Applying minirhizotrons to observe spatiotemporal variations in rooting depth and distribution in agroecosystems to improve the performance of hydrological models

• Published in: Vadose zone journal 2025-01, Vol.24 (1)
• Main Authors: Böske, Lennart N., Falge, Eva, Liedtke, Marco, Böttcher, Christopher, Iwers‐Braden, Dorothea, Meisner, Heike, Herbst, Mathias
• Format: Article
• Language: English
• ISSN: 1539-1663; 1539-1663
• DOI: 10.1002/vzj2.20382

To understand and explain soil moisture dynamics, the role of the vegetation is crucial. Hydrological processes in agricultural soils are strongly affected by rooting depth and root distribution. We present a new approach to monitor and model root dynamics and its influence on soil moisture using minirhizotrons combined with phenological observations. Field setups consist of a portable root scanner and acrylic glass tubes installed in the soil at the start of the growing season. 360° scans of soil and roots are taken regularly at different depths in the tubes. Root traits are identified automatically for each soil layer and complemented by observations of aboveground plant phenology. Results from minirhizotron data collected at an agrometeorological observatory in Germany show for both cereal and rapeseed ( Brassica napus L.) crops a higher root density in deeper soil layers and a lower density near the soil surface when compared to literature data. An opposite picture emerged for maize ( Zea mays L.) and potato ( Solanum tuberosum L.), whereas vertical root distribution in sugar beet ( Beta vulgaris subsp. vulgaris ) had a different seasonal course than expected from literature. Applying the new root distribution data in calculations of the soil water balance resulted in differences of more than 3% in absolute volumetric soil water content. A comparison with in situ measurements of volumetric soil moisture at 20‐ and 50‐cm depth revealed a significant improvement of the model results due to the new parameterization. Thus, we argue that minirhizotrons constitute a useful supplement to hydrological observatories and can help understand and predict soil moisture dynamics in the critical zone. Soil‐root images for different agricultural crops were taken with a minirhizotron over the course of the season. We developed our own soil‐root image analysis framework. The outcome was used to re‐parameterize a root distribution model, originally developed with data from literature. Implemented in a SVAT model, the new parametrization leads to significant differences in soil moisture. We propose the application of minirhizotrons as mandatory instrumentation for hydrological observatories. We used a portable root scanner, a so‐called minirhizotron, to take images of agricultural roots below ground for different crops (such as wheat, maize, and potatoes) over the course of the growing season. We studied the roots in the images to improve the root description in our compu