Including root architecture in a crop model improves predictions of spring wheat grain yield and above‐ground biomass under water limitations

Although the root length density ( RLD ) of crops depends on their root system architecture ( RSA ), the root growth modules of many 1D field crop models often ignored the RSA in the simulation of the RLD . In this study, two model set‐up scenarios were used to simulate the RLD , above‐ground biomass ( AGB ) and grain yield ( GY ) of water‐stressed spring wheat in Germany, aiming to investigate the impact of improved RLD on AGB and GY predictions. In scenario 1, SlimRoot, a root growth sub‐model that does not consider the RSA of the crop, was coupled to a Lintul5‐SlimNitrogen‐Soil CN ‐Hillflow1D crop model combination. In scenario 2, SlimRoot was replaced with the Somma sub‐model which considered the RSA for simulating RLD . The simulated RLD , AGB and GY were compared with observations. Scenario 2 predicted the RLD , AGB and GY with an average root mean square error ( RMSE ) of 0.43 cm/cm 3 , 0.59 t/ha and 1.03 t/ha, respectively, against 1.03 cm/cm 3 , 1.20 t/ha and 2.64 t/ha for scenario 1. The lower RMSE under scenario 2 shows that, even under water‐stress conditions, predictions of GY and AGB can be improved by considering the RSA of the crop for simulating the RLD .