Set-membership estimation from poor quality data sets: Modelling ammonia volatilisation in flooded rice systems |
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| Affiliation: | 1. Biological and Agricultural Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia;2. Biobased Chemistry and Technology, Wageningen University, PO Box 17, 6700 AA, Wageningen, The Netherlands;3. Centre for Crop Systems Analysis, Wageningen University, PO Box 430, 6700 AK, Wageningen, The Netherlands;1. Southern Regional Collaborative Innovation Center for Grain and Oil Crops (CICGO), Hunan Agricultural University, Changsha 410128, China;2. Key Laboratory of Crop Cultivation and Farming System, Guangxi University, Nanning 530004, China;1. State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China;2. University of Chinese Academy of Sciences, Beijing 100049, China;3. School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China;4. Jiangsu Key Laboratory of Low Carbon Agriculture and GHGs Mitigation, Nanjing Agricultural University, Nanjing 210095, China |
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| Abstract: | A set-membership (bounded-error) estimation approach can handle small and poor quality data sets as it does not require testing of statistical assumptions which is possible only with large informative data sets. Thus, set-membership estimation can be a good tool in the modelling of agri-environmental systems, which typically suffers from limited and poor quality observational data sets. The objectives of the paper are (i) to demonstrate how six parameters in an agri-environmental model, developed to estimate NH3 volatilisation in flooded rice systems, were estimated based on two data sets using a set-membership approach, and (ii) to compare the set-membership approach with conventional non-linear least-squares methods. Results showed that the set-membership approach is efficient in retrieving feasible parameter-vectors compared with non-linear least-squares methods. The set of feasible parameter-vectors allows the formation of a dispersion matrix of which the eigenvalue decomposition reflects the parameter sensitivity in a region. |
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| Keywords: | Set-membership approach Bounded-error Parameter estimation Uncertainty analysis Model calibration Ammonia volatilisation Flooded rice |
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