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Volume 22, issue 4 | Copyright
Hydrol. Earth Syst. Sci., 22, 2255-2267, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 13 Apr 2018

Research article | 13 Apr 2018

Using lagged dependence to identify (de)coupled surface and subsurface soil moisture values

Coleen D. U. Carranza1, Martine J. van der Ploeg1, and Paul J. J. F. Torfs2 Coleen D. U. Carranza et al.
  • 1Soil Physics and Land Management Group, Wageningen University, Wageningen, the Netherlands
  • 2Hydrology and Quantitative Water Management Group, Wageningen University, Wageningen, the Netherlands

Abstract. Recent advances in radar remote sensing popularized the mapping of surface soil moisture at different spatial scales. Surface soil moisture measurements are used in combination with hydrological models to determine subsurface soil moisture values. However, variability of soil moisture across the soil column is important for estimating depth-integrated values, as decoupling between surface and subsurface can occur. In this study, we employ new methods to investigate the occurrence of (de)coupling between surface and subsurface soil moisture. Using time series datasets, lagged dependence was incorporated in assessing (de)coupling with the idea that surface soil moisture conditions will be reflected at the subsurface after a certain delay. The main approach involves the application of a distributed-lag nonlinear model (DLNM) to simultaneously represent both the functional relation and the lag structure in the time series. The results of an exploratory analysis using residuals from a fitted loess function serve as a posteriori information to determine (de)coupled values. Both methods allow for a range of (de)coupled soil moisture values to be quantified. Results provide new insights into the decoupled range as its occurrence among the sites investigated is not limited to dry conditions.

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Short summary
Remote sensing has been popular for mapping surface soil moisture. However, estimating subsurface values using surface soil moisture remains a challenge, as decoupling can occur. Depth-integrated soil moisture values used in hydrological models are affected by vertical variability. Using statistical methods, we investigate vertical variability between the surface (5 cm) and subsurface (40 cm) to quantify decoupling. We also discuss potential controls for decoupling during wet and dry conditions.
Remote sensing has been popular for mapping surface soil moisture. However, estimating...