142-8 Calibration and Validation of the Cosmos Rover for Mesoscale Soil Moisture Mapping.
See more from this Division: SSSA Division: Soil Physics
See more from this Session: Symposium--Soil Science Challenges in Land Surface and Global Climate Modeling: I
Monday, November 4, 2013: 4:00 PM
Tampa Convention Center, Room 16
Abstract:
The mobile COsmic-ray Soil Moisture Observing System (COSMOS rover) may be useful for validating satellite remote sensing estimates of near surface soil moisture, but the accuracy with which the rover can estimate 0-5 cm soil moisture has not been previously determined. Our objectives were to calibrate and validate a COSMOS rover for mapping 0-5 cm soil moisture at spatial scales suitable for evaluating satellite-based soil moisture estimates. The COSMOS rover was calibrated to field average soil moisture measured with impedance probes. The resulting calibration was applied to map soil moisture on two dates for a 16 km × 10 km region around the Marena, Oklahoma In Situ Sensor Testbed (MOISST) in north central Oklahoma and one date for a 34 km × 14 km region in the Little Washita River watershed in southwestern Oklahoma, USA. The mapped soil moisture patterns were consistent with regional spatial variability of surface soil texture and with soil wetting by an intervening rainfall. The rover measured field average soil moisture with an RMSD of 0.034 cm3 cm-3 relative to the impedance probes. The regional average soil moisture estimates from the COSMOS rover differed by 0.012, -0.038, and 0.017 cm3 cm-3 from the best available independent estimates for the two MOISST surveys and the Little Washita survey, respectively. These results demonstrate that a COSMOS rover can be used effectively for near surface soil moisture mapping and for determining average soil moisture at spatial scales suitable for calibrating and validating satellite-based soil moisture estimates.
See more from this Division: SSSA Division: Soil Physics
See more from this Session: Symposium--Soil Science Challenges in Land Surface and Global Climate Modeling: I