Soil moisture retrieval from Sentinel-1 using a first-order radiative transfer model — A case-study over the Po-Valley

Abstract

Soil moisture is an important variable controlling many land surface processes and is used to quantify precipitation, drought, flooding, irrigation and other factors that influence decision making and risk-assessment. This paper presents the retrieval of high resolution (∼1 km) soil moisture data from Sentinel-1 C-band Synthetic Aperture Radar (SAR) backscatter measurements using a new bistatic radiative transfer modeling framework (RT1) previously only tested for scatterometer data. The model is applied over a diverse set of landcover types across the entire Po-Valley in Italy over a 4-year time-period from 2016 to 2019. The performance of the soil moisture retrievals is analyzed with respect to the ERA5-Land reanalysis dataset. The model parameterisation and retrieval method are chosen such as to constitute a trade-off between a physically plausible and a computationally feasible modeling approach. The results demonstrate the potential of RT1 for the retrieval of high-resolution soil moisture data from SAR time series.