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Optimal groundwater management under climate change and technical progress

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  • Quintana Ashwell, Nicolas E.
  • Peterson, Jeffrey M.
  • Hendricks, Nathan P.

Abstract

We develop a dynamic model of groundwater extraction for irrigation where climate change and technical change are included as exogenous state variables in addition to the usual state variable of the stock of groundwater. Our key contributions are (i) an intuitive description of the conditions under which groundwater extraction can be non-monotonic, (ii) a numerical demonstration that extraction is non-monotonic in an important region overlying the Ogallala Aquifer, and (iii) the predicted gains from management are substantially larger after accounting for climate and technical change. Intuitively, optimal extraction is increasing in early periods when the marginal benefits of extraction are increasing sufficiently fast due to climate and technical change compared to the increase in the marginal cost of extraction. In contrast, most previous studies include the stock of groundwater as the only state variable and recommend a monotonically decreasing extraction path. We conduct numerical simulations for a region in Kansas overlying the Ogallala Aquifer and find that optimal groundwater extraction peaks 23 years in the future and the gains from management are large (29.5%). Consistent with previous literature, the predicted gains from management are relatively small (6.1%) when ignoring climate and technical change. The realized gains from management are not substantially impacted by incorrect assumptions of climate and technical change when formulating the optimal plan.

Suggested Citation

  • Quintana Ashwell, Nicolas E. & Peterson, Jeffrey M. & Hendricks, Nathan P., 2018. "Optimal groundwater management under climate change and technical progress," Resource and Energy Economics, Elsevier, vol. 51(C), pages 67-83.
    • Handle: RePEc:eee:resene:v:51:y:2018:i:c:p:67-83
    DOI: 10.1016/j.reseneeco.2017.10.005
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    References listed on IDEAS

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    Cited by:

    1. Amanda M. Nelson & Nicolas E. Quintana Ashwell & Christopher D. Delhom & Drew M. Gholson, 2022. "Leveraging Big Data to Preserve the Mississippi River Valley Alluvial Aquifer: A Blueprint for the National Center for Alluvial Aquifer Research," Land, MDPI, vol. 11(11), pages 1-17, October.
    2. Lee, Juhee & Hendricks, Nathan P., 2022. "Crop Choice Decisions in Response to Soil Salinization on Irrigated Land in California," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322602, Agricultural and Applied Economics Association.
    3. Abbas Roozbahani & Ebrahim Ebrahimi & Mohammad Ebrahim Banihabib, 2018. "A Framework for Ground Water Management Based on Bayesian Network and MCDM Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(15), pages 4985-5005, December.
    4. Lee, Juhee & Hendricks, Nathan, 2022. "Irrigation Decisions in Response to Groundwater Salinity in Kansas," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 47(3), September.

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