近30年来密云水库上游水土流失动态监测

使用修正的通用土壤流失方程RUSLE,综合考虑降雨、土壤可蚀性、地形、土地覆盖和水土保持措施等因素,计算得密云水库上游地区1990年、2000年和2008年3期的土壤侵蚀数据,并对土壤侵蚀变化结果及其原因进行分析,发现：①研究区近20年水土流失状况经历由加剧到减轻的过程,但总体来说是减轻的,1990～2008年减轻区面积和加剧区面积分别为3083．11km。和2287．71km2;②研究区水土流失变化的原因主要为以土地利用类型变化为特征的人为因素,降雨也有影响,而与坡度没有关系。     

Estimating the rainfall erosivity for management planning in the Eastern Desert,Egypt

Soil erosion is one of the major causes of land degradation in arid areas. Soil erosion models, e.g. the revised universal soil loss equation (RUSLE), use arithmetical expressions to explore relationships among various processes occurring in the terrain. The established model includes soil parameters, slope, climate and human activities to estimate the water erosion rate and sediment yield. In this study, an approach was adopted to integrate RUSLE model and geographic information system to detect erosion vulnerability and determine the soil erosion risk in the study area. The study area is situated in the Eastern Desert, Egypt. Ground truth data were examined to represent two regions: Luxor-Suhag and Suhag–ElMinya. These regions are exampled by four dry valleys named Sannor, Tarfa, Asyut and Qena, which are planned for agricultural development. The results indicate high risk of water erosion and sediment load discharge into the cultivated land in Luxor–Suhag region. The other region of Suhag–ElMinya is moderately affected by water and sediment load discharge. A higher soil erosion rate was found in Qena wadi followed by Asyut, then Tarfa and Sannur, respectively.     

Soil Loss Mapping for Sustainable Development and Management of Land Resources in Warora Tehsil of Chandrapur District of Maharashtra: An Integrated Approach Using Remote Sensing and GIS

The study area is characterized by low and fluctuating rainfall pattern, thin soil cover, predominantly rain-fed farming with low productivity coupled with intensive mining activities, urbanization, deforestation, wastelands and unwise utilization of natural resources causing human induced environmental degradation and ecological imbalances, that warrant sustainable development and optimum management of land resources. Spatial information related to existing geology, land use/land cover, physiography, slope and soils has been derived through remote sensing, collateral data and field survey and used as inputs in a widely used erosion model (Universal Soil Loss Equation) in India to compute soil loss (t/ha/yr) in GIS. The study area has been delineated into very slight (<5 t/ha/yr), slight (5–10 t/ha/yr), moderate (10–15 t/ha/yr), moderately severe (15–20 t/ha/yr), severe (20–40 t/ha/yr) and very severe (>40 t/ha/yr) soil erosion classes. The study indicate that 45.4 thousand ha. (13.7% of TGA) is under moderate, moderately severe, severe and very severe soil erosion categories. The physiographic unit wise analysis of soil loss in different landscapes have indicated the sensitive areas, that has helped to prioritize development and management plans for soil and water conservation measures and suitable interventions like afforestation, agro-forestry, agri-horticulture, silvipasture systems which will result in the improvement of productivity of these lands, protect the environment from further degradation and for the ecological sustenance.     

Prediction of soil loss differences and sediment accumulation at the Nilufer creek watershed,Turkey, using multiyear satellite data in a GIS

This study integrates the RUSLE, remote sensing and GIS to assess soil loss and identify sensitive areas to soil erosion in the Nilufer creek watershed in Bursa province, Turkey. The annual average soil loss was generated separately for years 1984 and 2011, in order to expose possible soil loss differences occurred in 27 years. In addition, sediment accumulation and sediment yield of the studied watershed was also predicted and discussed. The results indicated that very severe erosion risk areas in 1984 was 13.4% of the area, but it was increased to 15.3% by the year 2011, which needs immediate attention from soil conservation point of view. Furthermore, the estimated annual sediment yield of the Nilufer creek watershed was increased from 903 to 979 Mg km^?2 y^?1 in 27 years period. The study also provides useful information for decision-makers and planners to take appropriate land management practices in the area.     

Assessment of soil erosion using remote sensing and GIS in Nagpur district, Maharashtra for prioritisation and delineation of conservation units

In the present study, soil loss in Nagpur district of Maharashtra is predicted employing USLE method and adopting integrated analysis in GIS to prioritise the tahsils for soil conservation and for delineation of suitable conservation units. Remote sensing techniques are applied to delineate the land cover of the district and to arrive at annual cover factors. Results indicate that potential soil loss of very slight to slight (>5–10 tons/ha/year) exist in the valleys in north western, northern and in the plains of central and eastern parts of the district. Moderate to moderately severe erosion rates (10 to 20 tones/ha/year) is noticed in the southeastern and some central parts. Severe, very severe and extremely severe erosion types (20 to 80 tons/ha/year) are noticed in the northern, western, southwestern and southern parts of the district. The average soil loss is estimated to be 23.1 and 15.5 tons/ha/yr under potential and actual conditions respectively. Slight, moderate, moderately severe and extremely severe potential erosion covering about 41 per cent area of the district is reduced to negligible and very slight rates of actual erosion under the influence of present land cover leading to a reduction of 7421.2 tones of potential soil loss. Priority rating of the tahsils is evaluated from the area weighted mean quantum of soil loss. Multi-criteria overlay analysis with the parameters of soil erosion, slope, soil depth, land cover and surface texture with rating for the constituent classes has resulted in delineation of nine conservation units. Appropriate agronomic and mechanical practices are suggested in the identified units for minimizing the erosion hazard.     

Application of GIS to estimate soil erosion using RUSLE

This paper describes the use of the Arc/Info and ArcView GIS tools to estimate soil erosion with Universal Soil Loss Equation (USLE).Calculations are be done by using capabilities available.This study start with a digital elevation model(DEM) of Shaanxi,which was created by digitizing contour and spot heights from the topographic map on 1:250000 scale and grid themes for the USLE K and C factors.It is note worthy that USLE K can be obtained by adding the K factor as an attribute to a soil theme‘s table.The C can be obtained from tables or using the information about land use and management given by USLE program.A land use theme can be used to add the C factors as an attribute field.The purpose of this study is to establish spatial information of soil erosion using USLE and GIS and discuss the analysis of the soil erosion and slope failures in GIS and formulate the possible framework.     

Effect of cover management factor in quantification of soil loss: case study of Sungai Akah subwatershed,Baram River basin Sarawak,Malaysia

The present study evaluates the effectiveness and suitability of cover management factors (C factor) generated through different techniques like land use/land cover-based arbitrary value (C_LULC), Normalised Different Vegetation Index-based methods C_NDVI1 and C_NDVI2 and Modified Soil Adjusted Vegetation Index 2-based method (C_MSAVI2). The C factors generated using these four methods were tested in the calculation and assessment of annual average soil loss from an upland forested subwatershed in the Baram river basin using the Revised Universal Soil Loss Equation (RUSLE). The four cover management factor maps generated by this analysis show some variation among the results. The LULC method uses a single arbitrary value for each LULC type mapped in the subwatershed. The other three methods show a range of C values within each mapped LULC type. The effects of these variations were tested in the RUSLE by keeping the factors such as rainfall erosivity (R), soil erodibility (K), slope-length and steepness (LS) constant. The maximum annual average soil loss is 1191 t. ha^?1. y^?1 based on the C_LULC. Soil losses estimated with other three methods are very different compared to those estimated with the C_LULC method. The highest calculated soil loss values were 1832, 1674 and 1608 t. ha^?1. y^?1 in the study area based, respectively, on C_NDVI1, C_NDVI2 and C_MSAVI2 C factors. These maximum values represent the worst pixel scenario values of soil loss in the region. The statistical analysis performed indicates different relationship between the parameters and suggests the acceptance of the methodology based on C_NDVI2 for the study area, instead of a single value method such as C_LULC. Among the other two methods, the C_MSAVI2 was found to be more consistent than the C_NDVI1 method, but both methods lead to over-prediction of annual soil loss rate and therefore need to be reconsidered before applied in the RUSLE.     

A comparative study of soil erosion modelling by MMF,USLE and RUSLE

The quantitative assessment of spatial soil erosion is valuable information to control the erosion. The study area in a part of Narmada river in central India is selected. The main objective is to assess and compare the results obtained from three soil erosion models using GIS platform. Variation in the rate of erosion of the three models is compared considering varying slope, soil and land use of the area. Three models selected are Morgan–Morgan–Finney (MMF), Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE). The best fit or the most reliable model for the study area is selected after validation with the observed sedimentation data. The results give –39.45%, –9.60% and 4.80% difference in the values of sedimentation by MMF, USLE and RUSLE, respectively, from the observed data. Finally, RUSLE model has been found to be most reliable for the study area.     

基于GIS的小流域水土流失遥感定量监测研究

以三峡库区典型小流域为研究区域，通过遥感和野外调查进行信息采集．建立了流域环境数据库；在GIS支持下，根据修正通用土壤流失方程（RUSLE）模型对数据库实施运算操作，探讨了流域内土壤侵蚀强度的空间分布规律，并估算了小流域水土流失量。     

Vegetational response of rainfall in Rajasthan using AVHRR imagery

The purpose of this paper is to demonstrate the suitability of NOAA-AVHRR imagery for monitoring vegetal cover. Of course, climate is recognized as the most important control on natural vegetation. However, spatial and seasonal changes in land cover are dependent on several factors including the crop species, soil hydrology, grazing conditions, harvest timing and above all on the frequency and amount of rainfall. The analysis is based on six maximum value composite (MVC) NDVI images with a spatial resolution of approximately 5.5 km. An attempt has also been made to examine the serial relationship between the NDVI and the rainfall occurrences at different stations. ‘Thar Desert’ is clearly visible in the images of summer months. A transitional zone is situated between the arid and semi-arid areas along the western fringe of the Aravalli Range. The elimination of time lag in vegetational response of rainfall indicates expected positive relationship between vegetal cover and rainfall.     

Timing of erosion and satellite data: A multi-resolution approach to soil erosion risk mapping

Erosion reduces soil productivity and causes negative downstream impacts. Erosion processes occur on areas with erodible soils and sloping terrain when high-intensity rainfall coincides with limited vegetation cover. Timing of erosion events has implications on the selection of satellite imagery, used to describe spatial patterns of protective vegetation cover. This study proposes a method for erosion risk mapping with multi-temporal and multi-resolution satellite data. The specific objectives of the study are: (1) to determine when during the year erosion risk is highest using coarse-resolution data, and (2) to assess the optimal timing of available medium-resolution images to spatially represent vegetation cover during the high erosion risk period. Analyses were performed for a 100-km² pasture area in the Brazilian Cerrados. The first objective was studied by qualitatively comparing three-hourly TRMM rainfall estimates with MODIS NDVI time series for one full year (August 2002–August 2003). November and December were identified as the months with highest erosion risk. The second objective was examined with a time series of six available ASTER images acquired in the same year. Persistent cloud cover limited image acquisition during high erosion risk periods. For each ASTER image the NDVI was calculated and classified into five equally sized classes. Low NDVI was related to high erosion risk and vice versa. A DEM was used to set approximately flat zones to very low erosion risk. The six resulting risk maps were compared with erosion features, visually interpreted from a fine-resolution QuickBird image. Results from the October ASTER image gave highest accuracy (84%), showing that erosion risk mapping in the Brazilian Cerrados can best be performed with images acquired shortly before the first erosion events. The presented approach that uses coarse-resolution temporal data for determining erosion periods and medium-resolution data for effective erosion risk mapping is fast and straightforward. It shows good potential for successful application in other areas with high spatial and temporal variability of vegetation cover.     

遥感与GIS支持下的土壤侵蚀强度快速评价方法研究

 以TM影像、1︰1万数字地形图以及其它辅助数据为基础，以土地利用类型、植被覆盖度以及坡度等作为影响因子，在遥感 和GIS技术的支持下，对余江县洪湖乡的土壤侵蚀强度进行了快速分级评价实验。结果表明，该方法所获取的土壤侵蚀强度信息与 实际情况比较吻合。     

Temporal and spatial relationships between soil erosion and ecological restoration in semi-arid regions: a case study in northern Shaanxi,China

ABSTRACT

To assess the effects of the Grain for Green Program (GGP) on soil erosion is essential to support better land management policies in the Chinese Loess Plateau. Studies on the evaluation of the effects of the GGP on soil erosion have garnered heightened attention. However, few studies examined the efficiency of GGP on soil erosion control through spatial relationship analysis. Thus, this study focuses on analyzing the spatial variation relationship between soil erosion and GGP in northern Shaanxi, Chinese Loess Plateau, from 1988 to 2015. The Universal Soil Loss Equation was used to quantify changes in soil erosion at the regional and watershed scales, and the Geographically Weighted Regression model was used to analyze the spatial relationships between land use and land cover (LULC) and soil erosion. Our results indicated that the major characteristic of LULC change during the GGP was a rapid increase of vegetation area and a rapid decrease of cropland. Bare lands contributed to the most serious soil loss, followed by croplands and sparse grasslands. The GGP had a globally positive influence on the decrease in soil erosion over the study area, but the amount of soil erosion in western and northern regions maintained a severe level. Spatial heterogeneity in the nature of the relationships among different vegetation, croplands, and soil erosion was also observed. The change rate of wood and the change rate of soil erosion in northern sub-watershed represented a negative relationship, while the change rate of sparse grassland was negatively correlated to the change rate of soil erosion in 21 sub-watersheds, account for 72% of the study area. The GGP implemented in northern sub-watersheds were more effective for soil erosion control than southern sub-watersheds. We propose that current areas of vegetation can support soil erosion control in the whole northern Shaanxi, but local-scale ecological restoration can be considered in northern sub-watersheds.     

An assessment of gully erosion along major armoured roads in south-eastern region of South Africa: a remote sensing and GIS approach

An assessment of gully erosion along road drainage-release sites is critical for understanding the contribution of roads to soil loss and for informed land management practices. Considering that road-related gully erosion has traditionally been measured using field methods that are expensive, tedious and limited spatially as well as temporally, it is important to identify affordable, timely and robust methods that can be used to effectively map and estimate the volume of gullies along the road networks. In this study, gullies along major roads were identified from remotely sensed data sets and their volumes were estimated in a Geographic Information Systems environment. Also, the biophysical and climatic factors such as vegetation cover, the road contributing surface area, the gradient of the discharge hillslope and rainfall were derived from remotely sensed data sets using Geographic Information Systems techniques to find out whether they could explain the morphology of gullies that existed in this area. The results of this study indicate that hillslope gradient (R²?=?0.69, α = 0.00) and road contributing surface area (R²?=?0.63, α = 0.00) have a strong influence on the volume of gullies along the major roads in the south-eastern region of South Africa, as might have been expected. However, other factors such as vegetation cover (R² = 0.52, α = 0.00) and rainfall (R² = 0.41 and α = 0.58) have a moderately weaker influence on the overall volume of gullies. Overall, the findings of this study highlight the importance of using remote sensing and Geographic Information Systems technologies in investigating gully erosion occurrence along major roads where detailed field work remains a challenge.     

Application of GIS to estimate soil erosion using RUSLE

This paper describes the use of the Arc/Info and ArcView GIS tools to estimate soil erosion with Universal Soil Loss Equation (USLE). Calculations are be done by using capabilities available. This study start with a digital elevation model (DEM) of Shaanxi, which was created by digitizing contour and spot heights from the topographic map on 1∶250 000 scale and grid themes for the USLEK andC factors. It is note worthy that USLEK can be obtained by adding the K factor as an attribute to a soil theme's table. TheC can be obtained from tables or using the information about land use and management given by USLE program. A land use theme can be used to add theC factors as an attribute field. The purpose of this study is to establish spatial information of soil erosion using USLE and GIS and discuss the analysis of the soil erosion and slope failures in GIS and formulate the possible framework.     

Land degradation mapping in the upper catchment of river Tons

A study on land degradation in the upper catchment of river Tons, a tributary of Yamuna river, in Uttarkashi district of the Uttarakhand state, was carried out using on-screen visual interpretation of IRS LISS-III + PAN merged data. The study area, which is largely mountainous, includes Govind Wildlife Sanctuary and National Park. Vegetation cover, slope and erosion status were used as criteria for the delineation of four major land degradation categories viz., undegraded, moderately degraded, degraded and severely degraded. More than 50 per cent of the study area is reported to be covered with snow and grassland. The moderate to severely degraded area worked out to be 42.4 per cent of the total area. The 32.8 per cent of area was found to be moderately degraded, followed by degraded (6.63%) and severely degraded (2.88%) areas. The depletion of vegetation cover on mountainous terrain and subsequent cultivation without proper protection measures is the reason for severe soil erosion and land degradation. In view of the existing land degradation situation, the catchment requires immediate treatment on priority for the sustenance of agriculture and wild life. It is expected that these measures will reduce the silt load in the river Tons and eventually, in river Yamuna.     

Characterization of biophysical land units using remote sensing and gis

In the present study, an attempt has been made to characterize the biophysical land units in Kanholi bara river basin of sub-humid tropical ecosystem of central India using remotely sensed data, field surveys and GIS based multi-criteria overlay analysis. The geo-spatial database on elevation, slope, landforms, soil depth, soil erosion, land use/land cover and hydrogeomorphological parameters has been generated using IRS-ID LISS-III satellite data coupled with soil survey data in GIS. The methodology followed in characterization of biophysical land units in GIS includes assigning scores for different classes of the layers and weighatges for different layers based on their characteristics and degree of influence on desired output. GIS based ‘multi criteria overlay’ analysis reveals seventeen distinct biophysical land units in the river basin. Severe (50.5-59.5) to very severe (59.5) biophysical stress units are found in plateau spurs, isolated mounds, linear ridges, dissected plateau and escarpments. These zones are associated with severe to very severe erosion, steep to very steep, extremely shallow soils, poor to very poor groundwater prospects, wastelands and scrublands. The characterization of biophysical land units helps in analysis of their potentials, problems and stress environment to plan and execute site-specific landscape management practices and maximize the productivity from each biophysical land unit. The present study demonstrates that generation of geo-spatial database based on remotely sensed data and field surveys in GIS and their analysis helps great extent in characterization of biophysical land units and analysis of their stress environment for management.     

Landslide Mapping and Assessment by Integrating Landsat-8, PALSAR-2 and GIS Techniques: A Case Study from Kelantan State,Peninsular Malaysia

Integration of satellite remote sensing data and GIS techniques is an applicable approach for landslide mapping and assessment in highly vegetated regions with a tropical climate. In recent years, there have been many severe flooding and landslide events with significant damage to livestock, agricultural crop, homes, and businesses in the Kelantan river basin, Peninsular Malaysia. In this investigation, Landsat-8 and phased array type L-band synthetic aperture radar-2 (PALSAR-2) datasets and analytical hierarchy process (AHP) approach were used to map landslide in Kelantan river basin, Peninsular Malaysia. Landslides were determined by tracking changes in vegetation pixel data using Landsat-8 images that acquired before and after flooding. The PALSAR-2 data were used for comprehensive analysis of major geological structures and detailed characterizations of lineaments in the state of Kelantan. AHP approach was used for landslide susceptibility mapping. Several factors such as slope, aspect, soil, lithology, normalized difference vegetation index, land cover, distance to drainage, precipitation, distance to fault, and distance to the road were extracted from remotely sensed data and fieldwork to apply AHP approach. The excessive rainfall during the flood episode is a paramount factor for numerous landslide occurrences at various magnitudes, therefore, rainfall analysis was carried out based on daily precipitation before and during flood episode in the Kelantan state. The main triggering factors for landslides are mainly due to the extreme precipitation rate during the flooding period, apart from the favorable environmental factors such as removal of vegetation within slope areas, and also landscape development near slopes. Two main outputs of this study were landslide inventory occurrences map during 2014 flooding episode and landslide susceptibility map for entire Kelantan state. Modeled/predicted landslides with a susceptible map generated prior and post-flood episode, confirmed that intense rainfall throughout Kelantan has contributed to produce numerous landslides with various sizes. It is concluded that precipitation is the most influential factor for landslide event. According to the landslide susceptibility map, 65% of the river basin of Kelantan is found to be under the category of low landslide susceptibility zone, while 35% class in a high-altitude segment of the south and south-western part of the Kelantan state located within high susceptibility zone. Further actions and caution need to be remarked by the local related authority of the Kelantan state in very high susceptibility zone to avoid further wealth and people loss in the future. Geo-hazard mitigation programs must be conducted in the landslide recurrence regions for reducing natural catastrophes leading to loss of financial investments and death in the Kelantan river basin. This investigation indicates that integration of Landsat-8 and PALSAR-2 remotely sensed data and GIS techniques is an applicable tool for Landslide mapping and assessment in tropical environments.     

长江上游小流域土壤侵蚀动态模拟与分析

以长江上游甘肃省尚沟流域为研究区,在遥感影像和GIS空间分析技术支撑下,根据USLE因子算法生成各因子栅格图,借助地图代数运算,估算了尚沟流域1998年和2004年的土壤侵蚀量,并对2004年土壤侵蚀与其环境背景因子进行叠加和空间统计分析。在此基础上,构建了与GIS软件平台集成的地理元胞自动机,模拟了该流域2004年、2010年和2020年土壤侵蚀空间演化情形。结果表明:研究区平均侵蚀量从1998年的6598.1t/km2下降到2004年的5923.3t/km2,侵蚀面积净减少172.3hm2,输沙量减少9.15×104t;1300～1400m的海拔高程带、25～35°坡度带、南坡和旱耕地是发生水土流失的主要区域;经模拟,2010年总侵蚀面积为93.49km2,侵蚀总量73.15×104t,侵蚀模数为5126t/km2,土壤侵蚀状况总体上将有所减缓。     

甘孜州九龙县水土流失评价研究

本文以九龙县为研究区,根据沟壑密度、坡度、植被盖度、土地利用类型和高程5个因子,结合ARC-GIS空间分析功能和MATLAB数学建模编程的功能,应用GA-BP模型(遗传算法优化BP神经网络)对研究区的水土流失进行非线性智能定量评价,并与层次分析法的结果对比分析,阐述了GA-BP模型的优越性。本次研究可以为九龙县水土流失预防和治理提供有益的参考。