Summary
This methodological paper presents novel approaches for detecting and quantifying decoupling between surface and subsurface soil moisture using time-series analysis. The authors employed distributed-lag nonlinear models to incorporate temporal lag structure, with validation through loess-based residual analysis. Key findings challenge the assumption that decoupling occurs primarily under dry conditions, suggesting more complex relationships across varying moisture states.
UK applicability
The methodological framework may be applicable to UK soil and hydrological monitoring programmes, particularly where radar remote sensing data are integrated with subsurface measurements. UK environmental agencies managing water resources and flood risk prediction could benefit from improved understanding of soil moisture decoupling dynamics.
Key measures
Lagged dependence between surface and subsurface soil moisture; coupled and decoupled soil moisture value ranges; temporal delay between surface and subsurface moisture conditions
Outcomes reported
The study developed and applied distributed-lag nonlinear models (DLNM) and loess-based residual analysis to identify and quantify decoupling between surface and subsurface soil moisture across multiple sites. Results demonstrated that decoupled soil moisture conditions occur across a range of moisture states, not limited to dry conditions as previously understood.
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