About the data:
This dataset consists of soil moisture and temperature measurements collected from TOMST (https://tomst.com/web/en/systems/tms/tms-4/) data loggers in several locations in Africa but also in Cuba. The dataset consists of three near-surface temperature measurements (12 cm ground surface (Temp: +12 cm), on the ground surface (Temp: 0 cm), and just below the surface (Temp: -6 cm). Measurements of soil moisture are collected at a depth of 15 cm below the ground using the Time Domain Transmittometry technique. The TOMST loggers record soil moisture measurements as raw electric signals, which have to be converted to volumetric soil moisture content by a calibration approach. At the moment, we have used a global calibration curve (independent of soil texture) as we calibrate the loggers for different textures. The dataset herein includes the raw sensor readings, which can be calibrated using the TMS calibration guide https://tomst.com/web/wp-content/uploads/2023/05/TMS-calibration-handbook.pdf
Utilization:
The dataset is intended for applications in hydrology to monitor long-term soil moisture conditions, agricultural droughts (vegetation water deficit), validate soil moisture and evapotranspiration observations from remote sensing, and soil water balance models. In some cases, the data is also being used to assess the suitability of using this type of sensor for irrigation scheduling and water conservation. We have deployed these loggers to evaluate whether the fine resolution (250m) data from FAO’s Water Productivity through Open access of Remotely sensed derived data (WaPOR) can be used to contribute to relevant and timely drought monitoring at micro-scale, and how drought indices computed from WaPOR-data correspond to soil moisture trends at field scale.
