Set-membership estimation from poor quality data sets: Modelling ammonia volatilisation in flooded rice systems

K. Nurulhuda, P.C. Struik, K.J. Keesman*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)138-150
JournalEnvironmental Modelling & Software
Volume88
DOIs
Publication statusPublished - 2017

Keywords

  • Ammonia volatilisation
  • Bounded-error
  • Flooded rice
  • Model calibration
  • Parameter estimation
  • Set-membership approach
  • Uncertainty analysis

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