Parameterizing a Dynamic Architectural Model of the Root System of Spring Barley from Minirhizotron Data

The development of models describing water and nutrient fluxes to and through 3-D spatially resolved root structures in soils brings along the need to predict or describe the root architecture and root growth in detail. However, detailed data to calibrate and validate such architecture and growth models is typically not available. Here, we investigate the sensitivity of the root architecture model RootTyp (Pagès et al., 2004) to changes in its model parameters and reconstructed the root system architecture of barley growing in an undisturbed lysimeter using minirhizotron images at four different depths. Root arrival curves from a series of minirhizotron images were used to parameterize RootTyp using a range of realistic architectures. We adjusted a simple architecture to the data, which contained only long primary roots starting from the seed. This simple model unfortunately could not reproduce the observed increase of root density with depth. The model was subsequently improved by allowing root branching and elongation to be horizon-dependent and by making reiteration of root tips possible. Reiteration is an alternative form of branching, where secondary roots can become as long and thick as primary roots. Our results show that minirhizotron data do not contain enough information to warrant identification of the parameters governing these processes, as the additional parameters act similarly on data characteristics as the initial ones. Therefore, different experimental techniques should be combined to constrain the model parameters better in the future.