Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
doi:10.5194/hess-2017-118
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
11 Apr 2017
Review status
This discussion paper is under review for the journal Hydrology and Earth System Sciences (HESS).
Multi-decadal analysis of root-zone soil moisture applying the exponential filter across CONUS
Kenneth J. Tobin1, Roberto Torres1, Wade T. Crow2, and Marvin E. Bennett1 1Texas A&M International University, Center for Earth and Environmental Studies, Laredo, Texas, United States
2United States Department of Agriculture, Agricultural Research Service Hydrology and Remote Sensing Laboratory, Beltsville, Maryland, United States
Abstract. This study applied the exponential filter to produce an estimate of root-zone soil moisture (RZSM). Four types of microwave-based, surface satellite soil moisture were used. The core remotely sensed data for this study came from NASA’s long lasting AMSR-E mission. Additionally three other products were obtained from the European Space Agency Climate Change Initiative (CCI). These datasets were blended based on all available satellite observations (CCI-Active; CCI-Passive; CCI-Combined). All of these products were quarter degree and daily. We applied the filter to produce a soil moisture index (SWI) that others have successfully used to estimate RZSM. The only unknown in this approach was the characteristic time of soil moisture variation (T). We examined five different eras (1997–2002; 2002–2005; 2005–2008; 2008–2011; 2011–2014) that represented periods with different satellite data sensors. SWI values were compared with in situ soil moisture data from the International Soil Moisture Network at a depth ranging from 20 to 25 cm. Selected networks included the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program (25 cm), Soil Climate Analysis Network (SCAN; 20.32 cm), SNOwpack TELemetry (SNOTEL; 20.32 cm), and the U.S. Climate Reference Network (USCRN; 20 cm). We selected in situ stations that had reasonable completeness. These datasets were used to filter out periods with freezing temperatures and rainfall using data from the Parameter elevation Regression on Independent Slopes Model (PRISM). Additionally, we only examined sites where surface and root zone soil moisture had a reasonable high lagged correlation coefficient (r > 0.5).

The unknown T value was constrained based on two approaches: optimization of root mean square error (RSME) and calculation based on the NDVI value. Both approaches yielded comparable results; although, as to be expected, the optimization approach generally outperformed NDVI based estimates. Best results were noted at stations that had an absolute bias within 10 %. SWI estimates were more impacted by the in situ network than the surface satellite product used to drive the exponential filter. Average Nash-Sutcliffe coefficients (NS) for ARM ranged from −0.1 to 0.3 and were similar to the results obtained from the USCRN network (0.2 to 0.3). NS values from the SCAN and SNOTEL networks were slightly higher (0.1 to 0.5). These results indicated that this approach had some skill in providing an estimate of RZSM. In terms of root mean square error (RMSE; in volumetric soil moisture) ARM values actually outperformed those from other networks (0.02 to 0.04). SCAN and USCRN RMSE average values ranged from 0.04 to 0.06 and SNOTEL average RMSE values were higher ranging (0.05 to 0.07). These values were close to 0.04, which is the baseline value for accuracy designated for many satellite soil moisture missions.


Citation: Tobin, K. J., Torres, R., Crow, W. T., and Bennett, M. E.: Multi-decadal analysis of root-zone soil moisture applying the exponential filter across CONUS, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2017-118, in review, 2017.
Kenneth J. Tobin et al.
Kenneth J. Tobin et al.
Kenneth J. Tobin et al.

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Short summary
This study applied the exponential filter to produce an estimate of root-zone soil moisture at 20 to 25 cm depths. Four types of microwave, surface satellite soil moisture were used. The study focused on the Continental United States and in situ data used from the International Soil Moisture Network for comparison. This study spans almost two decades of time (1997 to 2014). Root mean square error were close to 0.04, the baseline value for accuracy designated for many satellite missions.
This study applied the exponential filter to produce an estimate of root-zone soil moisture at...
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