Evaluation of the predicted error of the soil moisture retrieval from C-band SAR by comparison against modelled soil moisture estimates over Australia

Abstract

The Sentinel-1 will carry onboard a C-band radar instrument that will map the European continent once every four days and the global land surface at least once every twelve days with finest 5 × 20 m spatial resolution. The high temporal sampling rate and operational configuration make Sentinel-1 of interest for operational soil moisture monitoring. Currently, updated soil moisture data are made available at 1 km spatial resolution as a demonstration service using Global Mode (GM) measurements from the Advanced Synthetic Aperture Radar (ASAR) onboard ENVISAT. The service demonstrates the potential of the C-band observations to monitor variations in soil moisture. Importantly, a retrieval error estimate is also available; these are needed to assimilate observations into models. The retrieval error is estimated by propagating sensor errors through the retrieval model.In this work, the existing ASAR GM retrieval error product is evaluated using independent top soil moisture estimates produced by the grid-based landscape hydrological model (AWRA-L) developed within the Australian Water Resources Assessment system (AWRA). The ASAR GM retrieval error estimate, an assumed prior AWRA-L error estimate and the variance in the respective datasets were used to spatially predict the root mean square error (RMSE) and the Pearson's correlation coefficient R between the two datasets. These were compared with the RMSE calculated directly from the two datasets. The predicted and computed RMSE showed a very high level of agreement in spatial patterns as well as good quantitative agreement; the RMSE was predicted within accuracy of 4% of saturated soil moisture over 89% of the Australian land mass. Predicted and calculated R maps corresponded within accuracy of 10% over 61% of the continent. The strong correspondence between the predicted and calculated RMSE and R builds confidence in the retrieval error model and derived ASAR GM error estimates.The ASAR GM and Sentinel-1 have the same basic physical measurement characteristics, and therefore very similar retrieval error estimation method can be applied. Because of the expected improvements in radiometric resolution of the Sentinel-1 backscatter measurements, soil moisture estimation errors can be expected to be an order of magnitude less than those for ASAR GM. This opens the possibility for operationally available medium resolution soil moisture estimates with very well-specified errors that can be assimilated into hydrological or crop yield models, with potentially large benefits for land-atmosphere fluxes, crop growth, and water balance monitoring and modelling.

Global analysis of seasonal streamflow predictability using an ensemble prediction system and observations from 6192 small catchments worldwide

“…Model simulations also compared favorably with other methods when evaluated against in situ observations of soil moisture (I. Dharssi, Bureau of Meteorology; personal communication) and evapotranspiration measured at flux towers [Van Dijk and Warren, 2010;King et al, 2012]. Model predictions for Australia have been evaluated against remotely sensed time series of total terrestrial water storage Tregoning et al, 2012;Forootan et al, 2012;Van Dijk et al, 2013], surface soil wetness [Van Dijk and Warren, 2010;Doubkova et al, 2012], vegetation greenness [Van Dijk and Warren, 2010;Van Dijk et al, 2013], and vegetation cover fraction, leaf area, and surface albedo [Van Dijk and Warren, 2010]. The model has also been used in drought analysis and in examining the statistical detectability of land cover impacts on streamflow [Van Dijk et al, 2012b].…”

Evaluation of a Global Soil Moisture Product from Finer Spatial Resolution SAR Data and Ground Measurements at Irish Sites

“…The WS mode allowed a spatial resolution of 150 m, a radiometric accuracy of less than 0.6 dB and a maximum duty cycle (the measure of the fraction of the time the radar is transmitting) of 30%, whereas the GM mode provided data with a spatial resolution of 1 km, a radiometric accuracy of about 1.2 dB and a duty cycle of 100%. Although a number of soil moisture studies have been carried out by using ASAR GM images [29,46,47], the high level of noise affecting such data led us to focus on ASAR WS products. Given their higher spatial resolution and the possibility to collect theoretically up to 3-5 images a month, ASAR WS have the potential for better characterization and monitoring of soil moisture.…”

Comparison between SAR Soil Moisture Estimates and Hydrological Model Simulations over the Scrivia Test Site

“…Sentinel 1 will work at C-band with a rather high spatial resolution of 5 m × 20 m and the temporal repetition frequency of 5-6 days over the European continent and 12 days for global acquisitions. Moreover, recent studies based on Sentinel 1-like data indicated that the improved radiometric resolution of Sentinel 1 may also produce a reduction in the retrieval errors on SMC [14].…”