Integration of calibration and forcing methods for predicting timely crop states by using AquaCrop-OS model
conference contributionposted on 19.11.2019 by Tiangxiang Zhang, Jinya Su, Cunjia Liu, Wen-Hua Chen
Any type of content contributed to an academic conference, such as papers, presentations, lectures or proceedings.
This paper presents a framework for predicting canopy states in real time by adopting a recent MATLAB based crop model: AquaCrop-OS. The historical observations are firstly used to estimate the crop sensitive parameters in Bayesian approach. Secondly, the model states will be replaced by updating remotely sensed observations in a sequential way. The final predicted states will be in comparison with the groundtruth and the RMSE of these two are 39.4155 g/ 𝒎𝟐 (calibration method) and 19.3679 g/𝒎𝟐
(calibration with forcing method) concluding that the system is capable of predicting the crop status timely and improve the performance of calibration strategy.
Newton Fund UK-China Agri-Tech Network Plus managed by Rothamsted Research on behalf of Science and Technology Facilities Council (STFC)
Chinese Scholarship Council (CSC)
- Aeronautical, Automotive, Chemical and Materials Engineering
- Aeronautical and Automotive Engineering