Long-term soil moisture dynamics derived from GNSS interferometric reflectometry: a case study for Sutherland, South Africa
- 681 Downloads
Soil moisture is a geophysical key observable for predicting floods and droughts, modeling weather and climate and optimizing agricultural management. Currently available in situ observations are limited to small sampling volumes and restricted number of sites, whereas measurements from satellites lack spatial resolution. Global navigation satellite system (GNSS) receivers can be used to estimate soil moisture time series at an intermediate scale of about 1000 m2. In this study, GNSS signal-to-noise ratio (SNR) data at the station Sutherland, South Africa, are used to estimate soil moisture variations during 2008–2014. The results capture the wetting and drying cycles in response to rainfall. The GNSS Volumetric Water Content (VWC) is highly correlated (r 2 = 0.8) with in situ observations by time-domain reflectometry sensors and is accurate to 0.05 m3/m3. The soil moisture estimates derived from the SNR of the L1 and L2P signals compared to the L2C show small differences with a RMSE of 0.03 m3/m3. A reduction in the SNR sampling rate from 1 to 30 s has very little impact on the accuracy of the soil moisture estimates (RMSE of the VWC difference 1–30 s is 0.01 m3/m3). The results show that the existing data of the global tracking network with continuous observations of the L1 and L2P signals with a 30-s sampling rate over the last two decades can provide valuable complementary soil moisture observations worldwide.
KeywordsGNSS Reflectometry Soil moisture Signal-to-noise ratio
We thank Kristine Larson for her helpful advice and discussions, Benjamin Creutzfeldt, Pieter Fourie and Jaci Cloete for their help in the field with sensor installation and maintenance, the South African Astronomic Observatory for their hospitality and support and acknowledge the Helmholtz Alliance HA310 “Remote Sensing of Earth System Dynamics” (HGF EDA) for funding the first author of this study. Reviewers are gratefully acknowledged for their comments.
- Alonso-Arroyo A, Camps A, Aguasca A, Forte GF, Monerris A, Rudiger C, Walker JP, Park H, Pascual D, Onrubia R (2014) Dual-polarization GNSS-R interference pattern technique for soil moisture mapping. IEEE J Sel Top Appl Earth Obs Remote Sens 7(5):1533–1544. doi: 10.1109/JSTARS.2014.2320792 CrossRefGoogle Scholar
- Beckmann P, Spizzichino A (1987) The scattering of electromagnetic waves from rough surfaces. Artech House Radar LibraryGoogle Scholar
- Egido A, Paloscia S, Motte E, Guerriero L, Pierdicca N, Caparrini M, Santi E, Fontanelli G, Floury N (2014) Airborne GNSS-R polarimetric measurements for soil moisture and above-ground biomass estimation. IEEE J Sel Topics Appl Earth Obs Remote Sens 7(5):1522–1532. doi: 10.1109/JSTARS.2014.2322854 CrossRefGoogle Scholar
- Fontana RD, Cheung W, Novak PM, Thomas A (2001) The new L2P civil signal. In: Proceedings of ION ITM GPS Institute of Navigation, September, Salt Lake City UT, pp 617–631Google Scholar
- Gurtner W, Estey L (2007) RINEX: The receiver independent exchange format version 2.11. http://igscb.jpl.nasa.gov/igscb/data/format/rinex211.txt
- Martin-Neira M (1993) A passive reflectometry and interferometry system (PARIS): application to ocean altimetry. ESA J 17(4):331–355Google Scholar
- Vey S, Güntner A, Wickert J, Blume T, Ramatschi M (2015) Supplement to: long-term soil moisture dynamics derived from GNSS interferometric reflectometry: a case study for Sutherland, South Africa. GFZ German Research Center for Geosciences. doi: 10.5880/GFZ.1.1.2015.001
- Zavorotny VU, Masters D, Gasiewski A, Bartram B, Katzberg S, Axelrad P and Zamora R (2003) Seasonal polarimetric measurements of soil moisture using tower-based GPS bistatic radar. In: Proceedings of IEEE 2003 international geoscience and remote sensing symposium, IGARSS 2003, vol 2, pp 781–783. doi: 10.1109/IGARSS.2003.1293916