TR32-Database: Database of Transregio 32

[1036] - Spatio-temporal soil moisture patterns - a meta-analysis using plot to catchment scale data

All available metadata of the dataset are listed below. Some features are available, e.g. download of dataset or additional description file.

Features
Citation
Korres, W., Reichenau, T. G., Fiener, P., Koyama, C. N., Bogena, H., Cornelissen, T., Baatz, R., Herbst, M., Diekkrüger, B., Vereecken, H., Schneider, K., 2014. Spatio-temporal soil moisture patterns - a meta-analysis using plot to catchment scale data. Journal of Hydrology, 1 - 40.
Identification
Title(s):Main Title: Spatio-temporal soil moisture patterns - a meta-analysis using plot to catchment scale data
Description(s):Abstract: Soil moisture is a key variable in hydrology, meteorology and agriculture. It is influenced by many factors, such as topography, soil properties, vegetation type, management, and meteorological conditions. The role of these factors in controlling the spatial patterns and temporal dynamics is often not well known. The aim of the current study is to analyze spatio-temporal soil moisture patterns acquired across a variety of land use types, on different spatial scales (plot to meso-scale catchment) and with different methods (point measurements, remote sensing, and modelling). We apply a uniform set of tools to determine method specific effects, as well as site and scale specific controlling factors. Spatial patterns of soil moisture and their temporal development were analyzed using nine different datasets from the Rur catchment in Western Germany. For all datasets we found negative linear relationships between the coefficient of variation and the mean soil moisture, indicating lower spatial variability at higher mean soil moisture. For a forest sub-catchment compared to cropped areas, the offset of this relationship was larger, with generally larger variability at similar mean soil moisture values. Using a geostatistical analysis of the soil moisture patterns we identified three groups of datasets with similar values for sill and range of the theoretical variogram: (i) modelled and measured datasets from the forest sub-catchment (patterns mainly influenced by soil properties and topography), (ii) remotely sensed datasets from the cropped part of the Rur catchment (patterns mainly influenced by the land-use structure of the cropped area), and (iii) modelled datasets from the cropped part of the Rur catchment (patterns mainly influenced by large scale variability of soil properties). A fractal analysis revealed that all analyzed soil moisture patterns showed a multifractal behavior, with at least one scale break and generally high fractal dimensions. Corresponding scale breaks were found between different datasets. The factors causing these scale breaks are consistent with the findings of the geostatistical analysis. Furthermore, the joined analysis of the different datasets showed that small differences in soil moisture dynamics, especially at the upper and lower bounds of soil moisture (at maximum porosity and wilting point of the soils) can have a large influence on the soil moisture patterns and their autocorrelation structure. Depending on the prevalent type of land use and the time of year, vegetation causes a decrease or an increase of spatial variability in the soil moisture pattern.
Responsible Party
Creator(s):Author: Wolfgang Korres
Author: Tim G. Reichenau
Author: Peter Fiener
Author: Christian N. Koyama
Author: Heye Bogena
Author: Thomas Cornelissen
Author: Roland Baatz
Author: Michael Herbst
Author: Bernd Diekkrüger
Author: Harry Vereecken
Author: Karl Schneider
Publisher:Elsevier
Topic
TR32 Topic:Soil
Subject(s):CRC/TR32 Keywords: Soil Moisture, Pattern Analysis
Topic Category:Enviroment
File Details
File Name:Korres et al. (2014, submitted to JoH).pdf
Data Type:Text
File Size:4516 kB (4.41 MB)
Date(s):Date Submitted: 2014-09-04
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:In Process
Constraints
Download Permission:OnlyOwnSubproject
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
Geographic
North:-no map data
East:-
South:-
West:-
Measurement Region:RurCatchment
Measurement Location:--RurCatchment--
Specific Informations - Publication
Status:Submitted
Review:NoPeerReview
Year:2014
Type:Article
Article Type:Journal
Source:Journal of Hydrology
Page Range:1 - 40
Metadata Details
Metadata Creator:Sabrina Esch
Metadata Created:2014-09-05
Metadata Last Updated:2014-09-08
Subproject:C3
Funding Phase:2
Metadata Language:English
Metadata Version:V40
Dataset Metrics
Page Visits:153
Metadata Downloads:0
Dataset Downloads:1
Dataset Activity
Features