基于3S技术的流溪河流域水土流失分析研究

以GIS和RS技术为支撑,选取广东省流溪河流域为研究区域,选用通用土壤流失方程(RSLE),综合考虑降雨、植被、土壤、地形、土地利用等因子,对区域内的土壤侵蚀强度进行分析、评价,并对比分析研究区内土壤侵蚀强度及其空间分布特征,提出相应的水土流失治理措施.     

关于水土流失和水土保持定量研究的探讨

现阶段,我国对土壤流失和水土保持定量的研究可通过地块、水流域、区域或国家三大单位,融入统计性和物理性水土流失模式的研究、建立和评价,确定水土流失和水土保持定量研究发展方向,主要包括建立我国自主水土资源资料库、提高对土壤流失过程及影响因子的认知和提高水土空间特征认识。参考国外环境研究模型,从三个层次建模,优化我国水土流失评价模型系统,为我国水土流失和水土保持定量研究的发展提供一定的技术基础。     

云南省九大高原湖泊流域水土流失空间特征及影响因子分析

水土流失监测评价可为防治水土流失灾害、开展区域水土保持规划和生态环境建设提供科学依据。基于CSLE模型,采用遥感分析、野外调查、模型计算的方法,结合SL 190—2007《土壤侵蚀分类分级标准》等技术标准,分析了云南省九大高原湖泊流域水土流失因子及特征。2021年水土流失面积1 306.92 km²,占土地总面积的16.67%。从土地利用类型方面,水土流失面积主要分布在林地和耕地,分别占九湖流域水土流失面积的35.69%和31.60%,主要以轻度侵蚀为主;极强烈和剧烈侵蚀面积主要分布在耕地中,占九湖流域极强烈和剧烈侵蚀面积的82.85%。九大高原湖泊流域内,影响耕地和建设用地水土流失的主控因子是坡度;而影响园地、林地和草地水土流失的主控因子则为植被覆盖度和坡度。根据九湖流域的水土流失特点,针对林地需建设以水土保持林、水源涵养林为主的植被体系,加强远山封育保护等措施;对耕地进行以坡耕地整治为主的水土流失综合治理。研究通过获取九湖流域的水土流失空间分布特征,掌握流域内主要发生水土流失的土地利用类型,为水土流失综合治理提供支撑。     

基于CSLE模型的南、北盘江流域水土流失定量分析评价

水土流失定量评价可为防治水土流失灾害和开展生态环境建设提供科学依据。以多源遥感影像为信息源,基于ArcGIS平台的空间分析与数据管理等功能,获取南、北盘江流域土地利用、植被覆盖、地形坡度等数据,应用中国土壤流失方程(CSLE)计算土壤侵蚀模数,得到南、北盘江流域水土流失监测成果。结果表明,2021年南、北盘江流域水土流失面积共23 966.97 km²,以轻度侵蚀强度为主,流域东北部水土流失较西南部严重;水土流失主要发生在耕地、林地和草地,占总水土流失面积比例达90%以上,各等级园、林、草植被覆盖度均以轻度和中度侵蚀水土流失为主,整个区域水土流失主要发生在6～35°的坡度等级上。整体而言南、北盘江局部区域水土流失问题仍然突出,需以预防和治理相结合的手段改善该区域水土流失状况。     

河道整治区域水土流失监测与水土保持方法

在河道整治工程中,传统方法对区域性水土流失的监测准确率偏低。提出河道整治区域水土流失监测与水土保持方法,分别提取降雨侵蚀力因子、植被覆盖因子、坡度因子、土壤可蚀性因子及生物措施因子,在划分水土流失强度等级标准后,通过对水土流失因子的叠加计算,得到水土平均流失厚度,从而确定水土流失级别。通过对比结果发现,该方法能够准确监测水土流失强度等级。     

土地利用/覆盖对洞庭湖流域水土流失的影响

土地利用覆盖变化是当前国际地学研究的热点之一,通过大量的数据收集,利用灰色系统理论将洞庭湖各流域土地利用/覆盖对其水土流失的影响进行了聚类分析和关联分析.结果表明:1、耕地、荒山地、林地为洞庭湖流域水土流失影响的第一类因素,影响最大;非农业用地、草地为洞庭湖流域水土流失影响的第二类因素,影响居中;滩涂用地、园地、水域为洞庭湖流域水土流失影响的第三类因素,影响最小.2、各种土地利用类型对洞庭湖流域水土流失影响的排序为耕地、荒山地、林地、草地、非农业用地、园地、水域、滩涂用地.论文旨在为洞庭湖流域水土流失及洞庭湖的治理提供科学依据.     

基于GIS的陡河水库流域水土流失研究

基于GIS技术提取陡河库区流域水土流失影响因子,并运用通用土壤流失方程(RUSE)测算水土流失强度等级。结果表明,陡河水库流域水土流失强度分属微度、轻度、中度、强度4级,其分布面积分别占71.24%,17.67%,10.23%,0.84%,水土流失以微度为主。强度水土流失集中分布于建设用地和坡度介于8°~18°的地带,该区是水土流失治理的重点区域。鉴于库区林草覆被质量较好,整体水土流失较弱,应注重分区管理与生态防治。     

基于技术的生态小流域水土保持规划探究

近年来随着国家对生态经济的大力扶持，小流域治理成效显著，但在规划设计中以传统手段进行基础资料的获取居多，文中结合承德市艾峪口小流域设计进行探究，运用GIS技术及Arc View软件对流域水土流失各影响因子进行叠加分析，获取更精准的数据，运用所构建起的工程区水土保持规划数据库进行了流域水土流失现状的定量分析，并针对流域水土流失地块单元进行措施布置，从而实现工程区水土保持规划的总体布局，有效提升水土保持规划设计成果的直观性和准确性。     

豫西矿区土壤侵蚀因子及流失特点分析

豫西沿黄地区矿产资源丰富,矿山开采加剧了局部区域水土流失及其危害。为合理有效防治矿区水土流失,利用水土保持观测站的实测资料并通过典型矿区现场量测、高分辨率遥感影像解译、GIS分析计算等,对豫西沿黄典型矿区土壤侵蚀因子与土壤流失特点进行了分析,结果表明:降雨侵蚀力因子作为土壤侵蚀背景因子服从于区域性与潜在性整体规律,虽然其值大小不受采矿活动影响,但它是矿区土壤侵蚀的重要外营力,与矿区土壤侵蚀的其他因子共同作用,影响矿区土壤流失的时空分布;地形因子、土壤可蚀性因子、植被覆盖因子、水土保持措施因子是影响矿区土壤侵蚀发生发展与程度的关键因子,其抑制土壤侵蚀的作用受采矿活动的影响;矿区土壤流失在各时期的分布特点是开采期最大,从基建期到开采期再到停采后的恢复期,土壤流失量变化情况是由小变大再由大变小;土壤流失量空间分布特点是露天采场、排土场占比较大。矿区土壤流失量时空分布特点与矿区采矿活动对土壤侵蚀因子的改变密切相关,水土流失防治的重点时期是开采期、重点区域是露天采场和排土场。     

不同土地利用变化情景模式对大洋河水土流失影响研究

基于分布式水文模型SWAT模型,以大洋河为研究流域,通过设定三种土地利用情景模式,定量分析了不同土地利用情景模式对大洋河水土流失的影响。研究结果表明:SWAT模型适合于大洋河流域水土流失模拟,模拟的水土流失相对误差小于20%,确定性系数达到0.5以上;土地利用情景模式I(林地增加10%,旱地减少10%)下流域水土流失量减少6.8%~10.2%,土地利用情景模式II(林地面积减少10%,草地面积增加10%)下流域水土流失量增加3.2%~7.9%,土地利用情景模式III(林地减少10%,城镇用地增加10%)下流域水土流失量减少11.5%~15.2%,城镇用地对水土流失影响大于林地。研究成果对于大洋河流域水土流失治理和水土资源保护提供参考价值。     

三峡库区下岸溪小流域水土流失现状评估

 以三峡库区下岸溪小流域为研究区,在GIS软件的支持下,利用2008年SPOT5遥感影像和1∶5万DEM数据,提取坡度因子、植被覆盖度因子和土地利用类型因子作为水土流失风险评估指标因子,结合土壤侵蚀分级标准,生成研究区水土流失风险分级图,利用改进的工程侵蚀模数计算模型,对小流域土壤侵蚀量进行了估算。结果表明：①本流域以水力侵蚀为主,占研究区总面积的88.81%,其中中度侵蚀面积占该流域总面积的38.49%;②开矿等引起的工程侵蚀对该小流域土壤侵蚀量贡献率很大,占该流域水土流失量的41.43%。因此,在开矿和矿区基础设施建设等工程施工时,应采取有效的水土保持措施。     

筑坝河流不同尺度土地利用结构对库区水质的影响——以平寨水库为例

为了分析筑坝河流域人类活动与库区水质的响应关系,以平寨水库为例,选取子流域、河流缓冲区及监测点圆形缓冲区三种尺度,基于2017年Landsat8 OLI遥感影像解译结果所反映的土地利用结构特征,结合实测监测点水质指标数据,运用GIS空间分析及统计分析的方法,探讨筑坝河流流域土地利用结构对库区水质的影响。结果表明:(1)在三种尺度上,土地利用结构与库区水质都有显著相关性,河流缓冲区和子流域尺度相关规律基本一致,但与圆形缓冲区尺度相关规律差异较大;(2)不同土地利用类型面积比例对水质的影响存在尺度效应,不同尺度上表现出不同的"源"与"汇";(3)土地利用相对合理指数R与水质指标呈显著负相关,说明土地利用结构越合理,越有利于减少土壤侵蚀,水体中污染物浓度就越低。     

不同措施下土壤侵蚀特征值及其影响因子典型相关分析

根据东北沟小流域观测裸地、等高耕种、水平阶等3种措施径流小区的径流量和泥沙量资料,研究不同措施下径流泥沙与降雨等因素的相互关系,采用典型相关分析法分析不同措施下影响土壤侵蚀的主要因子。结果表明,在裸地和等高耕作措施下,径流深在土壤侵蚀特征因子中起主要作用,而在水平阶措施下,土壤流失模数在土壤侵蚀特征因子中起主要作用。不同措施下土壤侵蚀影响因子不同,在裸地和水平阶措施下,可以通过降雨量、雨强和雨前土壤含水量等土壤侵蚀影响因子来预测径流深和土壤流失模数,而在等高耕作措施下,用降雨量、雨强、降雨侵蚀力等土壤侵蚀影响因子预测土壤侵蚀特征因子更为准确。     

Integrated Remote Sensing and Geographic Information System Based RUSLE Modelling for Estimation of Soil Loss in Western Himalaya,India

Soil loss due to water erosion was estimated in Kangra region of western Himalaya using revised universal soil loss equation modelling (RUSLE) in conjunction with Remote Sensing (RS) and Geographic Information Systems (GIS). The various parameters such as rainfall erosivity (R), soil erodibility (K), topographic factor (LS), crop management factor (C) and support practice factor (P) were derived using standard techniques. The study revealed that forest cover, crop land and scrub/grass land constitute 87.4 % of soil erosion susceptible area. The rate of depletion of soil was estimated at 25.63 t/ha/yr. It was highest in stony/barren land (60.3 t/ha/yr) and lowest in case of tea garden (16.09 t/ha/yr). It was felt that there is a need of implementation of soil and water conservation measures in the region to curb the soil loss. The undulating nature of terrain was observed as the main contributing factor for soil erosion. It was concluded that RS and GIS based RUSLE model can be efficiently used in mountainous regions to determine the status and extent of soil erosion.     

RUSLE2 Model Application for Soil Erosion Assessment Using Remote Sensing and GIS

The study is focused on the estimation of rate of soil erosion, using Revised Universal Soil Loss Eq. 2 (RUSLE2), in the Veppanapalli subwatershed of Krishnagiri catchment located in Tamil Nadu, India. The soil erosion is estimated for each of the hillslope units in the study area. The factors considered are intensity of rainfall, type of soil, land use classification and the existing soil conservation practices. Detailed analysis of soil samples were done to assess the texture, structure, permeability and organic matter content of the soil samples of each hillslope unit. The required data for the other parameters were estimated by carrying out intense field investigations and by the analysis of the satellite imagery of 5.6 m resolution. A data base was created with all the subfactor values for the hillslope units. Incorporation of remote sensing technique and Geographic Information System (GIS) made the spatial analysis of the study more reliable and accurate. The annual average soil erosion rate is estimated as 25 t/ha/year, which is on a higher range. This indicates the immediate need for the adoption of proper conservation strategies in this area to control the eutrophication in the Krishnagiri reservoir and to prevent further watershed degradation.     

A GIS‐based approach to mapping probabilities of river bank erosion: regulated River Tummel,Scotland

This study explores the use of Geographic Information Systems (GIS) techniques for mapping river channel planform change and bank erosion probability. The method used is primarily based on an approach developed by Graf (Graf, W.L. 1984. ‘A probabilistic approach to the spatial assessment of river channel instability’, Water Resour. Res., 20 (7), 953–962), which proposed that bank erosion probability could be determined for any given cell on a floodplain by taking into account (i) its distance laterally and in the upstream direction to the active river channel, and (ii) a value representing flood magnitudes for the given period. In this study, Graf's method is refined by using a GIS approach and by incorporating the influence of geomorphic variables, such as river bank morphology, sediment type and floodplain vegetation, on bank erosion rates. In addition, the technique is applied to a wandering gravel‐bed river of roughly 80 m width, representing a different type and size of river to that used in Graf's study. Thus, the wider applicability of the technique is tested. In addition, the analysis here covers only a short time scale (1988–1994) compared with that used by Graf. The high temporal resolution of this study is enabled by the use of aerial photography and also by the substantial channel changes that occurred within this time period as a result of several high magnitude flood events. The results of the study indicate the usefulness and validity of the approach, particularly with regard to floodplain erosion hazard mapping and the assessment of the effects of altered flood regimes and land use. Copyright © 2000 John Wiley & Sons, Ltd.     

Effects of soil erosion on water quality and water uses in the upper Phong watershed.

The main objective of this paper is to simulate the effects of soil erosion on river water quality and on agricultural production as a result of the transformation of forestlands in the catchment of the upstream Phong River. Suspended solids carry down attached nutrients and agricultural chemicals causing water pollution in the downstream. There are four different types of land use in this simulation, namely forestlands, flatland and highland sugarcane plantation areas, and paddy fields. The highest mean annual amount of soil erosion is from paddy fields (585,700 tons/year), followed by highland (73,800 tons/year) and flatland (63,950 tons/year) sugarcane plantation areas and forestlands (41,800 tons/year), respectively. However, as most of paddy fields are located in a low land and are wet type cultivations, the soil erosion occurred has less impact on river water quality and its production compared to the soil erosion from the steeper slopes of highland plantation areas. Under the resource-based agriculture, the sugarcane production is mainly increased by expanding the plantation areas leading to a significant loss of topsoil and a considerable reduction of agricultural production. Soil erosion contributes to an increase in the average annual suspended solids concentration by 72 mg/l.     

Finite Element Method and GIS Based Distributed Model for Soil Erosion and Sediment Yield in a Watershed

The objective of this study is to develop a soil erosion and sediment yield model based on the kinematic wave approximation using the finite element method, remote sensing and geographical information system (GIS) for calculating the soil erosion and sediment yield in a watershed. Detachment of soil particles by overland flow occurs when the shear stress at the surface overcomes the gravitational forces and cohesive forces on the particles. Deposition occurs when the sediment load is greater than the transport capacity. Beasley et al.’s (Trans ASAE 23:938–944, 1980) transport equations for laminar and turbulent flow conditions are used to calculate the transport capacity. The model is capable of handling distributed information about land use, slope, soil and Manning’s roughness. The model is applied to the Catsop watershed in the Netherlands and the Harsul watershed in India. Remotely sensed data has been used to extract land use/land cover map of the Harsul watershed, and other thematic maps are generated using the GIS. The simulated results for both calibration and validation events are compared with the observed data for the watersheds and found to be reasonable. Statistical evaluation of model performance has been carried out. Further, a sensitivity analysis has also been carried out to study the effect of variation in model parameter values on computed volume of sediment, peak sediment and the time to peak sediment. Sensitivity analysis has also been carried out for grid size variation and time step variation of the Catsop watershed. The proposed model is useful in predicting the hydrographs and sedigraphs in the agricultural watersheds.     

基于RUSLE模型的辽宁省土壤侵蚀定量研究

以降雨量、土壤、遥感影像及土壤侵蚀普查数据等为基础数据,运用GIS技术,结合修正的通用土壤流失方程(RUSLE)模型对辽宁省土壤侵蚀状况进行研究,分析了土壤侵蚀的空间分布特征以及与不同土地利用类型的关系。研究结果表明:2011年辽宁省土壤侵蚀面积为459.36万hm²,年均土壤流失量为1.64亿t,年平均侵蚀模数为3 637.8 t/(km²·a),属于中度侵蚀,土壤侵蚀面积呈现上升趋势;辽西低山丘陵区的土壤侵蚀最为严重,侵蚀面积为191.99万hm²,城市受人为不合理的生产活动影响严重,导致土壤侵蚀面积增加;林地依旧是辽宁省土壤侵蚀发生的最主要的土地类型,占侵蚀总面积的57.66%,占土地利用类型的38.20%。     

基于GIS技术的贵州省土壤侵蚀危险性评价

针对目前喀斯特区土壤侵蚀潜在危险度研究相对薄弱的现状,以典型喀斯特区贵州省为研究对象,获取研究区土地利用类型、岩性、基岩裸露率等专题因子。基于地理信息系统(GIS)技术,在非喀斯特区和喀斯特区分别采用《土壤侵蚀分类分级标准》和《岩溶地区水土流失综合治理技术标准》解译出研究区土壤侵蚀强度等级分布图。并根据土壤允许流失量和土壤抗蚀年限,利用土壤侵蚀潜在危险度指数(SEPDI)对贵州省土壤侵蚀潜在危险度进行评价,为喀斯特区土壤侵蚀防治提供参考。结果显示:贵州省水土流失面积为47 831.73 km²,以轻度侵蚀为主,侵蚀模数为341 t/(km²·a),SEPDI为2.52,潜在危险等级较高。贵州25.3%行政村的SEPDI位于2~3之间,其中六盘水、黔西南市和毕节市危险度最高,建议将水土流失防治工作纳入SEPDI指标而非单从水土流失强弱等级进行治理,特别加强对SEPDI高但水土流失等级弱的区域的关注。