UC Berkeley

Soil moisture plays a key role in hydrological, biogeochemical, and energy budgets of terrestrial ecosystems. Accurate soil moisture measurements in remote ecosystems such as the Amazon are difficult and limited because of logistical constraints. Time domain reflectometry (TDR) sensors are widely used to monitor soil moisture and require calibration to convert the TDR's dielectric permittivity measurement (Ka) to volumetric water content (θv). In this study, our objectives were to develop a field-based calibration of TDR sensors in an old-growth upland forest in the central Amazon, to evaluate the performance of the calibration, and then to apply the calibration to determine the dynamics of soil moisture content within a 14.2-m-deep vertical soil profile. Depth-specific TDR calibration using local soils in a controlled laboratory setting yielded a novel Ka–θv third-degree polynomial calibration. The sensors were later installed to their specific calibration depth in a 14.2-m pit. The widely used Ka–θv relationship (Topp model) underestimated the site-specific θv by 22–42%, indicating significant error in the model when applied to these well-structured, clay-rich tropical forest soils. The calibrated wet- and dry-season θv data showed a variety of depth and temporal variations highlighting the importance of soil textural differentiation, root uptake depths, as well as event to seasonal precipitation effects. Data such as these are greatly needed for improving our understanding of ecohydrological processes within tropical forests and for improving models of these systems in the face of changing environmental conditions.