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 1:250000 scale and grid themes for the USLE K and C factors.It is note worthy that USLE K can be obtained by adding the K factor as an attribute to a soil theme‘s table.The C 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 the C 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.     

基于地形指数的砒砂岩黄土区土壤侵蚀分析

地形是土壤侵蚀进程的重要控制因子,在土壤侵蚀评价中发挥着重要作用.基于地形起伏表达构建了地形指数,结合降雨侵蚀力和植被盖度等建立了基于地形指数的土壤侵蚀方程,并分析了内蒙古自治区鄂尔多斯市北部十大孔兑砒砂岩黄土区1985-2018年土壤侵蚀时空变化特征.结果 表明:(1)研究区多年土壤侵蚀模数整体有下降趋势但变化差异不...     

Testing assumptions and procedures to empirically predict bare plot soil loss in a Mediterranean environment

Empirical prediction of soil erosion has both scientific and practical importance. This investigation tested USLE and USLE‐based procedures to predict bare plot soil loss at the Sparacia area, in Sicily. Event soil loss per unit area, A_e, did not vary appreciably with plot length, λ, because the decrease in runoff with λ was offset by an increase in sediment concentration. Slope steepness, s, had a positive effective on A_e, and this result was associated with a runoff coefficient that did not vary appreciably with s and a sediment concentration generally increasing with s. Plot steepness did not have a statistically detectable effect on the calculations of the soil erodibility factor of both the USLE, K, and the USLE‐M, K_UM, models, but a soil‐independent relationship between K_UM and K was not found. The erosivity index of the USLE‐MM model performed better than the erosivity index of the Central and Southern Italy model. In conclusion, the importance of an approach allowing soil loss predictions that do not necessarily increase with λ was confirmed together with the usability of already established and largely applied relationships to predict steepness effects. Soil erodibility has to be determined with reference to the specific mathematical scheme and conversion between different schemes seems to need taking into account the soil characteristics. The USLE‐MM shows promise for further developments. The evolutionary concept applied in the development of the USLE should probably be rediscovered to improve development of soil erosion prediction tools. Copyright © 2014 John Wiley & Sons, Ltd.     

Prediction reliability,quantitative differences and spatial variations of erosion models for long-range petroleum and gas infrastructure

The main goal of this study was to assess the prediction reliability, the quantitative differences and the spatial variations of the Morgan––Morgan–Finney (MMF) and the Universal Soil Loss Equation (USLE) erosion prediction models along the 442-km-long and 44-m-wide Right-of-Way of Baku–Tbilisi–Ceyhan oil and South Caucasus gas pipelines. USLE performed better than MMF erosion model by the accurate prediction of 61% of erosion occurrences. Paired-samples T-test with p-value less than 0.05 and bivariate correlation with the Pearson's correlation coefficient equal to 0.23 showed that the predictions of these two models were significantly different. MMF model revealed more clustered patterns of predicted critical erosion classes with a soil loss of more than 10 ton/ha/year in particular ranges of pipelines rather than USLE model with the widespread spatial distribution. The average coefficients of variation of predicted soil loss rates by these models and the number of accurately predicted erosion occurrences within the geomorphometric elements of terrain, vegetation cover and landuse categories were larger in the USLE model. This supported the hypothesis that larger spatial variations of erosion prediction models can contribute to the better soil loss prediction performance and reliability of erosion prediction models.     

通用土壤流失方程最新研究改进分析

通用土壤流失方程(USLE)是水动力土壤侵蚀研究领域应用广泛的经验模型。其结构简单,所需输入数据量少,计算结果可满足一定精度下,土壤侵蚀预测的要求。模型的改进使其应用范围扩大,适用性增强,计算精度提高。通用土壤流失方程的发展趋势:其一,传统方法,不改变模型的结构,通过引进合理的新参数或优化参数的取值来提高模型的预测能力;其二,非传统方法,通过模糊逻辑或人工神经网络方法来改变模型的结构,使土壤侵蚀影响因子的确定更加灵活合理,土壤流失量的计算结果更加精确可信。     

Application of the USLE in a Savannah Environment: Comparative Experiences from East and West Africa

The use of empirical models for predicting erosion hazard in Africa is widespread. One of the most commonly used models is the Universal Soil Loss Equation (USLE). This paper explores the applicability of the USLE in the East and West African Savannah environments, using both primary and secondary data. The results show that the USLE can be applied to Savannah conditions if some level of instrumentation is provided to enable model calibration and validation. The rainfall erosivity factor (R) is one variable which is calculated differently in both the East and the West African Savannah, reflecting differences in the storm characteristics between the two regions. The soil erodibility factor (K) is applied to cultivated soils with relatively high organic matter but does not adequately predict soil loss if the soils have large quantities of stone cover or if they exhibit surface sealing properties. The topographic factors (LS) are transferable, but in some parts of the Savannah, very steep slopes are cultivated, limiting the accuracy of the LS factor. The crop and management factor (C) is applicable for single stand crops, but more studies are required to develop C factors for multiple cropping and rangelands as these are more prevalent in the Savannah. The conservation practices factors (P) as described in the USLE routines do not adequately cater for soil conservation structures found in Africa, such as trash lines and stone lines. Thus, local indices need to be developed. In general, the USLE tends to underestimate soil erosion in East Africa while overestimating it in the West African Savannah. User‐friendly Geographical Information Systems (GIS) applications that depict the uncertainty of model estimates should be explored in the future.     

RUNOFF-ENERGY FACTORS FORMUSLE SEDIMENT-YIELD MODEL FOR SURFACE MINES

1INTRODUCTIONSediment-yieldestimatesarerequiredforsurfacec0al-minepermitsunderFederalandStatelaws-Estimatesareneededfordeterminingtheimpactsofminingandreclamationduringmine0Peration,fordiversi0nandsmallimpoundmentdesigns,andforsizingsedimentpondstocontrolsedimenttransporteddownstfeam0faproposedminesite.Technologiesavailablef0rsediment-yieldestimationsincludetheUniversalSoilLossEquati0n(USLE,WischmierandSmith,l978);theWaterErosionPredictionPr0ject(WEPP,FlanaganandLivingst0n,l995),…     

Dynamics and hotspots of soil erosion and management scenarios of the Central Rift Valley of Ethiopia

Most of the lowland in the central rift valley of Ethiopia is arid or semiarid and in degradation,with frequent occurrence of droughts.Soil erosion by water during the rainy season is a serious problem...     

Rill characteristics and sediment transport as a function of slope length during a storm event on loess soil

On the basis of detailed rill surveys carried out on bare plots of different lengths at slopes of 12 per cent, basic rill parameters were derived. Rill width and maximum depth increased with plot length, whereas rill amount and cross‐sectional area, expressed per unit length, remained similar. On smaller plots, all rills were connected in a continuous transport system reaching the plot outlet, whilst on larger plots (10 and 20 m long) part of the rills ended with a deposition areas inside the plots. Amounts of erosion, calculated from rill volume and soil bulk density, were compared with soil loss measured at the plot outlets. On plots 10 and 20 m long, erosion estimated from volume of all rills was larger than measured soil loss. The latter was larger than erosion estimated from volume of contributing rills. To identify contributing soil loss area on these plots, two methods were applied: (i) ratio of total soil loss to maximum soil loss per unit area, and (ii) partition of plot area according to the ratio of contributing to total rill volume. Both methods resulted in similar areas of 21·8–23·5 m² for the plot 10 m long and 31·2 m² for the plot 20 m long. Identification of contributing areas enabled rill (5·9 kg m^?2) and interrill (2·6 kg m^?2) erosion rate to be calculated, the latter being very close to the value predicted from the Universal Soil Loss Equation. Although rill and interrill rates seemed to be similar on all plots, their ratio increased slightly with plot length. Application of this ratio to compute slope length factor of the Revised Universal Soil Loss Equation resulted in similar values to those predicted with the model. The achieved balance of soil loss suggested that all the sediment measured at the plot outlet originated from contributing rills and associated contributing rill areas. The results confirmed the utility of different plot lengths as a research tool for analysing the dynamic response of soil to rainfall–runoff. Copyright © 2005 John Wiley & Sons, Ltd.