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首页> 外文期刊>Hydrology and Earth System Sciences >Mapping rainfall erosivity at a regional scale: a comparison of interpolation methods in the Ebro Basin (NE Spain)
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Mapping rainfall erosivity at a regional scale: a comparison of interpolation methods in the Ebro Basin (NE Spain)

机译:在区域尺度上绘制降雨侵蚀力图:埃布罗盆地内插方法的比较(西班牙东北)

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摘要

Rainfall erosivity is a major causal factor of soil erosion, and it is included in many prediction models. Maps of rainfall erosivity indices are required for assessing soil erosion at the regional scale. In this study a comparison is made between several techniques for mapping the rainfall erosivity indices: i) the RUSLE R factor and ii) the average EI30 index of the erosive events over the Ebro basin (NE Spain). A spatially dense precipitation data base with a high temporal resolution (15 min) was used. Global, local and geostatistical interpolation techniques were employed to produce maps of the rainfall erosivity indices, as well as mixed methods. To determine the reliability of the maps several goodness-of-fit and error statistics were computed, using a cross-validation scheme, as well as the uncertainty of the predictions, modeled by Gaussian geostatistical simulation. All methods were able to capture the general spatial pattern of both erosivity indices. The semivariogram analysis revealed that spatial autocorrelation only affected at distances of similar to 15 km around the observatories. Therefore, local interpolation techniques tended to be better overall considering the validation statistics. All models showed high uncertainty, caused by the high variability of rainfall erosivity indices both in time and space, what stresses the importance of having long data series with a dense spatial coverage.
机译:降雨侵蚀力是土壤侵蚀的主要因果关系,许多预测模型都包含了降雨侵蚀力。需要降雨侵蚀力指数地图来评估区域尺度的土壤侵蚀。在这项研究中,比较了几种用于绘制降雨侵蚀力指数的技术:i)RUSLE R因子,ii)埃布罗盆地(西班牙东北)侵蚀事件的平均EI30指数。使用了具有高时间分辨率(15分钟)的空间密集的降水数据库。使用全球,局部和地统计插值技术生成降雨侵蚀力指数图以及混合方法。为了确定地图的可靠性,使用了交叉验证方案,并通过高斯地统计模拟对预测的不确定性进行了计算,得出了一些拟合优度和误差统计信息。所有方法都能够捕获两个侵蚀指数的一般空间格局。半变异函数分析表明,空间自相关仅在天文台周围约15 km的距离上受到影响。因此,考虑到验证统计信息,局部插值技术总体上趋于更好。所有模型都显示出高度不确定性,这是由于降雨侵蚀力指数在时间和空间上的高度可变性所引起的,这强调了拥有长数据序列和密集空间覆盖的重要性。

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