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.

基于USLE模型的浐灞河流域土壤侵蚀研究

对浐灞河流域土壤侵蚀状况进行定量研究,识别出侵蚀集中来源区域,为全运湖水环境综合施策布局提供指导。利用实测数据、遥感数据及收集资料,按照通用土壤侵蚀方程USLE模型的国内研究成果进行土壤侵蚀空间识别研究。2020年浐灞河流域平均土壤侵蚀模数为830.91 t/(km2·a),土壤侵蚀面积为696.46 km2,占全流域土地面积的27.79%。从空间分布上看,土壤侵蚀主要集中于灞河流域,辋川河流域及库峪河流域。浐灞河流域依据侵蚀集中指数及识别区域,优先开展调控措施,全运湖的减蚀澄清效果将较为明显。

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.

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GIS/RS和USLE鄱阳湖流域土壤侵蚀变化

将空间信息技术(RS和GIS)和通用土壤流失方程(USLE)相结合对鄱阳湖流域土壤侵蚀量进行计算。分别利用1990年和2000年TM/ETM+影像分类得到两期土地利用/覆盖类型图,结合鄱阳湖流域数字高程模型(DEM)、土壤类型分布图和流域降雨资料分别获取USLE模型中各因子值的空间分布,最后计算流域2个年份的土壤侵蚀空间分布图。研究表明:鄱阳湖流域土壤侵蚀区域主要分布在赣江上游,信江上游,抚河上中游和修水上游地区;鄱阳湖流域1990年和2000年大范围土地经受着Ⅰ级微度与Ⅱ级轻度侵蚀,其侵蚀面积之和分别占流域面积的97.38%和97.30%;而流域产沙主要来源于Ⅱ级轻度侵蚀和Ⅲ级中度侵蚀,所占土壤侵蚀总量分别为58.16%和51.20%,其中中度以上等级的侵蚀对产沙量的贡献是不可忽视的;从1990年到2000年土壤侵蚀等级变化呈现了由中等级侵蚀(Ⅱ级轻度侵蚀和Ⅲ级中度侵蚀)向低等级(Ⅰ级微度侵蚀)和高等级侵蚀(Ⅴ级极强度和Ⅵ级剧烈侵蚀)的2个极端演化的趋势。鄱阳湖流域土壤侵蚀量从1990年到2000年增长幅度达6.3%;土壤平均侵蚀模数都约为1100t/(km2·a),属于Ⅱ级轻度侵蚀。分析2个年份的土地利用/覆盖变化,发现鄱阳湖流域湿地和农田面积减少,建筑用地增加均是造成土壤侵蚀量增加的因素,而降雨侵蚀力因子空间格局也对土壤侵蚀空间分布具有重要影响,最后提出了鄱阳湖流域水土保持规划措施。

基于GIS和USLE的九龙江流域土壤侵蚀量预测研究

探讨了GIS和USLE相结合预测南方中等尺度流域土壤侵蚀量、标识流域土壤侵蚀严重区域。运用GIS建立九龙江流域基础地理数据库,利用ARC/INFO的栅格数据空间分析功能,根据USLE土壤侵蚀预测模型对数据库进行图形运算,预测了九龙江流域的土壤侵蚀量。结果表明,流域的年均侵蚀模数为2 730.3 t/km^2,侵蚀强度属中度。占流域面积85.72％的区域土壤侵蚀强度在中度以下。这一区域对流域土壤侵蚀量的贡献率为58.26％,而流域41.74％的侵蚀泥沙来自于占流域面积14.28％的强度以上侵蚀区域。在流域侵蚀强度的空间分布上,8个子流域属中度侵蚀区,其中船场溪、花山溪和雁石溪三个子流域侵蚀强度较大;6个子流域属轻度侵蚀区,其中漳州平原的龙海和浦南两子流域侵蚀强度最弱。

应用USLE模型与地理信息系统IDRISI预测小流域土壤侵蚀量的研究

依据实地调查资料 ,建立了典型小流域地理数据库 ;应用径流小区观测结果 ,确定了定量计算通用土壤流失方程 USL E因子指标的方法。在地理信息系统 IDRISI支持下 ,根据USLE土壤侵蚀预测模型对数据库实施运算操作 ,预测了小流域土壤侵蚀量。结果表明 ,占流域面积 6 7%的区域土壤侵蚀微弱或轻度 ,这一区域对流域土壤侵蚀量的贡献率仅为 3% ,而流域 80 %的泥沙来自于占流域面积仅 2 0

基于GIS和USLE的土壤侵蚀定量分析研究——以四川省洪雅县为例

以四川省洪雅县为研究对象,运用GIS方法和USLE土壤侵蚀模型,分析与评价该区域的土壤侵蚀状况。结果表明:洪雅县土地利用单元的侵蚀强度存在显著差异,不同的土地利用类型与土壤侵蚀强度强弱有较为密切的联系。根据洪雅县的土地利用和自然经济状况,洪雅县可分为北部轻度侵蚀区、中部微度侵蚀区和西南部无明显侵蚀区3类土壤侵蚀强度类型区,并针对各区不同的情况模拟制定了相应的水土保持治理措施,为当地政府开展水土保持规划工作提供科学依据。

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GIS和USLE的下庄小流域土壤侵蚀量预测研究

将地理信息系统Geographical Information System(GIS)与通用土壤流失方程Universal Soil Loss Equation(USLE)相结合进行流域土壤侵蚀量的预测和估算.以福建省九龙江典型小流域下庄为研究区域,在桌面GIS软件MapInfo和ArcView的支持下,建立流域的空间数据库,利用GIS的栅格数据空间分析功能,将小流域空间离散化为10 m×10 m的栅格,根据合适的USLE因子算法生成各因子栅格图,借助GIS图形运算,实现了下庄小流域的土壤侵蚀量估算和土壤侵蚀关键源区的标识,进一步利用GIS和USLE结合对小流域进行土壤侵蚀控制措施的模拟,为下庄小流域土地利用和水土保持提供科学依据.研究结果表明,下庄小流域的平均土壤侵蚀模数为2 541.66 t/km2.a,土壤侵蚀强度属中度,强度侵蚀以上区域占流域面积的11.17%.在模拟实施控制管理措施后,小流域土壤侵蚀模数降为1 570.89 t/km2.a,土壤侵蚀强度属轻度,强度侵蚀以上区域降为3.75%.

水蚀模型USLE与WEPP在紫色土水蚀预测中的应用对比研究

该文分别确定了USLE与WEPP模型的参数指标,通过实测遂宁组紫色土的单次降雨产沙量,对降雨产沙实测值与模型预测值进行比较分析,结果表明:在20°休闲小区模拟预测WEPP模型预测效果多数情况下优于USLE模型;通过多因子贡献分析发现,降雨量因子对产沙量的影响最大,其对休闲区和布设措施小区产沙量的贡献率分别达到了48.0%和64.1%。根据统计学中累积贡献率大于80%确定公共因子的原则,确定降雨量与降雨历时为遂宁组紫色土地区侵蚀产沙量的公共因子。

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USLE的汶川地震后理县土壤侵蚀特征及分析

为了较准确地评估汶川地震后理县的土壤侵蚀状况,该研究结合GIS、RS、USLE(universal soil loss equation)定量地分析了汶川地震灾区理县的潜在土壤侵蚀和实际土壤侵蚀状况,并对地震前后土壤侵蚀量做了简要的对比分析,并且从坡度、坡向、土地利用类型、高程4个方面系统地研究了不同侵蚀强度区的面积和土壤侵蚀量的变化。研究结果表明:震后理县全年土壤侵蚀量达844.46万t/a,平均侵蚀量为1957.79t/(km2·a),属于轻度侵蚀,相比地震前轻度侵蚀、强度侵蚀、极强度侵蚀区域面积都有很大增长,有林地、坡度≥30°～50°、海拔≥2000～3000m、坡向为南坡、西坡的地带土壤侵蚀比较严重。该研究为理县震后土壤侵蚀的预防和治理工作提供了很好的依据。

基于GIS和USLE的龙墩水库小流域土壤侵蚀评估研究

本研究以南京市高淳区龙墩水库流域为研究对象,利用通用土壤流失方程(USLE)模型与地理信息系统(GIS)技术结合的方法对流域土壤侵蚀进行模拟预测。结果表明:整个流域年均土壤侵蚀模数为4 343.46 t/km^2,属中度侵蚀。整个流域微度和轻度侵蚀所占面积比例相对较大,两者所占面积比例之和超过了63%,极强度和剧烈侵蚀虽然所占面积较小,但却产生了超过了70%的侵蚀量。不同土地利用类型中土壤侵蚀强度差异较大,年均侵蚀模数旱田>草地>水田>林地,侵蚀量旱田>水田>草地>林地。通过GIS将整个流域划分为13个子流域,子流域4、5、10由于区域内大部分是旱田,土壤侵蚀模数较大,为流域内土壤侵蚀的关键源区,子流域10侵蚀模数和侵蚀量都比较大,应该重点关注;而子流域1、9和12由于侵蚀总量较大,也应该保持一定的关注。所有子流域土壤侵蚀量都主要来自高强度侵蚀等级,其中以剧烈侵蚀为主。因此,控制土壤侵蚀应该优先考虑高强度侵蚀等级区域。

基于GIS和USLE的密云县土壤侵蚀评价及空间特征研究

将地理信息系统与通用土壤流失方程(USLE)相结合进行密云县土壤侵蚀量的预测。在全面调查,收集研究区气候、地形、土壤等基础资料的基础上,通过Landsat-TM影像提取土地利用信息、植被覆盖度信息,并建立土壤侵蚀空间数据库。运用通用土壤侵蚀模型USLE定量计算出土壤侵蚀量,并对研究区土壤侵蚀强度进行了分级,旨在探求密云县土壤侵蚀空间分布的特点及成因,为该区域水土保持和北京市的安全供水提供科学依据。研究表明,地貌类型和土壤类型是密云县土壤侵蚀中影响较大的因子。