Articles | Volume 9, issue 11
https://doi.org/10.5194/gmd-9-4155-2016
https://doi.org/10.5194/gmd-9-4155-2016
Model evaluation paper
 | 
21 Nov 2016
Model evaluation paper |  | 21 Nov 2016

A land surface model combined with a crop growth model for paddy rice (MATCRO-Rice v. 1) – Part 2: Model validation

Yuji Masutomi, Keisuke Ono, Takahiro Takimoto, Masayoshi Mano, Atsushi Maruyama, and Akira Miyata

Abstract. We conducted two types of validation for the simulations by MATCRO-Rice developed by Masutomi et al. (2016). In the first validation, we compared simulations with observations for latent heat flux (LHF), sensible heat flux (SHF), net carbon uptake by crop, and paddy rice yield from 2003 to 2006 at the site where model parameters are parameterized. In the second validation, we compared the observed and simulated paddy rice yields over Japan from 1991 to 2010 between observations and simulations. The 4-year average root mean square errors (RMSEs) of the first validation for LHF and SHF were 18.20 and 15.47 W m−2, respectively. These values for errors are comparable to those reported in earlier studies. The comparison of biomass growth during growing periods from 2003 to 2006 at the parameterization site shows that the simulations were in agreement with the observations, indicating that the model can reproduce the net carbon uptake by crops well. The 4-year average RMSE of the first validation for crop yield in the same period was 410.6 kg ha−1, which accounted for 8.1 % of the mean observed yields. The error of the second validation for crop yield was 16.7 % and the correlation of crop yields between observations and simulations from 1991 to 2010 was significant at 0.663 (P < 0.01). These results indicate that MATCRO-Rice has high ability to accurately and consistently simulate LHF, SHF, net carbon uptake by crop, and crop yield.

Short summary
We conducted two types of validation for the simulations by MATCRO-Rice developed by Masutomi et al. (2016). The results of the validation indicate that MATCRO-Rice has a high ability to accurately and consistently simulate latent heat flux, sensible heat flux, net carbon uptake by crops, and crop yield.