Root growth traits are the dominant sources of uncertainty in simulating agricultural crop rotational systems

Abstract

Crop rotation systems effectively enhance resource use efficiency and biodiversity. Process-based agroecosystem models serve as valuable tools for their sustainable design. However, most model applications overlook the role of root characteristics on simulated above- and belowground model components. This is particularly critical in crop rotations, involving diverse species and cultivars. Overlooking this aspect can lead to significant inaccuracies in modelling crop yields, as well as soil organic carbon (SOC), and nitrogen leaching (N-leaching). This study quantifies the contribution of climate, management (crop rotation, irrigation and rainfed systems), and cultivar (phenology and root growth characteristics) factors on simulation of crop yields, N-leaching, and SOC. The analysis was conducted in mono-cropping and 10 different crop rotations (cereals-tuber, cereal-cereal, tuber-tuber crops). The MOdel of NItrogen and CArbon dynamics (MONICA) was used for this purpose. MONICA was parameterized and calibrated using detailed data on the time and amount of irrigation recorded for Hamerstorf experimental site located in Lower Saxony, Germany. Our results demonstrated a stronger effect of root depth factor on yield variability in rainfed compared to irrigated systems, accounting for approximately 60 % of the observed variation. In contrast, crop phenology had a greater impact on yield under irrigation. For N-leaching and SOC, crop rotation explained over 65 % of the variability. Root depth and root density contributed more significantly to SOC dynamics than to N-leaching. These findings highlight the importance of accurate estimation on root growth in models to reduce uncertainty in simulating crop rotation systems. Precise root growth characteristics become even more critical when modeling extends beyond yield to include nitrogen and SOC—key indicators of sustainable agricultural systems.