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Multi-objective calibration of a river water quality model—Information content of calibration data

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  • Rode, Michael
  • Suhr, Ursula
  • Wriedt, Gunter

Abstract

Substantial uncertainties exist in the identification of river water quality models, which partially depend on the information content of the calibration data. To evaluate the dependencies between available calibration data and model predictions, investigations were conducted based on a 536km free-flowing reach of the German part of the River Elbe. Five extensive flow-time-related longitudinal surveys with 14 sampling locations were used. The multi-objective calibration of the deterministic river water quality model QSIM was carried out with the nonlinear parameter estimator PEST. At the investigated river reach, parameter sensitivities were highly variable depending mainly on the growth of algal biomass. Based on 30 multi-objective calibration runs considering different numbers and combinations of the data sets, we found that calibration was only slightly improved using more than three data sets. Uncertainties can be decreased by increasing the amount of calibration data. For the calibration data sets, the cumulative distribution functions of the Nash and Sutcliffe coefficient steepen progressively and the uncertainties of model parameters decreased with an increased number of data sets included in the calibration procedure. Also the combination of different calibration data sets had an effect on the goodness of the model validation. Most uncertainties were associated with the calculation of oxygen. These findings are restricted to cases where data sets of different conditions are available. The suggested methodology for model calibration including a cross validation is especially suited for cases where available data are limited, which is common for river water quality modelling investigations. The results of this study will help model users to define appropriate data collections and monitoring schemes.

Suggested Citation

  • Rode, Michael & Suhr, Ursula & Wriedt, Gunter, 2007. "Multi-objective calibration of a river water quality model—Information content of calibration data," Ecological Modelling, Elsevier, vol. 204(1), pages 129-142.
  • Handle: RePEc:eee:ecomod:v:204:y:2007:i:1:p:129-142
    DOI: 10.1016/j.ecolmodel.2006.12.037
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    Citations

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    Cited by:

    1. Wagenschein, Dierk & Rode, Michael, 2008. "Modelling the impact of river morphology on nitrogen retention—A case study of the Weisse Elster River (Germany)," Ecological Modelling, Elsevier, vol. 211(1), pages 224-232.
    2. Haas, Marcelo B. & Guse, Björn & Pfannerstill, Matthias & Fohrer, Nicola, 2015. "Detection of dominant nitrate processes in ecohydrological modeling with temporal parameter sensitivity analysis," Ecological Modelling, Elsevier, vol. 314(C), pages 62-72.
    3. Park, Richard A. & Clough, Jonathan S. & Wellman, Marjorie Coombs, 2008. "AQUATOX: Modeling environmental fate and ecological effects in aquatic ecosystems," Ecological Modelling, Elsevier, vol. 213(1), pages 1-15.
    4. Simon Deslauriers & Tew-Fik Mahdi, 2018. "Flood modelling improvement using automatic calibration of two dimensional river software SRH-2D," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 91(2), pages 697-715, March.
    5. Li Li & Eun-Sung Chung & Kyung Soo Jun, 2018. "Robust Parameter Set Selection for a Hydrodynamic Model Based on Multi-Site Calibration Using Multi-Objective Optimization and Minimax Regret Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(12), pages 3979-3995, September.
    6. H. Boyacioglu & T. Vetter & V. Krysanova & M. Rode, 2012. "Modeling the impacts of climate change on nitrogen retention in a 4th order stream," Climatic Change, Springer, vol. 113(3), pages 981-999, August.
    7. Yunxing Yin & Sanyuan Jiang & Charlotta Pers & Xiaoying Yang & Qun Liu & Jin Yuan & Mingxing Yao & Yi He & Xingzhang Luo & Zheng Zheng, 2016. "Assessment of the Spatial and Temporal Variations of Water Quality for Agricultural Lands with Crop Rotation in China by Using a HYPE Model," IJERPH, MDPI, vol. 13(3), pages 1-19, March.
    8. Scharfe, Mirco & Callies, Ulrich & Blöcker, Gerd & Petersen, Wilhelm & Schroeder, Friedhelm, 2009. "A simple Lagrangian model to simulate temporal variability of algae in the Elbe River," Ecological Modelling, Elsevier, vol. 220(18), pages 2173-2186.
    9. Ruibin Zhang & Xin Qian & Xingcheng Yuan & Rui Ye & Bisheng Xia & Yulei Wang, 2012. "Simulation of Water Environmental Capacity and Pollution Load Reduction Using QUAL2K for Water Environmental Management," IJERPH, MDPI, vol. 9(12), pages 1-18, December.

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