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Spatial variability of rainfall on a sub-kilometre scale

机译:亚千米尺度上降雨的空间变异性

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The variability of rainfall in space and time is an essential driver of many processes in nature but little is known about its extent on the sub-kilometre scale, despite many agricultural and environmental experiments on this scale. A network of 13 tipping-bucket rain gauges was operated on a 1.4 km(2) test site in southern Germany for four years to quantify spatial trends in rainfall depth, intensity, erosivity, and predicted runoff. The random measuring error ranged from 10% to 0.1% in case of 1 mm and 100 mm rainfall, respectively. The wind effects could be well described by the mean slope of the horizon at the stations. Except for one station, which was excluded from further analysis, the relative differences due to wind were in maximum +/-5%. Gradients in rainfall depth representing the 1-km(2) scale derived by linear regressions were much larger and ranged from 1.0 to 15.7 mm km(-1) with a mean of 4.2 mm km(-1) (median 3.3 mm km(-1)). They mainly developed during short bursts of rain and thus gradients were even larger for rain intensities and caused a variation in rain erosivity of up to 255% for an individual event. The trends did not have a single primary direction and thus level out on the long term, but for short-time periods or for single events the assumption of spatially uniform rainfall is invalid on the sub-kilometre scale. The strength of the spatial trend increased with rain intensity. This has important implications for any hydrological or geomorphologic process sensitive to maximum rain intensities, especially when focusing on large, rare events. These sub-kilometre scale differences are hence highly relevant for environmental processes acting on short-time scales like flooding or erosion. They should be considered during establishing, validating and application of any event-based runoff or erosion model.
机译:降雨在空间和时间上的变化是自然界中许多过程的重要驱动因素,但是尽管在这一规模上进行了许多农业和环境实验,但对亚公里尺度的降雨程度知之甚少。在德国南部的一个1.4 km(2)测试地点运行了13个of斗式雨量计网络,历时四年,以量化降雨深度,强度,侵蚀力和预测径流量的空间趋势。在1 mm和100 mm降雨的情况下,随机测量误差的范围分别为10%至0.1%。风的影响可以用测站的地平线平均斜率很好地描述。除了一个站(不包括在进一步分析中)之外,由于风而引起的相对差异最大为+/- 5%。通过线性回归得出的代表1-km(2)尺度的降雨深度梯度要大得多,范围从1.0到15.7 mm km(-1),平均值为4.2 mm km(-1)(中位数为3.3 mm km(- 1))。它们主要是在短时暴雨期间形成的,因此降雨强度的梯度甚至更大,并导致单个事件的降雨侵蚀力变化高达255%。趋势没有单一的主要方向,因此从长期来看会趋于平稳,但是对于短期或单个事件,在亚公里尺度上假设空间均匀降雨是无效的。空间趋势强度随降雨强度的增加而增加。这对任何对最大降雨强度敏感的水文或地貌过程都具有重要意义,尤其是在关注大型罕见事件时。因此,这些亚公里尺度的差异与在短期尺度(例如洪水或侵蚀)上起作用的环境过程高度相关。在建立,验证和应用任何基于事件的径流或侵蚀模型时,都应考虑它们。

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