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.     

Risk assessment of soil erosion in semi-arid mountainous watershed in Saudi Arabia by RUSLE model coupled with remote sensing and GIS

Soil erosion is the most important factor in land degradation and influences desertification in semi-arid areas. A comprehensive methodology that integrates revised universal soil loss equation (RUSLE) model and GIS was adopted to determine the soil erosion risk (SER) in semi-arid Aseer region, Saudi Arabia. Geoenvironmental factors viz. rainfall (R), soil erodibility (K), slope (LS), cover management and practice factors were computed to determine their effects on average annual soil loss. The high potential soil erosion, resulting from high denuded slope, devoid of vegetation cover and high intensity rainfall, is located towards the north western part of the study area. The analysis is investigated that the SER over the vegetation cover including dense vegetation, sparse vegetation and bushes increases with the higher altitude and higher slope angle. The erosion maps generated with RUSLE integrated with GIS can serve as effective inputs in deriving strategies for land planning/management in the environmentally sensitive mountainous areas.     

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.     

永定河治理区土壤侵蚀时空变化分析

本文利用“北京一号”小卫星32 m多光谱数据提取研究区的植被覆盖信息与土地利用信息,利用1∶50 000DEM数据提取研究区坡度信息,采用中华人民共和国水利部部颁标准“土壤侵蚀分类分级标准SL 190-96”,评价研究区的水蚀风险等级;并结合全国第二次土壤侵蚀遥感(LandsatTM)调查数据,进行土壤侵蚀时空变化分析...     

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。     

Assessment of Post-fire Soil Erosion Risk in Fire-Affected Watersheds Using Remote Sensing and GIS

Soil erosion is a prominent cause of land degradation and desertification in Mediterranean countries. The detrimental effects of soil erosion are exemplified in climate (in particular climate change), topography, human activities, and natural disasters. Forest fires, which are an integral part of Mediterranean ecosystems, are responsible for the destruction of above-and below-ground vegetation that protects against soil erosion. Under this perspective, the estimation of potential soil erosion, especially after fire events, is critical for identifying watersheds that require management to prevent sediment loss, flooding, and increased ecosystem degradation. The objective of this study was to model the potential post-fire soil erosion risk following a large and intensive wildland fire, in order to prioritize protection and management actions at the watershed level in a Mediterranean landscape. Burn severity and preand post-fire land cover/uses were mapped using an ASTER image acquired two years before the fire, air photos acquired shortly after the fire, and a Landsat TM image acquired within one month after-fire. We estimated pre-and post-fire sediment loss using an integrated GIS-based approach, and additionally we analyzed landscape erosion patterns. The overall accuracy of the severity map reached 83%. Severe and heavy potential erosion classes covered approximately 90% of the total area following the fire, compared to 55% before. The fire had a profound effect on the spatial erosion pattern by altering the distribution of the potential erosion classes in 21 out of 24 watersheds, and seven watersheds were identified as being the most vulnerable to post-fire soil erosion. The spatial pattern of the erosion process is important because landscape cover heterogeneity induced especially by fire is a dominant factor controlling runoff generation and erosion rate, and should be considered in post-fire erosion risk assessment.     

安徽省大别山区江子河小流域的水文模拟与分析

目前,许多发达国家的研究已经证实,农业非点源污染是导致水环境恶化的主要原因之一。土壤侵蚀与非点源污染是一对密不可分的共生现象,特别在农业非点源污染中,土壤侵蚀是主要的发生形式,是一种重要的非点源污染。本文主要应用目前使用较广泛的非点源污染模型—SWAT模型对淮河流域安徽省大别山区水土流失较严重的江子河小流域进行径流量和泥沙量的模拟,并得到该小流域径流量和泥沙流失量的空间分布图。     

缅甸中部干旱地区土壤侵蚀的分析

伊落瓦底江中游是缅甸中部著名的干热地带,地壤流失严重。在研究中,首先利用遥感图像（１９９５年的ＴＭ图像,１９９８年的ＴＭ和ＳＰＯＴ图像）进行判读和土壤侵蚀地面实况的野外验证。同时,根据影响封侵蚀的生态环境因子,建立实验区的数字高程模型和窨数据库。然后,在地理信息系统（ＧＩＳ）中进行土壤侵蚀测定以及生态环境因子相关分析。影响土壤侵镅的生态环境因子很多,但植被和耕作方式是人们可以控制的因子。在此基础上     

Soil erosion prediction based on land cover dynamics at the Semenyih watershed in Malaysia using LTM and USLE models

This study attempts to identify and forecast future land cover (LC) by using the Land Transformation Model (LTM), which considers pixel changes in the past and makes predictions using influential spatial features. LTM applies the Artificial Neural Networks algorithm) in conducting the analysis. In line with these objectives, two satellite images (Spot 5 acquired in 2004 and 2010) were classified using the Maximum Likelihood method for the change detection analysis. Consequently, LC maps from 2004 to 2010 with six classes (forest, agriculture, oil palm cultivations, open area, urban, and water bodies) were generated from the test area. A prediction was made on the actual soil erosion and the soil erosion rate using the Universal Soil Loss Equation (USLE) combined with remote sensing and GIS in the Semenyih watershed for 2004 and 2010 and projected to 2016. Actual and potential soil erosion maps from 2004 to 2010 and projected to 2016 were eventually generated. The results of the LC change detections indicated that three major changes were predicted from 2004 to 2016 (a period of 12 years): (1) forest cover and open area significantly decreased at rates of almost 30 and 8 km², respectively; (2) cultivated land and oil palm have shown an increment in sizes at rates of 25.02 and 5.77 km², respectively; and, (3) settlement and Urbanization has intensified also by almost 5 km². Soil erosion risk analysis results also showed that the Semenyih basin exhibited an average annual soil erosion between 143.35 ton ha^?1 year^?1 in 2004 and 151 in 2010, followed by the expected 162.24 ton ha^?1 year^?1. These results indicated that Semenyih is prone to water erosion by 2016. The wide range of erosion classes were estimated at a very low level (0–1 t/ha/year) and mainly located on steep lands and forest areas. This study has shown that using both LTM and USLE in combination with remote sensing and GIS is a suitable method for forecasting LC and accurately measuring the amount of soil losses in the future.     

土壤水力侵蚀的遥感信息模型研究——以江西省为例

通过利用Terra/Aqua卫星上搭载的MODIS传感器计算获取的16d合成植被指数产品(MOD13A2),进一步按照最大值合成法计算月合成光谱植被指数,按照USLE模型月模式评价江西省2005年土壤侵蚀,并与传统的USLE模型年模式计算的结果进行了比较。     

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.     

Modelling monthly soil losses and sediment yields in Cyprus

The aim of this study was to map soil erosion on the Mediterranean island of Cyprus. The G2 model, an empirical model for month-time step erosion assessments, was used. Soil losses in Cyprus were mapped at a 100?m cell size, while sediment yields at a sub-basin scale of 0.62?km² mean size. The results indicated a mean annual erosion rate of 11.75?t?ha^?1?y^?1, with October and November being the most erosive months. The 34% of the island's surface was found to exceed non-sustainable erosion rates (>10?t?ha^?1?y^?1), with sclerophyllous vegetation, coniferous forests, and non-irrigated arable land being the most extensive non-sustainable erosive land covers. The mean sediment delivery ratio (SDR) was found to be 0.26, while the mean annual specific sediment yield (SSY) value for Cyprus was found to be 3.32?t?ha^?1?y^?1. The annual sediment yield of the entire island was found to be 2.746?Mt?y^?1. This study was the first to provide complete and detailed erosion figures for Cyprus at a country scale. The geodatabase and all information records of the study are available at the European Soil Data Centre (ESDAC) of the Joint Research Centre (JRC).     

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.     

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.     

Soil erosion modeling using MMF model -A remote sensing and GIS perspective

Hardly any part of the world has remained unchanged since the arrival of the speciesHomo sapiens including the mountain ecosystems. Himalayan physiographic unit of India in due course has become populated and is tolerating all kinds of human interventions. Soil erosion in this region has been identified as a major problem due to both natural and anthropogenic factors. Remote sensing and Geographical Information system (GIS) techniques hold great promises in the assessment and conservation of natural resources including the surface soil. The major objective of the present study was to apply a process based model to quantify soil erosion and to prioritize the sub-watershed on this basis. The sub-watershed located at Jakhan rao area of Western Dun in lower Himalayan belt was taken as the test site for the study at 1: 50,000 scale. Deforestation, unscientific agricultural practices, terrace farming, cattle grazing and land degradation in the sub-watershed are some of the anthropogenic factors causing soil erosion in the area. Here, MMF model was used for estimation of soil erosion by incorporating layers derived from both remote sensing and ancillary data. IRS 1C LISS III satellite data was used for the preparation of land use map that was used to derive RD map, BD map and K map. Digital Elevation Model (DEM) provided slope map, an intermediate layer used in equation 6 to generate G map, and soil map provided MS map, BD map and K map. The above intermediate layers generated were then integrated in GIS domain to estimate the amount of soil erosion in the sub-watershed area. Results show high values 4572.333 kg/m² for G map, which depicted transport capacity of overland flow. Comparatively lower values 13.15, and 7.98 kg/m²were observed for F map, which depicted soil detachment by raindrop impact. The subtracted image of the aforesaid layers produced the real picture, where in the highest value 3.770 kg/m² was found in the midland region of the site. The crossed erosion map was then classified into different erosion classes for sub-watershed area. This study illustrates the applications of remote sensing and GIS techniques for soil erosion modeling.     

Mapping of soil degradation hazards by remote sensing in Hanumangarh district (western Rajasthan)

In the present study, efforts have been made to identify and map areas affected by various soil degradation processes in Hanumangarh district of western Rajasthan. Soil degradation processes were identified by using IRS-1B satellite image of the year 1998, SOI toposheets, ground truth verification and soil studies. The kind, extent and degree of soil degradation have been mapped in an area of 9703 km². The study reveals that the soil degradation problems were mainly due to wind erosion/deposition and water-logging, followed by salinity/alkalinity, water erosion and wind and water erosion combinedly. Nearly 38.7% area is subjected to slight and moderate degradation, which can easily be combated by adopting the suggested techniques and 17.1% area is free of hazard. Soil degradation processes have resulted in the loss of organic carbon, available Phosphorus and Potassium. Soil degradation due to water logging/salinization has also shown a significant increase in electrical conductivity and available potassium content of soil.     

基于SPOT 5和北京一号小卫星数据的北京北部山区土壤侵蚀变化研究

利用2004年10月SPOT 5卫星影像及2007年9月北京一号小卫星多光谱和全色影像,以植被覆盖度、坡度、土壤可蚀性和土地利用4种影响因子作为辅助数据,进行土壤侵蚀信息提取。利用所提取的信息,分析2004~2007年北京北部山区土壤侵蚀在空间、面积上的变化状况、强度类型转化状况以及变化的驱动力。分析结果表明,北京北部山区土壤侵蚀主要为轻度侵蚀与中度侵蚀,以轻度侵蚀为主; 2004~2007年北京北部山区虽然局部地区土壤侵蚀强度增强,但土壤侵蚀总面积减少,大体上呈中度→轻度→微度发展趋势,总体状况得到明显改善。     

Drought mapping using Geoinformation technology for some sites in the Iraqi Kurdistan region

Abstract

Iraq has suffered severely from drought in recent years and the year 2008 was the driest, particularly in the Iraqi Kurdistan region. This study incorporated Geoinformation technology into mapping the drought that severely affected the Kurdistan region in the years 2007–2008. Geoinformation technology provides support in the theories, methods and techniques for building, and development of Digital Earth aspect. Five vegetation, soil, water, and land surface temperature (LST) indices were applied to two Landsat 7 ETM+ imageries of June 2007 and June 2008, to assess the drought impacts in Erbil governorate Kurdistan during the study period. The indices that were employed in this study were Normalized Difference Vegetation Index, Bare Soil Index, Normalized Differential Water Index, Tasseled Cap Transformation Wetness, and LST. The results revealed a significant decrease in the vegetative cover (56.7%) and a decline in soil/vegetation wetness (29.9%) of the total study area. Likewise, there was a significant reduction in the water bodies surface area in the region such as Dokan Lake, which lost 32.5% of its surface area in comparison with the previous year, 2007. The study results showed that the soil moisture content was the most effective actor on the vegetative cover, LST, and drought status in the study area.     

区域尺度海河流域水土流失风险评估

借鉴USLE的因子选择及综合方法,在遥感和GIS的支撑下对海河流域的水土流失风险进行评估,并对其空间分布特征进行分析.结果表明:海河流域山区水土流失风险显著高于平原地区,北三河山区水土流失风险最低,太行山区最高,永定河上游介于两者之间;水土流失风险"很低"等级主要分布在小于5°的平坦地区,"中"、"高"水土流失风险面积...     

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。