A roadmap to improve precise soil management by linking crop modelling and remote sensing images via data assimilation: feasibility study
UK Partners: Dr Xiaoxian Zhang , Rothamsted Research
Chinese Partners: Dr Yuanyuan Zha, Wuhan University; Dr. Ben Zhao and Qibiao Han, Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences; Yanan Zhao, Henan Agricultural University
ATCNN-funded projects have made progress in using remote sensing to diagnose water and nutrients in canopy, but applying them to the STB fields needs extra work because it is water and nutrients in soil that need management. While nutrient in canopy is controlled by nutrients in soil, they are not proportional. Uptake of nutrients by plant depends on their bioavailability rather than their absolute contents. Managing soil nutrients based on their contents in canopy is an improvement, but precise management is not achievable unless their dynamics in root-zone soil is known. This project aims to study the feasibility of achieving this by linking information retrieved from remote sensing and soil/crop model.
Water and nutrients dynamics in soil, as well as associated crop growth will be simulated using the models we have been using with slight modification. The outputs of the model, including change in leaf area index, nitrogen uptake rate and biomass accumulation rate, will be assimilated by mining parameters that control water flow and nutrients transformation until the simulated results and those retrieved from remote sensing converge. We will assess the model using the data we have obtained with a view to apply it to the STB site.