Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 4.256 IF 4.256
  • IF 5-year value: 4.819 IF 5-year 4.819
  • CiteScore value: 4.10 CiteScore 4.10
  • SNIP value: 1.412 SNIP 1.412
  • SJR value: 2.023 SJR 2.023
  • IPP value: 3.97 IPP 3.97
  • h5-index value: 58 h5-index 58
  • Scimago H index value: 99 Scimago H index 99
Discussion papers
https://doi.org/10.5194/hess-2018-396
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2018-396
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 17 Sep 2018

Research article | 17 Sep 2018

Review status
This discussion paper is a preprint. It has been under review for the journal Hydrology and Earth System Sciences (HESS). The manuscript was not accepted for further review after discussion.

Exploring hydrological similarity during soil moisture recession periods using time dependent variograms

Mirko Mälicke1, Sibylle K. Hassler1, Markus Weiler2, Theresa Blume3, and Erwin Zehe1 Mirko Mälicke et al.
  • 1Institute for Water and River Basin Management, Karlsruhe Institute of Technology (KIT), Germany
  • 2Hydrology, Faculty of Environment and Natural Resources, University of Freiburg, Germany
  • 3GFZ German Research Centre for Geosciences, Section 5.4 Hydrology, Germany

Abstract. This study proposes a new method for identifying temporally stable spatial patterns in soil moisture. Soil moisture patterns during rainfall-driven wetting conditions and during radiation-driven drying essentially reflect different processes with specific underlying controls. Consequently we expect that these patterns exhibit different covariance structures, and their spatial analysis should be separated accordingly. More specifically we hypothesize that: (H1): An ensemble of distributed soil moisture observations will converge to a rank-stable configuration during long-term drying periods and re-organize to stable ranks after disturbances; (H2): Variograms of these soil moisture ranks converge towards a stable configuration during drying periods, reflecting the covariance of the underlying time-invariant controls. These hypotheses were tested using soil moisture measurements which were recorded within the CAOS research unit in Luxembourg. We found evidence of stable rank configurations for time spans of several weeks. During rainfall events, these stable ranks were disturbed but later reorganized into the same pre-event configuration. Coupling time-shifting variograms with a density-based clustering algorithm enabled us to identify a convergence towards stable spatial variogram configurations. Moreover, the spatial organization of soil moisture showed preferred states with distinct patterns, depending on their respective drivers. This corroborates that the proposed method can be used to disentangle spatial structure originating from rainfall patterns from those controlled by the internal terrestrial system properties. Furthermore, we conclude that during stable states variogram aggregates originating from the density-based clustering could in principle be used for interpolation purposes, as they represent a temporally stable covariance. In contrast, an interpolation can be problematic while covariance is not stable in time. While the method has been developed and tested based on spatially distributed soil moisture data, it is also suitable for analyzing other state variables.

Mirko Mälicke et al.
Mirko Mälicke et al.
Model code and software

mmaelicke/scikit-gstat: Version 0.1.8 M. Mälicke and H. D. Schneider https://doi.org/10.5281/zenodo.1345585

Mirko Mälicke et al.
Viewed  
Total article views: 399 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
315 77 7 399 12 7 7
  • HTML: 315
  • PDF: 77
  • XML: 7
  • Total: 399
  • Supplement: 12
  • BibTeX: 7
  • EndNote: 7
Views and downloads (calculated since 17 Sep 2018)
Cumulative views and downloads (calculated since 17 Sep 2018)
Viewed (geographical distribution)  
Total article views: 381 (including HTML, PDF, and XML) Thereof 373 with geography defined and 8 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Cited  
Saved  
No saved metrics found.
Discussed  
No discussed metrics found.
Latest update: 16 Jan 2019
Publications Copernicus
Special issue
Download
Short summary
In this study we use time dependent variograms to identify periods of organized soil moisture during drying. We could identify emerging spatial patterns which imply periods of terrestrial control on soil moisture organization. The coupling of time dependent variograms with density based clustering is a new approach to detect similarity in spatial patterns. The presented method is useful to describe states of organization and improve kriging workflows by extending their prerequisites.
In this study we use time dependent variograms to identify periods of organized soil moisture...
Citation
Share