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| Titel |
Analysis of surface soil moisture patterns in agricultural landscapes using Empirical Orthogonal Functions |
| VerfasserIn |
W. Korres, C. N. Koyama, P. Fiener, K. Schneider |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 14, no. 5 ; Nr. 14, no. 5 (2010-05-12), S.751-764 |
| Datensatznummer |
250012299
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| Publikation (Nr.) |
 copernicus.org/hess-14-751-2010.pdf |
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| Zusammenfassung |
| Soil moisture is one of the fundamental variables in hydrology, meteorology
and agriculture. Nevertheless, its spatio-temporal patterns in
agriculturally used landscapes that are affected by multiple natural
(rainfall, soil, topography etc.) and agronomic (fertilisation, soil
management etc.) factors are often not well known. The aim of this study is
to determine the dominant factors governing the spatio-temporal patterns of
surface soil moisture in a grassland and an arable test site that are
located within the Rur catchment in Western Germany. Surface soil moisture
(0–6 cm) was measured in an approx. 50×50 m grid during 14 and 17
measurement campaigns (May 2007 to November 2008) in both test sites. To
analyse the spatio-temporal patterns of surface soil moisture, an Empirical
Orthogonal Function (EOF) analysis was applied and the results were
correlated with parameters derived from topography, soil, vegetation and
land management to link the patterns to related factors and processes. For
the grassland test site, the analysis resulted in one significant spatial
structure (first EOF), which explained 57.5% of the spatial variability
connected to soil properties and topography. The statistical weight of the
first spatial EOF is stronger on wet days. The highest temporal variability
can be found in locations with a high percentage of soil organic carbon
(SOC). For the arable test site, the analysis resulted in two significant
spatial structures, the first EOF, which explained 38.4% of the spatial
variability, and showed a highly significant correlation to soil properties,
namely soil texture and soil stone content. The second EOF, which explained
28.3% of the spatial variability, is linked to differences in land
management. The soil moisture in the arable test site varied more strongly
during dry and wet periods at locations with low porosity. The method
applied is capable of identifying the dominant parameters controlling
spatio-temporal patterns of surface soil moisture without being affected by
single random processes, even in intensively managed agricultural areas. |
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