使用校准曲线数和径流驱动的USLE模型估算Sparacia(西西里岛,意大利南部)地块的事件土壤流失量

IF 2.9 3区 地球科学 Q1 Environmental Science
Vincenzo Pampalone, Dario Autovino, Maria Angela Serio, Vincenzo Bagarello, Vito Ferro
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引用次数: 0

摘要

自然资源保护局(NRCS)-曲线数(CN)方法最初被提出用于预测中小流域的径流,但它也被用于侵蚀地块的规模。在这种情况下,由于尺度效应等因素影响实验CN值,存在不确定性。在这项研究中,通过使用在Sparacia侵蚀地块(意大利南部西西里岛)收集的数据,分析了CN方法在再现地块径流方面的可靠性,这些地块具有不同的大小和陡峭度。本研究旨在测试在通用土壤流失方程(USLE)型模型中使用模拟径流的可能性,将径流作为侵蚀因子中的一项。该分析指出,CN方法的初始抽象比的实验确定值很低(0.0001)。对于每种样地类型(即固定长度和陡峭度),对三个降雨范围(所有数据、降雨深度小于中位数和超过中位数)、两种校准方法(最小二乘和中位数)和三个数据集(所有数据、interrill和rill)的18种组合进行了校准。对于降雨深度小于中位数的数据,系统地产生了最好的CN模型拟合。最小二乘校准方法通常比中位数校准方法稍好。结果表明,CN方法仅对产生细纹的事件有效。CN值一般随样地坡度增大而增大,随样地长度增大而减小。各样地类型的CN随降雨前土壤湿度的增加呈增加趋势,但湿度和降雨深度对CN方差的贡献率较小(19.5% ~ 41%)。最后,发现采用CN方法模拟径流的USLE-MB可以令人满意地预测(相对标准误差= 0.69,Nash和Sutcliffe效率指数= 0.54)由于Sparacia站记录的降雨深度较高而导致的沟间和沟间同时侵蚀造成的事件土壤流失。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Use of the Calibrated Curve Number and a Runoff-Driven USLE Model to Estimate Event Soil Loss From Sparacia (Sicily, Southern Italy) Plots

Use of the Calibrated Curve Number and a Runoff-Driven USLE Model to Estimate Event Soil Loss From Sparacia (Sicily, Southern Italy) Plots

The Natural Resources Conservation Service (NRCS)-curve number (CN) method was originally proposed to predict runoff on small and midsize catchments, but it has also been used at the scale of erosion plots. In this case, uncertainties exist with reference to the factors, for example, scale effects, affecting the experimental CN values. In this study, the reliability of the CN method in reproducing plot runoff is analysed by using data collected at the Sparacia erosion plots (Sicily, Southern Italy), which are characterised by different sizes and steepness. This investigation aimed to test the possibility of using simulated runoff within universal soil loss equation (USLE)-type models, including runoff as a term in the erosivity factor. This analysis pointed out that the experimentally determined value of the initial abstraction ratio of the CN method was very low (0.0001). For each plot type (i.e., fixed length and steepness), the calibration was performed for 18 combinations of three rainfall ranges (all data, rainfall depth less than the median, and exceeding the median), two calibration approaches (least-squares and median value) and three datasets (all data, interrill, and rill). The best CN model fit was systematically produced for data with rainfall depth less than the median. The least-squares calibration approach generally performed slightly better than the median value one. Results showed that the CN method can be considered effective only for events producing rills. The CN values generally increased with plot steepness and decreased as plot length increased. For each plot type, CN tendentially increased for increasing soil moisture before the rainfall event, but moisture and rainfall depth were able to explain a minor part (from 19.5% to 41%) of CN variance. Finally, the USLE-MB that incorporates runoff simulated by the CN method was found to satisfactorily predict (relative standard error = 0.69, Nash and Sutcliffe Efficiency Index = 0.54) event soil loss caused by simultaneous interrill and rill erosion due to the higher rainfall depths recorded at the Sparacia station.

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来源期刊
Hydrological Processes
Hydrological Processes 环境科学-水资源
CiteScore
6.00
自引率
12.50%
发文量
313
审稿时长
2-4 weeks
期刊介绍: Hydrological Processes is an international journal that publishes original scientific papers advancing understanding of the mechanisms underlying the movement and storage of water in the environment, and the interaction of water with geological, biogeochemical, atmospheric and ecological systems. Not all papers related to water resources are appropriate for submission to this journal; rather we seek papers that clearly articulate the role(s) of hydrological processes.
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