基于模糊神经系统与GIS的区域土壤侵蚀快速评价

土壤侵蚀调查与评价是水土保持工作的重要组成部分。该文对区域土壤侵蚀评价进行了尝试性研究,提出一种基于模糊神经系统和GIS技术的快速评价方法。研究中利用模糊神经系统技术从地面监测调查数据中提取土壤侵蚀强度的评价规则,建立能够全面、客观地反映特定区域范围内土壤侵蚀自然特征及规律的评价标准,在此基础之上结合GIS技术以实现对整个地区的快速评价。采用该方法进行湖北省土壤侵蚀普查,结果表明全省侵蚀面积约占国土总面积的30.1%。其中,鄂西南、鄂西北高山区土壤侵蚀情况最严重,鄂东南、鄂东北低山丘陵区次之,鄂北岗地中度侵蚀面积较大,而江汉平原基本无明显侵蚀。经验证评价结果与实际情况具有较好的一致性。     

Large‐scale soil maps and a supplementary database for land use planning in Estonia

A soil map at the scale 1:10,000 serves as a major important document for land owners and local governments, which allows them to use soil information in their daily activity. The intensity of exploitation of soil maps will increase when the very map and its legend are supplemented, within colored and indexed polygons, with information about soil texture and reaction by layers, but also about the thickness and characterization of the epipedon, quality indices for soil assessment, classes of stoniness, and prevalent fractions of stones, erosion risk, etc. Special maps of agronomical status, with a list of proper measures for improvement of soils and their associations, should form a regular component of large‐scale mapping. As decrease in arable land and increase in the forest area are common trends in land use, these maps and general soil data should serve as the fundamental source of information for decision making concerning land use. Data indicating the suitability of any soil for any crop should be entered in a database. Application of GIS on any level of national economy, digitization of a large‐scale soil database and making it accessible to land users would allow to expand the amount of available information for each soil map polygon.     

Quantification of soil properties based on external information by means of fuzzy‐set theory

The increasing demand for improved large‐scale thematic maps of soil properties for use in such areas as hydrological modeling and landscape planning requires the inclusion of external information in the computerized construction of soil maps. As this data is often purely qualitative, regionalization methods are called for, that permit consideration of uncertain empirical information. A method based on fuzzy‐set theory is presented, which enables a GIS‐based quantification of soil properties with no loss of content input when transforming ”︁soft” data. This approach, which is also applicable to other tasks, is demonstrated by the construction of maps of soil properties based on uncertain qualitative information from the Hessian Forestry Survey and the small‐scale soil map of Hesse (1:50.000). Quality and uncertainty can be judged from a separate map of uncertainty indices. The thematic output map of the available water capacity of the rooting zone in the Dietzhölztal (Hesse) research site prepared using the fuzzy approach provided an increase of 101 % in spatial resolution compared with the 1:50.000 soil map.     

A conditional GIS‐interpolation‐based model for mapping soil‐water erosion processes in Lebanon

Soil erosion by water is a major cause of landscape degradation in Mediterranean environments, including Lebanon. This paper proposes a conditional decision‐rule interpolation‐based model to predict the distribution of multiple erosion processes (i.e. sheet, mass and linear) in a representative area of Lebanon from the measured erosion signs in the field (root exposure, earth pillars, soil etching and drift and linear channels). First, erosion proxies were derived from the structural OASIS classification of Landsat thematic mapper (TM) imageries combined with the addition of several thematic erosion maps (slope gradient, aspect and curvature, drainage density, vegetal cover, soil infiltration and erodibility and rock infiltration/movement) under a geographic information systems (GIS) environment. Second, erosion signs were measured in the field, and interpolated by the statistical moments (means and variance) in the defined erosion proxies, thus producing quantitative erosion maps (t ha⁻¹) at a scale of 1:100 000. Seven decision rules were then generated and applied on these maps in order to produce the overall decisive erosion map reflecting all existing erosion processes, that is, equality (ER), dominance (DOR), bimodality (BR), masking (MR), aggravating (AR), dependence (DER) and independence (IR). The produced erosion maps are divided into seven classes ranging between 0 and more than 1·8 t ha⁻¹ for sheet erosion, and 0 and more than 10·5 t ha⁻¹ for mass and linear erosion. They are fairly matching with coincidences values equal to 43 per cent (sheet/linear), 48 per cent (sheet/mass) and 49 per cent (linear/mass). The overall accuracies of these maps were estimated to be 76 per cent (sheet erosion), 78 per cent (mass erosion) and 78·5 per cent (linear erosion). The overall decisive erosion map with 15 classes corresponds well to land management needs. The model used is relatively simple, and may also be applied to other areas. It is particularly useful when GIS database on factors influencing erosion is limited. Copyright © 2007 John Wiley & Sons, Ltd.     

吉林省土壤侵蚀敏感性评价

以通用土壤流失方程(USLE)为理论基础,在GIS的支持下采用地图代数方法,对吉林省的土壤侵蚀敏感性进行影响因子的逐一评价和综合评价。针对吉林省土壤侵蚀的实际情况,借鉴国内外的相关研究成果,选择了降雨侵蚀力、地形起伏度、植被类型和土壤质地等4个因子。通过分析与综合评价,明确了吉林省土壤侵蚀发生的可能程度、地区范围和空间分布规律,并进一步探讨了针对不同土壤侵蚀敏感区的有效控制水土流失的对策。研究结果将为吉林省的生态环境分区管理,合理开发利用土地资源,有效控制土壤侵蚀的发生和发展提供重要的依据。     

基于RUSLE和GIS的绥化市土壤侵蚀评估

基于修正的通用土壤流失方程RUSLE和GIS技术,结合绥化市的自然地理环境特征,分别计算了影响土壤侵蚀的各种因子,获取了绥化市2004年土壤侵蚀现状图,并对各区县以及不同土地利用类型的土壤侵蚀状况进行了统计,结果表明:绥化市土壤侵蚀以轻度为主,共有16083.9 km2,占46.34%,中度侵蚀面积共有1583.52 km2,占4.56%;轻度侵蚀集中连片分布,而中度以上侵蚀主要分布在河流沿岸的河流阶地与河漫滩过渡地带;兰西和青冈两个地区是土壤侵蚀面积最大的地区,而望奎、北林和海伦三个地区是中度以上土壤侵蚀的面积最大的;土地利用类型中以旱田土壤侵蚀最严重,面积也最大,未利用地主要表现为中度以上土壤侵蚀,林地和草地以轻度侵蚀为主。     

湖北省水土保持监测站点的空间优化布局

[目的]对湖北省水土保持监测站点空间优化布局进行探究,为该区水土保持监测系统的完善、水土保持科学管理与决策提供支撑。[方法]收集湖北省土壤侵蚀相关资料,利用GIS空间分析功能开展湖北省土壤侵蚀强度分级评价,在此基础上应用尺度理论对监测站点进行空间优化布局,并对优化结果进行分析验证。[结果]经过优化研究,湖北省共需布设86个监测点,其中一级尺度12个监测点,二级尺度26个监测点,三级尺度布设48个监测点。经泰森多边形验证,优化后的站点布设合理,控制突出,层次分明。[结论]湖北省丹江口水库周边山地丘陵水质维护保土区、南阳盆地及大洪山丘陵保土农田防护区和鄂渝山地水源涵养保土区水土流失严重,需要在现有基础上进一步增加水土保持监测站点密度;江汉平原及周边丘陵农田防护人居环境维护区等地区水土流失轻微,可适当减少水土流失监测站点数量。     

基于RUSLE和GIS的绥化市土壤侵蚀评估

基于修正的通用土壤流失方程RUSLE和GIS技术,结合绥化市的自然地理环境特征,分别计算了影响土壤侵蚀的各种因子,获取了绥化市2004年土壤侵蚀现状图,并对各区县以及不同土地利用类型的土壤侵蚀状况进行了统计,结果表明:绥化市土壤侵蚀以轻度为主,共有16083.9 km2,占46.34%,中度侵蚀面积共有1583.52 km2,占4.56%;轻度侵蚀集中连片分布,而中度以上侵蚀主要分布在河流沿岸的河流阶地与河漫滩过渡地带;兰西和青冈两个地区是土壤侵蚀面积最大的地区,而望奎、北林和海伦三个地区是中度以上土壤侵蚀的面积最大的;土地利用类型中以旱田土壤侵蚀最严重,面积也最大,未利用地主要表现为中度以上土壤侵蚀,林地和草地以轻度侵蚀为主。     

Mapping soil erosion risk in Rondônia,Brazilian Amazonia: using RUSLE,remote sensing and GIS

This article discusses research in which the authors applied the Revised Universal Soil Loss Equation (RUSLE), remote sensing, and geographical information system (GIS) to the maping of soil erosion risk in Brazilian Amazonia. Soil map and soil survey data were used to develop the soil erodibility factor (K), and a digital elevation model image was used to generate the topographic factor (LS). The cover‐management factor (C) was developed based on vegetation, shade, and soil fraction images derived from spectral mixture analysis of a Landsat Enhanced Thematic Mapper Plus image. Assuming the same climatic conditions and no support practice in the study area, the rainfall–runoff erosivity (R) and the support practice (P) factors were not used. The majority of the study area has K values of less than 0·2, LS values of less than 2·5, and C values of less than 0·25. A soil erosion risk map with five classes (very low, low, medium, medium‐high, and high) was produced based on the simplified RUSLE within the GIS environment, and was linked to land use and land cover (LULC) image to explore relationships between soil erosion risk and LULC distribution. The results indicate that most successional and mature forests are in very low and low erosion risk areas, while agroforestry and pasture are usually associated with medium to high risk areas. This research implies that remote sensing and GIS provide promising tools for evaluating and mapping soil erosion risk in Amazonia. Copyright © 2004 John Wiley & Sons, Ltd.     

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.     

湖北省坡耕地现状分析及宜耕性评价

坡耕地是耕地资源的重要组成部分,也是土壤侵蚀的策源地和水土保持的重点区域。为探究湖北省坡耕地资源现状及其宜耕性,利用GIS技术,构建了湖北省坡耕地的坡度、土壤侵蚀、土壤剖面构型和理化特性等数据库,筛选耕地坡度、土层厚度、土壤质地、土壤pH值和土壤侵蚀程度5个代表性指标,采用“限制因子法”对湖北省全域坡耕地进行了宜耕性评价。结果表明：湖北省坡耕地总面积为9 438.64 km²,占总耕地面积的18.87%,不宜耕坡耕地总面积为2 178.36 km²,占现有坡耕地面积的23.08%;砾石含量和坡度过高是造成坡耕地不宜耕的主要因素,其中砾石含量>15%的坡耕地总面积为1 205.72 km²,坡度≥25°的坡耕地总面积为1 097.32 km²;其次不宜耕主导因素是土壤过酸,pH值≤4.5造成坡耕地不宜耕的面积为669.60 km²,土壤侵蚀严重(极强烈以上侵蚀强度)和土层浅薄(土层厚度<30 cm)造成的不宜耕坡耕地面积分别为336.48 km²...     

Multi‐scale analysis of soil erosion dynamics in Kwazulu‐Natal,South Africa

For a case study area in the Okhombe catchment in the province of KwaZulu‐Natal, South Africa, a multi‐scale analysis of soil erosion dynamics was performed. At sub‐catchment level, the dynamics of erosional features were investigated by means of aerial photographs. At site level, the changes in soil physical and chemical properties were investigated by means of a fence‐line contrast study. Attention was paid to both surface and subsurface erosion phenomena. The number of erosional features in the study area in 2000 was not substantially different from the number of features in 1945. At sub‐catchment level, an increase in the number of gullies was observed from 1975 to 2000 but this followed a substantial inactivation of most erosional features from 1962 to 1975. Increases in erosional activity in 1962 compared to 1945 were mainly related to abandoned cultivated fields. At site level, a significant decrease in soil C/N ratio was observed within the fenced site within three years. For the same site, total carbon, saturated hydraulic conductivity and bulk density were not significantly different for the topsoil inside the fenced area compared with outside. Subsurface erosion phenomena mainly occur in the communal grazing areas and are mostly related to transitions between permeable and less permeable layers. The complex relationships between soil erosion, land use change and climate might further be understood by involving local people in the development, monitoring and evaluation of alternative types of land use, which is also likely to facilitate future steps in controlled grazing management. Copyright © 2005 John Wiley & Sons, Ltd.     

Soil‐quality‐index model for assessing the impact of groundwater on soil in an intensively farmed coastal area of E China

Soil quality is important in measuring sustainable land‐use and soil‐management practices. It is usually assessed by evaluating important physical, chemical, and biological soil properties. For this study, a site‐specific 22 variables representing pertinent soil (0–10 cm) and groundwater properties were selected as potential soil‐quality indicators in a coastal salt‐affected farmland of E China. To investigate the role of groundwater in soil‐quality assessment, we designed two sets of minimum data sets (MDSs). Minimum data set 1 (MDS1) had inputs of the 19 soil chemical and physical properties whereas MDS2 was based on the 22 soil and groundwater properties. Using principal‐component analysis, discriminant analysis, and soil‐quality‐index (SQI) model, we demonstrated the procedures of MDS selection, indicator normalization, and integration of MDS into SQI value for soils used for the two cropping systems. Results indicated selection of SOCD, AK, and ρ_b as MDS1 indicators but MDS2 indicators included SOM, SOCD, Cl, Na, WT_g, and EC_g. These were found to be the most effective discriminators between the two cropping systems. Available K (AK) made greatest contribution to SQI using MDS1 indicators, however, WT_g, EC_g, and Cl were the greatest contributors to the SQI for MDS2. Contribution of SOCD to SQI was severely inhibited in cotton–barley rotation system while EC_g and WT_g contributions to SQI were inhibited in rice–rape rotation system. In general, cotton–barley rotation system had a better soil quality over rice–rape rotation system as the former had higher SQI values than the latter for both MDSs. Crop parameters did also exhibit significant relationship with the SQI values using MDS2 but it was not significant for MDS1. Our results suggest that in addition to soil chemical, physical, and biological indicators, groundwater properties particularly the WT_g and EC_g are also important for assessing soil quality in an intensively farmed coastal area.     

基于CSLE和高分辨率航空影像的孤山川流域土壤侵蚀定量评价

20世纪80年代起,GIS技术开始应用于我国水土保持领域。该文是在GIS和RS的支持下,利用孤山川流域2012年9月高分辨率（0.38 m）航空影像、流域周边200 km范围内13个雨量站62 a的降雨数据、DEM（5 m）、以及土壤类型图等数据,结合孤山川流域特征,运用CSLE模型对黄土高原孤山川流域土壤侵蚀进行了定量研究和土壤侵蚀强度分级,并对侵蚀结果进行空间分析。结果表明:孤山川流域年侵蚀总量为274.89万t,年均侵蚀模数为2 161.06 t/（km²·a）,其中由微度到剧烈侵蚀的面积比例依次递减;随着植被覆盖度的降低以及坡度的增加,其侵蚀程度越来越严重;另外土地类型为裸地、荒草地等的水土保持效益较差,其侵蚀程度明显高于流域年均侵蚀。     

Integration of biophysical and socio‐economic factors to assess soil erosion hazard in the Upper Kaligarang Watershed,Indonesia

Soil erosion is one form of land degradation, which is caused by the interacting effects of numerous factors such as biophysical characteristics and socio‐economic condition of a particular watershed. Previous erosion studies focused on the use of soil erosion models (e.g. USLE, EUROSEM, SLEMSA etc.), which have been developed under local conditions (e.g. United States, Europe, Africa, etc) and mostly use only biophysical factors as inputs to the models. In this study, a methodology that integrates both biophysical and socio‐economic aspects into a framework for soil erosion hazard assessment using principal component analysis (PCA) is described. The analysis is done at the land unit level. With the particular conditions of the study area that is characterized by Inceptisols and Alfisols soil types, nine different land uses with mixed vegetation and forest area dominant in the steep slope, high annual rainfall (>2500 mm), high population with mostly low income and low education, were considered. These were used in formulating a soil erosion hazard index (EHI) equation which relates a number of key factors consisting of biophysical and socio‐economic variables, namely soil texture, slope steepness, land cover, soil conservation practices, income and farmers' knowledge. Weighting and scoring of these key factors were used to develop the EHI equation and to calculate an index value of erosion hazard for every land unit. Results indicate that more than 60% of the area has erosion hazard ranging from moderate to very severe, and most of the land units with high erosion hazard were found at the mountain areas. It was also found that erosion hazard was severe in areas with high silt content, followed by high rainfall and steep slope, low crop cover without any soil conservation practices coupled with lack of awareness on soil erosion and low income. The key factors identified and level of erosion hazard obtained can be used to formulate conservation measures in critical areas which are prone to soil erosion. Copyright © 2007 John Wiley & Sons, Ltd.     

基于GIS和RS的巢湖流域水土流失评估

基于地理信息系统(GIS)和遥感技术(RS),提取了巢湖流域地表覆盖、水土保持措施、坡度坡长、土壤可蚀性、降雨侵蚀力5个主要影响水土流失的因子,并运用修正的通用土壤侵蚀模型(revised univer-sal soil loss equation,RUSLE)估算土壤侵蚀量,生成水土流失等级分布图,从而完成对巢湖流域水土流失现状和空间分布特征的评估分析.结果表明,巢湖流域水土流失主要为微度侵蚀和轻度侵蚀,分别占流域总面积的93.87％和6.04％.此外,坡度和植被覆盖是影响流域土壤侵蚀的主要因素.研究结果可为巢湖流域水土流失治理及决策提供科学参考.     

Land use and soil erosion in the upper reaches of the Yangtze River: some socio‐economic considerations on China's Grain‐for‐Green Programme

Soil erosion in the upper reaches of the Yangtze River in China is a major concern and the Central Government has initiated the Grain‐for‐Green Programme to convert farmland to forests and grassland to improve the environment. This paper analyses the relationship between land use and soil erosion in Zhongjiang, a typical agricultural county of Sichuan Province located in areas with severe soil erosion in the upper reaches of the Yangtze River. In our analysis, we use the ArcGIS spatial analysis module with detailed land‐use data as well as data on slope conditions and soil erosion. Our research shows that the most serious soil erosion is occurring on agricultural land with a slope of 10∼25 degrees. Both farmland and permanent crops are affected by soil erosion, with almost the same percentage of soil erosion for corresponding slope conditions. Farmland with soil erosion accounts for 86·2 per cent of the total eroded agricultural land. In the farmland with soil erosion, 22·5 per cent have a slope of < 5 degrees, 20·3 per cent have a slope of 5∼10 degrees, and 57·1 per cent have a slope of > 10 degrees. On gentle slopes with less than 5 degrees inclination, some 6 per cent of the farmland had strong (5000∼8000 t km⁻² y⁻¹) or very strong (8000∼15000 t km⁻² y⁻¹) erosion. However, on steep slopes of more than 25 degrees, strong or very strong erosion was reported for more than 42 per cent of the farmland. These numbers explain why the task of soil and water conservation should be focused on the prevention of soil erosion on farmland with steep or very steep slopes. A Feasibility Index is developed and integrated socio‐economic assessment on the feasibility of improving sloping farmland in 56 townships and towns is carried out. Finally, to ensure the success of the Grain‐for‐Green Programme, countermeasures to improve sloping farmland and control soil erosion are proposed according to the values of the Feasibility Index in the townships and towns. These include: (1) to terrace sloping farmland on a large scale and to convert farmland with a slope of over 25 degrees to forests or grassland; (2) to develop ecological agriculture combined with improving the sloping farmland and constructing prime farmland and to pay more attention to improving the technology for irrigation and cultivation techniques; and (3) to carry out soil conservation on steep‐sloping farmland using suggested techniques. In addition, improving ecosystems and the inhabited environment through yard and garden construction for households is also an effective way to prevent soil erosion. Copyright © 2006 John Wiley & Sons, Ltd.     

Towards a Pan‐European Assessment of Land Susceptibility to Wind Erosion

Understanding spatial and temporal patterns in land susceptibility to wind erosion is essential to design effective management strategies to control land degradation. The knowledge about the land surface susceptible to wind erosion in European contexts shows significant gaps. The lack of researches, particularly at the landscape to regional scales, prevents national and European institutions from taking actions aimed at an effective mitigating of land degradation. This study provides a preliminary pan‐European assessment that delineates the spatial patterns of land susceptibility to wind erosion and lays the groundwork for future modelling activities. An Index of Land Susceptibility to Wind Erosion (ILSWE) was created by combining spatiotemporal variations of the most influential wind erosion factors (i.e. climatic erosivity, soil erodibility, vegetation cover and landscape roughness). The sensitivity of each input factor was ranked according to fuzzy logic techniques. State‐of‐the‐art findings within the literature on soil erodibility and land susceptibility were used to evaluate the outcomes of the proposed modelling activity. Results show that the approach is suitable for integrating wind erosion information and environmental factors. Within the 34 European countries under investigation, moderate and high levels of land susceptibility to wind erosion were predicted, ranging from 25·8 to 13·0 M ha, respectively (corresponding to 5·3 and 2·9% of total area). New insights into the geography of wind erosion susceptibility in Europe were obtained and provide a solid basis for further investigations into the spatial variability and susceptibility of land to wind erosion across Europe. © 2014 The Authors. Land Degradation and Development published by John Wiley & Sons, Ltd.     

Quantitative assessment of rill and interrill soil erosion in Romania

Soil erosion is an important geomorphological process with potential negative consequences especially on land agricultural potential. Unsuitable agricultural practices may increase soil erosion, leading to rapid loss of soil fertility and decrease of crop production. It is therefore important to correctly quantify soil erosion rates in order to adapt agricultural practices and implement proper conservation measures. This study attempts to assess the rill and interrill erosion in Romania, using the Romanian soil erosion model and GIS techniques. The database includes the digital terrain model, the soil map of Romania, the land use map of Romania and the rainfall erosivity regions. The results show that the high and very high erosion risk classes include 4.1% of the Romanian territory (9,627 km²). Most of this land is present in the hilly and plateau areas (Subcarpathians, Moldavian Plateau, Getic Plateau, Western Hills, Dobrogea Plateau). The model was validated by comparison of its predictions with long‐term erosion measurements from different locations in the country. Comparison with previous non‐GIS assessments of soil erosion at national level shows that the total estimated rill and interrill erosion in our study was very close to previous estimates. Comparison with the RUSLE 2015 model computed for Europe as a whole reveals that the two models assign almost 54% of their shared area to the same erosion class, while for 39% of the territory there is one class difference between the models. The results can be used for evaluations of erosion risk at national and regional scales.     

Potential of multi‐objective models for risk‐based mapping of the resilience characteristics of soils: demonstration at a national level

Policy makers rely on risk‐based maps to make informed decisions on soil protection. Producing the maps, however, can often be confounded by a lack of data or appropriate methods to extrapolate using pedotransfer functions. In this paper, we applied multi‐objective regression tree analysis to map the resistance and resilience characteristics of soils onto stress. The analysis used a machine learning technique of multiple regression tree induction that was applied to a data set on the resistance and resilience characteristics of a range of soils across Scotland. Data included both biological and physical perturbations. The response to biological stress was measured as changes in substrate mineralization over time following a transient (heat) or persistent (copper) stress. The response to physical stress was measured from the resistance and recovery of pore structure following either compaction or waterlogging. We first determined underlying relationships between soil properties and its resistance and resilience capacity. This showed that the explanatory power of such models with multiple dependent variables (multi‐objective models) for the simultaneous prediction of interdependent resilience and resistance variables was much better than a piecewise approach using multiple regression analysis. We then used GIS techniques coupled with an existing, extensive soil data set to up‐scale the results of the models with multiple dependent variables to a national level (Scotland). The resulting maps indicate areas with low, moderate and high resistance and resilience to a range of biological and physical perturbations applied to soil. More data would be required to validate the maps, but the modelling approach is shown to be extremely valuable for up‐scaling soil processes for national‐level mapping.