Estimation and Validation Study of Soil Moisture Using GPS-IR Technique Over a Tropical Region: Variability of SM With Rainfall and Energy Fluxes

Soil Moisture (SM) data play an important role in different fields of research like hydrology, agriculture, climatology, etc. In this article, global positioning system interferometric reflectometry technique was used to estimate SM. Estimated SM data have been validated and compared with collocated...

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Bibliographic Details
Published inIEEE journal of selected topics in applied earth observations and remote sensing Vol. 15; pp. 42 - 49
Main Authors Madhavi, G. N., Sharath Kumar, P., Chipade, R. A., Bhate, Jyoti, Sarma, Tummalapalli Venkata Chandrasekhar
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Agricultural research
Atmospheric measurements
Atmospheric modeling
Climatology
Correlation
Data collection
Enthalpy
Global positioning systems
GPS
Heat
Heat flux
Heat transfer
Heating systems
Hydrology
Interferometry
Latent heat
microwave radio propagation
Positioning systems
Rain
Rainfall
Receivers
reflectometry
remote sensing
satellite navigation systems
Satellites
Sea measurements
Seasonal variation
Seasonal variations
Sensible heat
Soil
soil measurements
Soil moisture
Tropical climate
Tropical environment
Tropical environments
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Summary:Soil Moisture (SM) data play an important role in different fields of research like hydrology, agriculture, climatology, etc. In this article, global positioning system interferometric reflectometry technique was used to estimate SM. Estimated SM data have been validated and compared with collocated in situ probe, Soil Moisture and Ocean Salinity (SMOS) satellite measurements, ECMWF ERA-5, and NASA Global Land Data Assimilation System (GLDAS); the former shows a good correlation of 0.98 but the magnitudes of SMOS, ERA-5 are overestimated and GLDAS data are underestimated. Variability of SM with rainfall and energy fluxes like latent and sensible heat fluxes from ERA-5 and GLDAS data are investigated. Observed SM values are positively correlated with rainfall during the study period. Seasonal variations of SM with rainfall in different monsoons are clearly noticed. Latent heat fluxes are more during spring, summer months and positively correlated with rainfall, whereas sensitive heat fluxes show negative correlation.
ISSN:1939-1404
2151-1535
DOI:10.1109/JSTARS.2021.3127469