Articles | Volume 19, issue 1
Hydrol. Earth Syst. Sci., 19, 615–629, 2015
https://doi.org/10.5194/hess-19-615-2015
Hydrol. Earth Syst. Sci., 19, 615–629, 2015
https://doi.org/10.5194/hess-19-615-2015

Research article 30 Jan 2015

Research article | 30 Jan 2015

Correction of systematic model forcing bias of CLM using assimilation of cosmic-ray Neutrons and land surface temperature: a study in the Heihe Catchment, China

X. Han et al.

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Cited articles

Anderson, M. C., Norman, J. M., Kustas, W. P., Li, F., Prueger, J. H., and Mecikalski, J. R.: Effects of Vegetation Clumping on Two–Source Model Estimates of Surface Energy Fluxes from an Agricultural Landscape during SMACEX, J. Hydrometeorol., 6, 892–909, 2005.
Barrett, D. J. and Renzullo, L. J.: On the Efficacy of Combining Thermal and Microwave Satellite Data as Observational Constraints for Root-Zone Soil Moisture Estimation C-7972-2009, J. Hydrometeorol., 10, 1109–1127, 2009.
Bateni, S. M. and Entekhabi, D.: Surface heat flux estimation with the ensemble Kalman smoother: Joint estimation of state and parameters, Water Resour. Res., 48, W08521, https://doi.org/10.1029/2011wr011542, 2012.
Bogena, H. R., Herbst, M., Huisman, J. A., Rosenbaum, U., Weuthen, A., and Vereecken, H.: Potential of Wireless Sensor Networks for Measuring Soil Water Content Variability, Vadose Zone J., 9, 1002–1013, 2010.
Bogena, H. R., Huisman, J. A., Baatz, R., Hendricks Franssen, H. J., and Vereecken, H.: Accuracy of the cosmic-ray soil water content probe in humid forest ecosystems: The worst case scenario, Water Resour. Res.., 49, 5778–5791, 2013.
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This paper presents the joint assimilation of cosmic-ray neutron counts and land surface temperature with parameter estimation of leaf area index at an irrigated corn field. The results show that the data assimilation can reduce the systematic input errors due to the lack of irrigation data. The estimations of soil moisture, evapotranspiration and leaf area index can be improved in the joint assimilation framework.