A comparative analysis of sediment yield simulation by empirical and process-oriented models in Thailand / Une analyse comparative de simulations de l'exportation sédimentaire en Thaïlande à l'aide de modèles empiriques et de processus

Abstract

Although soil erosion has been recognized worldwide as a threat to the sustainability of natural ecosystems, its quantification presents one of the greatest challenges in natural resources and environmental planning. Precise modelling of soil erosion and sediment yield is particularly difficult, as soil erosion is a highly dynamic process at the spatial scale. The main objective of this study was to simulate soil erosion and sediment yield using two fundamentally different approaches: empirical and process-oriented. The revised form of the Universal Soil Loss Equation (RUSLE), along with a sediment delivery distributed model (SEDD) and the Modified Universal Soil Loss Equation (MUSLE), which are popular empirical models, were applied in a sub-basin of the Mun River basin, Thailand. The results obtained from the RUSLE/SEDD and MUSLE models were compared with those obtained from a process-oriented soil erosion and sediment transport model. The latter method involves spatial disaggregation of the catchment into homogeneous grid cells to capture the catchment heterogeneity. A GIS technique was used for the spatial discretization of the catchment and to derive the physical parameters related to erosion in the grid cells. The simulated outcomes from the process-oriented model were found to be closer to observations as compared to the outcomes of the empirical approaches.     

黑龙江典型黑土区土壤侵蚀遥感监测技术研究

以遥感和GIS技术为支撑,利用修正后的通用土壤流失方程RUSLE为评价模型,对黑龙江省绥化市2003、2015年的土壤侵蚀量进行了计算,并结合水土流失强度分级标准,生成了黑龙江省绥化市水土流失强度分布图.在此基础上,对黑龙江省绥化市2003、2015年的水土流失现状、空间分布及2003～2015年水土流失的变化及原因进行了分析.结果表明：从2003～2015年间,水土保持措施增加,土壤侵蚀状况有向好的趋势.从统计结果看出,强度、极强度侵蚀面积比例减少,相对的轻度和微度的侵蚀面积增加.2015年,强度侵蚀等级水土流失面积相比2003年减少522.75 km²,轻度侵蚀增长近1000 km².     

基于RUSLE模型的土壤侵蚀时空分异特征分析——以辽宁省朝阳市为例

以数字高程模型(DEM)、降雨量、土壤、遥感影像等为基础数据,运用GIS与遥感技术,结合RUSLE模型研究辽宁省朝阳市2001~2010 年的土壤侵蚀时空分异特征。研究结果如下:① 2001~2010 年土壤侵蚀模数总体呈下降趋势,其中2009 年的平均土壤侵蚀模数为254.02 t·hm^-2·a^-1,为10 a 间最低值;② 微度土壤侵蚀面积总体呈上升趋势,但以上2 个指标在2010 年均出现了不同程度的反弹;③ 朝阳县是土壤侵蚀最严重的地区,土壤侵蚀模数的平均值最高,为747.33 t·hm^-2·a^-1,中度以上土壤侵蚀面积分别为29.2%、32.67%、34.57%、31.41%。     

Modeling erosion and sediment control practices with RUSLE 2.0: a management approach for natural gas well sites in Denton County,TX, USA

Sediment yields from natural gas well sites in Denton County, TX, USA can be substantial and warrant consideration of appropriate erosion and sediment control best management practices (BMPs). Version 2 of the revised universal soil loss equation (RUSLE 2.0) was used to predict sediment yields and evaluate the efficiency of BMPs for multiple combinations of different land surface conditions (soil erodibility and slope) commonly found at gas well sites in the area. Annual average sediment yield predictions from unprotected site conditions ranged from 12.1 to 134.5 tonnes per hectare per year (t/ha/yr). Sediment yield predictions for 1, 2, 5, and 10-year design storms ranged from 8.1 to 20.6 t/ha. When site conditions were modeled with BMPs, predicted sediment yields were 52–93% less. A comparison of modeled efficiency values to a review of laboratory and field data suggests that modeled (theoretical) sediment yield results with BMPs are likely best case scenarios. This study also evaluated BMPs in the context of site management goals and implementation cost, demonstrating a practical approach for the application of RUSLE 2.0 for managing soil loss and understanding the importance of selecting appropriate site-specific BMPs for disturbed site conditions.     

陕北地区退耕还林还草工程土壤保护效应的时空特征

以中国退耕还林生态工程重点区域陕北地区作为研究区,基于耕地遥感监测数据集,分析了陕北地区2000-2013年耕地的时空变化特征;基于梯田空间分布,对RUSLE模型进行改进,模拟生成陕北地区土壤侵蚀模数栅格数据并进行精度验证;最后结合耕地变化数据集对陕北地区退耕还林（草）地及未退耕地的土壤侵蚀变化特征进行对比分析,以明确工程对全区土壤侵蚀变化的影响。结果表明,2000-2010年,陕北退耕农田内部侵蚀模数减少了22.70 t/hm ²,是退耕农田区2000年土壤侵蚀模数的47.08%。同期,陕北地区未退耕农田侵蚀模数减少了10.99 t/hm ²,占未退耕农田区域2000年土壤侵蚀模数的28.60%。从陕北全区的角度看,各种土地利用类型2000-2010年土壤侵蚀模数平均减少了14.51 t/hm ²,占2000年全区土壤侵蚀模数的41.87%。由此可见,退耕还林还草工程可以有效减少土壤侵蚀模数,达到土壤保护的作用。其中,由耕地转为林草所导致的侵蚀减少最为显著,对土壤保护的贡献作用最大。但是,2010年以后（2010-2013年）为退耕还林还草巩固时期,因此该阶段陕北地区土壤侵蚀模数和土壤侵蚀量变化较前10年显著降低。     

Quantitative attribution analysis of soil erosion in different geomorphological types in karst areas: Based on the geodetector method

Journal of Geographical Sciences - The formation mechanism and influencing factors identification of soil erosion are the core and frontier issues of current research. However, studies on the...     

Accounting for the influence of runoff on event soil erodibilities associated with the EI30 index in RUSLE2

Soil erodibilities (K) associated with the EI₃₀ index vary not only with soil properties but also with soil moisture as it varies in time and space. In Revised Universal Soil Loss Equation Version 2 (RUSLE2), temporal variations in soil erodibility in the USA are calculated using monthly precipitation and temperature as independent variables. K_UM, the soil erodibility factor associated with the Q_REI₃₀ index, varies independently of runoff and the product of K_UM and the runoff ratio for the unit plot (Q_R1) provides an alternative to the temporally varying Ks currently used in predicting storm soil loss in RUSLE2. Comparisons were made between the product of Q_R1 and K_UM and RUSLE2 Ks for representative storms at four locations representing the north to south variation in climate in the USA. Peak erosion associated with the current approach used in RUSLE2 was slightly higher at two locations and slightly lower at the other two locations. One other location, Morris, MN, provided an exception with the peak loss predicted by using the product of Q_R1 and K_UM being 1.7 times that obtained using RUSLE2 Ks. In theory, average annual K_UM values should be better related to soil properties than the average annual values of K frequently used when the average annual values of EI₃₀ are used to predict soil loss. However, work has yet to be performed to determine how K_UM varies directly with soil properties and in space and time. Copyright © 2014 John Wiley & Sons, Ltd.     

Managing Soil Erosion Potential by Integrating Digital Elevation Models with the Southern China's Revised Universal Soil Loss Equation——A Case Study for the West Lake Scenic Spots Area of Hangzhou,China

In China,many scenic and tourism areas are suffering from the urbanization that results from physical development of tourism projects,leading to the removal of the vegetative cover,the creation of areas impermeable to water,in-stream modifications,and other problems. In this paper,the risk of soil erosion and its ecological risks in the West Lake Scenic Spots (WLSS) area were quantitatively evaluated by integrating the revised universal soil loss equation (RUSLE) with a digital elevation model (DEM) and geographical information system (GIS) software. The standard RUSLE factors were modified to account for local climatic and topographic characteristics reflected in the DEM maps,and for the soil types and vegetation cover types. An interface was created between the Arcinfo software and RUSLE so that the level of soil erosion and its ecological risk in the WLSS area could be mapped immediately once the model factors were defined for the area. The results from an analysis using the Arcinfo-RUSLE interface showed that the risk value in 93 % of the expanding western part of the WLSS area was moderate or more severe and the soil erosion risk in this area was thus large compared with that in the rest of the area. This paper mainly aimed to increase the awareness of the soil erosion risk in urbanizing areas and suggest that the local governments should consider the probable ecological risk resulting from soil erosion when enlarging and developing tourism areas.     

Predicting soil erosion hazard in Lattakia Governorate(W Syria)

The main objective of this study is to predict soil erosion in the Lattakia Governorate(WSyria)using the Water Erosion Prediction Project model(WEPP)and to compare the result with that of the RUSLE.Field survey and data collection were carried out,and 44 soil samples were analyzed.In addition,all the necessary input files were prepared for use in the WEPP model and RUSLE.Results show that more than of 80%of the locations studied experience slight to moderate erosion(less than 5 t/ha/y),whereas the rest of the locations experience severe soil erosion hazard.Moreover,the volume of runoff estimated by the WEPP model is in the range of 51e321 mm,and the R^2 between the simulated soil erosion and the predicted runoff reached 0.68.Interestingly,the R^2 between the WEPP model and RUSLE is 0.56,which indicates a good correlation between the two models.