An overview of methods to evaluate uncertainty of deterministic models in decision support

Laura Uusitalo, Annukka Lehikoinen, Inari Helle, Kai Myrberg

Tutkimustuotos: ArtikkelijulkaisuKatsausartikkeliTieteellinenvertaisarvioitu

Kuvaus

There is an increasing need for environmental management advice that is wide-scoped, covering various interlinked policies, and realistic about the uncertainties related to the possible management actions. To achieve this, efficient decision support integrates the results of pre-existing models. Many environmental models are deterministic, but the uncertainty of their outcomes needs to be estimated when they are utilized for decision support. We review various methods that have been or could be applied to evaluate the uncertainty related to deterministic models' outputs. We cover expert judgement, model emulation, sensitivity analysis, temporal and spatial variability in the model outputs, the use of multiple models, and statistical approaches, and evaluate when these methods are appropriate and what must be taken into account when utilizing them. The best way to evaluate the uncertainty depends on the definitions of the source models and the amount and quality of information available to the modeller.
Alkuperäiskielienglanti
LehtiEnvironmental Modelling & Software
Vuosikerta63
Sivut24-31
Sivumäärä8
ISSN1364-8152
DOI - pysyväislinkit
TilaJulkaistu - 2015
OKM-julkaisutyyppiA2 Katsausartikkeli tieteellisessä aikakauslehdessä

Tieteenalat

  • 1172 Ympäristötiede

Lainaa tätä

@article{f6d51453c24d4c658289f23ff9258b9f,
title = "An overview of methods to evaluate uncertainty of deterministic models in decision support",
abstract = "There is an increasing need for environmental management advice that is wide-scoped, covering various interlinked policies, and realistic about the uncertainties related to the possible management actions. To achieve this, efficient decision support integrates the results of pre-existing models. Many environmental models are deterministic, but the uncertainty of their outcomes needs to be estimated when they are utilized for decision support. We review various methods that have been or could be applied to evaluate the uncertainty related to deterministic models' outputs. We cover expert judgement, model emulation, sensitivity analysis, temporal and spatial variability in the model outputs, the use of multiple models, and statistical approaches, and evaluate when these methods are appropriate and what must be taken into account when utilizing them. The best way to evaluate the uncertainty depends on the definitions of the source models and the amount and quality of information available to the modeller.",
keywords = "1172 Environmental sciences",
author = "Laura Uusitalo and Annukka Lehikoinen and Inari Helle and Kai Myrberg",
year = "2015",
doi = "10.1016/j.envsoft.2014.09.017",
language = "English",
volume = "63",
pages = "24--31",
journal = "Environmental Modelling & Software",
issn = "1364-8152",
publisher = "ELSEVIER SCI IRELAND LTD",

}

An overview of methods to evaluate uncertainty of deterministic models in decision support. / Uusitalo, Laura; Lehikoinen, Annukka; Helle, Inari; Myrberg, Kai.

julkaisussa: Environmental Modelling & Software, Vuosikerta 63, 2015, s. 24-31.

Tutkimustuotos: ArtikkelijulkaisuKatsausartikkeliTieteellinenvertaisarvioitu

TY - JOUR

T1 - An overview of methods to evaluate uncertainty of deterministic models in decision support

AU - Uusitalo, Laura

AU - Lehikoinen, Annukka

AU - Helle, Inari

AU - Myrberg, Kai

PY - 2015

Y1 - 2015

N2 - There is an increasing need for environmental management advice that is wide-scoped, covering various interlinked policies, and realistic about the uncertainties related to the possible management actions. To achieve this, efficient decision support integrates the results of pre-existing models. Many environmental models are deterministic, but the uncertainty of their outcomes needs to be estimated when they are utilized for decision support. We review various methods that have been or could be applied to evaluate the uncertainty related to deterministic models' outputs. We cover expert judgement, model emulation, sensitivity analysis, temporal and spatial variability in the model outputs, the use of multiple models, and statistical approaches, and evaluate when these methods are appropriate and what must be taken into account when utilizing them. The best way to evaluate the uncertainty depends on the definitions of the source models and the amount and quality of information available to the modeller.

AB - There is an increasing need for environmental management advice that is wide-scoped, covering various interlinked policies, and realistic about the uncertainties related to the possible management actions. To achieve this, efficient decision support integrates the results of pre-existing models. Many environmental models are deterministic, but the uncertainty of their outcomes needs to be estimated when they are utilized for decision support. We review various methods that have been or could be applied to evaluate the uncertainty related to deterministic models' outputs. We cover expert judgement, model emulation, sensitivity analysis, temporal and spatial variability in the model outputs, the use of multiple models, and statistical approaches, and evaluate when these methods are appropriate and what must be taken into account when utilizing them. The best way to evaluate the uncertainty depends on the definitions of the source models and the amount and quality of information available to the modeller.

KW - 1172 Environmental sciences

U2 - 10.1016/j.envsoft.2014.09.017

DO - 10.1016/j.envsoft.2014.09.017

M3 - Review Article

VL - 63

SP - 24

EP - 31

JO - Environmental Modelling & Software

JF - Environmental Modelling & Software

SN - 1364-8152

ER -