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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 21, issue 5
Hydrol. Earth Syst. Sci., 21, 2509–2530, 2017
https://doi.org/10.5194/hess-21-2509-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 21, 2509–2530, 2017
https://doi.org/10.5194/hess-21-2509-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 16 May 2017

Research article | 16 May 2017

Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction

Roland Baatz et al.

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Cited articles

Ajami, H., McCabe, M. F., Evans, J. P., and Stisen, S.: Assessing the impact of model spin-up on surface water-groundwater interactions using an integrated hydrologic model, Water Resour. Res., 50, 2636–2656, https://doi.org/10.1002/2013wr014258, 2014.
Anderson, J. L.: An ensemble adjustment Kalman filter for data assimilation, Mon. Weather Rev., 129, 2884–2903, https://doi.org/10.1175/1520-0493(2001)129<2884:Aeakff>2.0.Co;2, 2001.
Avery, W. A., Finkenbiner, C., Franz, T. E., Wang, T. J., Nguy-Robertson, A. L., Suyker, A., Arkebauer, T., and Munoz-Arriola, F.: Incorporation of globally available datasets into the roving cosmic-ray neutron probe method for estimating field-scale soil water content, Hydrol. Earth Syst. Sci., 20, 3859–3872, https://doi.org/10.5194/hess-20-3859-2016, 2016.
Baatz, R., Bogena, H. R., Hendricks Franssen, H. J., Huisman, J. A., Qu, W., Montzka, C., and Vereecken, H.: Calibration of a catchment scale cosmic-ray probe network: A comparison of three parameterization methods, J. Hydrol., 516, 231–244, https://doi.org/10.1016/j.jhydrol.2014.02.026, 2014.
Baatz, R., Bogena, H. R., Hendricks Franssen, H. J., Huisman, J. A., Montzka, C., and Vereecken, H.: An empirical vegetation correction for soil water content quantification using cosmic ray probes, Water Resour. Res., 51, 2030–2046, https://doi.org/10.1002/2014WR016443, 2015.
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Short summary
Soil moisture is a major variable that affects regional climate, weather and hydrologic processes on the Earth's surface. In this study, real-world data of a network of cosmic-ray sensors were assimilated into a regional land surface model to improve model states and soil hydraulic parameters. The results show the potential of these networks for improving model states and parameters. It is suggested to widen the number of observed variables and to increase the number of estimated parameters.
Soil moisture is a major variable that affects regional climate, weather and hydrologic...
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