|Title||Set-membership estimation from poor quality data sets : Modelling ammonia volatilisation in flooded rice systems|
|Author(s)||Nurulhuda, K.; Struik, P.C.; Keesman, K.J.|
|Source||Environmental Modelling & Software 88 (2017). - ISSN 1364-8152 - p. 138 - 150.|
Biobased Chemistry and Technology
|Publication type||Refereed Article in a scientific journal|
|Keyword(s)||Ammonia volatilisation - Bounded-error - Flooded rice - Model calibration - Parameter estimation - Set-membership approach - Uncertainty analysis|
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.