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21.
Improving empirical prediction of plot soil erosion at the event temporal scale has both scientific and practical importance. In this investigation, 492 runoff and soil loss data from plots of different lengths, λ (11 ≤ λ ≤ 44 m), and steepness, s (14.9 ≤ s ≤ 26.0%), established at the Sparacia experimental station, in Sicily, South Italy, were used to derive a new version of Universal Soil Loss Equation (USLE)‐MM model, by only assuming a value of one for the topographic length, L, and steepness, S, factors for λ = 22 m and s = 9%, respectively. An erosivity index equal to (QREI30)b1, QR and EI30 being the runoff coefficient and the event rainfall erosivity index, respectively, with b1 > 1 was found to be an appropriate choice for the Sparacia area. The specifically developed functions for L and S did not differ appreciably from other, more widely accepted relationships (maximum differences by a factor of 1.22 for L and 1.09 for S). The new version of the USLE‐MM performed particularly well for highly erosive events, because predicted soil loss differed by not more than a factor of 1.19 from the measured soil loss for measured values of more than 100 Mg ha?1. The choice of the relationships to predict topographic effects on plot soil loss should not represent a point of particular concern in the application of the USLE‐MM in other environments. However, tests of the empirical approach should be carried out in other experimental areas in an attempt to develop analytical tools, usable at the event temporal scale, reasonably simple and of wide validity. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   
22.
Hydrological processes at the river basin influence the quality of downstream water bodies by controlling the loads of nutrients and suspended solids. Although their monitoring is important for social, economic and environmental reasons, in‐situ measurements are too expensive and thus too sparse to describe their relations. The aim of this study is to investigate the temporal relations of soil erosion in the upstream part of river basins with water quality characteristics in the downstream coastal zone, using satellite remote sensing and GIS modelling. Data from satellite missions of MODIS, SRTM and TRMM were used to describe the soil erosion factors of the Universal Soil Loss Equation in three river basins, and MERIS satellite data was used to estimate chlorophyll‐a and total suspended matter concentrations in the coastal zone of northwest Aegean Sea in Greece, where the rivers discharge. The resulting time series showed an average correlation of upstream rainfall with downstream water quality, which increased when soil erosion was introduced. Higher correlations were observed with the use of a time lag, revealing a variable delay between the three test sites. Lower correlation coefficients were observed for chlorophyll‐a, due to the sensitivity of algae to environmental conditions. The use of free of charge satellite data and easy to operate GIS models renders the findings of this work useful for coastal zone management bodies, in order to help increase aquaculture productivity, predict algal blooms and predict siltation of ports. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   
23.
Processes of soil erosion and sediment transport are strongly influenced by land use changes so the modelling of land use changes is important with respect to the simulation of soil degradation and its on‐site and off‐site consequences. The reliability of simulation results from erosion models is circumscribed by considerable spatial variation in many parameters. However, most of the currently widely used erosion models at the mesoscale are semidistributed, which leads to difficulties in incorporating a high degree of spatial information, especially land use information, so that the effects of land use changes on soil erosion have hitherto not been investigated in detail using these models. In this article, a grid‐based distributed erosion and sediment transport model is introduced, which simulates the spatial pattern of erosion and deposition rates and sediment transport processes in river channels. In this model, land use affects soil erosion through altering soil loss and influencing sediment delivery. Simulated soil erosion for events recorded in 1989 and 1996 in the Lushi basin in China was analyzed by comparing it with historical land use maps. The results indicated that even relatively minor land use changes had a significant effect on regional soil erosion rates and sediment transport to rivers. The average erosion rate increased from 1989 to 1996, after the transformation of forest to farmland. The results of the study suggest that the proposed soil erosion model can be applied in similar river basins. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   
24.
Interpreting rainfall‐runoff erosivity by a process‐oriented scheme allows to conjugate the physical approach to soil loss estimate with the empirical one. Including the effect of runoff in the model permits to distinguish between detachment and transport in the soil erosion process. In this paper, at first, a general definition of the rainfall‐runoff erosivity factor REFe including the power of both event runoff coefficient QR and event rainfall erosivity index EI30 of the Universal Soil Loss Equation (USLE) is proposed. The REFe factor is applicable to all USLE‐based models (USLE, Modified USLE [USLE‐M] and Modified USLE‐M [USLE‐MM]) and it allows to distinguish between purely empirical models (e.g., Modified USLE‐M [USLE‐MM]) and those supported by applying theoretical dimensional analysis and self‐similarity to Wischmeier and Smith scheme. This last model category includes USLE, USLE‐M, and a new model, named USLE‐M based (USLE‐MB), that uses a rainfall‐runoff erosivity factor in which a power of runoff coefficient multiplies EI30. Using the database of Sparacia experimental site, the USLE‐MB is parameterized and a comparison with soil loss data is carried out. The developed analysis shows that USLE‐MB (characterized by a Nash–Sutcliffe Efficiency Index NSEI equal to 0.73 and a root mean square error RMSE = 11.7 Mg ha?1) has very similar soil loss estimate performances as compared with the USLE‐M (NSEI = 0.72 and RMSE = 12.0 Mg ha?1). However, the USLE‐MB yields a maximum discrepancy factor between predicted and measured soil loss values (176) that is much lower than that of USLE‐M (291). In conclusion, the USLE‐MB should be preferred in the context of theoretically supported USLE type models.  相似文献   
25.
Planning soil conservation strategies requires predictive techniques at event scale because a large percentage of soil loss over a long‐time period is due to relatively few large storms. Considering runoff is expected to improve soil loss predictions and allows relation of the process‐oriented approach with the empirical one, furthermore, the effects of detachment and transport on soil erosion processes can be distinguished by a runoff component. In this paper, the empirical model USLE‐MB (USLE‐M based), including a rainfall‐runoff erosivity factor in which the event rainfall erosivity index EI30 of the Universal Soil Loss Equation (USLE) multiplies the runoff coefficient QR raised to an exponent b1 > 1 is tested by the measurements carried out for the Masse (10 plots) and Sparacia (22 plots) experimental stations in Italy. For the Masse experimental station, an exponent b1 > 1 was also estimated by tests carried out by a nozzle‐type rainfall simulator. For each experimental site in fallow conditions, the effect of the sample size of the plot soil loss measurements on the estimate of the b1 coefficient was also studied by the extraction of a fixed number N of randomly obtained pairs of the normalized soil loss and runoff coefficient. The analysis showed that the variability of b1 with N is low and that 350 pairs are sufficient to obtain a stable estimate of b1. A total of 1,262 soil loss data were used to parameterize the model both locally and considering the two sites simultaneously. The b1 exponent varied between the two sites (1.298–1.520), but using a common exponent (1.386) was possible. Using a common b1 exponent for the two experimental areas increases the practical interest for the model and allows the estimation of a baseline component of the soil erodibility factor, which is representative of the at‐site soil intrinsic and quasi‐static properties. Development of a single USLE‐MB model appears possible, and sampling other sites is advisable to develop a single USLE‐MB model for general use.  相似文献   
26.
Paolo Porto 《水文研究》2016,30(10):1551-1562
The rainfall erosivity factor R of the Universal Soil Loss Equation is a good indicator of the potential of a storm to erode soil, as it quantifies the raindrop impact effect on the soil based on storm intensity. The R‐factor is defined as the average annual value of rainfall erosion index, EI, calculated by cumulating the EI values obtained for individual storms for at least 22 years. By definition, calculation of EI is based on rainfall measurements at short time intervals over which the intensity is essentially constant, i.e. using so‐called breakpoint data. Because of the scarcity of breakpoint rainfall data, many authors have used different time resolutions (Δt = 5, 10, 15, 30, and 60 min) to deduce EI in different areas of the world. This procedure affects the real value of EI because it is strongly dependent on Δt. In this contribution, after a general overview of similar studies carried out in different countries, the relationship between EI and Δt is explored in Calabria, southern Italy. The use of 17 139 storm events collected from 65 rainfall stations allowed the calculation of EI for different time intervals ranging from 5 to 60 min. The overall results confirm that calculation of EI is dependent on time resolution and a conversion factor able to provide its value for the required Δt is necessary. Based on these results, a parametric equation that gives EI as a function of Δt is proposed, and a regional map of the scale parameter a that represents the conversion factor for converting fixed‐interval values of (EI30)Δt to values of (EI30)15 is provided in order to calculate R anywhere in the region using rainfall data of 60 min. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   
27.
祁连山石羊河上游山区土壤侵蚀的环境因子特征分析   总被引:3,自引:1,他引:2  
在GIS技术支持下, 运用通用水土流失方程USLE, 对祁连山北坡东段的哈溪林区的土壤侵蚀量及空间分布进行了模拟运算, 并定量分析了各种环境因子与土壤侵蚀之间的关系. 结果显示: 研究区平均土壤侵蚀模数为25.1 t·hm-2·a-1, 微度和轻度侵蚀面积占总面积的80%, 而强度到剧烈侵蚀产生的侵蚀量占78.3%; 各土地类型土壤侵蚀模数由高到低依次是裸地>草地>农田>灌丛>乔木林, 裸地侵蚀量占到总侵蚀量的54.9%; 乔木林和灌木林95%以上侵蚀面积属微度侵蚀区, 农田中度到剧烈侵蚀的面积比例达到35.9%, 高于草地和其他植被类型, 而草地剧烈侵蚀面积比例高于农田. 海拔高度范围与土壤流失量之间的关系与植被的海拔分布范围明显相关; 土壤平均侵蚀模数随坡度的增加而增大, 土壤侵蚀量主要分布在15°~45°的坡度范围, 不同植被覆盖下土壤流失随坡度变化的趋势可在一定程度上反映该类植被对土壤流失的防止作用.  相似文献   
28.
The Brazilian savanna (cerrado) is a large and important economic and environmental region that is experiencing significant loss of its natural landscapes due to pressures of food and energy production, which in turn has caused large increases in soil erosion. However the magnitude of the soil erosion increases in this region is not well understood, in part because scientific studies of surface runoff and soil erosion are scarce or nonexistent in the cerrado as well as in other savannahs of the world. To understand the effects of deforestation we assessed natural rainfall‐driven rates of runoff and soil erosion on an undisturbed tropical woodland classified as ‘cerrado sensu stricto denso’ and bare soil. Results were evaluated and quantified in the context of the cover and management factor (C‐factor) of the Universal Soil Loss Equation (USLE). Replicated data on precipitation, runoff, and soil loss on plots (5 × 20 m) under undisturbed cerrado and bare soil were collected for 77 erosive storms that occurred over 3 years (2012 through 2014). C‐factor was computed annually using values of rainfall erosivity and soil loss rate. We found an average runoff coefficient of ~20% for the plots under bare soil and less than 1% under undisturbed cerrado. The mean annual soil losses in the plots under bare soil and cerrado were 12.4 t ha‐1 yr‐1 and 0.1 t ha‐1 yr‐1, respectively. The erosivity‐weighted C‐factor for the undisturbed cerrado was 0.013. Surface runoff, soil loss and C‐factor were greatest in the summer and fall. Our results suggest that shifts in land use from the native to cultivated vegetation result in orders of magnitude increases in soil loss rates. These results provide benchmark values that will be useful to evaluate past and future land use changes using soil erosion models and have significance for undisturbed savanna regions worldwide. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   
29.
基于DEM的USLE土壤侵蚀方程地形因子获取与分析   总被引:1,自引:0,他引:1  
隋欣  王维芳 《测绘工程》2010,19(5):20-23
坡长和坡度是研究水土流失问题中必须要考虑的重要地形因子,坡长的空间分布特征和规律、地貌发育对坡长的影响,以及坡长与坡度之间的关系,是研究水土流失、侵蚀规律的重要条件之一。利用GIS以及相关软件为平台,在黑龙江省通河地区建立USLE水土流失方程模型,研究LS因子在水土流失中的影响以及作用,并探讨DEM数据分辨率变化对LS值的影响。  相似文献   
30.
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