Performance assessment of the FAO AquaCrop model for soil water, soil evaporation, biomass and yield of soybeans in North China plain - Paredes, P. (2015)
tFour years of soybean experimental data observed at Daxing, North China Plain, were used to assess theability of the AquaCrop model to predict soybean final biomass and yield. The model was parameterizedand calibrated using field data on leaf area index (LAI), available soil water, soil evaporation, biomass andfinal yield data. The model was assessed using calibrated and default parameters. Data on LAI were usedto derive the fraction of ground cover and to calibrate the green canopy cover (CC) curve. An accurate cal-ibration of the CC curve was performed, with low root mean square errors (RMSE < 7.3%). Results relativeto soil water balance simulations show a high variability of the predictions, thus a bias of the estimation,with R2ranging 0.22–0.86 and low Nash-Sutcliffe efficiency EF, ranging between −0.47 and 0.82. The esti-mation errors were relatively high, with RMSE not exceeding 22.9 mm. AquaCrop was compared withthe soil water balance model SIMDualKc, that has shown better performance with R2≥ 0.83, EF generallygreater than 0.75 and RMSE smaller than 12.5 mm. The soil evaporation (Es) simulations were comparedwith the observations performed using microlysimeters; results for Aquacrop have shown a clear trendfor under-estimation of Es, with “goodness-of-fit” results worse than for SIMDualKc (Wei et al., 2015).In general, AquaCrop has shown serious limitations to estimate crop transpiration or soil evaporation,which is likely due to abandoning the FAO dual Kcapproach. However, the model performed well relativeto biomass and yield predictions, with a yield RMSE of 302 kg ha−1. Overall, results show the adequacyof AquaCrop for estimating soybean biomass and yield when the model is appropriately parameterized.However, AquaCrop is not appropriate to support irrigation scheduling