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Evaluation of the portability of an EOF-based method to downscale soil moisture patterns based on topographical attributes.

机译：基于地形属性的基于EOF的方法对降低土壤水分模式的可移植性的评估。

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摘要

Soil moisture influences many hydrologic applications including agriculture, land management, and flood prediction. Most remote-sensing methods that estimate soil moisture produce coarse-resolution patterns, so methods are required to downscale such patterns to the resolutions required by these applications (e.g., 10-30 m grid cells). At such resolutions, topography is known to impact soil moisture patterns. Although methods have been proposed to downscale soil moisture based on topography, they usually require the availability of past high-resolution soil moisture patterns from the application region. The objective of this paper is to determine whether a single topographic-based downscaling method can be used at multiple locations without relying on detailed local observations. The evaluated downscaling method is developed based on empirical orthogonal function (EOF) analysis of space-time soil moisture data at a reference catchment. The most important EOFs are then estimated from topographic attributes and the associated expansion coefficients (ECs) are estimated based on the spatial-average soil moisture. To test the portability of this EOF-based method, it is developed separately using four datasets (Tarrawarra, Tarrawarra2, Cache la Poudre, and Satellite Station), and the relationships that are derived from these datasets to estimate the EOFs and ECs are compared. In addition, each of these downscaling methods is applied not only for the catchment where it was developed but also to the other three catchments. The results suggest that the EOF downscaling method performs well for the location where it is developed, but its performance degrades when applied to other catchments.
机译：土壤水分会影响许多水文应用，包括农业，土地管理和洪水预报。大多数估算土壤湿度的遥感方法会产生粗略的分辨率模式，因此需要将这些模式缩小到这些应用所需的分辨率的方法（例如10-30 m的网格单元）。在这样的分辨率下，已知地形会影响土壤湿度模式。尽管已经提出了基于地形来降低土壤湿度的方法，但是它们通常需要可从应用区域获得过去高分辨率土壤湿度模式的信息。本文的目的是确定是否可以在不依赖于详细的本地观测值的情况下，在多个位置使用基于地形的降尺度方法。基于经验性正交函数（EOF）分析参考流域的时空土壤水分数据，开发了评估的降尺度方法。然后根据地形属性估算最重要的EOF，并根据空间平均土壤湿度估算相关的膨胀系数（EC）。为了测试此基于EOF的方法的可移植性，使用四个数据集（Tarrawarra，Tarrawarra2，Cache la Poudre和Satellite Station）分别开发了该方法，并比较了从这些数据集得出的估计EOF和EC的关系。此外，这些缩小比例的方法中的每一种不仅适用于其开发所在的流域，而且还适用于其他三个流域。结果表明，EOF缩减方法在开发位置上表现良好，但将其应用于其他集水区时性能却下降。

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  • 作者

    Busch, Frederick A.;

  • 作者单位

    Colorado State University.;

  • 授予单位 Colorado State University.;
  • 学科 Engineering Civil.
  • 学位 M.S.
  • 年度 2011
  • 页码 52 p.
  • 总页数 52
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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