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首页> 外文期刊>Journal of Water Resource and Protection >Uncertainty Analysis of Interpolation Methods in Rainfall Spatial Distribution–A Case of Small Catchment in Lyon
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Uncertainty Analysis of Interpolation Methods in Rainfall Spatial Distribution–A Case of Small Catchment in Lyon

机译:降雨空间分布插值方法的不确定性分析-以里昂小流域为例

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摘要

Quantification of spatial and temporal patterns of rainfall is an important step toward developing regional water sewage models, the intensity and spatial distribution of rainfall can affect the magnitude and duration of water sewage. However, this input is subject to uncertainty, mainly as a result of the interpolation method and stochastic error due to the random nature of rainfall. In this study, we analyze some rainfall series from 30 rain gauges located in the Great Lyon area, including annual, month, day and intensity of 6mins, aiming at improving the understanding of the major sources of variation and uncertainty in small scale rainfall in-terpolation in different input series. The main results show the model and the parameter of Kriging should be different for the different rainfall series, even if in the same research area. To the small region with high den-sity of rain gauges (15km2), the Kriging method superiority is not obvious, IDW and the spline interpolation result maybe can be better. The different methods will be suitable for the different research series, and it must be determined by the data series distribution.
机译:降雨时空格局的量化是发展区域污水模型的重要一步,降雨的强度和空间分布会影响污水的数量和持续时间。但是,此输入存在不确定性,这主要是由于内插法和降雨随机性导致的随机误差的结果。在这项研究中,我们分析了位于大里昂地区的30个雨量计的一些降雨序列,包括年,月,日和6分钟的强度,旨在增进对小规模降雨的主要变化和不确定性来源的认识。在不同的输入序列中进行插值。主要结果表明,即使在同一研究区域内,不同降雨序列的克里格模型和参数也应不同。对于雨量计高密度的小区域(15 km2),克里格方法的优势并不明显,IDW和样条插值结果可能会更好。不同的方法将适用于不同的研究系列,并且必须由数据系列的分布来确定。

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