Summary
This methodological study presents new approaches for identifying temporal decoupling between surface and subsurface soil moisture using time-series analysis. By incorporating lagged dependence through distributed-lag nonlinear models and exploratory residual analysis, the authors quantify the range of decoupled soil moisture conditions across multiple sites, finding that decoupling occurs more broadly than previously understood and is not confined to dry conditions. The work has implications for improving hydrological model parameterisation when using remotely sensed surface soil moisture data.
UK applicability
The methodology is broadly applicable to UK hydrological and soil moisture monitoring contexts, where radar remote sensing is increasingly used for water resource management and flood prediction. However, site-specific validation would be needed to determine how decoupling patterns vary under UK climate and soil conditions.
Key measures
Lagged dependence between surface and subsurface soil moisture; distributed-lag nonlinear model (DLNM) functional relations; decoupled soil moisture ranges identified via loess residual analysis
Outcomes reported
The study developed and applied methods to identify decoupling between surface and subsurface soil moisture values using lagged dependence analysis. Results demonstrated that decoupled soil moisture conditions occur across multiple sites and are not limited to dry conditions.
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