Estimation of soil erosion using RUSLE in a GIS framework: a case study in the Buyukcekmece Lake watershed,northwest Turkey

This study was aimed at predicting soil erosion risk in the Buyukcekmece Lake watershed located in the western part of Istanbul, Turkey, by using Revised Universal Soil Loss Equation (RUSLE) model in a GIS framework. The factors used in RUSLE were computed by using different data obtained or produced from meteorological station, soil surveys, topographic maps, and satellite images. The RUSLE factors were represented by raster layers in a GIS environment and then multiplied together to estimate the soil erosion rate in the study area using spatial analyst tool of ArcGIS 9.3. In the study, soil loss rate below 1 t/ha/year was defined as low erosion, while those >10 t/ha/year were defined as severe erosion. The values between low and severe erosion were further classified as slight, moderate, and high erosion areas. The study provided a reliable prediction of soil erosion rates and delineation of erosion-prone areas within the watershed. As the study revealed, soil erosion risk is low in more than half of the study area (54%) with soil loss <1 t/ha/year. Around one-fifth of the study area (19%) has slight erosion risk with values between 1 and 3 t/ha/year. Only 11% of the study area was found to be under high erosion risk with soil loss between 5 and 10 t/ha/year. The severe erosion risk is seen only in 5% of the study area with soil loss more than 10 t/ha/year. As the study revealed, nearly half of the Buyukcekmece Lake watershed requires implementation of effective soil conservation measures to reduce soil erosion risk.     

Spatial estimation of soil erosion risk using RUSLE/GIS techniques and practices conservation suggested for reducing soil erosion in Wadi Mina watershed (northwest,Algeria)

The Wadi Mina Watershed, western area of Algeria is characterized by rare and irregular rains and a fragile and weak vegetable cover. The sediments resulting from erosion are transported and contributed to silting dam Sidi Mhamed Benaouda. The combination of the thematical maps of the various erosive factors according to the Revised Universal Soil Loss Equation (RUSLE) in SIG by ArcGIS 10.2 software provided a reliable forecast of the annual rates of soil loss by delimiting the areas prone to erosive risk in the catchment above mentioned. The estimated potential average annual soil loss is 11.2 t/ha/yr., and the potential erosion rates from recognized erosion classes ranged from 0.0 to plus 100 t/ha/yr. About 50% of the catchment area was predicted to have very low to low erosion risk, with soil loss between 0 and 7.4 t/ha/yr. Erosion risk is moderate over 13.9% of the catchment, where calculated soil loss is between 7.4 and 12 t/ha/yr. Erosion risk is high to dangerous over 36.1% of the catchment, where calculated soil loss is more than 12 t/ha/yr. According to this study, it appeared clearly that we must intervene quickly by using reliable and effective conservation techniques.     

Spatio-temporal changes in rate of soil loss and erosion vulnerability of selected region in the tropical forests of Borneo during last three decades

An attempt has been made to analyze the spatial-temporal characteristics of soil erosion vulnerability and soil loss from the forested region in the north-eastern Borneo, Sarawak, Malaysia during the last three decades (1991–2015) using the revised universal soil loss equation (RUSLE) and geographical information systems (GIS). The components of RUSLE such as rainfall erosivity (R), soil erodibility (K), slope-length and steepness (LS), cover management (C) and conservation practice (P) factors were grouped into two categories by keeping one set as temporally changing and others as static. Among them the R and C factors are calculated for the years 1991, 2001 and 2015 whereas the K and LS factors are considered for the single time frame. Because of the forested nature of the study area, the P factor is kept constant for the whole analysis. The R factor and C factor is shown changes in values and its distribution over the years, which reflected in the final soil loss and erosion vulnerability map as a change in the rate of erosion and spatial domain. The analysis of three time slices has shown that the maximum value of the soil loss per unit area i.e. at erosion hotspots, is relatively similar throughout at around 1636 to 1744 t/ha/y. This is the result of maximum values of R factor and C factor i.e. high rainfall erosivity combined with lack of vegetation cover in those hotspots, which are generally steeply sloping terrain. The reclassification of annual soil loss map into erosion vulnerability zones indicated a major increase in the spatial spread of erosion vulnerability from the year 1991 to 2015 with a significant increase in the high and critical erosion areas from 2.3% (1991) to 31.5% (2015). In 1991, over 84% of the study area was under low erosion vulnerability class but by the year 2015 only 12% was under low erosion vulnerability class. Moreover, a dynamic nature in the erosion pattern was found from the year 1991 to 2015 with more linear areas of land associated with higher rate of soil loss and enhanced erosion vulnerability. The linearity in the spatial pattern is correlated with the development of logging roads and logging activities which has been confirmed by the extraction of exposed areas from satellite images of different years of analysis. The findings of the present study has quantified the changes in vegetation cover from dense, thick tropical forest to open mixed type landscapes which provide less protection against erosion and soil loss during the severe rainfall events which are characteristic of this tropical region.     

Assessing water erosion in Mediterranean tree crops using GIS techniques and field measurements: the effect of climate change

In this work, a dynamic GIS modeling approach is presented that incorporates: a) geoinformatic techniques, b) 55-year historical meteorological data, and c) field measurements, in order to estimate soil erosion risk in intensively cultivated regions. The proposed GIS-based modeling approach includes the estimation of soil erosion rates due to surface water flow under current and future climate change scenarios A2 and B1 for the years 2030 and 2050. The soil erosion was estimated using the Universal Soil Loss Equation (USLE). The proposed soil erosion model was validated using field measurements at different sites of the study area. The results show that an extended part of the study area is under intense erosion with the mean annual loss to be 4.85 t/ha year⁻¹. Moreover, an increase in rainfall intensity, especially for scenario B1, can generate a significant increase (32.44 %) in soil loss for the year 2030 and a much more (50.77 %) for the year 2050 in comparison with the current conditions. Regarding the scenario A2, a slight decrease (1.85 %) in soil loss was observed for the year 2030, while for 2050 the results show an adequate increase (7.31 %) in comparison with the present. All these approaches were implemented at one of the most productive agricultural areas of Crete in Greece dominated by olive and citrus crops.

     

贵州茂兰峰丛草地洼地小流域侵蚀产沙的137Cs法研究

在贵州茂兰峰丛洼地区的工程碑草地洼地典型小流域进行了洼地沉积泥沙^137Cs示踪分析研究。研究结果表明：（1）草地洼地土壤剖面属于堆积土壤剖面,土壤剖面中^137Cs浓度分布特征反映了泥沙堆积与表层土壤侵蚀的信息。受岩土分布、微地形的影响,^137Cs初始沉降后出现不均匀再分布,面积活度的空间变化较大,变异系数为1.35,不能表征土壤侵蚀状况。（2）根据草地洼地典型堆积农耕地土壤剖面A-1的^137Cs浓度分布特征,1963年以来的流域平均堆积泥沙数量是16.6t/km^2.a,流域平均土壤侵蚀速率为45.95t/km^2.a,约占侵蚀产沙数量63.88%的泥沙以地下流失的形式散失;（3）草地洼地小流域内地面土壤流失与地下土壤流失的相对贡献率分别是70.13%和29.87%;（4）以茂兰地区最大成土速率为依据推算出的允许土壤侵蚀量是13.51t/km^2.a,草地洼地的土壤侵蚀危险程度极高。     

Spatial and isotopic analysis of watershed soil loss and reservoir sediment accumulation rates in Lake Anna, Virginia, USA

Soil erosion and associated sedimentation are a threat to the sustainable use of surface water resources through the loss of volume storage capacity and conveyance of pollutants to receiving water bodies. The RUSLE2 empirical model and isotopic sediment core analyses were used to evaluate watershed erosion and reservoir sediment accumulation rates for Lake Anna, in Central Virginia. A sediment flux rate of 66,000 Mg/year was estimated from the upper basin and land use was determined to be the primary factor contributing to soil erosion. Barren lands and agricultural activities were estimated to contribute the most sediment (>20 Mg/ha/year), whereas forested and herbaceous landscapes were less likely to erode (<0.3 Mg/ha/year). Eleven separate ²¹⁰Pb-based estimates of sediment accumulation were used to construct reservoir-scale sedimentation rates. Sedimentation rates in the upper reaches of the reservoir were variable, ranging from 2.3 to 100 Mg/ha/year, with a median rate of 8.4 Mg/ha/year. Historical sedimentation showed an increase in annual accumulation from 1972 to present. Based on these data the reservoir has experienced a 2% loss of volume storage capacity since impoundment in 1972. Results from this study indicate that Lake Anna is not currently experiencing excessive sedimentation and erosion problems. However, the predominance of highly erosive soils (soil erodibility factor >0.30) within the watershed makes this system highly vulnerable to future anthropogenic stressors.     

Estimation of soil losses by USLE model using GIS at Mashhad plain, Northeast of Iran

The Universal Soil Loss Equation (USLE) is an erosion estimation model to assess the soil losses that would generally result from splash, sheet, and rill erosion. At the present study, spatial distribution of different erosion prone areas were identified by USLE model to determine the average annual soil losses at Mashhad plain, northeast of Iran. Soil losses were estimated on a 100?×?100 m cell basis resolution by overlaying the five digital parameter layers (R, K, LS, C, P). To determine the critical soil loss regions at the plain, cell-based USLE parameters were multiplied by Arc-GIS ver.9.3. The estimated annual soil losses values were subsequently grouped into five classes ranging from 0 to 0.25 t/h/year around the trough line of the plain at Kashaf-rud River to 2–10 t/ha/year at the hills and pediment plains. Our results indicated a good correlation between land units of hills and pediment plains with the values of soil losses at the study area (R ² ?=?0.72), also the statistical analysis exhibited a high correlation between land use/cover of dry farming and soil losses (R ² ?=?0.78).     

Mapping soil erosion susceptibility using remote sensing and GIS: a case of the Upper Nam Wa Watershed,Nan Province,Thailand

Land degradation is still a very common problem in the mountains of Asia because of inappropriate land use practice in steep topography. Many studies have been carried out to map shifting cultivation and areas susceptible to soil erosion. Mostly, estimated soil loss is taken as the basis to classify the level of soil loss susceptibility of area. Factors that influence soil erosion are: rainfall erosivity, soil erodibility, slope length and steepness, crop management and conservation practices. Thus the reliability of estimated soil loss is based on how accurately the different factors were estimated or prepared. As each and every small pixel of our earth surface is different from one area to another, the manner in which the study area was discretized into smaller homogenous sizes and how the most accurate and efficient technique were adopted to estimate the soil loss are very important. The purpose of this study is to produce erosion susceptibility maps for an area that has suffered because of shifting cultivation located in the mountainous regions of Northern Thailand. For this purpose, an integrated approach using RS and GIS-based methods is proposed. Data from the Upper Nam Wa Watershed, a mountainous area of the Northern Thailand were used. An Earth Resources Data Analysis System (ERDAS) imagine image processor has been used for the digital analysis of satellite data and topographical analysis of the contour data for deriving the land use/land cover and the topographical data of the watershed, respectively. ARCInfo and ARCView have been used for carrying out geographical data analysis. The watershed was discretized into hydrologically, topographically, and geographically homogeneous grid cells to capture the watershed heterogeneity. The soil erosion in each cell was calculated using the universal soil loss equation (USLE) by carefully determining its various parameters and classifying the watershed into different levels of soil erosion severity. Results show that during the time of this study most of the areas under shifting cultivation fell in the highest severity class of susceptibility.     

Estimation of spatial patterns of soil erosion using remote sensing and GIS: a case study of Indravati catchment

Soil erosion is a serious environmental problem in Indravati catchment. It carries the highest amount of sediments compared with other catchments in India. This catchment spreading an area of 41,285 km² is drained by river Indravati, which is one of the northern tributaries of the river Godavari in its lower reach. In the present study, USLE is used to estimate potential soil erosion from river Indravati catchment. Both magnitude and spatial distribution of potential soil erosion in the catchment is determined. The derived soil loss map from USLE model is classified into six categories ranging from slight to very severe risk depending on the calculated soil erosion amount. The soil erosion map is linked to elevation and slope maps to identify the area for conservation practice in order to reduce the soil loss. From the model output predictions, it is found that average erosion rate predicted is 18.00 tons/ha/year and sediment yield at the out let of the catchment is 22.30 Million tons per annum. The predicted sediment yield verified with the observed data.     

桂江流域土壤侵蚀估算及其时空特征分析

桂江流域的水土流失现状研究对珠江三角洲的水生态安全有重要的现实意义。采用修正的通用土壤流失方程（RUSLE）估算了桂江流域的土壤侵蚀模数与年侵蚀总量,分析流域内土壤侵蚀的时空分布特征,探讨了影响该区域土壤侵蚀强度的自然与人文因素。结果表明,桂江流域51.8%的地表都在发生不同程度的土壤侵蚀。从全流域平均土壤侵蚀强度来看,属于中度侵蚀。从土壤侵蚀面积来看,约85%的地表处于微度、轻度与中度侵蚀。4-6月的全流域平均土壤侵蚀强度最大,侵蚀总量也是最大的。流域的土壤侵蚀主要发生在高程在30~600m的低山丘陵-高地地貌区内的林地与耕地中。流域内岩溶区的土壤侵蚀强度随着石漠化程度从无到中度逐渐增加,轻、中度石漠化区的土壤侵蚀强度达到强度侵蚀等级。      

西南喀斯特区土壤侵蚀研究进展

西南喀斯特区土层浅薄、成土速率低等特点决定了其允许土壤流失量小,土壤一旦流失,极难恢复,土壤侵蚀及其造成的石漠化现象已成为制约该区可持续发展最严重的生态环境问题。文章首先明晰西南喀斯特区土壤侵蚀特征,从坡面、小流域和区域三个尺度上系统概括西南喀斯特区土壤侵蚀的相关研究进展。针对当前喀斯特区土壤侵蚀研究野外径流小区、小流域及区域空间尺度数据缺少和相关研究模型限制性强等不足,建议从不同尺度深入研究喀斯特区土壤侵蚀发生发展规律及时空演化格局,并结合高新遥感、地球物理探测技术及模型,同步监测坡面—小流域—区域土壤流失,对土壤侵蚀进行定量评估,结合不同空间尺度土壤侵蚀特征构建系统性水土保持生态恢复治理模式和监测系统评价体系。     

Soil loss tolerance limits: an environmental management tool

Soil loss tolerance is defined as the maximum acceptable level of soil loss from an area which will allow a high level of productivity to be maintained. Furthermore the criteria which determines soil loss tolerance limits are discussed, and two methods currently in use in Southern Africa, i.e. those proposed by the Department of Agricultural Technical Services (DATS) and Skidmore are discussed. It is concluded that for various reasons the latter approach is more acceptable, and that it is imperative that a different T-value be determined for each soil series.Application of the principle of soil loss tolerance in the Tugela River Basin reveals that various areas are subjected to severe stress. Maps indicating areas with soil loss of more than 10 t/ha/yr; areas with a soil loss higher than its allocated soil loss tolerance limits; and soil loss as a percentage of its T-values are included. These maps reveal startling facts, and emphasize the need for swift action in order to combat the problem of soil erosion in the area.The conclusion is drawn that the technique by which soil loss tolerance limits are determied could be applied to large areas, and its representation on large scale maps could be very useful in environmental planning and management.     

Modeling soil erosion using RUSLE and GIS in a watershed occupied by rural settlement in the Brazilian Cerrado

The installation of a rural settlement complex in the watershed stream Indaiá has promoted changes in land-use and vegetation cover dynamics; however, the effects of intensive agriculture and cattle farming in rural settlements on soil loss rates are not well known. Predictive models implemented in geographic information systems have proven to be effective tools for estimating erosive processes. The erosion predictive model Revised Universal Soil Loss Equation (RUSLE) is a useful tool for analyzing, establishing and managing soil erosion. RUSLE has been widely used to estimate annual averages of soil loss, by both interrill and rill erosion, worldwide. Therefore, the aim of this work was to estimate the soil loss in the watershed stream Indaiá, using the RUSLE model and geoprocessing techniques. To estimate soil loss, the following factors were spatialized: erosivity (R), erodibility (K), topography (LS), land-use and management (C) and conservation practices (P); the annual soil loss values were calculated using the RUSLE model equation. The estimated value of soil loss in the hydrographic basin ranged from 0 to 4082.16 Mg ha^?1 year^?1 and had an average value of 47.81 Mg ha^?1 year^?1. These results have demonstrated that 68.16 % of the study area showed little or no soil loss based on the Food and Agriculture Organization’s (FAO 1980) classification. When comparing the average value of soil loss obtained using the RUSLE model with the Natural Potential for Erosion, a 16-fold reduction in soil was found, which highlighted the fact that vegetation cover (C factor) has a greater influence than other factors (R, K and LS) on soil loss prediction attenuation. These results lead to the conclusion that soil loss occurs by different methods in each settlement in the basin and that erosive processes modeled by geoprocessing have the potential to contribute to an orderly land management process.     

喀斯特裸坡土壤侵蚀模拟研究

文章通过人工模拟降雨试验,研究不同地下孔（裂）隙度、基岩裸露率和雨强对地表、地下产流、产沙的影响,其结果表明:（1）土壤侵蚀与地下孔（裂）隙度具有较高相关性,地表产流、产沙随地下孔（裂）隙度的增大而减小,而地下则相反;（2）坡面径流刚产生时,雨滴击溅和薄层水流冲刷,土壤细小颗粒堵塞其毛管空隙,渗漏率减小,而地表径流量增大,土壤团聚体被破坏、分散和迁移,降水与土壤渗漏率增大,地表径流量减小,雨滴击溅增强,如此循环,降水与土壤渗漏率呈波动性变化;总体而言,地表、地下悬移质均随降雨历时呈下降趋势,而地表推移质则相反,地表、地下产流量变幅较小,趋于平行;（3）地表产流、产沙量随基岩裸露率增大呈波动性变化,总体呈下降趋势;而地下产流、产沙量随基岩裸露率增大呈波动性变化,总体呈增大趋势;（4）在较小雨强30 mm/h时,地表只产生悬移质流失,没有产生推移质流失;地表、地下产流、产沙都是随雨强增大而增大;雨强由30 mm/h增大到150 mm/h,地表累积产流量为538.5 L,累积产沙量为2 393.81 g,地下累积产流量为207.8 L,累积产沙量为687.73 g,累积产沙量的递增速率比累积产流量的递增速率要大,地表产流、产沙的递增速率大于地下产流、产沙的递增速率;（5）各因子与土壤侵蚀间相关程度为:降雨历时>雨强>地下孔（裂）隙度>基岩裸露率。该实验有助于为喀斯特地区的水土流失研究、评价及制订石漠化治理措施提供理论依据。      

Assessment of soil erosion risk using SWAT model

Soil erosion is one of the most serious land degradation problems and the primary environmental issue in Mediterranean regions. Estimation of soil erosion loss in these regions is often difficult due to the complex interplay of many factors such as climate, land uses, topography, and human activities. The purpose of this study is to apply the Soil and Water Assessment Tool (SWAT) model to predict surface runoff generation patterns and soil erosion hazard and to prioritize most degraded sub-catchment in order to adopt the appropriate management intervention. The study area is the Sarrath river catchment (1,491 km²), north of Tunisia. Based on the estimated soil loss rates, the catchment was divided into four priority categories for conservation intervention. Results showed that a larger part of the watershed (90 %) fell under low and moderate soil erosion risk and only 10 % of the watershed was vulnerable to soil erosion with an estimated sediment loss exceeding 10 t?ha^?1?year^?1. Results indicated that spatial differences in erosion rates within the Sarrath catchment are mainly caused by differences in land cover type and gradient slope. Application of the SWAT model demonstrated that the model provides a useful tool to predict surface runoff and soil erosion hazard and can successfully be used for prioritization of vulnerable areas over semi-arid catchments.     

Modeling erosion and sediment control practices with RUSLE 2.0: a management approach for natural gas well sites in Denton County,TX, USA

Sediment yields from natural gas well sites in Denton County, TX, USA can be substantial and warrant consideration of appropriate erosion and sediment control best management practices (BMPs). Version 2 of the revised universal soil loss equation (RUSLE 2.0) was used to predict sediment yields and evaluate the efficiency of BMPs for multiple combinations of different land surface conditions (soil erodibility and slope) commonly found at gas well sites in the area. Annual average sediment yield predictions from unprotected site conditions ranged from 12.1 to 134.5 tonnes per hectare per year (t/ha/yr). Sediment yield predictions for 1, 2, 5, and 10-year design storms ranged from 8.1 to 20.6 t/ha. When site conditions were modeled with BMPs, predicted sediment yields were 52–93% less. A comparison of modeled efficiency values to a review of laboratory and field data suggests that modeled (theoretical) sediment yield results with BMPs are likely best case scenarios. This study also evaluated BMPs in the context of site management goals and implementation cost, demonstrating a practical approach for the application of RUSLE 2.0 for managing soil loss and understanding the importance of selecting appropriate site-specific BMPs for disturbed site conditions.     

WEPP模型(坡面版)在贵州石漠化地区土壤侵蚀模拟的适用性评价

文章以贵州花江喀斯特石漠化地区为研究区域,利用WEPP模型(坡面版)分别模拟2006年、2010年土壤侵蚀模数,并将实测数据与WEPP模型模拟值作比较,探讨WEPP软件在喀斯特石漠化地区的适用性。研究表明：WEPP模型对于模拟喀斯特石漠化地区土壤侵蚀有较大误差,对土壤侵蚀模数模拟的有效性系数均为负值,不适用于直接计算该区域土壤侵蚀模数。WEPP模型对微度侵蚀模拟精度不够,但能大体反映不同径流小区之间土壤侵蚀强弱的关系和生态修复过程土壤侵蚀的变化趋势。若要应用WEPP模型对喀斯特地区土壤侵蚀模数模拟计算,必须考虑水土的地下漏失、地表裸岩率、地形高度破碎等环境条件。裸岩率、土壤漏失、地形条件等都是WEPP模型修正所必须注意的内容。     

Assessment of soil erosion in a tropical mountain river basin of the southern Western Ghats,India using RUSLE and GIS

Revised Universal Soil Loss Equation(RUSLE) model coupled with transport limited sediment delivery(TLSD) function was used to predict the longtime average annual soil loss, and to identify the critical erosion-/deposition-prone areas in a tropical mountain river basin, viz., Muthirapuzha River Basin(MRB; area=271.75 km~2), in the southern Western Ghats, India. Mean gross soil erosion in MRB is 14.36 t ha~(-1) yr~(-1), whereas mean net soil erosion(i.e., gross erosion-deposition) is only 3.60 t ha~(-1) yr~(-1)(i.e., roughly 25% of the gross erosion). Majority of the basin area(~86%) experiences only slight erosion(5 t ha~(-1) yr~(-1)), and nearly 3% of the area functions as depositional environment for the eroded sediments(e.g., the terraces of stream reaches, the gentle plains as well as the foot slopes of the plateau scarps and the terrain with concordant summits). Although mean gross soil erosion rates in the natural vegetation belts are relatively higher, compared to agriculture, settlement/built-up areas and tea plantation, the sediment transport efficiency in agricultural areas and tea plantation is significantly high,reflecting the role of human activities on accelerated soil erosion. In MRB, on a mean basis, 0.42 t of soil organic carbon(SOC) content is being eroded per hectare annually, and SOC loss from the 4th order subbasins shows considerable differences, mainly due to the spatial variability in the gross soil erosion rates among the sub-basins. The quantitative results, on soil erosion and deposition, modelled using RUSLE and TLSD, are expected to be beneficial while formulating comprehensive land management strategies for reducing the extent of soil degradation in tropical mountain river basins.     

基于3S技术的小流域水土流失过程数值模拟与定量研究

运用3S技术和不同水蚀区修正的土壤流失方程,对金沙江流域龙川江上游的水土流失量和需要治理的面积进行了数值模拟和定量研究.结果表明:①旱年1998年土壤流失总量为840069.19t,流失总面积为2293.7841km2;涝年1999年土壤流失总量为8690182.6t,流失总面积为2293.7841km2;1999年和1998年强度、重度和剧烈以上流失面积分别达85%和66.8%,该项指标1999年明显强于1998年.②从流失面积来看,1999年中度以上流失面积占流失总面积的35.2%,而1998年只占26%.③1988年和1999年防治强度分级中急需治理和需要治理的面积占总面积的比例分别为16.27%和14.63%.④模拟计算结果与实测值接近,说明该方法对西南红壤季风区的水土流失定量监测与分析具有准确、实用和方便的特点.     

风蚀对中国北方脆弱生态系统碳循环的影响

风蚀是中国北方脆弱生态系统土壤质量退化和沙漠化的关键因素。文章基于土壤剖面普查和土壤侵蚀遥感调查数据,计算出风蚀土壤有机碳的侵蚀量和空间分布,并与风蚀区的净第一性生产力(NPP)比较。结果发现土壤风蚀区的一个显著特征是表层土壤有机质含量较小,并且随着土壤风蚀强度的增加,相应的表层土壤平均有机质含量和NPP基本上逐渐减小,而相应的土壤有机碳的侵蚀量却明显增大。在中国北方严重风蚀的脆弱生态区,土壤有机碳的侵蚀量超过了NPP,风蚀影响了生态系统的正常碳循环。