Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/51946
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Type: Journal article
Title: Process-based simulation library SALMO-OO for lake ecosystems. Part 2: Multi-objective parameter optimization by evolutionary algorithms
Author: Cao, H.
Recknagel, F.
Cetin, L.
Zhang, H.
Citation: Ecological Informatics, 2008; 3(2):181-190
Publisher: Elsevier Science BV
Issue Date: 2008
ISSN: 1574-9541
1878-0512
Statement of
Responsibility: 
Hongqing Cao, Friedrich Recknagel, Lydia Cetina and Byron Zhang
Abstract: SALMO-OO represents an object-oriented simulation library for lake ecosystems that allows to determine generic model structures for certain lake categories. It is based on complex ordinary differential equations that can be assembled by alternative process equations for algal growth and grazing as well as zooplankton growth and mortality. It requires 128 constant parameters that are causally related to the metabolic, chemical and transport processes in lakes either estimated from laboratory and field experiments or adopted from the literature. An evolutionary algorithm (EA) was integrated into SALMO-OO in order to facilitate multi-objective optimization for selected parameters and to substitute them by optimum temperature and phosphate functions. The parameters were related to photosynthesis, respiration and grazing of the three algal groups diatoms, green algae and blue-green algae. The EA determined specific temperature and phosphate functions for same parameters for 3 lake categories that were validated by ecological data of six lakes from Germany and South Africa. The results of this study have demonstrated that: (1) the hybridization of ordinary differential equations by EA provide a sophisticated approach to fine-tune crucial parameters of complex ecological models, and (2) the multi-objective parameter optimization of SALMO-OO by EA has significantly improved the accuracy of simulation results for three different lake categories.
Keywords: Multi-objective parameter optimization; SALMO-OO; Lake categories; Evolutionary algorithms; Genetic programming
Description: Copyright © 2008 Elsevier B.V. All rights reserved. ScienceDirect® is a registered trademark of Elsevier B.V.
RMID: 0020081552
DOI: 10.1016/j.ecoinf.2008.02.001
Appears in Collections:Earth and Environmental Sciences publications
Environment Institute publications

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