高而逐渐增加。因此在黄河中游降雨侵蚀性增加的地区,应采取适当措施,减少土壤侵蚀的潜在风险,确保区域生态安全的可持续发展。     

贵州省降雨侵蚀力时空分布规律分析

降水是导致土壤侵蚀的主要动力因素,降雨侵蚀力反映了降雨对土壤侵蚀的潜在能力。贵州省是我国典型的生态环境脆弱区之一,水土流失十分严重。以全省19个气象台站1951—2001年逐日降雨资料,利用日降雨侵蚀力模型,估算了贵州省降雨侵蚀力,分析了其时空分异规律。结果显示近50a来贵州省降雨侵蚀力呈增加趋势,即由降雨引起的土壤水蚀潜在能力增加。降雨侵蚀力年内分配主要集中在夏季,占年均降雨侵蚀力的68.48%。在空间分布上,降雨侵蚀力由南向北递减,并且在西南部和东南边缘形成侵蚀力高值中心,在西北部形成低值中心。根据年降雨侵蚀力的季节分配特征,可以将贵州省划分为3个类型区。     

Temporal variability of rainfall in a semiarid environment in Brazil and its effect on sediment transport processes

Purpose

The temporal variabilities of both soil erosion by water and sediment redistribution in watersheds are directly related to rainfall characteristics. The purpose of this work was to assess the temporal pattern of rainfall in a semiarid watershed in Brazil and explain how this feature controls soil erosion and sediment yield.

Materials and methods

Daily and 5-min rainfall records were used to assess the temporal pattern down to the sub-hourly scale. To study the effect of the rainfall on sediment processes, erosivity and sediment yield at the Aiuaba (12 km²) and Benguê (933 km²) watersheds, Brazil were determined. Erosivity was calculated based on the rainfall kinetic energy method, while sediment yield was estimated from sediment rating curves and daily water discharge measurements.

Results and discussion

A large portion of annual rainfall is restricted to a few rain events and strong concentration in the sub-daily scale occurs, producing high erosivity. The temporal concentration of erosivity is greater than that of rainfall; the 10th percentile of the highest magnitude events encompasses 51% of the precipitation, but 80% of the erosivity. The temporal concentration of sediment yield is more pronounced; 88 and 98% of the sediment yield for the Aiuaba and Benguê watersheds, respectively, are within the 10th percentile of events.

Conclusions

The strong temporal concentration of precipitation causes events with high intensity and erosivity, thus allowing for soil detachment. Nonetheless, the low runoff rates limit downstream sediment transport. Such behavior produces a much higher temporal concentration of sediment yield, which reaches its maximal after a sequence of rainy days, when hydrological connectivity is enhanced and the sediments are propagated throughout the entire transport-limited system.     

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。