共查询到17条相似文献，搜索用时 456 毫秒
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GIS技术在通用土壤流失方程中的应用研究 总被引：4，自引：0，他引：4
通用土壤流失方程(USLE)在我国应用,重要的是要对各相关因子值进行科学的确定。结合遥感与地理信息系统(GIS)技术,可以实现以USLE为平台的区域土壤流失遥感监测。本研究介绍了USLE中因子的GIS生成以及土壤流失量的GIS生成过程,其研究成果可作为水行政部门决策与执法的依据,也可作为研究区域基础地理信息资料进行储存备份与延伸应用。 相似文献
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迄今为止，USLE是世界上应用最为广泛的水蚀模型。我省在引进、应用USLE的过程中对土壤主要侵蚀因素R、K、S、L、C、P做了大量的基础研究。本文重点介绍了中式USLE的特点，它来源于USLE，其形式和USLE相同，但因子的算法却不相同，尤其是它将USLE的6大因子完全基于GIS和RS的运算中，提高了精度和速度，成功地在福建省泉州市的11个县市区进行了推广应用。本文对水土流失定量监测技术在福建省的应用和发展作了评述，对存在的问题进行了分析，并讨论了统计模型与过程模型的各自优缺点。 相似文献
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USLE/RUSLE是土壤侵蚀监测与预报的核心工具,方程中各因子赋值的合理性决定了方程应用结果的准确度。然而,由于我国地形条件的复杂性等原因,方程在我国范围内的应用受到限制。因此,为明晰土壤流失方程各因子计算中需把握的关键因素,以及当前我国研究中存在的主要问题,采用文献综合对比研究的方法,通过CNKI中国学术期刊全文数据库和Web of Science数据库,搜集了土壤流失方程因子相关文献共373篇。文献综合分析结果表明：各因子的研究普遍存在缺乏估算公式选用和估算结果的精度检验,坡长坡度因子存在公式误用的情况,作物覆盖与管理因子、水土保持措施因子缺少系统性定量计算的方法,土壤可蚀性因子计算的背景条件差异大,难以进行横向比较。为此,提出两条提高模型使用精度的建议,一是通过建设标准化的地面监测系统,系统观测和建立土壤侵蚀因子定量方法,二是明确此类模型应用边界,在较为适合的环境应用。 相似文献
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水土流失已对我国危害深远,与此同时,随着经济和社会的发展,人为的侵蚀造成的水土流失也越来越严重。对水土流失作了简要的分析并具体根据新疆头屯河流域运用韦斯曼（USLE）方程分析水土流失,并根据水土流失的共性和个性针对新疆头屯河提出了相应的水土保持措施。 相似文献
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输电线路建设引发的水土流失常引发各类自然灾害,对人类的生存和发展构成了潜在威胁,已引起国内外的广泛关注。本文针对山西省输电线路走向,结合通用土壤流失方程(USLE,Universal Soil Loss Equation)和改进型土壤流失方程(Revised Universal Soil Loss Equation)[1],对山西省特定地貌特征的输电线路建设工程水土流失预测进行探讨,得到适用于山西省地貌特征的水土流失参数及计算方法,可为山西省输电线路建设的水土流失防控工作提供参考。 相似文献
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USLE模型中植被覆盖因子的遥感数据定量估算 总被引：70，自引：5，他引：70
植被具有截留降雨、减缓径流、保土固土等功能 ,对水土流失起着决定性的作用 ,植被盖度的大小直接影响着水土流失程度的强弱。植被因子是通用水土流失方程 (USLE)中的重要影响因素。选择相适应的卫星遥感时间和空间分辨率ETM数据可以提取植被盖度参数。一般说来 ,归一化植被指数Ic比较真实地表现了影像数据上植被的分布 ,但是Ic 仅仅定性地反映了植被盖度的相对大小 ,要想量化植被盖度还必须进行野外采样 ,样方与影像Ic 作回归统计分析 ,建立经验公式 ,最终反演植被覆盖度。这种方法不仅耗费大量的人力物力 ,而且不利于大区域土壤侵蚀的监控和预测。针对这个问题提出利用线性混合像元分解的方法对影像逐个像元中的植被盖度进行计算和提取 ,提高了模型中植被盖度因子的精度 ,降低研究成本 ,进而可以快速地进行土壤侵蚀量变化动态监测 相似文献
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《Land Degradation \u0026amp; Development》2017,28(3):994-1004
Soil erosion is a key process to understand the land degradation, and modelling of soil erosion will help to understand the process and to foresee its impacts. The applicability of the Universal Soil Loss Equation (USLE) at event scale is affected by the fact that USLE rainfall erosivity factor does not take into account runoff explicitly. USLE‐M and USLE‐MM, including the effect of runoff in the event rainfall–runoff erosivity factor, are characterized by a better capacity to predict event soil loss. The specific objectives of this paper were (i) to determine the suitable parameterization of USLE, USLE‐M and USLE‐MM by using the dataseries of Sparacia experimental site and (ii) to evaluate their performances at both event and annual scale. The measurements allowed to establish the relationships for calculating the factors of USLE, USLE‐M and USLE‐MM usable at the Sparacia experimental area. At first, for slope‐length values greater than 33 m, the calibration of USLE model at event scale pointed out that sediment delivery processes, that is processes involving deposition of the transported eroded soil particles, occur. The analysis showed that USLE and USLE‐M tend to overestimate low event soil losses, while for USLE‐MM, this tendency is less pronounced. However, the USLE‐MM performed better than USLE and USLE‐M and was able to reproduce better than other two models the highest soil loss values that are the most interesting from a practical point of view. The results obtained at annual scale were generally consistent with those obtained at event scale. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
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基于GIS和USLE模型对滇池宝象河流域土壤侵蚀量的研究 总被引：18，自引：4，他引：18
滇池已被列入国家“三河三湖”治理的重点,也是云南省9大高原湖泊治理的重中之重。非点源污染是滇池污染的主要原因,而水土流失则是非点源污染的主要来源,占非点源污染总量的80%。运用GIS栅格模块的空间分析功能,根据USLE模型的各个因子进行图形运算,估算了小流域土壤侵蚀量。结果表明,流域的年均土壤侵蚀模数为983.51 t/km2,侵蚀强度为轻度,占流域面积91.53%的区域土壤侵蚀强度在轻度以下,对流域土壤侵蚀量的贡献率为52.80%;而流域47.2%的土壤侵蚀来自于占流域面积8.5%的中度以上侵蚀区域。 相似文献
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Soil erosion prediction in the Grande River Basin, Brazil using distributed modeling 总被引：2，自引：0，他引：2
Mapping and assessment of erosion risk is an important tool for planning of natural resources management, allowing researchers to modify land-use properly and implement management strategies more sustainable in the long-term. The Grande River Basin (GRB), located in Minas Gerais State, is one of the Planning Units for Management of Water Resources (UPGRH) and is divided into seven smaller units of UPGRH. GD1 is one of them that is essential for the future development of Minas Gerais State due to its high water yield capacity and potential for electric energy production. The objective of this study is to apply the Universal Soil Loss Equation (USLE) with GIS PCRaster in order to estimate potential soil loss from the Grande River Basin upstream from the Itutinga/Camargos Hydroelectric Plant Reservoir (GD1), allowing identification of the susceptible areas to water erosion and estimate of the sediment delivery ratio for the adoption of land management so that further soil loss can be minimized. For the USLE model, the following factors were used: rainfall–runoff erosivity (R), erodibility (K), topographic (LS), cover-management (C) and support practice (P). The Fournier Index was applied to estimate R for the basin using six pluviometric stations. Maps of the K, C, LS and P factors were derived from the digital elevation model (DEM), and soil and land-use maps, taking into account information available in the literature. In order to validate the simulation process, Sediment Delivery Ratio (SDR) was estimated, which is based on transported sediment (TS) to basin outlet and mean soil loss in the basin (MSL). The SDR calculation included data (total solids in the water and respective discharge) between 1996 and 2003 which were measured at a gauging station located on the Grande River and a daily flow data set was obtained from the Brazilian National Water Agency (ANA). It was possible to validate the erosion process based on the USLE and SDR application for the basin conditions, since absolute errors of estimate were low. The major area of the basin (about 53%) had an average annual soil loss of less than 5 t ha− 1 yr− 1. With the results obtained we were able to conclude that 49% of the overall basin presently has soil loss greater than the tolerable rate, thus indicating that there are zones where the erosion process is critical, meaning that both management and land-use have not been used appropriately in these areas of the basin. The methodology applied showed acceptable precision and allowed identification of the most susceptible areas to water erosion, constituting an important predictive tool for soil and environmental management in this region, which is highly relevant for prediction of varying development scenarios for Minas Gerais State due to its hydroelectric energy potential. This approach can be applied to other areas for simple, reliable identification of critical areas of soil erosion in watersheds. 相似文献
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Erodibility of agricultural soils on the Loess Plateau of China 总被引：6，自引：0，他引：6
Soil erodibility is thought of as the ease with which soil is detached by splash during rainfall or by surface flow. Soil erodibility is an important factor in determining the rate of soil loss. In the universal soil loss equation (USLE) and the revised universal soil loss equation (RUSLE), soil erodibility is represented by an erodibility factor (K). The K factor was defined as the mean rate of soil loss per unit rainfall erosivity index from unit runoff plots. Although high rate of soil loss from the Loess Plateau in China is well known and widely documented, it is remarkable that there is little systematic attempt to develop and validate an erodibility index for soils on the Loess Plateu for erosion prediction. Field experimental data from four sites on the Loess Plateau were analyzed to determine the K factor for USLE/RUSLE and to compare with another erodibility index based on soil loss and runoff commonly used for the region. The data set consists of event erosivity index, runoff, and soil loss for 17 runoff plots with slope ranging from 8.7 to 60.1%. Results indicate that the K factor for USLE/RULSE is more appropriate for agricultural soils on the Loess Plateau than the erodibility index developed locally. Values of the K factor for loessial soils range from 0.0096 to 0.0269 t h/(MJ mm). The spatial distribution of the K value in the study area follows a simple pattern showing high values in areas with low clay content. For the four sites investigated, the K factor was significantly related to the clay content, (K=0.031−0.0013 Cl, r2=0.75), where Cl is the clay content in percent. The measured values of the K factor are systematically lower than the nomograph-based estimates by a factor of 3.3–8.4. This implies that use of the nomograph method to estimate soil erodibility would considerably over-predict the rate of soil loss, and local relationship between soil property and the K factor is required for soil erosion prediction for the region. 相似文献