Repository logo
 

Spatial patterns from EOF/PC analysis of soil moisture and their dependence on soil, land-use, and topographic properties

Date

2005

Authors

Conklin, Summer, author
Niemann, Jeffrey D., advisor
Smith, Freeman M., committee member
Ramírez, Jorge A., committee member

Journal Title

Journal ISSN

Volume Title

Abstract

Soil moisture is a highly variable parameter in both space and time, and accurate measurements are needed in hydrology and many other disciplines. While remote sensing techniques can measure near-surface soil moisture, such measurements are available at spatial resolutions that are too coarse for most applications. Thus, downscaling methods are needed. If regional characteristics that are readily available at a finer resolution are closely related to soil moisture patterns, then those characteristics could be used to downscale observations of soil moisture from remote sensing. We hypothesize that the variability in soil moisture patterns can be described by a relatively small number of spatial structures that are related to soil texture, land-use, and topographic characteristics. To test this hypothesis, an empirical orthogonal function and principal component (EOF/PC) analysis has been conducted using soil moisture data from the Southern Great Plains field campaign of 1997. This dataset contains 16 days of remotely sensed data on a 0.64 km2 grid over nearly 10,000 km2. From the EOF/PC analysis of spatial soil moisture anomalies, we identify one spatial structure (EOF) that explains 61% of the total variance, and find that three such structures explain 87% of the variance. To identify the regional characteristics that are most influential in determining soil moisture patterns, each of these EOFs has been compared to regional characteristics using a correlation analysis. The primary EOF is most highly correlated with the percent sand in the soil. Similar analyses were conducted for wet, average, and dry days, and the role of percent sand is greatest for wet days. As the soil becomes more dry, percent clay becomes more important than percent sand. We have also considered temporal soil moisture anomalies, which identify locations with more or less dynamic soil moisture. The spatial patterns for the temporal anomalies are more complex than those for the spatial anomalies. One EOF is only able to explain 50% of the total variance. Percent sand is also related to the primary EOF for the temporal anomalies, but percent clay becomes unimportant. Topographic characteristics are usually not important over the range of scales we consider, although elevation may play a role in identifying locations with more dynamic soil moisture.

Description

Covers not scanned.
Print version deaccessioned 2022.

Rights Access

Subject

Soil moisture -- Measurement -- Remote sensing

Citation

Associated Publications