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Titolo:
Biogeochemical model of Lake Zurich: sensitivity, identifiability and uncertainty analysis
Autore:
Omlin, M; Brun, R; Reichert, P;
Indirizzi:
Swiss Fed Inst Environm Sci & Technol, Dept Syst Anal Integrated Assessment & Modelling, EAWAG, CH-8600 Dubendorf, Switzerland Swiss Fed Inst Environm Sci & Technol Dubendorf Switzerland CH-8600 land
Titolo Testata:
ECOLOGICAL MODELLING
fascicolo: 1-3, volume: 141, anno: 2001,
pagine: 105 - 123
SICI:
0304-3800(20010701)141:1-3<105:BMOLZS>2.0.ZU;2-A
Fonte:
ISI
Lingua:
ENG
Soggetto:
WATER-QUALITY; ECOLOGICAL MODELS; VALIDATION;
Keywords:
dependence analysis; identifiability analysis; Lake Zurich; parameter estimation; sensitivity analysis; uncertainty analysis; water-quality modelling;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Agriculture,Biology & Environmental Sciences
Citazioni:
23
Recensione:
Indirizzi per estratti:
Indirizzo: Reichert, P Swiss Fed Inst Environm Sci & Technol, Dept Syst Anal Integrated Assessment & Modelling, EAWAG, POB 611, CH-8600 Dubendorf, Switzerland Swiss Fed Inst Environm Sci & Technol POB 611 Dubendorf Switzerland CH-8600
Citazione:
M. Omlin et al., "Biogeochemical model of Lake Zurich: sensitivity, identifiability and uncertainty analysis", ECOL MODEL, 141(1-3), 2001, pp. 105-123

Abstract

A model for the description of nutrient, oxygen and plankton dynamics in Lake Zurich, Switzerland has recently been developed. Because, with this model, an attempt is made to describe mechanistically the most important mass fluxes and conversion processes in the water column and sediment of the lake, it is already too complicated to allow all of its parameters to be identifiable from the monthly measured profiles. This raises the questions of how to select a subset of model parameters to be included in a formal parameter estimation process and how to estimate model prediction uncertainty. In this paper, a systematic approach to tackle this problem is applied to thismodel. The technique consists of the combination of an analysis of the sensitivity of model results to single parameters with an analysis of the approximate linear dependence of sensitivity functions of parameter subsets. Itis demonstrated that the most severe parameter identifiability problems are caused by the parameterization of light dependence of algae growth, by competing effects of production, respiration and death of algae and zooplankton, and by the interactions between algae and zooplankton. The dynamics of dissolved variables is much easier to describe. The results of the analysisare used to select a parameter subset for a fit with measured data, to analyse the effect of other, fixed parameters on the estimates of the selectedparameters, and to estimate the uncertainty of model predictions. (C) 2001Elsevier Science B.V. All rights reserved.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 23/01/21 alle ore 10:15:23