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Value of decadal climate variability information for agriculture in the Missouri River basin

Author

Listed:
  • Mario Andres Fernandez

    (Auckland Council)

  • Pei Huang

    (S&P Global Platts)

  • Bruce McCarl

    (Texas A&M University)

  • Vikram Mehta

    (Center for Research on the Changing Earth)

Abstract

This study estimates economic value and management adaptations associated with decadal climate variability (DCV) information. We develop a stylized model to illustrate the value of climate information where agricultural decisions are conditional to different sets of DCV information. The decision maker can adjust management given such information where the economic value and associated adaptations are of interest. The framework is implemented within a stochastic programming model that simulates market activities and welfare changes under different probability distributions on DCV phase occurrence in the Missouri River Basin (MRB), the largest river basin in the USA. This basin produces approximately 46 % of the wheat, 33 % of the cattle, and 26 % of the grain corn in the USA. The results show that a conditional DCV information generates net benefits of $28.84 million annually, while the perfect information results in net benefits of $82.30 million. In addition, crop acreage shifts and the extent of irrigation vary with different DCV information. This study shows that the benefits gained from accurate climate information may address the producers’ needs across a range of DCV scenarios characterized by the persistence of the impacts. Most notably, this is the first economic study to our knowledge to investigate the combined occurrence of three DCV phenomena, and the joint and persistent impacts over crop yields. Our results provide compelling evidence for long-term planning of crop mix selection, and infrastructure related to water irrigation mechanisms.

Suggested Citation

  • Mario Andres Fernandez & Pei Huang & Bruce McCarl & Vikram Mehta, 2016. "Value of decadal climate variability information for agriculture in the Missouri River basin," Climatic Change, Springer, vol. 139(3), pages 517-533, December.
    • Handle: RePEc:spr:climat:v:139:y:2016:i:3:d:10.1007_s10584-016-1807-x
    DOI: 10.1007/s10584-016-1807-x
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    1. Mjelde, J. W. & Hill, H. S. J., 1999. "The effect of the use of improved climate forecasts on variable costs, input usage, and production," Agricultural Systems, Elsevier, vol. 60(3), pages 213-225, June.
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    Cited by:

    1. Francesco Cavazza & Francesco Galioto & Meri Raggi & Davide Viaggi, 2020. "Digital Irrigated Agriculture: Towards a Framework for Comprehensive Analysis of Decision Processes under Uncertainty," Future Internet, MDPI, vol. 12(11), pages 1-16, October.
    2. Cavazza, F. & Galioto, F. & Raggi, M. & Viaggi, D., 2018. "Changes in the information environment of water management: the role of ICT," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277247, International Association of Agricultural Economists.
    3. Vikram M. Mehta & Katherin Mendoza & Norman J. Rosenberg & Raghavan Srinivasan, 2021. "High-resolution simulations of decadal climate variability impacts on spring and winter wheat yields in the Missouri River Basin with the Soil and Water Assessment Tool (SWAT)," Climatic Change, Springer, vol. 168(3), pages 1-19, October.

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