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Spatio-temporal patterns of field-scale soil moisture and their implications for in situ soil moisture network design.

机译:田间土壤水分的时空格局及其对原位土壤水分网络设计的影响。

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摘要

This dissertation describes efforts to overcome the challenges in designing in situ soil moisture observation network. The surface soil moisture data collected at two spatial scales in a working field in Iowa throughout the growing seasons in 2004 to 2008 were used to describe the spatio-temporal characteristics of soil moisture at field scale. The rank stability analysis was used to identify the locations on the ground to represent the mean soil moisture at the field scale across five different growing seasons. Optimal sampling locations (OSLs), giving accurate estimates of field mean soil moisture for each season, were selected using the rank stability analysis. The results indicated that there were OSLs in the field for each growing season and for the compiled five-season, and these locations were different from each sampling season to the next, which suggested that it is not sufficient to use only one year or a few years' data to identify the soil moisture rank stable behavior using rank stability analysis. The spatial patterns of soil moisture exhibited certain consistency across multiple seasons. The OSLs all tended to be located at those locations with higher elevation. Therefore, multiple linear regression was used to predict recurring soil moisture patterns with topographic indices at optimal resolutions. A genetic algorithm was developed to select the input independent variables over a range of resolutions for multiple linear regression models. Using this approach, not only were the primary influential topographic indices to soil moisture patterns uncovered, but the most appropriate resolutions for each influential index was identified. The recurring patterns at field scale were well predicted by the combination of static topographic indices at optimal resolutions. Although the studies included in the dissertation contributed knowledge to in situ soil moisture network design, more work is required to obtain a complete scheme for implementing a ground-based observation network effectively.
机译:本文介绍了克服原位土壤水分观测网络设计难题的工作。在爱荷华州一个工作区,在2004年至2008年整个生长季节中,在两个空间尺度上收集的地表土壤水分数据用于描述田间尺度下土壤水分的时空特征。等级稳定性分析用于确定地面上的位置,以表示五个不同生长季节田间尺度上的平均土壤湿度。使用等级稳定性分析选择最佳采样位置(OSL),以给出每个季节的田间平均土壤湿度的准确估计。结果表明,每个生长季节和五个季节的田间都有OSL,并且每个采样季节到下一个采样季节的位置都不同,这表明仅使用一年或几年是不够的等级稳定性分析来确定土壤水分等级稳定性行为的多年数据。在多个季节中,土壤水分的空间格局表现出一定的一致性。 OSL都倾向于位于海拔较高的位置。因此,使用多元线性回归以最佳分辨率预测具有地形指数的重复土壤水分模式。开发了一种遗传算法来选择多个线性回归模型在一定分辨率范围内的输入独立变量。使用这种方法,不仅发现了土壤湿度模式的主要影响地形指数,而且确定了每种影响指数的最合适分辨率。通过以最佳分辨率进行静态地形指数的组合,可以很好地预测田间尺度的重复模式。尽管论文中的研究为原位土壤水分网络设计提供了知识,但仍需要做更多的工作才能获得有效实施地面观测网络的完整方案。

著录项

  • 作者

    Yang, Lingyuan.;

  • 作者单位

    Iowa State University.;

  • 授予单位 Iowa State University.;
  • 学科 Environmental Sciences.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 122 p.
  • 总页数 122
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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