Articles | Volume 25, issue 8
https://doi.org/10.5194/hess-25-4567-2021
https://doi.org/10.5194/hess-25-4567-2021
Research article
 | 
24 Aug 2021
Research article |  | 24 Aug 2021

Satellite soil moisture data assimilation for improved operational continental water balance prediction

Siyuan Tian, Luigi J. Renzullo, Robert C. Pipunic, Julien Lerat, Wendy Sharples, and Chantal Donnelly

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Cited articles

Alemohammad, S. H., McColl, K. A., Konings, A. G., Entekhabi, D., and Stoffelen, A.: Characterization of precipitation product errors across the United States using multiplicative triple collocation, Hydrol. Earth Syst. Sci., 19, 3489–3503, https://doi.org/10.5194/hess-19-3489-2015, 2015. 
Alvarez-Garreton, C., Ryu, D., Western, A. W., Su, C. H., Crow, W. T., Robertson, D. E., and Leahy, C.: Improving operational flood ensemble prediction by the assimilation of satellite soil moisture: comparison between lumped and semi-distributed schemes, Hydrol. Earth Syst. Sci., 19, 1659–1676, https://doi.org/10.5194/hess-19-1659-2015, 2015. 
Anderson, J., Hoar, T., Raeder, K., Liu, H., Collins, N., Torn, R., and Avellano, A.: The data assimilation research testbed: A community facility, B. Am. Meteorol. Soc., 90, 1283–1296, 2009. 
AWRA-CMS – The Australian Water Resources Assessment: Community Modelling System (Frost et al. 2018), Github [code], availalbe at: https://github.com/awracms/awra_cms, last access: 1 September 2021. 
Baldwin, D., Manfreda, S., Keller, K., and Smithwick, E.: Predicting root zone soil moisture with soil properties and satellite near-surface moisture data across the conterminous United States, J. Hydrol., 546, 393–404, 2017. 
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Short summary
Accurate daily continental water balance predictions are valuable in monitoring and forecasting water availability and land surface conditions. A simple and robust method was developed for an operational water balance model to constrain model predictions temporally and spatially with satellite soil moisture observations. The improved soil water storage prediction can provide constraints in model forecasts that persist for several weeks.
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