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Practice and perspectives in the validation of resource management models

Author

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  • Sibel Eker

    (International Institute for Applied Systems Analysis (IIASA))

  • Elena Rovenskaya

    (International Institute for Applied Systems Analysis (IIASA)
    Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University)

  • Michael Obersteiner

    (International Institute for Applied Systems Analysis (IIASA))

  • Simon Langan

    (International Institute for Applied Systems Analysis (IIASA))

Abstract

Quantitative modelling is commonly used to assist the policy dimension of sustainability problems. Validation is an important step to make models credible and useful. To investigate existing validation viewpoints and approaches, we analyse a broad academic literature and conduct a survey among practitioners. We find that empirical data plays an important role in the validation practice in all main areas of sustainability science. Qualitative and participatory approaches that can enhance usefulness and public reliability are much less visible. Data-oriented validation is prevalent even when models are used for scenario exploration. Usefulness regarding a given task is more important for model developers than for users. As the experience of modellers and users increases, they tend to better acknowledge the decision makers’ demand for clear communication of assumptions and uncertainties. These findings provide a reflection on current validation practices and are expected to facilitate communication at the modelling and decision-making interface.

Suggested Citation

  • Sibel Eker & Elena Rovenskaya & Michael Obersteiner & Simon Langan, 2018. "Practice and perspectives in the validation of resource management models," Nature Communications, Nature, vol. 9(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-07811-9
    DOI: 10.1038/s41467-018-07811-9
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    Cited by:

    1. Andrea Saltelli & Arnald Puy, 2023. "What can mathematical modelling contribute to a sociology of quantification?," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-8, December.
    2. Bram Govaerts & Christine Negra & Tania Carolina Camacho Villa & Xiomara Chavez Suarez & Anabell Diaz Espinosa & Simon Fonteyne & Andrea Gardeazabal & Gabriela Gonzalez & Ravi Gopal Singh & Victor Kom, 2021. "One CGIAR and the Integrated Agri-food Systems Initiative: From short-termism to transformation of the world’s food systems," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-15, June.
    3. Fan He & Yang Yang & Xin Liu & Dong Wang & Junping Ji & Zhibin Yi, 2021. "Input–Output Analysis of China’s CO 2 Emissions in 2017 Based on Data of 149 Sectors," Sustainability, MDPI, vol. 13(8), pages 1-27, April.
    4. Charlie Wilson & Céline Guivarch & Elmar Kriegler & Bas Ruijven & Detlef P. Vuuren & Volker Krey & Valeria Jana Schwanitz & Erica L. Thompson, 2021. "Evaluating process-based integrated assessment models of climate change mitigation," Climatic Change, Springer, vol. 166(1), pages 1-22, May.
    5. Planque, Benjamin & Aarflot, Johanna M. & Buttay, Lucie & Carroll, JoLynn & Fransner, Filippa & Hansen, Cecilie & Husson, Bérengère & Langangen, Øystein & Lindstrøm, Ulf & Pedersen, Torstein & Primice, 2022. "A standard protocol for describing the evaluation of ecological models," Ecological Modelling, Elsevier, vol. 471(C).
    6. Sibel Eker, 2020. "Validity and usefulness of COVID-19 models," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-5, December.
    7. Katzin, David & van Henten, Eldert J. & van Mourik, Simon, 2022. "Process-based greenhouse climate models: Genealogy, current status, and future directions," Agricultural Systems, Elsevier, vol. 198(C).
    8. Btool H. Mohamed & Ibrahim Ari & Mohammed bin Saleh Al-Sada & Muammer Koç, 2021. "Strategizing Human Development for a Country in Transition from a Resource-Based to a Knowledge-Based Economy," Sustainability, MDPI, vol. 13(24), pages 1-27, December.

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