Monitoring and managing spatial-temporal variability on farm: a crop modelling approach for nitrogen management

Abstract

Spatial variability in soil properties leads to significant differences in nitrogen use efficiency and crop response, creating challenges for optimising fertiliser management in wheat production. This research evaluates the feasibility of using the Sirius Crop Simulation Model to inform site-specific N management, integrating high-resolution soil sensing, long-term yield maps, and agronomic data. A systematic review identified key knowledge gaps, including the lack of crop simulation model applications for UK wheat at the sub-field scale and challenges in spatially parameterising soil properties. To address these, Sirius was validated using long-term agronomic data, accurately simulating spatial- temporal variability in grain N uptake (RRMSE = 19.5%), demonstrating its potential for spatial N management. A framework for cleaning, validating, and applying whole-farm yield map datasets was developed and applied to a 435 ha commercial farm. This enabled management zone delineation based on soil and economic performance and demonstrated how such techniques could be used to support precision agriculture, including crop modeling parametrisation. Sirius was then parameterised and applied across 30.5 ha using these management zones techniques, generating zone-specific N recommendations ranging from 160–216 kg N ha⁻¹, simulating potential for improvements in nitrogen use efficiency and reducing unutilised N, particularly in low available water capacity zones where current farm standard N application increased leaching risk by up to 31.1 kg N ha⁻¹. This research demonstrates a novel integration of crop simulation models into precision N management for UK wheat, combining validated models with refined spatial data techniques to improve farm-scale decision-making. While some model limitations remain, particularly in biomass simulations, the study highlights the potential for models to support economic and environmental sustainability in wheat production. Future work should validate model-derived recommendations in field trials, explore multi-model comparisons, and assess broader rotational impacts to enhance long-term farm management.