Soil moisture in the shallow subsurface is a primary hydrologic state governing
land-atmosphere interaction at various scales. The primary objectives of this study are to
model soil moisture in the root zone in a distributed manner and determine scaling
properties of surface soil moisture using passive microwave remote sensing. The study
was divided into two parts. For the first study, a root zone soil moisture assessment tool
(SMAT) was developed in the ArcGIS platform by fully integrating a one-dimensional
vadose zone hydrology model (HYDRUS-ET) with an ensemble Kalman filter (EnKF)
data assimilation capability. The tool was tested with dataset from the Southern Great
Plain 1997 (SGP97) hydrology remote sensing experiment. Results demonstrated that
SMAT displayed a reasonable capability to generate soil moisture distribution at the
desired resolution at various depths of the root zone in Little Washita watershed during
the SGP97 hydrology remote sensing experiment. To improve the model performance,
several outstanding issues need to be addressed in the future by: including "effective"
hydraulic parameters across spatial scales; implementing subsurface soil properties data
bases using direct and indirect methods; incorporating appropriate hydrologic processes across spatial scales; accounting uncertainties in forcing data; and preserving
interactions for spatially correlated pixels.
The second study focused on spatial scaling properties of the Polarimetric
Scanning Radiometer (PSR)-based remotely sensed surface soil moisture fields in a
region with high row crop agriculture. A wavelet based multi-resolution technique was
used to decompose the soil moisture fields into larger-scale average soil moisture fields
and fluctuations in horizontal, diagonal and vertical directions at various resolutions. The
specific objective was to relate soil moisture variability at the scale of the PSR footprint
(800 m X 800 m) to larger scale average soil moisture field variability. We also
investigated the scaling characteristics of fluctuation fields among various resolutions.
The spatial structure of soil moisture exhibited linearity in the log-log dependency of the
variance versus scale-factor, up to a scale factor of -2.6 (6100 m X 6100 m) irrespective
of wet and dry conditions, whereas dry fields reflect nonlinear (multi-scaling) behavior
at larger scale-factors.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/4881 |
| Date | 25 April 2007 |
| Creators | Das, Narendra N. |
| Contributors | Mohanty, Binayak P. |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Thesis, text |
| Format | 1044409 bytes, electronic, application/pdf, born digital |
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