This title appears in the Scientific Report :
2013
Please use the identifier:
http://hdl.handle.net/2128/5792 in citations.
Investigating local controls on temporal stability of soil water content using sensor network data and an inverse modelling approach
Investigating local controls on temporal stability of soil water content using sensor network data and an inverse modelling approach
Soil water content is a key variable in the soil, vegetation and atmosphere continuum with high spatial and temporal variability. Temporal stability of soil water content (SWC) has been observed in multiple monitoring studies and the quantification of controls on soil moisture variability and tempor...
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Personal Name(s): | Qu, Wei (Corresponding author) |
---|---|
Bogena, Heye / Huisman, Johan Alexander / Martinez, G. / Pachepsky, Y. A. / Vereecken, Harry | |
Contributing Institute: |
Agrosphäre; IBG-3 |
Imprint: |
2013
|
Conference: | AGU, San Francisco (USA), 2013-12-09 - 2013-12-13 |
Document Type: |
Poster |
Research Program: |
Modelling and Monitoring Terrestrial Systems: Methods and Technologies |
Link: |
OpenAccess |
Publikationsportal JuSER |
Soil water content is a key variable in the soil, vegetation and atmosphere continuum with high spatial and temporal variability. Temporal stability of soil water content (SWC) has been observed in multiple monitoring studies and the quantification of controls on soil moisture variability and temporal stability presents substantial interest. The objective of this work was to assess the effect of soil hydraulic parameters on the temporal stability. The inverse modeling based on large observed time series SWC with in-situ sensor network was used to estimate the van Genuchten-Mualem (VGM) soil hydraulic parameters in a small grassland catchment located in western Germany. For the inverse modeling, the shuffled complex evaluation (SCE) optimization algorithm was coupled with the HYDRUS 1D code. We considered two cases: without and with prior information about the correlation between VGM parameters. The temporal stability of observed SWC was well pronounced at all observation depths. Both the spatial variability of SWC and the robustness of temporal stability increased with depth. Calibrated models both with and without prior information provided reasonable correspondence between simulated and measured time series of SWC. Furthermore, we found a linear relationship between the mean relative difference (MRD) of SWC and the saturated SWC (θs). Also, the logarithm of saturated hydraulic conductivity (Ks), the VGM parameter n and logarithm of α were strongly correlated with the MRD of saturation degree for the prior information case, but no correlation was found for the non-prior information case except at the 50cm depth. Based on these results we propose that establishing relationships between temporal stability and spatial variability of soil properties presents a promising research avenue for a better understanding of the controls on soil moisture variability. |