区域土壤侵蚀遥感与核素示踪联合评价技术

土壤侵蚀遥感调查具有宏观、快速、信息量大等优点,但是实际应用中有3大制约因素：1）廉价高分辨率影像的获取;2）科学准确的判读和解译方法;3）成熟的土壤侵蚀评价模型或系统的观测数据。我国普遍缺乏土壤侵蚀评价模型和长期观测数据,技术问题比较突出。土壤侵蚀遥感调查中,采用经验分级指标法得出土壤侵蚀现状或强度,影响了土壤侵蚀评价的精度、准确性和应用范围。利用土壤侵蚀核素示踪技术测算不同土地利用单元的土壤侵蚀量,能够突破了遥感土壤侵蚀调查依赖模型和观测数据的限制,实现土壤侵蚀评价的宏观与微观、点与面、估算与实测的结合,为区域土壤侵蚀快速评价提供一条高效途径。     

基于GIS和CSLE的陕西省土壤侵蚀定量评价方法研究

通过对陕西省土壤侵蚀的定量评估,探索省域尺度上土壤侵蚀定量评价制图方法,以期为第四次全国土壤侵蚀普查提供技术支撑.利用陕西省日降雨数据、土壤类型图、土地利用图、DEM、植被覆盖图,选择CSLE模型.在ArcGIS平台上计算研究区2006年土壤侵蚀量,并与水利部标准评价结果进行对比分析.探索了坡度坡长变换对土壤侵蚀的影响.定量化的评价结果能较好的反映气候,土壤及水保措施对土壤侵蚀的影响,比水利部标准评价结果更能反映实际侵蚀.坡度坡长变换后对土壤侵蚀有明显影响.在GIS支持下,通过土壤侵蚀模型进行定量评价,可高效、客观反映土壤侵蚀情况及其主要影响因子,对区域治理和有关决策有极其重要参考价值.为了准确真实的反映土壤侵蚀程度,必须进行坡度坡长变换.     

GIS支持下的土壤侵蚀敏感性评价研究

区域土壤侵蚀受到多种因素的影响和制约,在综合分析了影响福建省土壤侵蚀的主要因子:降水、地形起伏、土壤质地、植被因子和人为活动因子的基础上,根据国内外对土壤侵蚀敏感性评价的研究成果以及福建省的自然环境特征,确定了影响福建省土壤侵蚀的主要因子和敏感性等级。在GIS软件支持下,完成了评价指标数据的提取和集成,并按照敏感性等级标准进行土壤侵蚀敏感性评价。     

遥感技术在土壤侵蚀研究中的应用述评

[目的]对遥感技术在土壤侵蚀研究中的应用进行述评,探索土壤侵蚀遥感研究的发展方向,并为研究者快速选择适宜的遥感数据源和研究方法提供参考。[方法]通过文献查阅,从不同研究方面开展综述和分析。[结果]针对不同研究区域和主题,总结了土壤侵蚀研究中常用遥感平台和数据源,综述了遥感技术在区域土壤侵蚀特征识别、监测与尺度效应研究中的应用。以及遥感技术在通用土壤流失方程关键因子获取中的应用。同时分析了目前研究中存在的问题并提出相应建议。[结论]遥感技术作为开展大范围、长时间序列土壤侵蚀研究的重要技术手段,在我国土壤侵蚀研究中发挥了巨大作用。但实际应用中也存在基层遥感数据时效性不强、数据源单一和识别因子针对性不强等问题。其高效应用和推广需要技术层面和人员、经济支持层面共同发展与创新。     

黄河下游防洪工程的生态环境影响分析

区域土壤侵蚀受到多种因素的影响和制约，在综合分析了影响福建省土壤侵蚀的主要因子：降水、地形起伏、土壤质地、植被因子和人为活动因子的基础上，根据国内外对土壤侵蚀敏感性评价的研究成果以及福建省的自然环境特征，确定了影响福建省土壤侵蚀的主要因子和敏感性等级。在GIS软件支持下，完成了评价指标数据的提取和集成，并按照敏感性等级标准进行土壤侵蚀敏感性评价。     

杏子河流域土壤侵蚀空间差异快速评估与验证

利用RS与GIS相结合的技术手段,探讨了流域下垫面覆盖信息和地形信息的快速提取方法;在对土壤侵蚀评价因子进行合理筛选以后,参考国家土壤侵蚀分级分类及其参考指标,利用ERADS图像处理软件提供的专家分类器,实现对土壤侵蚀强度及其空间差异的快速、精确评估,并以水文站的观测数据进行验证。     

黄土高原中小流域土壤侵蚀快速评估方法研究——以杏子河流域为例

以杏子河流域为例 ,利用RS与GIS相结合的技术手段 ,快速提取流域下垫面覆盖信息和地形信息 ,在对土壤侵蚀评价因子进行合理筛选以后 ,参照国家土壤侵蚀分级分类指标 ,利用ERADS图像处理软件提供的专家分类器 ,实现对土壤侵蚀强度及其空间差异的快速、精确评估 ,并利用水文站的观测数据进行了验证     

贵州高原水土流失及其影响因素研究

在利用遥感技术编制贵州省土壤侵蚀图的基础上,阐述了贵州省不同级别水土流失强度分布状况,水土流失在危险程度及水土流失强度分区;分析了贵州高原流失产生的自然背景与影响因素;并根据贵州高原的特点提出了治理保护的战略措施。     

基于GIS和RUSLE的粤东黄冈河流域土壤侵蚀评估

以TM影像图、数字高程模型DEM、土地利用类型图、土壤数据为信息源,以GIS技术和RUSLE模型为研究方法,对粤东黄冈河流域土壤侵蚀进行了评估,并分析了影响土壤侵蚀的主要因素。结果表明,降雨是影响土壤侵蚀的最主要因素,该流域多年平均土壤侵蚀模数为1 745.5 t/(km2.a),属轻度侵蚀;地形地貌是影响土壤侵蚀的显著因素,随着地形坡度的增加土壤侵蚀模数显著增大;不同土地利用类型的土壤侵蚀量差异较大。根据研究结果,指出15°—25°、25°—35°两个坡度带和居民点及交通用地、草地为黄冈河流域土壤侵蚀防治的重点区域。     

应用遥感技术动态监测土壤侵蚀的研究

在建立湖北省土壤侵蚀强度分级体系基础上 ,应用遥感技术进行了“湖北省第三次土壤侵蚀动态遥感调查” ,根据遥感资料解译结果对土壤侵蚀动态变化进行了分析 ,划分了不同的土壤侵蚀景观区。在 1995年第二次遥感调查数据的基础上 ,经过 2 0 0 0年遥感图像数据的动态监测调查 ,得出了土壤动态监测成果数据 ,进而对动态变化趋势和原因进行了分析。     

Guest editorial – soil erosion assessment,tools and data: A special issue from the Global Symposium on soil Erosion 2019

This special issue on soil erosion assessment, tools and data creation, consolidation and harmonization presents advances in soil erosion research with a focus on new tools that are being used to assess soil erosion rates. This publication includes eleven selected contributions presented at the Global Symposium on Soil Erosion (GSER, 15–17 May 2019, Rome, Italy) dealing with erosion indicators’ improvement, the use of remote sensing, nuclear techniques and geochemical fingerprinting as promising methods to assess soil losses, management practices that reduce soil erosion in vineyards and olive groves plantations and their modelling, and national and regional erosion assessments.     

Satellite remote sensing for water erosion assessment: A review

Water erosion creates negative impacts on agricultural production, infrastructure, and water quality across the world. Regional-scale water erosion assessment is important, but limited by data availability and quality. Satellite remote sensing can contribute through providing spatial data to such assessments. During the past 30 years many studies have been published that did this to a greater or lesser extent. The objective of this paper is to review methodologies applied for water erosion assessment using satellite remote sensing. First, studies on erosion detection are treated. This comprises the detection of erosion features and eroded areas, as well as the assessment of off-site impacts such as sediment deposition and water quality of inland lakes. Second, the assessment of erosion controlling factors is evaluated. Four types of factors are discussed: topography, soil properties, vegetation cover, and management practices. Then, erosion mapping techniques are described that integrate products derived from satellite remote sensing with additional data sources. These techniques include erosion models and qualitative methods. Finally, validation methods used to assess the accuracy of maps produced with satellite data are discussed. It is concluded that a general lack of validation data is a main concern. Validation is of utmost importance to achieve regional operational monitoring systems, and close collaboration between the remote sensing community and field-based erosion scientists is therefore required.     

Gully erosion modelling and landscape response in the Mbuluzi River catchment of Swaziland

In southern African countries soil erosion and the related problems, such as water quality issues or decreasing soil productivity, are the main topics affecting the inhabitants of both rural and urban areas. Therefore, the attention has been recently placed on those problems related to soil erosion. This can also be documented by an increasing number of studies carried out on erosion and by the development and application of erosion models. Nevertheless, gully erosion phenomena have been widely neglected in erosion modelling. This is because the development of erosion models was focused on those regions with an intense agriculture typical of developed countries on the one hand, and because of the spatial and temporal heterogeneity of gully erosion processes on the other hand. This study regards the identification of gully erosion forms and processes in the Mbuluzi River catchment (Kingdom of Swaziland) by using the Erosion Response Units (ERU) concept. The following modelling of gully erosion was done through the stable gully model [Catena 37 (1999) 401]. The input data were obtained through the application of remote sensing techniques (API method) and GIS-analyses. The example from Swaziland shows that the applied methods are able to identify areas affected by gully erosion. Furthermore, it is possible to estimate the amount of soil loss due to gully erosion, which, for example, is not taken into consideration by the USLE-type models.     

石家庄市土壤侵蚀定量评价研究

运用地理信息系统方法,结合遥感数字图像处理,对石家庄市土壤侵蚀进行了定量评价。通过对地形、地貌、土壤、植被等自然条件的分析和野外调查,收集到与侵蚀有关的遥感、气候资料及各类专题图件,筛选出了影响土壤侵蚀的12个因子,结合专家打分模型得到多因子融合后的复合评价结果,并与野外调查取得了很好的一致性。同时还对评价结果进行了验证和解释。     

IMPACT OF LAND USE CHANGE ON EROSION RISK: AN INTEGRATED REMOTE SENSING,GEOGRAPHIC INFORMATION SYSTEM AND MODELING METHODOLOGY

The objective of this study was to evaluate the impact of rapidly changing land use on erosion and sedimentation in a mixed land use watershed in the Ozark Highlands of the USA. The research combines a geographic information system‐based soil erosion modeling approach with land use change detection to quantify the influence of changing land use on erosion risk. Five land use/land cover maps were generated or acquired for a 20‐year period (1986 through 2006) at approximately 5‐year intervals to assess land use change and to predict a projected (2030) land use scenario for the West Fork White River watershed in Northwest Arkansas. The Unit Stream Power based Erosion/Deposition model was applied to the observed and predicted land use to assess the impact on erosion. Total erosion from urban areas was predicted to increase by a factor of six between 1986 and 2030 based on the projected 2030 land use. Results support previous reports of increased urbanization leading to increased soil erosion risk. This study highlights the interaction of changes in land use with soil erosion potential. Soil erosion risk on a landscape can be quantified by incorporating commonly available biophysical data with geographic information system and remote sensing, which could serve as a land/watershed management tool for the rapid assessment of the effects of environmental change on erosion risk. Copyright © 2011 John Wiley & Sons, Ltd.     

利用侵蚀模型普查黄土高原土壤侵蚀状况

土壤侵蚀普查对于土地资源保护和自然灾害防治具有重要意义。为了测试抽样方法和土壤侵蚀模型在土壤侵蚀普查中的适用性,该文以陕西吴起县为试点,采用1%均匀抽样方法,调查39个抽样单元的土壤侵蚀影响因子,使用中国侵蚀预报模型CSLE(Chinese soilloss equation)估算土壤侵蚀模数,并与基于遥感数据的水蚀分级分类方法进行比较。两种方法估算的全县平均土壤侵蚀模数分别为4571和5504t/(km2a),但不同分级侵蚀强度的面积和空间分布存在较大差异。抽样方法在土地利用与覆盖、水土保持措施及土壤特性方面获得的信息量大于遥感方法,同时对于区域具有很好的代表性;使用模型估算土壤侵蚀考虑的影响因子与分级方法相比,还包括了土壤可蚀性、坡长因子以及水土保持措施因子等,由此计算的土壤侵蚀模数和强度具有更高的可信度。因此,虽然基于抽样方法和土壤侵蚀模型的土壤侵蚀普查方法也存在一定的问题,但与土壤侵蚀分类分级方法相比具有明显的优越性。     

中巴地球资源卫星在土壤侵蚀监测中的应用研究

土壤侵蚀造成一系列的危害,己成为威胁生态安全的头号问题。采用中巴地球资源卫星02星的遥感资料,选取适合的波段,结合实地考察收集的信息,采用了第二次全国土壤侵蚀遥感调查中的多因素综合法,提取了对土壤侵蚀起主导作用的植被覆盖度、土地利用类型,借助数字高程模型提取地形坡度,依据《土壤侵蚀分类分级标准》建立了土壤侵蚀分析模型,将上述几个因子进行交叉分析,得到了研究区的不同土壤侵蚀强度的分布、面积情况,为中巴地球资源卫星在生态环境监测中的应用提供了经验。     

第一次全国水利普查水土保持普查方案

第一次全国水利普查水土保持情况普查包括水土流失、侵蚀沟道和水土保持措施等3种对象.水土流失普查,采取宏观遥感调查与地面系统抽样调查相结合的方式,利用土壤侵蚀模型评价不同侵蚀类型的分布、面积和强度.侵蚀沟道普查,利用遥感影像、DEM(数字高程模型)等基础数据得到侵蚀沟道位置,通过野外调查和空间分析,得到侵蚀沟道面积、数量与分布.水土保持措施普查,利用各种基础资料综合分析得到水土保持工程措施和植物措施的类型和数量.     

辽宁省侵蚀沟发育特性及地形分异特征

在不同层面对研究区数字高程模型(DEM)重分级,探讨地形因素对侵蚀沟发育的影响。以第一次全国水利普查侵蚀沟普查成果(2010年)与辽宁省第五次土壤侵蚀普查侵蚀沟普查成果(2015年)获取侵蚀沟分布数据,基于1∶50 000DEM获取侵蚀沟高程、坡度、坡向、坡长和空间分异特征。在地理信息系统(GIS)和遥感(RS)技术的支持下,分析辽宁省侵蚀沟发育特性与地形分异特征。结果表明:5年间研究区侵蚀沟密度增加0.02km/km~2,侵蚀沟高发区主要集中在辽西;70%以上区域密度变化值50m/km~2,大部分处于微度增加区;高程在325~350m时密度变化值最大;坡向上南坡、西南坡为密度变化高值区;坡度在1.5°~15°时密度变化曲线呈抛物线形,1.5°和15°时无明显变化;坡长在600~800m时密度变化值最大,坡长1 000m时密度变化值无明显差异。     

Soil loss estimation using rusle model to prioritize erosion control in KELANI river basin in Sri Lanka

Soil erosion contributes negatively to agricultural production, quality of source water for drinking, ecosystem health in land and aquatic environments, and aesthetic value of landscapes. Approaches to understand the spatial variability of erosion severity are important for improving landuse management. This study uses the Kelani river basin in Sri Lanka as the study area to assess erosion severity using the Revised Universal Soil Loss Equation (RUSLE) model supported by a GIS system. Erosion severity across the river basin was estimated using RUSLE, a Digital Elevation Model (15 × 15 m), twenty years rainfall data at 14 rain gauge stations across the basin, landuse and land cover, and soil maps and cropping factors. The estimated average annual soil loss in Kelani river basin varied from zero to 103.7 t ha-1 yr⁻¹, with a mean annual soil loss estimated at 10.9 t ha⁻¹ yr⁻¹. About 70% of the river basin area was identified with low to moderate erosion severity (<12 t ha−1 yr⁻¹) indicating that erosion control measures are urgently needed to ensure a sustainable ecosystem in the Kelani river basin, which in turn, is connected with the quality of life of over 5 million people. Use of this severity information developed with RUSLE along with its individual parameters can help to design landuse management practices. This effort can be further refined by analyzing RUSLE results along with Kelani river sub-basins level real time erosion estimations as a monitoring measure for conservation practices.