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Structural uncertainty in a river water quality modelling system

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  • Lindenschmidt, Karl-Erich
  • Fleischbein, Katrin
  • Baborowski, Martina

Abstract

There are many sources of uncertainty in modelling systems including uncertainty due to parameter estimations, input data and structure of the system. In this paper, modelling system structure is understood to be the algorithms and equations used to describe and calculate processes. Specific attention is given to the uncertainty in the equations, which link models interactively in a modelling system and algorithms, which pass information between the models. This paper places emphasis on structural uncertainty in modelling systems since this topic has received very little attention in research compared to the wealth of literature on parameter and input data uncertainty. This imbalance is partly due to the difficulty in quantifying structural uncertainty and an example is given showing how this may be done.

Suggested Citation

  • Lindenschmidt, Karl-Erich & Fleischbein, Katrin & Baborowski, Martina, 2007. "Structural uncertainty in a river water quality modelling system," Ecological Modelling, Elsevier, vol. 204(3), pages 289-300.
    • Handle: RePEc:eee:ecomod:v:204:y:2007:i:3:p:289-300
    DOI: 10.1016/j.ecolmodel.2007.01.004
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    1. J. Refsgaard & H. Sørensen & I. Mucha & D. Rodak & Z. Hlavaty & L. Bansky & J. Klucovska & J. Topolska & J. Takac & V. Kosc & H. Enggrob & P. Engesgaard & J. Jensen & J. Fiselier & J. Griffioen & S. H, 1998. "An Integrated Model for the Danubian Lowland – Methodology and Applications," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 12(6), pages 433-465, December.
    2. Signorino, Curtis S., 2003. "Structure and Uncertainty in Discrete Choice Models," Political Analysis, Cambridge University Press, vol. 11(4), pages 316-344.
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    2. Qiang Xu & Zhimin Qiang & Qiuwen Chen & Kuo Liu & Nan Cao, 2018. "A Superposed Model for the Pipe Failure Assessment of Water Distribution Networks and Uncertainty Analysis: A Case Study," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(5), pages 1713-1723, March.
    3. Kooi, B.W. & Bontje, D. & van Voorn, G.A.K. & Kooijman, S.A.L.M., 2008. "Sublethal toxic effects in a simple aquatic food chain," Ecological Modelling, Elsevier, vol. 212(3), pages 304-318.
    4. Li, Y.P. & Huang, G.H. & Zhang, N. & Nie, S.L., 2011. "An inexact-stochastic with recourse model for developing regional economic-ecological sustainability under uncertainty," Ecological Modelling, Elsevier, vol. 222(2), pages 370-379.
    5. Xuan Wang & Wenchong Tian & Zhenliang Liao, 2022. "Framework for Hyperparameter Impact Analysis and Selection for Water Resources Feedforward Neural Network," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(11), pages 4201-4217, September.
    6. Huang, Jiacong & Gao, Junfeng & Liu, Jutao & Zhang, Yinjun, 2013. "State and parameter update of a hydrodynamic-phytoplankton model using ensemble Kalman filter," Ecological Modelling, Elsevier, vol. 263(C), pages 81-91.

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