TR32-Database: Database of Transregio 32

[693] - Patterns and Scaling Properties of Surface Soil Moisture in an Agricultural Landscape: An Ecohydrological Modeling Study

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Citation
Korres, W., Reichenau, T. G., Schneider, K., 2013. Patterns and Scaling Properties of Surface Soil Moisture in an Agricultural Landscape: An Ecohydrological Modeling Study. Journal of Hydrology, 498, 89 - 102. DOI: 10.1016/j.jhydrol.2013.05.050.
Identification
Title(s):Main Title: Patterns and Scaling Properties of Surface Soil Moisture in an Agricultural Landscape: An Ecohydrological Modeling Study
Description(s):Abstract: Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m_2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale patterns that are induced by soil properties are superimposed by the small scale land use pattern and the resulting small scale variability of evapotranspiration. However, this influence decreases at larger spatial scales. Most precipitation events cause temporarily higher surface soil moisture autocorrelation lengths at all spatial scales for a short time even beyond the autocorrelation lengths induced by soil properties. The relation of daily spatial variance to the spatial scale of the analysis fits a power law scaling function, with negative values of the scaling exponent, indicating a decrease in spatial variability with increasing spatial resolution. High evapotranspiration rates cause an increase in the small scale soil moisture variability, thus leading to large negative values of the scaling exponent. Utilizing a multiple regression analysis, we found that 53% of the variance of the scaling exponent can be explained by a combination of an independent LAI parameter and the antecedent precipitation.
Identifier(s):DOI: 10.1016/j.jhydrol.2013.05.050
Responsible Party
Creator(s):Author: Wolfgang Korres
Author: Tim G. Reichenau
Author: Karl Schneider
Publisher:Elsevier
Topic
TR32 Topic:Other
Subject(s):CRC/TR32 Keywords: Catchment Hydrology, Soil Moisture, Ecohydrological Crop Model, Pattern, Scale, Autocorrelation
File Details
File Name:2013_Korres_JoH.pdf
Data Type:Text
Size(s):14 Pages
File Size:3746 kB (3.658 MB)
Date(s):Date Accepted: 2013-05-31
Available: 2013-06-07
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:50.8728952
East:6.4582092
South:50.8620614
West:6.4410431
Measurement Region:Ellebach
Measurement Location:Selhausen
Specific Informations - Publication
Status:Published
Review:PeerReview
Year:2013
Type:Article
Article Type:Journal
Source:Journal of Hydrology
Volume:498
Number Of Pages:14
Page Range:89 - 102
Metadata Details
Metadata Creator:Wolfgang Korres
Metadata Created:2013-12-03
Metadata Last Updated:2013-12-03
Subproject:C3
Funding Phase:2
Metadata Language:English
Metadata Version:V40
Dataset Metrics
Page Visits:154
Metadata Downloads:0
Dataset Downloads:5
Dataset Activity
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