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.     

Integrated approach of using remote sensing and GIS to study watershed prioritization and productivity

Soil data obtained from soil resource inventory, land and climate were derived from the remote sensing satellite data (Landsat TM, bands 1 to 7) and were integrated in GIS environment to obtain the soil erosion loss using USLE model for the watershed area. The priorities of different sub-watershed areas for soil conservation measures were identified. Land productivity index was also used as a measure for land evaluation. Different soil and land attribute maps were generated in GIS, and R,K,LS,C and P factor maps were derived. By integrating these soil erosion map was generated. The mapping units, found not suitable for agriculture production, were delineated and mapped as non-arable land. The area suitable for agricultural production was carved out for imparting the productivity analysis; the land suitable for raising agricultural crops was delineated into different mapping units as productivity ratings good, fair, moderate and poor. The analysis performed using remote sensing and GIS helped to generate the attribute maps with more accuracy and the ability of integrating these in GIS environment provided the ease to get the required kind of analysis. Conventional methods of land evaluation procedures in terms of either soil erosion or productivity are found not comparable with the out put generated by using remote sensing and GIS as the limitations in generating the attribute maps and their integration. The results obtained in this case study show the use of different kinds of data derived from different sources in land evaluation appraisals.     

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.     

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。     

基于GIS、RS的黄土高原USLE模型改进方法

结合地理信息系统技术、遥感技术,探讨美国通用土壤流失方程（USLE）在我国黄土高原土壤侵蚀产沙模型应用中的改进方法。USLE属于因子分析模型,由于USLE考虑因素全面,因子具有物理意义,形式简单,所用资料广泛,统一了土壤侵蚀模型形式,故在全世界得到了广泛应用。但是我国黄土高原地区土壤流失严重,影响流失的因素极其多样,使得USLE模型不能很好的应用于该地特殊的地理条件。基于此,采用GIS方法探讨USLE模型在黄土高原改进方法问题。     

An integrated approach for prioritization of reservoir catchment using remote sensing and geographic information system techniques

This study is aimed at evolving a watershed prioritization of reservoir catchment based on vegetation, morphological and topographical parameters, and average annual soil loss using geographic information system (GIS) and remote sensing techniques. A large multipurpose river valley project, Upper Indravati reservoir, situated in the state of Orissa, India, has been chosen for the present work. Watershed prioritization is useful to soil conservationist and decision makers. This study integrates the watershed erosion response model (WERM) and universal soil loss equation (USLE) with a geographic information system (GIS) to estimate the erosion risk assessment parameters of the catchment. The total catchment is divided into 15 sub-watersheds. Various erosion risk parameters are determined for all the sub-watersheds separately. Average annual soil loss is also estimated for the sub-watersheds using USLE. The integrated effect of all these parameters is evaluated to recommend the priority rating of the watersheds for soil conservation planning.     

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.     

Integrating terrain and vegetation indices for identifying potential soil erosion risk area

The present paper offers an innovative method to monitor the change in soil erosion potential by integrating terrain and vegetation indices derived from remote sensing data. Three terrain indices namely, topographic wetness index (TWI), stream power index (SPI) and slope length factor (LS), were derived from the digital elevation model. Normalized vegetation index (NDVI) was derived for the year 1988 and 2004 using remote sensing images. K-mean clustering was performed on staked indices to categorize the study area into four soil erosion potential classes. The validation of derived erosion potential map using USLE model showed a good agreement. Results indicated that there was a significant change in the erosion potential of the watershed and a gradual shifting of lower erosion potential class to next higher erosion potential class over the study period.     

Quantitative Determination of Soil Erosion and Prioritization of Micro-Watersheds Using Remote Sensing and GIS

Soil erosion which occurs at spatially varying rate is a widespread threat to sustainable resource management at watershed scale. Thus estimation of soil loss and identification of critical area for implementation of best management practice is central to success of soil conservation programme. The present study focuses application of most widely used Universal Soil Loss Equation (USLE) to determine soil erosion and prioritization of micro-watersheds of Upper Damodar Valley Catchment (UDVC) of India. Annual average soil loss for the entire basin is 23.17 t/ha/yr; for micro-watersheds. High soil loss is observed in 345 micro-watersheds, medium in 159 micro-watersheds and low soil loss is observed in 201 micro-watersheds. It is found that, out of 705 micro-watersheds of UDVC, 453 micro-watersheds are in agreement with AISLUS suggested priority which is based on observed sediment yield, 116 micro-watersheds under predict and 136 micro-watersheds over predict the priority. Geographic Information System (GIS) is applied to prepare various layers of USLE parameters which interactively estimate soil erosion at micro-watershed level. The main advantage of the GIS methodology is in providing quick information on the estimated value of soil loss for any part of the investigated area.     

基于GIS的东营市土地适宜性评价研究

依据土地适宜性评价原则,以山东省东营市土地适宜性评价为例,探讨了运用GIS技术对用地的自然、社会属性进行综合评价的数量化方法,结合当地实际情况,选取了土壤类型、地下水位、全氮、全磷、土壤盐分五个评价因子,各因子的适宜度的确定和各单元因素适宜性的评价,对评价结果进行了分析,提出了土地改良应用的合理化建议。将GIS引入到土地适宜性的空间评价中评价方法更科学,使评价结果能更好地为土地利用和规划服务。     

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.     

基于DEM的USLE土壤侵蚀方程地形因子获取与分析

坡长和坡度是研究水土流失问题中必须要考虑的重要地形因子,坡长的空间分布特征和规律、地貌发育对坡长的影响,以及坡长与坡度之间的关系,是研究水土流失、侵蚀规律的重要条件之一。利用GIS以及相关软件为平台,在黑龙江省通河地区建立USLE水土流失方程模型,研究LS因子在水土流失中的影响以及作用,并探讨DEM数据分辨率变化对LS值的影响。     

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.     

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。     

The assessment of potential land use in the proposed irrigation command using Remote Sensing and GIS

Standard false colour composites (Std. FCC) on 1:50,000 scale was visually interpreted in conjunction with soil survey to prepare physiographic-soil map. Thirteen mapping units were delineated indicating soil association at family-level. Soil and land resource was evaluated for their land capability and irrigation suitability for its sustained use under irrigation. Land capability and land irrigability maps were generated as attribute map. These maps were integrated to suggest potential land use map. Current land use/land cover map prepared by visual analysis was spatially analysed in relation to potential land use to study potential changes in land use / land cover using GIS. The study reveals that 14.66% area has no limitation and can be brought to intensive agriculture by double cropping.     

Soil erosion modelled with USLE and PESERA using QuickBird derived vegetation parameters in an alpine catchment

The focus of soil erosion research in the Alps has been in two categories: (i) on-site measurements, which are rather small scale point measurements on selected plots often constrained to irrigation experiments or (ii) off-site quantification of sediment delivery at the outlet of the catchment. Results of both categories pointed towards the importance of an intact vegetation cover to prevent soil loss. With the recent availability of high-resolution satellites such as IKONOS and QuickBird options for detecting and monitoring vegetation parameters in heterogeneous terrain have increased. The aim of this study is to evaluate the usefulness of QuickBird derived vegetation parameters in soil erosion models for alpine sites by comparison to Cesium-137 (Cs-137) derived soil erosion estimates. The study site (67 km²) is located in the Central Swiss Alps (Urseren Valley) and is characterised by scarce forest cover and strong anthropogenic influences due to grassland farming for centuries. A fractional vegetation cover (FVC) map for grassland and detailed land-cover maps are available from linear spectral unmixing and supervised classification of QuickBird imagery. The maps were introduced to the Pan-European Soil Erosion Risk Assessment (PESERA) model as well as to the Universal Soil Loss Equation (USLE). Regarding the latter model, the FVC was indirectly incorporated by adapting the C factor. Both models show an increase in absolute soil erosion values when FVC is considered. In contrast to USLE and the Cs-137 soil erosion rates, PESERA estimates are low. For the USLE model also the spatial patterns improved and showed “hotspots” of high erosion of up to 16 t ha⁻¹ a⁻¹. In conclusion field measurements of Cs-137 confirmed the improvement of soil erosion estimates using the satellite-derived vegetation data.     

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.     

GIS-based evaluation of micro-watersheds to ascertain site suitability for water conservation structures

The planning of conservation measures to conserve water and soil resources taking hydrological planning unit as micro-watershed is considered to be effective. The automated watershed delineation technique using the spline interpolated filled digital elevation model (DEM) is effective in converging slopes of the area in which the stream patterns match with the manually digitized stream patterns of the topographical map. The various vector spatial layers like the slope/aspect, land-use/land-cover, runoff potential, soil erosion potential and the associated attribute information governing the criteria for different conservation structures can act as input layers in integrated spatial analysis module in GIS environment to evolve derived layers indicating the locations of conservation sites meeting the requisite criteria. The reliability of suitable conservation sites suggested out of integrated spatial GIS analysis could be ascertained using the multi criteria analysis incorporating the various factors controlling soil erosion process in the micro-watershed groups. The details of the above work are discussed in the paper.     

Soil resource assessment and mapping using remote sensing and GIS

In this study digital image processing for physiographic analysis and soil resource mapping of Solani watershed was carried out using satellite remote sensing data and GIS. Digital image processing of satellite data facilitated in accurately delineating and identifying various soil mapping units. The physiography of the study area is mainly influenced by denudational and colluvial processes in the upper part and by sedimentation processes in the lower part. Topography of the land and nature of parent material along with the time factor seemed to have played a vital role in the genesis of soils. Majority of the mapping units are Typic Haplustepts with Entisols and Inceptisols being the major soil orders. The soils of the Siwalik hills experiences severe erosion, which prevents the maturation of soil profile. The present study demonstrated that satellite remote sensing and GIS is a valuable tool for physiographic analysis and soil resource mapping.