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Bayesian calibration of AquaCrop model
conference contribution
posted on 2019-11-19, 12:24 authored by Tianxiang Zhang, Jinya Su, Cunjia LiuCunjia Liu, Wen-Hua ChenWen-Hua ChenThe AquaCrop simulation model, modelling the dynamic change of crop growth status, is an important crop management tool for quantifying crop yield response to water. To effectively simulate the soil water balance and the crop growth process, a number of system parameters and canopy state variables are inevitably adopted. As a result, certain key parameters need to be calibrated so that the AquaCrop model can achieve a better performance of prediction for various scales of regions. This paper aims to apply Bayesian technique to calibrate the AquaCrop model. In this approach, the prior information regarding the system parameters is expressed in the form of a uniform probability distribution. Then with the advent of output variable measurement (e.g. biomass) by remote sensing techniques, the parameter distributions are iteratively updated by using Bayesian Markov Chain Monte Carlo (MCMC) method. The calibrated system parameters are expressed by the posterior distributions and gained by distribution mean value. Finally, the Bayesian calibration is compared with the conventional optimisation based calibration in terms of biomass and canopy cover, where simulated annealing is chosen as the optimisation approach, indicating a better calibration performance can be achieved by using Bayesian methods. Consequently, it is recommended that Bayesian calibration is one promising approach to the problem of crop model calibration.
Funding
Science and Technology Facilities Council (STFC) under Newton fund with grant number ST/N006852/1
History
School
- Aeronautical, Automotive, Chemical and Materials Engineering
Department
- Aeronautical and Automotive Engineering
Published in
2018 37th Chinese Control Conference (CCC)Pages
10334 - 10339Source
2018 37th Chinese Control Conference (CCC)Publisher
IEEEVersion
- AM (Accepted Manuscript)
Rights holder
© Technical Committee on Control Theory, Chinese Association of AutomationPublisher statement
© 2018 Technical Committee on Control Theory, Chinese Association of Automation. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Acceptance date
2018-05-21Publication date
2018-10-08Copyright date
2018ISBN
9789881563958eISSN
1934-1768Publisher version
Language
- en
Location
Wuhan, ChinaEvent dates
25th July 2018 - 27th July 2018Depositor
Tianxiang Zhang. Deposit date: 18 November 2019Usage metrics
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