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1.
The study evaluated the performance and suitability of AnnAGNPS model in assessing runoff, sediment loading and nutrient loading under Malaysian conditions. The watershed of River Kuala Tasik in Malaysia, a combination of two sub-watersheds, was selected as the area of study. The data for the year 2004 was used to calibrate the model and the data for the year 2005 was used for validation purposes. Several input parameters were computed using methods suggested by other researchers and studies carried out in Malaysia. The study shows that runoff was predicted well with an overall R2 value of 0.90 and E value of 0.70. Sediment loading was able to produce a moderate result of R2 = 0.66 and E = 0.49, nitrogen loading predictions were slightly better with R2 = 0.68 and E = 0.53, and phosphorus loading performance was slightly poor with an R2 = 0.63 and E = 0.33. The erosion map developed was in agreement with the erosion risk map produced by the Department of Agriculture, Malaysia. Rubber estates and urban areas were found to be the main contributors to soil erosion. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for planning and management of watersheds under Malaysian conditions.  相似文献   
2.
RUSLE及其影响因子的快速计算分析   总被引:4,自引:0,他引:4  
RUSLE是目前应用最广泛的土壤侵蚀模型。虽然是一种经验模型,但是其影响因子计算仍然非常复杂,满足不了区域土壤侵蚀的快速提取要求。针对这种状况,文章在介绍RUSLE手册中每个影响因子计算方式基础上,分析总结了可进行快速计算的方法,实验表明,采用文章推荐的因子计算方式,可达到快速有效的目的。  相似文献   
3.
The use of loose spoils on steep slopes for surface coal mining reclamation sites has been promoted by the US Department of Interior, Office of Surface Mining for the establishment of native forest, as prescribed by the Forest Reclamation Approach (FRA). Although low‐compaction spoils improve tree survival and growth, erodibility on steep slopes was suspected to increase. This study quantified a combined KC factor (combining the effects of the soil erodibility K factor and cover management C) for low compaction, steep‐sloped (>20°) reclaimed mine lands in the Appalachian region, USA. The combined KC factor was used because standard Unit Plot conditions required to separate these factors, per Revised Universal Soil Loss Equation (RUSLE) experimental protocols, were not followed explicitly. Three active coal mining sites in the Appalachian region of East Tennessee, each containing four replicate field plots, were monitored for rainfall and sediment yields during a 14‐month period beginning June 2009. Average cumulative erosivity for the study sites during the monitoring period was measured as 5248.9 MJ·mm·ha?1·h?1. The KC ranged between 0.001 and 0.05 t·ha·h·ha?1·MJ?1·mm?1, with the highest values occurring immediately following reclamation site construction as rills developed (June – August 2009). The KC for two study sites with about an 18–20 mm spoil D84 were above 0.01 t·ha·h·ha?1·MJ?1·mm?1 during rill development, and below 0.003 t·ha·h·ha?1·MJ?1·mm?1 after August 2009 for the post‐rill development period. The KC values for one site with a 40 mm spoil D84 were never above 0.008 t·ha·h·ha?1·MJ?1·mm?1 and also on average were lower, being more similar to the other two sites after the rill development period. Based on an initial KC factor (Ke) measured during the first few storm events, the average C factor (Ce) was estimated as 0.58 for the rill development period and 0.13 for the post‐rill development period. It appears that larger size fractions of spoils influence KC and Ce factors on low‐compaction steep slopes reclamation sites. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   
4.
Revised Universal Soil Loss Equation(RUSLE) model coupled with transport limited sediment delivery(TLSD) function was used to predict the longtime average annual soil loss, and to identify the critical erosion-/deposition-prone areas in a tropical mountain river basin, viz., Muthirapuzha River Basin(MRB; area=271.75 km~2), in the southern Western Ghats, India. Mean gross soil erosion in MRB is 14.36 t ha~(-1) yr~(-1), whereas mean net soil erosion(i.e., gross erosion-deposition) is only 3.60 t ha~(-1) yr~(-1)(i.e., roughly 25% of the gross erosion). Majority of the basin area(~86%) experiences only slight erosion(5 t ha~(-1) yr~(-1)), and nearly 3% of the area functions as depositional environment for the eroded sediments(e.g., the terraces of stream reaches, the gentle plains as well as the foot slopes of the plateau scarps and the terrain with concordant summits). Although mean gross soil erosion rates in the natural vegetation belts are relatively higher, compared to agriculture, settlement/built-up areas and tea plantation, the sediment transport efficiency in agricultural areas and tea plantation is significantly high,reflecting the role of human activities on accelerated soil erosion. In MRB, on a mean basis, 0.42 t of soil organic carbon(SOC) content is being eroded per hectare annually, and SOC loss from the 4th order subbasins shows considerable differences, mainly due to the spatial variability in the gross soil erosion rates among the sub-basins. The quantitative results, on soil erosion and deposition, modelled using RUSLE and TLSD, are expected to be beneficial while formulating comprehensive land management strategies for reducing the extent of soil degradation in tropical mountain river basins.  相似文献   
5.
A comparative study of soil erosion modelling by MMF,USLE and RUSLE   总被引:1,自引:0,他引:1  
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.  相似文献   
6.
The formation mechanism and influencing factors identification of soil erosion are the core and frontier issues of current research. However, studies on the multi-factor synthesis are still relatively lacked. In this study, the simulation of soil erosion and its quantitative attribution analysis have been conducted in different geomorphological types in a typical karst basin based on the RUSLE model and the geodetector method. The influencing factors, such as land use type, slope, rainfall, elevation, lithology and vegetation cover, have been taken into consideration. Results show that the strength of association between the six influencing factors and soil erosion was notably different in diverse geomorphological types. Land use type and slope were the dominant factors of soil erosion in the Sancha River Basin, especially for land use type whose power of determinant(q value) for soil erosion was much higher than other factors. The q value of slope declined with the increase of relief in mountainous areas, namely it was ranked as follows: middle elevation hill> small relief mountain> middle relief mountain. Multi-factors interactions were proven to significantly strengthen soil erosion, particularly for the combination of land use type with slope, which can explain 70% of soil erosion distribution. It can be found that soil erosion in the same land use type with different slopes(such as dry land with slopes of 5° and above 25°) or in the diverse land use types with the same slope(such as dry land and forest with a slope of 5°), varied much. These indicate that prohibiting steep slope cultivation and Grain for Green Project are reasonable measures to control soil erosion in karst areas. Based on statistics of soil erosion difference between diverse stratifications of each influencing factor, results of risk detector suggest that the amount of stratification combinations with significant difference accounted for 55% at least in small relief mountain and middle relief mountainous areas. Therefore, the spatial heterogeneity of soil erosion and its influencing factors in different geomorphological types should be investigated to control karst soil loss more effectively.  相似文献   
7.
陕北地区退耕还林还草工程土壤保护效应的时空特征   总被引:1,自引:1,他引:0  
This paper looks at the Green for Grain Project in northern Shaanxi Province.Based on remote sensing monitoring data,this study analyzes the locations of arable land in northern Shaanxi in the years 2000,2010 and 2013 as well as spatio-temporal changes over that period,and then incorporates data on the distribution of terraced fields to improve the input parameters of a RUSLE model and simulate and generate raster data on soil erosion for northern Shaanxi at different stages with a accuracy verification.Finally,combined with the dataset of farmland change,compared and analyzed the characteristics of soil erosion change in the converted farmland to forest(grassland)and the unconverted farmland in northern Shaanxi,so as to determine the project’s impact on soil erosion over time across the region.The results show that between 2000 and 2010,the soil erosion modulus of repurposed farmland in northern Shaanxi decreased 22.7 t/ha,equivalent to 47.08%of the soil erosion modulus of repurposed farmland in 2000.In the same period,the soil erosion modulus of non-repurposed farmland fell 10.99 t/ha,equivalent to 28.6%of the soil erosion modulus of non-repurposed farmland in 2000.The soil erosion modulus for all types of land in northern Shaanxi decreased by an average of 14.51 t/ha between 2000 and 2010,equivalent to 41.87%of the soil erosion modulus for the entire region in 2000.This suggests that the Green for Grain Project effectively reduced the soil erosion modulus,thus helping to protect the soil.In particular,arable land that was turned into forest and grassland reduced erosion most noticeably and contributed most to soil conservation.Nevertheless,in the period 2010 to 2013,which was a period of consolidation of the Green for Grain Project,the soil erosion modulus and change in volume of soil erosion in northern Shaanxi were significantly lower than in the previous decade.  相似文献   
8.
退耕还林(草)等生态工程对区域用地结构及生态系统服务功能产生了重要影响。本研究基于RUSLE模型,并辅以遥感监测与GIS空间分析方法,对北方农牧交错带西段2000-2015年退耕状况及其引起的土壤保持功能变化分3个时段(2000-2005年、2005-2010年及2010-2015年)进行了探究。结果表明:北方农牧交错带西段地区2000-2015年耕地面积净减少1663.83 km2,以转为林地、草地、建设用地为主,其中耕地转林、草地净减少面积为1113.64 km2,草地和未利用地是新增耕地的主要来源;15年间土壤保持功能提升显著,退耕还林(草)工程的实施使土壤保持量增加了56.50×104 t,2005-2010年由退耕所带来的土壤保持增加量在3段时期中最高;不同坡度等级的生态退耕引起的土壤保持增加量差别较大,总体随着坡度升高呈下降趋势,但在25°以上的陡坡耕地由退耕还林(草)带来的土壤保持效益又有所升高。研究对于评估北方农牧交错带西段地区实施退耕还林(草)等工程的生态效益具有重要意义,并能为区域生态保护与修复工程的建设规划提供科学依据。  相似文献   
9.
彭建  李丹丹  张玉清 《山地学报》2007,25(5):548-556
土壤侵蚀空间分布特征,是进行土壤侵蚀防治规划、实践的重要基础与依据。研究以云南省丽江县为例,应用RUSLE估算了县域土壤侵蚀量,并基于G IS的空间统计分析功能,分析了土壤侵蚀在海拔、坡度与土地利用类型等方面的空间分布特征。结果表明,全县平均土壤侵蚀模数为52.50 t/(hm2.a),属于强度侵蚀,县域东部的金沙江沿岸、3 500~6 000 m高程带、25°~90°坡度带,以及裸地与荒草地、旱地等不同类型区域是研究区土壤侵蚀治理的重点地区。  相似文献   
10.
ABSTRACT

The accurate representation of the Earth’s surface plays a vital role in soil erosion modelling. Topography is parameterized in the Universal Soil Loss Equation (USLE) and Revised USLE (RUSLE) by the topographic (LS) factor. For slope gradients of < 20%, soil loss values are similar for both models, but when the gradient is increased, RUSLE estimates are only half of those of USLE. The study aims to assess the validity of this statement for complex hillslope profiles. To that end, both models were applied at eight diverse mountainous sub-watersheds. The USLE and RUSLE indices were estimated utilizing the SEAGIS model and a European dataset, respectively. LS factors were in a 3:1 ratio (i.e. USLE:RUSLE) considering the entire basin area. For areas with slopes <20%, gross erosion estimates of both models converged. Sites of strong relief (>20%) USLE yielded significantly higher values than RUSLE.  相似文献   
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