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A Risk-Informed Decision-Making Framework for Climate Change Adaptation through Robust Land Use and Irrigation Planning

Author

Listed:
  • Tatiana Ermolieva

    (International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria)

  • Petr Havlik

    (International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria)

  • Stefan Frank

    (International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria)

  • Taher Kahil

    (International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria)

  • Juraj Balkovic

    (International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria)

  • Rastislav Skalsky

    (International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria)

  • Yuri Ermoliev

    (International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria)

  • Pavel S. Knopov

    (Institute of Cybernetics, 03187 Kiev, Ukraine)

  • Olena M. Borodina

    (Institute of Economics and Forecasting, 01011 Kiev, Ukraine)

  • Vasyl M. Gorbachuk

    (Institute of Cybernetics, 03187 Kiev, Ukraine)

Abstract

Uncertainty and variability are key challenges for climate change adaptation planning. In the face of uncertainty, decision-making can be addressed in two interdependent stages: make only partial ex ante anticipative actions to keep options open until new information is revealed, and adapt the first-stage decisions with respect to newly acquired information. This decision-making approach corresponds to the two-stage stochastic optimization (STO) incorporating both anticipative ex ante and adaptive ex post decisions within a single model. This paper develops a two-stage STO model for climate change adaptation through robust land use and irrigation planning under conditions of uncertain water supply. The model identifies the differences between decision-making in the cases of perfect information, full uncertainty, and two-stage STO from the perspective of learning about uncertainty. Two-stage anticipative and adaptive decision-making with safety constraints provides risk-informed decisions characterized by quantile-based Value-at-Risk and Conditional Value-at-Risk risk measures. The ratio between the ex ante and ex post costs and the shape of uncertainty determine the balance between the anticipative and adaptive decisions. Selected numerical results illustrate that the alteration of the ex ante agricultural production costs can affect crop production, management technologies, and natural resource utilization.

Suggested Citation

  • Tatiana Ermolieva & Petr Havlik & Stefan Frank & Taher Kahil & Juraj Balkovic & Rastislav Skalsky & Yuri Ermoliev & Pavel S. Knopov & Olena M. Borodina & Vasyl M. Gorbachuk, 2022. "A Risk-Informed Decision-Making Framework for Climate Change Adaptation through Robust Land Use and Irrigation Planning," Sustainability, MDPI, vol. 14(3), pages 1-14, January.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:3:p:1430-:d:734916
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    References listed on IDEAS

    as
    1. Yuri Ermoliev & Detlof Winterfeldt, 2012. "Systemic Risk and Security Management," Lecture Notes in Economics and Mathematical Systems, in: Yuri Ermoliev & Marek Makowski & Kurt Marti (ed.), Managing Safety of Heterogeneous Systems, edition 127, pages 19-49, Springer.
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