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Spatial and temporal characteristics of soil moisture in an intensively monitored agricultural field (OPE3)

机译:在集约化监控的农田中土壤水分的时空特征(OPE3)

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A four-dimensional dataset of soil moisture from the Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) field has been analyzed for temporal and spatial characteristics. Knowledge of soil moisture patterns improves the understanding of processes in the land surface system and helps to identify these processes for use in modeling research. Statistics describing the soil moisture distribution in time showed a lower temporal variability at points in deeper soil layers, except for the deep sensors which were influenced by subsurface flow, where a high temporal variability could be found. The temporal autocorrelation increased with depth in the soil profile. The cross correlation between time series of soil moisture at different points in space decreased with depth and was more variable in deeper soil layers. For the spatial pattern of soil moisture, geostatistical information was extracted from variograms. The evolution of the spatial patterns was dependent on the soil moisture state. In the upper layer, the spatial variability and range increased with increasing soil moisture, while the opposite was found for deeper layers. For deeper layers, the range was mostly limited due to the complex hydrogeology. In this paper, all analyses were related to the needs in modeling and assimilation practices. (c) 2006 Elsevier B.V. All rights reserved.
机译:分析了来自经济和环境优化优化生产投入(OPE3)领域的土壤水分的三维数据集的时空特征。了解土壤湿度模式可以提高对陆地表面系统过程的了解,并有助于识别这些过程以用于建模研究。描述土壤水分及时分布的统计数据表明,深层土壤中各个点的时间变化性较低,但受地下流量影响的深层传感器除外,在地下传感器中存在较高的时间变化性。时间自相关随土壤剖面深度的增加而增加。空间中不同点的土壤水分时间序列之间的相互关系随着深度的增加而减小,而在较深的土壤层中变化更大。对于土壤水分的空间格局,从变异函数中提取了地统计信息。空间格局的演变取决于土壤的水分状态。在上层,空间变异性和范围随土壤湿度的增加而增加,而在较深层则相反。对于较深的层,由于复杂的水文地质,范围大多受到限制。在本文中,所有分析都与建模和同化实践的需求有关。 (c)2006 Elsevier B.V.保留所有权利。

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