TR32-Database: Database of Transregio 32

[744] - Analysis of surface soil moisture patterns in agricultural landscapes using Empirical Orthogonal Functions

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Citation
Korres, W., Koyama, C. N., Fiener, P., Schneider, K., 2010. Analysis of surface soil moisture patterns in agricultural landscapes using Empirical Orthogonal Functions. Hydrology and Earth System Sciences, 14, 751 - 764. DOI: 10.5194/hess-14-751-2010.
Identification
Title(s):Main Title: Analysis of surface soil moisture patterns in agricultural landscapes using Empirical Orthogonal Functions
Description(s):Abstract: 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 spatiotemporal 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. 50×50m 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.
Identifier(s):DOI: 10.5194/hess-14-751-2010
Responsible Party
Creator(s):Author: Wolfgang Korres
Author: Christian N. Koyama
Author: Peter Fiener
Author: Karl Schneider
Publisher:European Geosciences Union
Topic
TR32 Topic:Soil
Subject(s):CRC/TR32 Keywords: Soil Moisture, Agriculture, Hydrology
File Details
File Name:2010_Korres_HESS.pdf
Data Type:Text
Size(s):14 Pages
File Size:417 kB (0.407 MB)
Date(s):Date Accepted: 2010-04-14
Issued: 2010-05-12
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
Constraints
Download Permission:OnlyTR32
General Access and Use Conditions:For internal use only
Access Limitations:For internal use only
Licence:TR32DB Data policy agreement
Geographic
North:50.8737076
East:6.4582521
South:50.8628740
West:6.4410860
Measurement Region:Ellebach
Measurement Location:Selhausen
Specific Informations - Publication
Status:Published
Review:PeerReview
Year:2010
Type:Article
Article Type:Journal
Source:Hydrology and Earth System Sciences
Volume:14
Number Of Pages:14
Page Range:751 - 764
Metadata Details
Metadata Creator:Wolfgang Korres
Metadata Created:2013-12-02
Metadata Last Updated:2013-12-02
Subproject:C3
Funding Phase:1
Metadata Language:English
Metadata Version:V40
Dataset Metrics
Page Visits:208
Metadata Downloads:0
Dataset Downloads:0
Dataset Activity
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