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首页> 外文OA文献 >Geostatistical Interpolation In The Analysis Of Spatial Distribution Of Annual Rainfall And Of Its Relationship To Altitude [interpoladores Geoestatísticos Na Análise Da Distribuição Espacial Da Precipitação Anual E De Sua Relação Com Altitude]
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Geostatistical Interpolation In The Analysis Of Spatial Distribution Of Annual Rainfall And Of Its Relationship To Altitude [interpoladores Geoestatísticos Na Análise Da Distribuição Espacial Da Precipitação Anual E De Sua Relação Com Altitude]

机译：年降水量空间分布及其与海拔高度关系的地统计插值

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The objective of this work was to quantify the contribution of the auxiliary variable elevation in the estimate of the spatial distribution of annual average rainfall in the state of São Paulo, Brazil. The statistic mean square error (MSQR) was used in two observation sets for the mean annual rainfall (1957 to 1997): a full set, with 1,027 observations, and a reduced one, with 445. Areas of rainfall concentration were clearly defined in spatial variability maps that used the full data set, indicating possible microclimates. Ordinary kriging geostatistical interpolation had a performance 82 times more accurate than that of interpolation by the inverse square of the distance when the MSQR was used as a benchmark for the full set. For the reduced set, this magnitude was of two times. The estimation errors obtained by ordinary kriging were lower in the full set, whereas those obtained by ordinary cokriging were lower in the reduced one. This indicates that these interpolators should be used for determining the spatial distribution of annual average rainfall. The use of altitude as an auxiliary variable benefits the ordinary cokriging interpolator and defines more uniform micro regions as to the spatial distribution of annual average rainfall.
机译：这项工作的目的是量化辅助变量高度对巴西圣保罗州年平均降雨量空间分布的估计。统计均方误差（MSQR）用于两个年平均降水量（1957年至1997年）的观测值：全套观测值1,027项，减少观测值的445项。在空间上明确定义了降雨集中区域使用完整数据集的可变性图，指示可能的微气候。当将MSQR用作全套基准时，普通克里金法地统计插值的性能比插值的精度高82倍。对于缩减集，此大小是两倍。普通克里金法获得的估计误差在全套中较低，而普通克里金法获得的估计误差在缩小集合中较低。这表明应使用这些插值器确定年平均降雨量的空间分布。使用海拔高度作为辅助变量有利于普通的cokriging插值器，并在年平均降雨量的空间分布方面定义了更均匀的微观区域。

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