Articles | Volume 27, issue 5
https://doi.org/10.5194/hess-27-1173-2023
https://doi.org/10.5194/hess-27-1173-2023
Research article
 | 
16 Mar 2023
Research article |  | 16 Mar 2023

A comprehensive assessment of in situ and remote sensing soil moisture data assimilation in the APSIM model for improving agricultural forecasting across the US Midwest

Marissa Kivi, Noemi Vergopolan, and Hamze Dokoohaki

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Cited articles

Albergel, C., Rüdiger, C., Pellarin, T., Calvet, J.-C., Fritz, N., Froissard, F., Suquia, D., Petitpa, A., Piguet, B., and Martin, E.: From near-surface to root-zone soil moisture using an exponential filter: an assessment of the method based on in-situ observations and model simulations, Hydrol. Earth Syst. Sci., 12, 1323–1337, https://doi.org/10.5194/hess-12-1323-2008, 2008. 
Chakrabarti, S., Bongiovanni, T., Judge, J., Zotarelli, L., and Bayer, C.: Assimilation of SMOS soil moisture for quantifying drought impacts on crop yield in agricultural regions, IEEE J. Select. Top. Appl., 7, 3867–3879, https://doi.org/10.1109/JSTARS.2014.2315999, 2014. 
Chen, Y., Zhang, Z., and Tao, F. : Improving regional winter wheat yield estimation through assimilation of phenology and leaf area index from remote sensing data, Eur. J. Agron., 101, 163–173, https://doi.org/10.1016/j.eja.2018.09.006, 2018. 
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Short summary
This study attempts to provide a framework for direct integration of soil moisture observations collected from soil sensors and satellite imagery into process-based crop models for improving the representation of agricultural systems. The performance of this framework was evaluated across 19 sites times years for crop yield, normalized difference vegetation index (NDVI), soil moisture, tile flow drainage, and nitrate leaching.