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Four years of soybean experimental data observed at Daxing, North China Plain, were used to assess the ability of the AquaCrop model to predict soybean final biomass and yield. The model was parameterized and calibrated using field data on leaf area index (LAI), available soil water, soil evaporation, biomass and final yield data. The model was assessed using calibrated and default parameters. Data on LAI was used to derive the fraction of ground cover and to calibrate the green canopy cover (CC) curve. An accurate calibration of the CC curve was performed, with low root mean square errors (RMSE < 7.3%). Results relative to soil water balance simulations show a high variability of the predictions, thus a bias of the estimation, with R 2 ranging 0.22-0.86 and low Nash-Sutcliffe efficiency EF, ranging between-0.47 and 0.82. The estimation errors were relatively high, with RMSE not exceeding 22.9 mm. AquaCrop was compared with the soil water balance model SIMDualKc, that has shown better performance with R 2 ≥ 0.83, EF generally greater than 0.75 and RMSE smaller than 12.5 mm. The soil evaporation (E s) simulations were compared with the observations performed using microlysimeters; results for Aquacrop have shown a clear trend for underestimation of E s , 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 *Revised Manuscript with No changes Marked Click here to view linked References

Abstract. Aiming at developing real time water balance modelling for irrigation scheduling, this study assesses the accuracy of using the reference evapotranspiration (ET o ) estimated from daily weather forecast messages (ET o,WF ) as model input. A previous study applied to eight locations in China (Cai et al., 2007) has shown the feasibility for estimating ET o,WF with the FAO Penman-Monteith equation using daily forecasts of maximum and minimum temperature, cloudiness and wind speed. In this study, the global radiation is estimated from the difference between the forecasted maximum and minimum temperatures, the actual vapour pressure is estimated from the forecasted minimum temperature and the wind speed is obtained from converting the common wind scales into wind speed. The present application refers to a location in the North China Plain, Daxing, for the wheat crop seasons of 2005-2006 and 2006-2007. Results comparing ET o,WF with ET o computed with observed data (ET o,obs ) have shown favourable goodness of fitting indicators and a RMSE of 0.77 mm d −1 . ET o was underestimated in the first year and overestimated in the second. The water balance model ISAREG was calibrated with data from four treatments for the first season and validated with data of five treatments in the second season using observed weather data. The calibrated crop parameters were used in the simulations of the same treatments using ET o,WF as model input. Errors in predicting the soil water content are small, 0.010 and 0.012 m 3 m −3 , respectively for the first and second year. Other indicators also confirm the goodness of model predictions. It could be concluded that using ET o computed from daily weather forecast messages provides for accurate model predictions and to use an irrigation scheduling model in real time.

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