贵州普定后寨河流域土壤侵蚀模型与应用研究

在典型岩溶区，由于喀斯特的强烈发育，自然条件差，加上人为因素的不良影响（毁林开荒、乱砍滥伐等），水土流失问题十分严重。随着遥感（Remote Sensing)技术的飞跃发展，计算机技术有普遍应用，特别是近年来地理信息系统（GIS）研究的迅速发展与应用，使土壤侵蚀研究从土壤侵蚀类型、分类、侵蚀地貌、侵蚀模数等定性、定量研究深入到潜在危害的研究阶段。本文是前人研究工作的基础上，以普定后寨河岩溶流域（普定岩溶野外试验场）为研究区，利用遥感（RS）和地理信息系统（GIS）技术建立起适合于岩溶流域使用的土壤侵蚀定量模型，并在PAMAP GIS的支持下，探讨了利用遥感信息、GIS自动提取土壤侵蚀因子，最后得到流域实际的土壤侵蚀图、潜在的土壤侵蚀图等一系列图件，为岩溶流域的综合治理提供有效的理论研究依据。     

贵州省乌江流域土壤侵蚀模拟——基于GIS、RUSLE和ANN技术的研究

本研究在GIS技术支撑下选择RUSLE模型作为基础模型,估算乌江流域20世纪80年代和90年代年均土壤侵蚀量,结合ANN技术,预测2001—2010年乌江流域的土壤侵蚀量,分析了该流域近30年来土壤侵蚀动态变化规律,以期为研究区土壤侵蚀防治工作提供理论依据。研究结果表明:应用RUSLE模型计算乌江流域年均土壤侵蚀模数,计算结果和以往土壤侵蚀调查估计的结果比较吻合,但由于RUSLE模型不计算重力侵蚀,因此计算结果仍与实测输沙模数有所出入。90年代潜在土壤侵蚀模数比80年代高,流域潜在土壤侵蚀呈增加趋势,其中三岔河流域和马蹄河/印江河流域年均潜在土壤侵蚀模数最高。3种主要土地覆被类型中,林地的土壤保持量最大,耕地次之,草地最少,这与非喀斯特地区在水土保持效果上通常林地草地旱地的结论有所不同。通过构建BP神经网络,预测得到乌江流域2001—2010年土壤侵蚀模数,结果显示,21世纪前10年,流域土壤侵蚀模数大幅降低,流域年均土壤侵蚀模数由90年代的23.13 t/(hm2·a)降低为1.01 t/(hm2·a)。三岔河流域的水土流失得到了控制,黔西、金沙、息烽、修文、贵阳、平坝、思南、石阡、沿河和松桃等县市应是"十二五"期间的水土流失重点治理对象。     

基于RS/GIS和RUSLE的流域土壤侵蚀定量研究——以福建省吉溪流域为例

借用地理信息系统(GIS)和遥感(ERDAS)技术,以修正的通用水土流失方程(RUSLE)为核心,根据吉溪流域2001年和2003年的遥感影像解译数据和统计资料得到地貌、降雨量、植被等资料,量化流域土壤侵蚀评价因子,对吉溪流域土壤侵蚀进行了定量化分析.结果表明,吉溪流域年均土壤侵蚀模数为2 339.21t/km2,侵蚀强度属轻度,2003年较2001年土壤侵蚀有所改善,中度侵蚀及其以上等级的土壤侵蚀量分别占总侵蚀量的48.71%和77.51%.最后确定流域土壤侵蚀重点治理的区域和流域最佳管理措施(BMPS),为吉溪流域水土保持和水环境保护研究工作提供科学依据.     

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。      

祁连山石羊河上游山区土壤侵蚀的环境因子特征分析

在GIS技术支持下, 运用通用水土流失方程USLE, 对祁连山北坡东段的哈溪林区的土壤侵蚀量及空间分布进行了模拟运算, 并定量分析了各种环境因子与土壤侵蚀之间的关系. 结果显示: 研究区平均土壤侵蚀模数为25.1 t·hm^-2·a^-1, 微度和轻度侵蚀面积占总面积的80%, 而强度到剧烈侵蚀产生的侵蚀量占78.3%; 各土地类型土壤侵蚀模数由高到低依次是裸地>草地>农田>灌丛>乔木林, 裸地侵蚀量占到总侵蚀量的54.9%; 乔木林和灌木林95%以上侵蚀面积属微度侵蚀区, 农田中度到剧烈侵蚀的面积比例达到35.9%, 高于草地和其他植被类型, 而草地剧烈侵蚀面积比例高于农田. 海拔高度范围与土壤流失量之间的关系与植被的海拔分布范围明显相关; 土壤平均侵蚀模数随坡度的增加而增大, 土壤侵蚀量主要分布在15°～45°的坡度范围, 不同植被覆盖下土壤流失随坡度变化的趋势可在一定程度上反映该类植被对土壤流失的防止作用.     

基于RUSLE模型的安徽郎溪县土壤侵蚀时空变化及其影响因素分析

为配合正在安徽省郎溪县开展的1∶50 000土地质量地球化学调查评价项目,给郎溪县土地质量地球化学调查与评价提供丰富的遥感层面数据,同时为地方政府对土地利用规划、农作物种植、农业林业生产管理、地质灾害治理和生态环境保护等方面提供数据支撑,本文基于RUSLE模型、GIS与RS技术获取了郎溪县2010年、2020年土壤侵蚀空间分布及2011—2020年的平均土壤侵蚀空间分布,探究在强降水事件及长时序、常态化下郎溪县土壤侵蚀的时空变化及其主要影响因素。结果表明：郎溪县土壤侵蚀等级较高区域主要集中于东北侧和西南侧丘陵山区,2010年平均土壤侵蚀模数为549.148 t/(km²·a),2020年为704.924 t/(km²·a),土壤侵蚀减弱区域占全县面积的9.3%,土壤侵蚀增加区域占全县面积的44.0%,因此,2020年强降水事件对郎溪县土壤侵蚀影响显著,且土壤侵蚀加剧的主要影响范围集中于微度侵蚀和轻度侵蚀层面,并多发于高植被覆盖且低地势耕地区域。2011—2020年间的平均土壤侵蚀模数为443.923 t/(km²·a),...     

基于集水单元的岩溶山区小流域泥石流敏感性评价——以贵州威宁二塘河流域为例

本文选取岩溶区小流域,查明了泥石流分布及土壤侵蚀现状,分析了泥石流固体物质来源并对土壤侵蚀模数进行了计算,选取了地形地貌和物源状态两类评价因子,基于集水单元完成了研究区泥石流敏感性评价。结果表明,研究区土壤侵蚀是泥石流的主要固体物质来源,评价结果与泥石流分布特征及活动历史相符合,为指导研究区泥石流防治工作和岩溶区小流域泥石流敏感性评价提供参考。     

基于RS与GIS的麻地沟土壤侵蚀及其生态环境效应研究

以GIS、RS和修正的土壤流失方程(RUSLE)为基础,结合遥感影像解译数据、地形图及降雨资料等,对麻地沟的土壤侵蚀进行了定量分析,并根据土壤侵蚀定量计算结果,结合景观生态学的方法,分析土壤侵蚀引起生态环境效应的因子,包括植被指数和景观指数等,对麻地沟地区的生态环境效应进行了分析。结果表明:研究区土壤侵蚀状况正在逐步好转,坡耕地和坡荒地是发生土壤侵蚀面积相对较高的两种土地利用类型,在保证当地居民所需坡耕地的情况下,修造梯田和植树造林是控制土壤侵蚀最有效的方式。     

沙河市土壤侵蚀模数分析计算

河流泥沙是流域降水和径流作用的共同产物,利用水文比批法,对影响因素进行修正,用参证站的侵蚀模数乘以影响系数计算出其它流域的土壤侵蚀模数。计算结果表明:划分后三个区域土壤侵蚀模数分别为,第Ⅰ区为521 t/km2·a,第Ⅱ区为595 t/km2·a,第Ⅲ区为670 t/km2·a。     

密云沙厂小流域土壤侵蚀GIS和RS评价方法研究

从GIS和RS研究的角度对沙厂小流域实测的土壤侵蚀数据进行分析,建立基于3S的土壤侵蚀综合评价指标模型,快速地计算出土壤侵蚀量,并对其侵蚀的动态过程进行监测,为沙厂小流域综合治理的快速决策提供科学的平台和依据.     

Temporal soil erosion risk evaluation: a CORINE methodology application at Elmalı dam watershed,Istanbul

Geographical information systems (GIS)-based soil erosion risk assessment models continue to play an important role in soil conservation planning. In the present study, soil erosion risk of Istanbul–Elmalı dam watershed was determined within GIS-based COoRdination of INformation on the Environment (CORINE) soil erosion risk assessment method. Initially soil texture, soil depth, and surface stoniness maps were created and were intersected in GIS environment in order to generating erodibility map. Then, Fournier precipitation and Bagnouls–Gaussen drought indices determined based on meteorological data and erosivity were calculated. The composed erodibility map was co-evaluated within erosivity value and slope map of the site for composing potential erosion risk map. At the final step, the previous yearly land use maps which belong to years 1984, 1992, and 2003 intersected with potential erosion risk maps and temporal actual erosion risk alteration were assessed. In conclusion, according to our results in Elmalı watershed dam in 1984 there have been low, medium, and high erosion risks at rates 29.67, 52.49, and 17.84%, respectively, whereas in 2003 the erosion risk values have changed from low to high as 26.43, 46.57, and 27.00%, respectively. Inter-year comparison alteration to the advantage of the high erosion risk could have resulted from over degradation and high exposure to anthropogenic activities.     

Regional soil erosion risk mapping using RUSLE,GIS, and remote sensing: a case study in Miyun Watershed,North China

This paper applied the Revised Universal Soil Loss Equation (RUSLE), remote-sensing technique, and geographic information system (GIS) to map the soil erosion risk in Miyun Watershed, North China. The soil erosion parameters were evaluated in different ways: the R factor map was developed from the rainfall data, the K factor map was obtained from the soil map, the C factor map was generated based on a back propagation (BP) neural network method of Landsat ETM+ data with a correlation coefficient (r) of 0.929 to the field collected data, and a digital elevation model (DEM) with a spatial resolution of 30 m was derived from topographical map at the scale of 1:50,000 to develop the LS factor map. P factor map was assumed as 1 for the watershed because only a very small area has conservation practices. By integrating the six factor maps in GIS through pixel-based computing, the spatial distribution of soil loss in the upper watershed of Miyun reservoir was obtained by the RUSLE model. The results showed that the annual average soil loss for the upper watershed of Miyun reservoir was 9.86 t ha⁻¹ ya⁻¹ in 2005, and the area of 47.5 km² (0.3%) experiences extremely severe erosion risk, which needs suitable conservation measures to be adopted on a priority basis. The spatial distribution of erosion risk classes was 66.88% very low, 21.90% low, 6.19% moderate, 2.90% severe, and 1.84% very severe. Among all counties and cities in the study area, Huairou County is in the extremely severe level of soil erosion risk, about 39.6% of land suffer from soil erosion, while Guyuan County in the very low level of soil erosion risk suffered from 17.79% of soil erosion in 2005. Therefore, the areas which are in the extremely severe level of soil erosion risk need immediate attention from soil conservation point of view.     

Spatio-temporal analysis of different levels of road expansion on soil erosion distribution: a case study of Fengqing county, Southwest China

The construction of roads has direct and indirect impacts on soil erosion, with spatio-temporal variations existing among different levels of road zones. Aiming to quantitatively analyze the soil loss, this paper explored the relationship between the erosion of soil and its distance from the road in Fengqing county, Southwest China in 1987 and 2004, respectively. The average soil erosion was calculated and expressed with grid map using universal soil loss equation (USLE) model based on GIS and RS. Along the different levels of roads classified as trunk, county, town, village and unpaved road, the buffer zones were subdivided into five stripes, each of which was 200 meters wide. The average soil erosion modulus of each buffer zone was also counted. Results show that the soil loss decreases with increasing distance to the road except rare trunk roads in the region. In addition, the declined intensity varies with the different levels of roads. Soil erosion was more serious along the lower level road than the higher ones. And soil erosion was more severe for all levels of roads in 1987 than those in 2004 because much more rainfalls affected the situation of soil erosion in 1987.     

http://www.sciencedirect.com/science/article/pii/S1674987111001034

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 vulnerability 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^-1 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.     

基于网格数据的贵州土壤侵蚀敏感性评价及其空间分异

在通用土壤侵蚀方程的基础上,建立了土壤侵蚀敏感性评价指标体系,利用GIS方法对影响土壤侵蚀敏感性的单因子进行评价,并将各因子进行网格化,运用网格数据的空间叠加分析方法对贵州省土壤侵蚀敏感性进行综合评价。在此基础上探讨了贵州省土壤侵蚀敏感性空间分异规律。通过与已有的土壤侵蚀现状图比较,发现土壤侵蚀高敏感区与水土流失严重区并不吻合,并进一步指出,脆弱的喀斯特环境是产生严重水土流失和导致石漠化的地质基础,强烈的人类活动是加速这一过程的主要驱动力量。      

Relationship between soil erosion, slope, parent material, and distance to road (Case study: Latian Watershed, Iran)

Soil erosion is the dominating factor of damaging roads in Iran. Roads are a critical component of civilization. Developing and maintaining the economic activity that is vital for the quality of modern life would be difficult without roads. Accelerated erosion and increased sediment yields resulting from changes in land use are critical environmental problems, and one of the important changes is road construction. Construction and condition of roadways are associated with direct and indirect impacts on soil erosion. This paper presents the relationship between soil erosion and some characteristics such as distance to roadway, slope, and parent material in Latian Watershed, Tehran Province, Iran. Soil erosion map was interpreted using aerial photos and GIS technology. Buffer zones, subdivided into 12 strips, each 0.2 km wide, which were located alongside roadway. The distribution patterns of various types of erosion were also identified by GIS by overlaying road buffer strips and soil erosion map. The results show that soil erosion landform such as land slide, badland, bank erosion, channel erosion, etc. found in buffer zones along both sides of roads.     

Estimation of soil erosion using RUSLE in Caijiamiao watershed,China

Soil erosion is a serious environmental and production problem in China. In particular, natural conditions and human impact have made the Chinese Loess Plateau particularly prone to intense soil erosion area. To decrease the risk on environmental impacts, there is an increasing demand for sound, and readily applicable techniques for soil conservation planning in this area. This work aims at the assessment of soil erosion and its spatial distribution in hilly Loess Plateau watershed (northwestern China) with a surface area of approximately 416.31 km². This study was conducted at the Caijiamiao watershed to determine the erosion hazard in the area and target locations for appropriate initiation of conservation measures using the revised universal soil loss equation (RUSLE). The erosion factors of RUSLE were collected and processed through a geographic information system (GIS)-based approach. The soil erosion parameters were evaluated in different ways: The R-factor map was developed from the rainfall data, the K-factor map was obtained from the soil map, the C-factor map was generated based on Landsat-5 Thematic Mapper image and spectral mixture analysis, and a digital elevation model with a spatial resolution of 25 m was derived from topographic map at the scale of 1:50,000 to develop the LS-factor map. Support practice P factor was from terraces that exist on slopes where crops are grown. By integrating the six-factor maps in GIS through pixel-based computing, the spatial distribution of soil loss in the study area was obtained by the RUSLE model. The results showed that spatial average soil erosion at the watershed was 78.78 ton ha^?1 year^?1 in 2002 and 70.58 ton ha^?1 year^?1 in 2010, while the estimated sediment yield was found to be 327.96 × 10⁴ and 293.85 × 10⁴ ton, respectively. Soil erosion is serious, respectively, from 15 to 35 of slope degree, elevation area from 1,126 to 1,395 m, in the particular area of soil and water loss prevention. As far as land use is concerned, soil losses are highest in barren land and those in waste grassland areas are second. The results of the study provide useful information for decision maker and planners to take appropriate land management measures in the area. It thus indicates the RUSLE–GIS model is a useful tool for evaluating and mapping soil erosion quantitatively and spatially at a river watershed scale on a cell basis in Chinese Loess Plateau and for planning of conservation practices.     

Risk assessment of water soil erosion in upper basin of Miyun Reservoir,Beijing, China

This research selected water soil erosion indicators (land cover, vegetation cover, slope) to assess the risk of soil erosion, ARCMAP GIS ver.9.0 environments and ERDAS ver.9.0 were used to manage and process satellite images and thematic tabular data. Landsat TM images in 2003 were used to produce land/cover maps of the study area based on visual interpreting method and derived vegetation cover maps, and the relief map at the scale of 1:50,000 to calculate the slope gradient maps. The area of water soil erosion was classified into six grades by an integration of slope gradients, land cover types, and vegetation cover fraction. All the data were integrated into a cross-tabular format to carry out the grid-based analysis of soil erosion risk. Results showed that the upper basin of Miyun Reservoir, in general, is exposed to a moderate risk of soil erosion, there is 715,848 ha of land suffered from water soil erosion in 2003, occupied 46.62% of total area, and most of the soil erosion area is on the slight and moderate risk, occupied 45.60 and 47.58% of soil erosion area, respectively.     

吉林省中部不同土地利用类型的土壤侵蚀强度变化分析

在GIS支持下,应用TM遥感影像提取土地利用和土壤侵蚀的相关信息,采用叠加分析法研究了吉林省中部不同土地利用状况的土壤侵蚀规律。结果表明：吉林省中部土壤侵蚀整体呈减弱趋势,主要为占吉林省中部面积比例大的耕地侵蚀面积减少所致。但其他土地利用类型则表现为随着土地利用强度的增大,土壤侵蚀速度和侵蚀强度加剧。侵蚀类型由水蚀向风蚀转化,表明中部气候向干旱气候转化的趋势。不合理的土地利用是导致土壤侵蚀强度增大和气候向干旱转化的根本原因,进而又导致吉林省中部土地进一步退化,形成恶性循环。因此,进行水土资源优化利用和合理开发势在必行。