Monday, January 20, 2014

Luca's references on soil moisture spatial variability and remote sensing

In trying to extract the publishable results from Ageel Bushara Ph.D. thesis,  a good work indeed, but weakened by my ignorance in remote sensing, I started a conversation with Luca Brocca, one of the most prominent young italian hydrologists.  As befits in good conversations, Luca suggested some initial readings.
Here they are:


1) Teuling et al. 2005 GRL they obtained good results comparing the spatial variability of the data but they do not have lateral flow of water

2) Brocca et al. 2013 JoH. As for Teuling, good results in the estimation of the spatial variability (however, the model is calibrated in any single point). Here we had a different scope, which was to obtain a lon soil moisture time series.

3) Walker et al. 2002 HYP using soil moisture estimates from SAR and comparison with ground data. IMHO not very good results (in Australia).

4) Li and Rodell 2013 HESS: they obtain that the spatial variability of in situ data (SCAN) is very different from the one modelled (Noah land surface model) and also different from the one obtain by another satellite (AMSRE, microwave passive sensor, 25 km). The study covers all the USA (CONUS).


  1. Thank you for posting this valuable short article.

  2. Dear Riccardo,

    thanks for sharing my comments. Anyhow, I would like to draw your attention to this very recent paper published (yesterday) on JoH:
    Cornelissen, T., Diekkrüger, B. Bogena, H.R. (2014). Significance of scale and lower boundary condition in the 3D simulation of hydrological processes and soil moisture variability in a forested headwater catchment, Journal of Hydrology, in press, doi: 10.1016/j.jhydrol.2014.01.060.

    The manuscript describes a very interesting effort to model discharge and soil moisture through a physically based spatially distributed hydrogeological model (HGS) in a very well instrumented small catchment (Wustebach, 0.27 km²) in western Germany. Specifically, the soil moisture dataset collected in the catchment is really impressive (900 sensors!!!).

    However.... the HGS model failed to simulate the spatial variability of soil moisture observations, or alternatively, the spatial variability of observed data is different from the modelled data (see Figures 6, 7, and 8 and the Kappa value in section 4.3).

    My question is: why is the model wrong in reproducing soil moisture SPATIAL variability?
    The authors underline that the model doesn't simulate the macropore flow (and the flow in the fractures) and this could be one reason.
    Further reasons: 1) uncertainty in the measured data that increases their standard deviation (see Brocca et al., 2013, JoH), 2) wrong SPATIAL parameterization of the hydrological model (e.g. the soil layer thickness).
    Other reasons???

  3. I add here also another paper, suggested by Luca, by Riley and Shen, just appeared on HESS: