Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/gmd-2017-182
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Development and technical paper
18 Sep 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).
Auto-calibration of a one-dimensional hydrodynamicecological model (DYRESM 4.0-CAEDYM 3.1) using a Monte Carlo approach: simulations of hypoxic events in a polymictic lake
Liancong Luo1, David Hamilton2, Jia Lan3, Chris McBride4, and Dennis Trolle5 1State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, P.R. China
2Australian Rivers Institute, Griffith University, Nathan Qld 4111, Australia
3Chunan Environmental Protection Bureau, Chunan, 311700, China
4Environmental Research Institute, Waikato University, Hamilton 3240, New Zealand
5Department of Bioscience, Aarhus University, Aarhus 8000, Denmark
Abstract. Automated calibration of complex deterministic water quality models with a large number of biogeochemical parameters can reduce time-consuming iterative simulations involving empirical judgements of model fit. We undertook auto-calibration of the one-dimensional hydrodynamic-ecological lake model DYRESM-CAEDYM, using a Monte Carlo Sampling (MCS) method, in order to test the applicability of this procedure for shallow, polymictic Lake Rotorua (New Zealand). The calibration procedure involved independently minimising the root-mean-square-error (RMSE), maximizing the Pearson correlation coefficient (r) and Nash-Sutcliffe efficient coefficient (Nr) for comparisons of model state variables against measured data. An assigned number of parameter permutations was used for 10,000 simulation iterations. The optimal temperature calibration produced a RMSE of 0.54 °C, Nr-value of 0.99 and r-value of 0.98 through the whole water column based on comparisons with 540 observed water temperatures collected between 13 July 2007–13 January 2009. The modeled bottom dissolved oxygen concentration (20.5 m below surface) was compared with 467 available observations. The calculated RMSE of the simulations compared with the measurements was 1.78 mg L−1, the Nr-value was 0.75 and the r-value was 0.87. The autocalibrated model was further tested for an independent data set by simulating bottom-water hypoxia events for the period 15 January 2009 to 8 June 2011 (875 days). This verification produced an accurate simulation of five hypoxic events corresponding to DO < 2 mg L−1 during summer of 2009–2011. The RMSE was 2.07 mg L−1, Nr-value 0.62 and r-value of 0.81, based on the available data set of 738 days. The auto-calibration software of DYRESM-CAEDYM developed here is substantially less time-consuming and more efficient in parameter optimisation than traditional manual calibration which has been the standard tool practiced for similar complex water quality models.

Citation: Luo, L., Hamilton, D., Lan, J., McBride, C., and Trolle, D.: Auto-calibration of a one-dimensional hydrodynamicecological model (DYRESM 4.0-CAEDYM 3.1) using a Monte Carlo approach: simulations of hypoxic events in a polymictic lake, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-182, in review, 2017.
Liancong Luo et al.
Liancong Luo et al.
Liancong Luo et al.

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Short summary
We developed an auto-calibration software for the hydrodynamic-ecological lake model DYRESM-CAEDYM with massive water quality papameters, using a Monte Carlo Sampling method, in order to reduce time-consuming iterative simulations with empirical judgements and find optimal model parameter set. The successful applications to Lake Rotorua suggest this software is much more efficient than traditional methods and of wide applicability to other water quality models.
We developed an auto-calibration software for the hydrodynamic-ecological lake model...
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