排序方式： 共有51条查询结果，搜索用时 15 毫秒
11.
A. Ugur Ozcan Gunay Erpul Mustafa Basaran H. Emrah Erdogan 《Environmental Geology》2008,53(8):1731-1741
The universal soil loss equation (USLE) is an erosion model to estimate average soil loss that would generally result from
splash, sheet, and rill erosion from agricultural plots. Recently, use of USLE has been extended as a useful tool predicting
soil losses and planning control practices by the effective integration of the GIS-based procedures to estimate the factor
values on a grid cell basis. This study was performed for five different lands uses of Indağı Mountain Pass, Cankırı to predict
the soil erosion risk by the USLE/GIS methodology for planning conservation measures in the site. Of the USLE factors, rainfall-runoff
erosivity factor (USLE-R) and topographic factor (USLE-LS) were greatly involved in GIS. These were surfaced by correcting
USLE-R site-specifically using DEM and climatic data and by evaluating USLE-LS by the flow accumulation tool using DEM and
watershed delineation tool to consider the topographical and hydrological effects on the soil loss. The study assessed the
soil erodibility factor (USLE-K) by randomly sampled field properties by geostatistical analysis. Crop management factor for
different land-use/land cover type and land use (USLE-C) was assigned to the numerical values from crop and flora type, canopy
and density of five different land uses, which are plantation, recreational land, cropland, forest and grassland, by means
of reclassifying digital land use map available for the site. Support practice factor (USLE-P) was taken as a unit assuming
no erosion control practices. USLE/GIS technology together with the geostatistics combined these major erosion factors to
predict average soil loss per unit area per unit time. Resulting soil loss map revealed that spatial average soil loss in
terms of the land uses were 1.99, 1.29, 1.21, 1.20, 0.89 t ha−1 year−1 for the cropland, grassland, recreation, plantation and forest, respectively. Since the rate of soil formation was expected
to be so slow in Central Anatolia of Turkey and any soil loss of more than 1 ton ha−1 year−1 over 50–100 years was considered as irreversible for this region, soil erosion in the Indağı Mountain Pass, to the great
extent, attained the irreversible state, and these findings should be very useful to take mitigation measures in the site. 相似文献
12.
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). 相似文献
13.
Land degradation by water erosion is one of the majorissues in the field of environmental planning. Soilerosion and sediment transport are spatiallydistributed processes, and their evaluation can beeasily realised by means of the use of GeographicInformation Systems. The greater availability ofdigital and geo-lithological data managed and storedinside GIS has implied the development of techniquesand procedures aimed at the definition of the spatialprediction of erosion and deposition rates across acatchment. In this paper using terrain data measuredon an experimental basin in southern Italy, asensitivity analysis on different GIS-basedmethodologies for the estimate of a Length-Slope factorhas been developed with the aim of determining whichof these is more reliable for spatial erosion riskassessment. Specifically, by using the unit stream powertheory, different estimates are shown, depending on thescheme adopted to represent the hydrological andtopographic three-dimensional effects inside theLength-Slope factor. The performances of theprocedures analysed have been evaluated through theinformation content of the corresponding spatialdistributions, estimated as an entropy measure. Theresults obtained have shown that among the approachesutilised to describe the routing of the surface runoffalong the hillslope profiles, the two-dimensionalscheme appeared to be more realistic both on divergingand converging surfaces. Such a scheme, during thecomputational phases also aimed at distinguishing the areasof the basin experiencing net erosion from those areasexperiencing net deposition, resulted, being inaccordance with on-site investigations. 相似文献
14.
Ruzhong Li 《中国地理科学(英文版)》2008,18(4):348-355
Many kinds of uncertainties are involved, such as random, fuzzy, grey, unascertained property and so on, in soil erosion process. To exactly predict the non-point source pollution loads, some uncertainties should be taken into consideration. Aiming at the deficiency of present blind number theory being helpless for fuzziness, a novel blind number, i.e. extended-blind number, was introduced by substituting a set of triangular fuzzy numbers （TFNs）, expressed as a-cuts, for interval values in present blind number, and the expected value of extended-blind number was also brought forward by referring to the current blind number theory. On the basis of denoting the parameters of Uni- versal Soil Loss Equation （USLE） as extended-blind parameters, a novel USLE model was established for quantitatively evaluating soil erosion loss and non-point source pollution loads. As a case, the uncertain USLE was employed for predicting the soil erosion loss and non-point source pollution loads of absorbed nitrogen and phosphorus in a dis- trict in the Hangbu-Fengle River basin, in the upstream of Chaohu Lake watershed. The results show that it is feasible in theory to extend blind number into fuzzy environment and reliable on conclusion to apply extended-blind number theory for predicting non-point source pollution loads. 相似文献
15.
P. I. A. Kinnell 《水文研究》2008,22(16):3168-3175
The Universal Soil Loss Equation (USLE) or the revised USLE (RUSLE) are often used together with sediment delivery ratios in order to predict sediment delivery from hillslopes. In using sediment delivery ratios for this purpose, it is assumed that the sediment delivery ratio for a given hillslope does not vary with the amount of erosion occurring in the upslope area. This assumption is false. There is a perception that hillslope erosion is calculated on the basis that hillslopes are, in effect, simply divided into 22·1 m long segments. This perception fails to recognize the fact the inclusion of the 22·1 m length in the calculation has no physical significance but simply produces a value of 1·0 for the slope length factor when slopes have a length equal to that of the unit plot. There is a perception that the slope length factor is inappropriate because not all the dislodged sediment is discharged. This perception fails to recognize that the USLE and the RUSLE actually predict sediment yield from planar surfaces, not the total amount of soil material dislocated and removed some distance by erosion within an area. The application of the USLE/RUSLE to hillslopes also needs to take into account the fact that runoff may not be generated uniformly over that hillslope. This can be achieved by an equation for the slope length factor that takes account of spatial variations in upslope runoff on soil loss from a segment or grid cell. Several alternatives to the USLE event erosivity index have been proposed in order to predict event erosion better than can be achieved using the EI30 index. Most ignore the consequences of changing the event erosivity index on the values for the soil, crop and soil conservation protection factors because there is a misconception that these factors are independent of one another. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
16.
Sampling the collected suspension in a storage tank is a common procedure to obtain soil loss data. A calibration curve of the tank has to be used to obtain actual concentration values from those measured by sampling. However, literature suggests that using a tank calibration curve was not a common procedure in the past. For the clay soil of the Sparacia (Italy) experimental station, this investigation aimed to establish a link between the relative performances of the USLE‐M and USLE‐MM models, usable to predict plot soil loss at the event temporal scale, and soil loss measurement errors. Using all available soil loss data, lower soil loss prediction errors were obtained with the USLE‐MM (exponent of the erosivity term, b1 > 1) than the USLE‐M (b1 = 1). A systematic error of the soil loss data is unexpected for the Sparacia soil because the calibration curve does not depend on the water level in the tank. In any case, this type of error does not have any effect on the b1 exponent. Instead, this exponent decreases as the level of underestimation increases for increasing soil loss values. This type of error can occur at Sparacia if it is assumed that a soil loss measurement can be obtained by a bottle sampler dipped close to the bottom of the tank after mixing the suspension and assuming that the measured concentration coincides with the actual one. In this case, the risk is to obtain a lower b1 value than the actual one. In conclusion, additional investigations on the factors determining errors in soil loss data collected by a sampling procedure are advisable because these errors can have a noticeable effect on the calibrated empirical models for soil loss prediction. 相似文献
17.
18.
Mushtak Jabbar 《地球空间信息科学学报》2013,16(1):34-37
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. 相似文献
19.
海南省松涛水库流域土壤侵蚀及控制方案 总被引：2，自引：1，他引：1
采用RS和GIS技术,基于USLE方程实现了热带地区海南岛松涛水库流域2003~2005年平均土壤侵蚀的定量模拟,通过情景分析研究了流域土壤侵蚀控制方案。结果表明:流域内潜在土壤侵蚀量约为4261万t/a,超过容许土壤流失量的60倍;在植被的保护下,现有年均土壤侵蚀量约为51.46万t/a,主要集中在退化的林地、浆纸林和橡胶林;流域平均土壤侵蚀模数略低于容许土壤流失量,但空间分布不均,部分区域侵蚀发育强烈;如对经济林、园地和耕地采取水土保持措施或恢复林草植被,能有效控制流域内土壤侵蚀,分别减少侵蚀量22.46万t和14.15万t,减少侵蚀面积98.48km2和65.90km2。 相似文献
20.
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。 相似文献