Estimation of soil erosion risk within a small mountainous sub-watershed in Kerala,India,using Revised Universal Soil Loss Equation(RUSLE) and geo-information technology

A comprehensive methodology that integrates Revised Universal Soil Loss Equation （RUSLE） model and Geographic Information System （GIS） techniques was adopted to determine the soil erosion vulner- ability of a forested mountainous sub-watershed in Kerala, India. The spatial pattern of annual soil erosion rate was obtained by integrating geo-environmental variables in a raster based GIS method. GIS data layers including, rainfall erosivity （R）, soil erodability （K）, slope length and steepness （LS）, cover management （C） and conservation practice （P） factors were computed to determine their effects on average annual soil loss in the area. The resultant map of annual soil erosion shows a maximum soil loss of 17.73 t h-1 y i with a close relation to grass land areas, degraded forests and deciduous forests on the steep side-slopes （with high LS ）. The spatial erosion maps generated with RUSLE method and GIS can serve as effective inputs in deriving strategies for land planning and management in the environmentally sensitive mountainous areas.

Integrated Approach of Universal Soil Loss Equation (USLE) and Geographical Information System (GIS) for Soil Loss Risk Assessment in Upper South Koel Basin, Jharkhand

Soil erosion is a growing problem especially in areas of agricultural activity where soil erosion not only leads to decreased agricultural productivity but also reduces water availability. Universal Soil Loss Equation (USLE) is the most popular empirically based model used globally for erosion prediction and control. Remote sensing and GIS techniques have become valuable tools specially when assessing erosion at larger scales due to the amount of data needed and the greater area coverage. The present study area is a part of Chotanagpur plateau with undulating topography, with a very high risk of soil erosion. In the present study an attempt has been made to assess the annual soil loss in Upper South Koel basin using Universal Soil Loss Equation (USLE) in GIS framework. Such information can be of immense help in identifying priority areas for implementation of erosion control measures. The soil erosion rate was determined as a function of land topography, soil texture, land use/land cover, rainfall erosivity, and crop management and practice in the watershed using the Universal Soil Loss Equation (for Indian conditions), remote sensing imagery, and GIS techniques. The rainfall erosivity R-factor of USLE was found as 546 MJ mm/ha/hr/yr and the soil erodibility K-factor varied from 0.23 - 0.37. Slopes in the catchment varied between 0% and 42% having LS factor values ranging from 0 - 21. The C factor was computed from NDVI (Normalized Difference Vegetative Index) values derived from Landsat-TM data. The P value was computed from existing cropping patterns in the catchment. The annual soil loss estimated in the watershed using USLE is 12.2 ton/ha/yr.

Evaluation of C and P Factors in Universal Soil Loss Equation on Trapping Sediment: Case Study of Santubong River

Universal Soil Loss Equation (USLE) is the most comprehensive technique available to predict the long term average annual rate of erosion on a field slope. USLE was governed by five factors include soil erodibility factor (K), rainfall and runoff erodibility index (R), crop/vegetation and management factor (C), support practice factor (P) and slope length-gradient factor (LS). In the past, K, R and LS factors are extensively studied. But the impacts of factors C and P to outfall Total Suspended Solid (TSS) and % reduction of TSS are not fully studied yet. Therefore, this study employs Buffer Zone Calculator as a tool to determine the sediment removal efficiency for different C and P factors. The selected study areas are Santubong River, Kuching, Sarawak. Results show that the outfall TSS is increasing with the increase of C values. The most effective and efficient land use for reducing TSS among 17 land uses investigated is found to be forest with undergrowth, followed by mixed dipt. forest, forest with no undergrowth, cultivated grass, logging 30, logging 10^6, wet rice, new shifting agriculture, oil palm, rubber, cocoa, coffee, tea and lastly settlement/cleared land. Besides, results also indicate that the % reduction of TSS is increasing with the decrease of P factor. The most effective support practice to reduce the outfall TSS is found to be terracing, followed by contour-strip cropping, contouring and lastly not implementing any soil conservation practice.

Factor value determination and applicability evaluation of universal soil loss equation in granite gneiss region

Six types of runoff plots were set up and an experimental study was carried out to examine natural rate of soil and water loss in the granite gneiss region of northern Jiangsu Province in China. Through correlation analysis of runoff and soil loss during 364 rainfall events, a simplified and convenient mathematical formula suitable for calculating the rainfall erosivity factor （R） for the local region was established. Other factors of the universal soil loss equation （USLE model） were also determined. Relative error analysis of the soil loss of various plots calculated by the USLE model on the basis of the observed values showed that the relative error ranged from -3.5% to 9.9% and the confidence level was more than 90%. In addition, the relative error was 5.64% for the terraced field and 12.36% for the sloping field in the practical application. Thus, the confidence level was above 87.64%. These results provide a scientific basis for forecasting and monitoring soil and water loss, for comprehensive management of small watersheds, and for soil and water conservation planning in the region.

基于RUSLE模型的秦岭—大巴山地土壤侵蚀时空特征分析

[目的]秦岭—大巴山地(秦巴山地)是我国重要的南北地理—生态过渡带主体,对秦巴山地的土壤侵蚀研究将有助于该区域的生态保护和水土资源管理。[方法]基于RUSLE模型计算秦巴山地的土壤侵蚀模数,并量化分析了该区域的土壤侵蚀的时空分布格局。[结果](1)2000—2020年秦巴山地的微度侵蚀面积呈上升趋势,轻度侵蚀及其以上等级的土壤侵蚀面积均呈下降趋势;从空间来看,秦巴山地东北和西南部的土壤侵蚀等级较高,中间较低;(2)秦巴山地的土壤侵蚀相对集中在500~1500 m、坡度15°~25°区域内;(3)秦巴山地发生土壤侵蚀最主要的土地利用类型为林地,耕地、林地的微度侵蚀以及草地的微度、剧烈侵蚀面积呈上升趋势;(4)秦巴山地土壤侵蚀主要分布在陕西、四川和甘肃,且甘肃和四川的剧烈侵蚀呈上升趋势。[结论]2000—2020年秦巴山地的侵蚀面积和强度呈“双下降”的态势,其整体侵蚀状况好转,但侵蚀分布存在明显空间差异。

Combining RUSLE model and the vegetation health index to unravel the relationship between soil erosion and droughts in southeastern Tunisia

Droughts and soil erosion are among the most prominent climatic driven hazards in drylands,leading to detrimental environmental impacts,such as degraded lands,deteriorated ecosystem services and biodiversity,and increased greenhouse gas emissions.In response to the current lack of studies combining drought conditions and soil erosion processes,in this study,we developed a comprehensive Geographic Information System(GIS)-based approach to assess soil erosion and droughts,thereby revealing the relationship between soil erosion and droughts under an arid climate.The vegetation condition index(VCI)and temperature condition index(TCI)derived respectively from the enhanced vegetation index(EVI)MOD13A2 and land surface temperature(LST)MOD11A2 products were combined to generate the vegetation health index(VHI).The VHI has been conceived as an efficient tool to monitor droughts in the Negueb watershed,southeastern Tunisia.The revised universal soil loss equation(RUSLE)model was applied to quantitatively estimate soil erosion.The relationship between soil erosion and droughts was investigated through Pearson correlation.Results exhibited that the Negueb watershed experienced recurrent mild to extreme drought during 2000–2016.The average soil erosion rate was determined to be 1.8 t/(hm2•a).The mountainous western part of the watershed was the most vulnerable not only to soil erosion but also to droughts.The slope length and steepness factor was shown to be the most significant controlling parameter driving soil erosion.The relationship between droughts and soil erosion had a positive correlation(r=0.3);however,the correlation was highly varied spatially across the watershed.Drought was linked to soil erosion in the Negueb watershed.The current study provides insight for natural disaster risk assessment,land managers,and stake-holders to apply appropriate management measures to promote sustainable development goals in fragile environments.

Evaluating estimated sediment delivery by Revised Universal Soil Loss Equation(RUSLE)and Sediment Delivery Distributed(SEDD)in the Talar Watershed,Iran

The performance of the Revised Universal Soil Loss Equation(RUSLE)as the most widely used soil erosion model is a challenging issue.Accordingly,the objective of this study is investigating the estimated sediment delivery by the RUSLE method and Sediment Delivery Distributed(SEDD)model.To this end,the Talar watershed in Iran was selected as the study area.Further,700 paired sediment-discharge measurements at Valikbon and Shirgah-Talar hydrometric stations between the years 1991 and 2011 were collected and used in sediment rating curves.Nine procedures were investigated to produce the required RUSLE layers.The estimated soil erosion by RUSLE was evaluated using sediment rating curve data by two methods including least squares and quantile regression.The average annual suspended sediment load was calculated for each sub-watershed of the study area using the SEDD model.Afterwards,a sediment rating curve was estimated by least squares and quantile regression methods using paired discharge-sediment data.The average annual suspended sediment load values were calculated for two hydrometric stations and were further evaluated by the SEDD model.The results indicated that the first considered procedure,which utilized 15-min rainfall measurements for the rainfall factor(R),and the classification method of SENTINEL-2 MSI image for the cover management factor(C),offered the best results in producing RUSLE layers.Furthermore,the results revealed the advantages of utilizing satellite images in producing cover management layer,which is required in the RUSLE method.

基于RUSLE和GIS的博罗县土壤侵蚀特征分析

以广东省博罗县流域为例,在GIS与RS技术支持下,利用气象数据、土壤数据、DEM数据、植被覆盖与土地利用等基础数据,对修正通用土壤流失方程各因子进行量化分析与强度分级.结果表明:(1)2021年博罗县域土壤平均侵蚀模数为9721.24t·km^(-2)·a^(-1),总体水土流失较为严重,年侵蚀量892.61×10^(4)t,其中剧烈等级土壤侵蚀量占到总侵蚀量的54.70%;6个侵蚀强度等级面积大小依次是微度>剧烈>轻度>强度>极强度>中度;(2)石湾镇及园洲镇属微度,而西北部及东中部山地丘陵区的罗浮山、横河镇、公庄镇、柏塘镇及泰美镇等区域土壤侵蚀较为严重;(3)土壤侵蚀量与坡度存在明显正相关,每增加一个等级,平均侵蚀模数呈增大趋势,而且增大幅度较大;有林地的面积为52.64%,其土壤侵蚀量比重占45.08%,而裸地虽然面积比重仅占0.45%,但其土壤侵蚀量却占到总土壤侵蚀量的6.41%,属于激烈侵蚀等级;(4)植被覆盖度小于20%和大于65%的区域土壤侵蚀面积高达26.78%和24.57%,其他植被覆盖度级别下的土壤侵蚀面积变化不大;植被覆盖度20%~65%之间的土壤侵蚀面积为48.64%,但其土壤侵蚀总量比重达81.23%.利用该方程进行土壤侵蚀量估算,为促进博罗县土壤侵蚀动态精准监测、侵蚀因子评价和后续水土保持规划与工程实施提供参考依据.

Influence of varied drought types on soil conservation service within the framework of climate change:insights from the Jinghe River Basin,China

Severe soil erosion and drought are the two main factors affecting the ecological security of the Loess Plateau,China.Investigating the influence of drought on soil conservation service is of great importance to regional environmental protection and sustainable development.However,there is little research on the coupling relationship between them.In this study,focusing on the Jinghe River Basin,China as a case study,we conducted a quantitative evaluation on meteorological,hydrological,and agricultural droughts(represented by the Standardized Precipitation Index(SPI),Standardized Runoff Index(SRI),and Standardized Soil Moisture Index(SSMI),respectively)using the Variable Infiltration Capacity(VIC)model,and quantified the soil conservation service using the Revised Universal Soil Loss Equation(RUSLE)in the historical period(2000-2019)and future period(2026-2060)under two Representative Concentration Pathways(RCPs)(RCP4.5 and RCP8.5).We further examined the influence of the three types of drought on soil conservation service at annual and seasonal scales.The NASA Earth Exchange Global Daily Downscaled Projections(NEX-GDDP)dataset was used to predict and model the hydrometeorological elements in the future period under the RCP4.5 and RCP8.5 scenarios.The results showed that in the historical period,annual-scale meteorological drought exhibited the highest intensity,while seasonal-scale drought was generally weakest in autumn and most severe in summer.Drought intensity of all three types of drought will increase over the next 40 years,with a greater increase under the RCP4.5 scenario than under the RCP8.5 scenario.Furthermore,the intra-annual variation in the drought intensity of the three types of drought becomes smaller under the two future scenarios relative to the historical period(2000-2019).Soil conservation service exhibits a distribution pattern characterized by high levels in the southwest and southeast and lower levels in the north,and this pattern has remained consistent both in the historical and future periods.Over the past 20 years,the intra-annual variation indicated peak soil conservation service in summer and lowest level in winter;the total soil conservation of the Jinghe River Basin displayed an upward trend,with the total soil conservation in 2019 being 1.14 times higher than that in 2000.The most substantial impact on soil conservation service arises from annual-scale meteorological drought,which remains consistent both in the historical and future periods.Additionally,at the seasonal scale,meteorological drought exerts the highest influence on soil conservation service in winter and autumn,particularly under the RCP4.5 and RCP8.5 scenarios.Compared to the historical period,the soil conservation service in the Jinghe River Basin will be significantly more affected by drought in the future period in terms of both the affected area and the magnitude of impact.This study conducted beneficial attempts to evaluate and predict the dynamic characteristics of watershed drought and soil conservation service,as well as the response of soil conservation service to different types of drought.Clarifying the interrelationship between the two is the foundation for achieving sustainable development in a relatively arid and severely eroded area such as the Jinghe River Basin.

基于GIS和RUSLE的黄土高原小流域土壤侵蚀评估

对基于上坡汇流面积的坡长因子算法进行改进,提出考虑上坡土地利用/覆盖对汇流影响的坡长因子算法,运用GIS和RUSLE评估黄土高原四面窑沟流域的土壤侵蚀强度及其与环境因素的关系。结果表明,流域多年平均侵蚀强度4399.79t/(km2·a),属中度侵蚀;侵蚀强度和侵蚀量均随坡度增加而显著增加,80.59%的侵蚀量来源于占流域总面积59.06%的25°以上坡度带;不同坡向的侵蚀强度表现为正阳坡>半阳坡>半阴坡>正阴坡,其中,占总面积45.07%的阳坡产生56.50%的侵蚀量;不同土地利用类型中,占总面积57.07%的草地产生96.37%的侵蚀量,成为目前流域内主要侵蚀产沙源。研究为应用修正通用土壤流失方程在黄土高原进行侵蚀评估提供技术范例,为该区侵蚀防治和水土资源利用提供有益参考。

基于GIS和RUSLE的土壤侵蚀量计算——以贵州省猫跳河流域为例

为了解西南喀斯特山区土壤侵蚀空间分布特征,该文以贵州省猫跳河流域为研究区,在GIS技术支撑下,应用修正的通用土壤流失方程(RUSLE)估算了研究区2002年现实土壤侵蚀量和潜在土壤侵蚀量,得到了研究区现实土壤侵蚀量和潜在土壤侵蚀量的空间分布特征,计算了各种土地利用类型的土壤保持能力,并对研究区土壤侵蚀防治措施进行了探讨.结果表明,研究区年均现实土壤侵蚀模数为28.70t(hm2·a),年均土壤流失量875.65×104ta,年均土壤保持量25095.73×104ta.旱地的土壤保持能力最小,研究区进行水土流失防治除对25°以上的旱地实行退耕还林、裸岩荒地植树造林外,还应加强对6°～25°的旱地进行治理如坡改梯等.

USLE／RUSLE中植被覆盖与管理因子研究进展

通用土壤流失方程(USLE)及修正通用土壤流失方程(RUSLE)是世界范围内应用最广泛的土壤侵蚀预报模型,模型中C因子表示植被覆盖和管理措施对土壤侵蚀的作用,是人为控制土壤侵蚀的重要因子。回溯了C因子发展演变历程,依据国内外最新研究成果,系统阐述了不同尺度C因子估算方法。在小区、坡面、小流域尺度上,C因子确定主要依赖于野外实验观测,研究条件的一致性尤其是标准小区的统一是C因子值可比性的前提。流域、区域尺度C因子确定通常需要利用遥感影像,遥感技术的发展促进了流域、区域尺度C因子估算方法的进步,使提取的C因子图更加精细、准确,但是使用遥感数据全面刻画C因子含义仍然是一大挑战,因此仍需加强C因子相关研究。共归纳了10种确定C因子的方法,介绍了不同方法的优缺点及适用条件,提出了我国C因子研究应加强的工作,希望为相关领域研究者提供参考。

基于RUSLE的黄土洼小流域土壤侵蚀与水土保持研究

采用修订的通用水土流失方程(RUSLE)、调查还原法和淹没分析等方法,对天然淤地坝多年平均拦截泥沙量和天然淤地坝所在黄土洼小流域侵蚀空间分布进行研究。结果表明:2000—2011年坝淤地及上游丘陵沟壑区平均土壤侵蚀模数为8 116.14t/(km2·a);RUSLE模拟的淤地坝及上游丘陵沟壑侵蚀区土壤侵蚀模数为7 714.73t/(km2·a),通过与实测值对比,模拟精度为95%。模拟的黄土洼小流域强烈侵蚀、极强烈侵蚀和剧烈侵蚀区域占流域面积的53.18%,研究区土壤侵蚀严重;黄土洼天然坝地的泥沙主要来源于坡度大于15°的粱峁耕种区、沟间地和坝地边缘。黄土洼小流域进行人工水土保持措施后侵蚀模数降低26.15%;天然淤地坝将周围控制区域的泥沙全部拦截,对黄土洼小流域泥沙拦截贡献率高达77%,水土保持效益明显。黄土洼天然淤地坝在没有人为干扰的情况下,还可淤积泥沙体积约为2.303×106 m3。

基于RUSLE模型的三江源高寒草地土壤侵蚀评价

探讨三江源区高寒草地生态系统土壤侵蚀问题在保障青藏高原乃至全球生态和生产功能方面具有重要意义。以^(137)Cs示踪法为基础,结合RUSLE(Revised Universal Soil Loss Equation)模型,以GIS反演为手段,综合分析三江源区2001-2012年土壤侵蚀影响因子的特征和土壤侵蚀空间分布规律。结果表明,1)土壤侵蚀影响因子呈现空间异质性特征,降雨侵蚀力因子年际浮动变化较大,但总体呈上升态势;土壤可蚀性因子呈斑块化分布特征,较高可蚀性类占到总面积的95.66%;坡度坡长因子的空间分布规律受海拔显著影响;植被覆盖与管理因子在研究区自西北向东南呈现空间异质性特点,过度放牧是引起下垫面侵蚀现象严重的主要原因。2)对RUSLE模型的验证显示相关系数和平均均方根偏差分别为0.49和75.29%,RUSLE模型估算存在一定的高估,在没有形成三江源区高寒草地土壤侵蚀机理模型前,应用RUSLE模型仍然是较好的现实选择之一。3)利用RUSLE模型估算的三江源2001-2012年平均侵蚀量为3.1×109 t/年,侵蚀强度分级重心转移分析表明中度侵蚀、强度和极强度侵蚀重心相对集中,侵蚀程度最高的3个地区为格尔木市唐古拉乡、治多县和兴海县。4)由土壤流失量结合市场价值法,估算出研究区2001-2012年平均有机质经济损失价值为114354元/km2,总年均经济损失达399亿元,整个研究区受土壤侵蚀现象所产生的经济损失数额巨大。因此,创新发展三江源区高寒草地"分类、分级、分段、分区"的土壤侵蚀防治措施已迫在眉睫。

基于RUSLE和景观安全格局的土壤侵蚀风险格局研究——以甘肃省甘南藏族自治州迭部县为例

土壤侵蚀是我国目前面临的重大生态问题之一。利用GIS技术和修正的水土流失方程(RUSLE)模型对降雨侵蚀造成的土壤流失进行预测估算是目前较为常用的一种土壤侵蚀研究方法。以RUSLE模型的基本构建方法为基础,结合景观生态安全格局理论,对甘肃省甘南州迭部县县域内的土壤侵蚀状况进行了估测性。分析了模型中各个作用因子在当地的分布及表现特点,并构建了该县的土壤侵蚀风险格局。提出在土壤侵蚀格局的关键点或地带,依靠坡改梯,增加护坡,种植等高植物篱,提高植被郁闭度等手法,提高流失斑块的破碎度,降低地表径流能量,弱化土壤侵蚀的规模化效应,以期起到解决或减弱当地土壤严重流失问题的作用。土壤流失风险格局也可以为土地利用格局的改造提供指导性依据。

基于GIS和RUSLE的三峡库区小流域土壤侵蚀量估算研究

本研究以三峡库区菱角塘小流域为研究对象,在GIS技术的支持下,通过遥感技术和野外调查进行信息采集,对修正的通用土壤流失方程（RUSLE）各因子进行量化分析,从而对三峡库区菱角塘小流域土壤侵蚀量进行定量评价,并对土壤侵蚀强度进行分级;在此基础上分析不同坡度和土地利用类型的土壤侵蚀空间分布特征。结果表明,菱角塘小流域年土壤侵蚀量为208.32t/a,土壤侵蚀模数为1 987.75t/（km2·a）,属于轻度侵蚀。28.62%的区域为中度、强度或极强度侵蚀,但是其侵蚀量却占总侵蚀量的82.36%,是预防和加强水土流失治理的重点区域。土壤侵蚀主要发生在坡度为15°-35°的区域,其中15°-25°的坡度土壤侵蚀属于中度侵蚀;坡耕地侵蚀最为严重,15°-25°的坡耕地侵蚀量占总侵蚀量的57.15%,表明坡耕地是该小流域水土流失的主要策源地。同时用137 Cs核素示踪技术测定的坡耕地和林地土壤侵蚀模数证实了RUSLE模型具有较高的准确性和可靠性,该模型在库区地块尺度具有一定的推广价值。

基于RUSLE的土壤侵蚀量研究——以南水北调中线陕西水源区为例

目的对南水北调中线陕西水源区的土壤侵蚀进行了初步研究,为水源区的生态保护、水土保持和生态补偿提供重要的依据。方法在GIS技术的支持下,利用遥感影像解译资料、数字高程模型(DEM)及土壤、降雨等数据,对土壤流失方程RUSLE中各因子进行了量化分析,从而实现对南水北调中线陕西水源区土壤侵蚀量的估算,并对结果进行土壤侵蚀强度分级。结果通过计算可得,在南水北调中线陕西水源区,微度侵蚀面积占12.87%,轻度侵蚀面积占30.4%,中度侵蚀面积占30.66%,强度侵蚀面积占26.07%。土壤侵蚀空间分布具有明显的地带性和垂直地带性规律。结论南水北调中线水源区陕西段绝大部分地区属于强度侵蚀地区,仅有少数地区达到微度侵蚀,水土保持任务很艰巨。

RUSLE侵蚀模型的应用及进展

RUSLE模型是在美国通用土壤流失模型USLE的基础上建立起来的,是目前国内外应用广泛的土壤侵蚀预测模型之一。从RUSLE模型开发背景,RUSLE模型的主要修订内容,模型的实施与进展,RUSLE2模型介绍,RUSLE模型的局限性及RUSLE模型的应用前景等6个方面对模型的应用及研究进展进行了综合性评述,为我国土壤侵蚀模型的建立提供参考。

基于RS/GIS和RUSLE的福建武步溪流域土壤侵蚀研究

将地理信息系统(GIS)、遥感技术(RS)和美国修正的通用土壤流失方程(RUSLE)相结合对武步溪流域的土壤侵蚀量进行计算。运用ERDASIMAGINE8.4软件对武步溪流域2001年和2003年的遥感影像进行监督分类,结合数字高程模型(DEM)和土壤分布图在Ar-cView3.2软件平台上获取RUSLE模型中的LS、C、P、R因子,通过Ar-cView3.2软件进行数据处理和叠加分析,最终得到武步溪流域两个年份的土壤侵蚀等级的空间分布图及土壤侵蚀量。研究结果表明:2001年和2003年中度侵蚀及其以上等级的土壤侵蚀量分别占同年总侵蚀量的88.1%和59.8%,2001年的土壤侵蚀状况比2003年更为严重,其主要原因是2001年降雨侵蚀因子大于2003年的降雨侵蚀因子。改变不合理的土地利用方式将有利于改善该流域土壤流失状况。

基于RUSLE和SDR的香溪河流域土壤流失脆弱区识别

基于修正的通用土壤流失方程RUSLE和分布式泥沙输移比SDR函数,构建了由降雨侵蚀力因子、土壤可蚀性因子、坡度坡长因子、植被覆盖因子和泥沙输移因子组成的流域土壤流失脆弱性评估模型。针对三峡库区香溪河流域,在GIS和RS技术支持下,利用流域降雨、土壤类型分布、DEM及NDVI数据,评估了流域土壤流失脆弱性并对其进行了区划,识别出了香溪河流域内对于土地利用和水土保持等人类活动更为敏感的土壤流失脆弱区。结果显示,香溪河流域土壤流失脆弱区面积为326.33 km2,占流域总面积的10.53%;5个子流域中,土壤流失脆弱区分布比例从高到低依次为:湘坪河子流域、古夫河子流域、湘坪河口—峡口区间、峡口以下区域和高岚河子流域,其中前2个子流域土壤流失脆弱区分布比例超过全流域的平均值。研究结果可为香溪河流域土地利用方式的调整和水土保持提供科学依据。