Dual state/rainfall correction via soil moisture assimilation  for improved streamflow simulation: evaluation of a  large-scale implementation with Soil Moisture Active  Passive (SMAP) satellite data

Mao, Yixin; Crow, Wade T.; Nijssen, Bart

doi:https://doi.org/10.5194/hess-24-615-2020

Articles | Volume 24, issue 2

https://doi.org/10.5194/hess-24-615-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-24-615-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 24, issue 2

Research article

|

13 Feb 2020

Research article |

| 13 Feb 2020

Dual state/rainfall correction via soil moisture assimilation for improved streamflow simulation: evaluation of a large-scale implementation with Soil Moisture Active Passive (SMAP) satellite data

Yixin Mao, Wade T. Crow, and Bart Nijssen

Supplement

https://doi.org/10.5194/hess-24-615-2020-supplement

Model code and software

Mao_etal_dualDA_Nov2019 Yixin Mao https://doi.org/10.5281/zenodo.3547877

Short summary

The new generation of satellite soil moisture observations are used to correct the streamflow in a regional-scale river basin simulated by a mathematical model. The correction is done via both the direct updating of soil moisture and correction of rainfall input. Results show some streamflow improvement, but the magnitude is small. A larger improvement will need future generations of even higher-quality satellite soil moisture data and better process representation in the mathematical model.