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Integrated Management of the South Oahu Aquifer System: A Spatial and Temporal Approach

Author

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  • James Roumasset

    (Department of Economics, University of Hawaii at Manoa)

  • Christopher Wada

    (Department of Economics, University of Hawaii at Manoa)

Abstract

Although the economics of groundwater management is typically modelled as a single aquifer serving a single group of consumers, resource managers must often decide how to manage multiple aquifers simultaneously. We propose a temporal and spatial model to determine the efficient allocation of groundwater when two coastal aquifers are available for exploitation. Along the optimal trajectory extraction may switch from single to simultaneous use, depending on how the total marginal cost of each resource evolves over time. A numerical simulation for the South Oahu aquifer system illustrates the switching behavior.

Suggested Citation

  • James Roumasset & Christopher Wada, 2009. "Integrated Management of the South Oahu Aquifer System: A Spatial and Temporal Approach," Working Papers 200902, University of Hawaii at Manoa, Department of Economics.
  • Handle: RePEc:hai:wpaper:200902
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    File URL: http://www.economics.hawaii.edu/research/workingpapers/WP_09-2.pdf
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    References listed on IDEAS

    as
    1. Darrell Krulce & James A. Roumasset & Tom Wilson, 1997. "Optimal Management of a Renewable and Replaceable Resource: The Case of Coastal Groundwater," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(4), pages 1218-1228.
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    More about this item

    Keywords

    Renewable resources; dynamic optimization; multiple resources;
    All these keywords.

    JEL classification:

    • Q25 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Water
    • Q28 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Government Policy
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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