Summary
This study develops methodological approaches to assess coupling and decoupling between surface and subsurface soil moisture using time series data and distributed-lag nonlinear modelling. The authors demonstrate that surface soil moisture conditions propagate to subsurface layers with a measurable delay, and that decoupled conditions occur across a broader range of soil moisture states than previously recognised. The findings have implications for improving hydrological model parameterisation and remote-sensing-based soil moisture mapping at multiple depths.
UK applicability
The methodology could support UK hydrological and environmental monitoring programmes that rely on radar remote sensing for soil moisture estimation, particularly for flood forecasting and drought prediction. However, applicability would depend on validation in UK soil and climatic conditions, which the abstract does not specify.
Key measures
Lagged dependence between surface and subsurface soil moisture; decoupling ranges identified through distributed-lag nonlinear model (DLNM); loess function residuals
Outcomes reported
The study quantified the occurrence and range of decoupled soil moisture values between surface and subsurface layers using distributed-lag nonlinear modelling and loess residual analysis. Results demonstrated that decoupling is not limited to dry conditions, providing new insights into the depth-dependent variability of soil moisture across the soil column.
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