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Tradeoffs among Ecosystem Services, Performance Certainty, and Cost-efficiency in Implementation of the Chesapeake Bay Total Maximum Daily Load

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  • Wainger, Lisa A.
  • Van Houtven, George
  • Loomis, Ross
  • Messer, Jay
  • Beach, Robert
  • Deerhake, Marion

Abstract

The cost-effectiveness of total maximum daily load (TMDL) programs depends heavily on program design. We develop an optimization framework to evaluate design choices for the TMDL for the Potomac River, a Chesapeake Bay sub-basin. Scenario results suggest that policies inhibiting nutrient trading or offsets between point and nonpoint sources increase compliance costs markedly and reduce ecosystem service co-benefits relative to a least-cost solution. Key decision tradeoffs highlighted by the analysis include whether agricultural production should be exchanged for low-cost pollution abatement and other environmental benefits and whether lower compliance costs and higher co-benefits provide adequate compensation for lower certainty of water-quality outcomes.

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  • Wainger, Lisa A. & Van Houtven, George & Loomis, Ross & Messer, Jay & Beach, Robert & Deerhake, Marion, 2013. "Tradeoffs among Ecosystem Services, Performance Certainty, and Cost-efficiency in Implementation of the Chesapeake Bay Total Maximum Daily Load," Agricultural and Resource Economics Review, Cambridge University Press, vol. 42(1), pages 196-224, April.
    • Handle: RePEc:cup:agrerw:v:42:y:2013:i:01:p:196-224_00
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    1. Hanson, James C. & McConnell, Kenneth E., 2008. "Simulated Trading for Maryland's Nitrogen Loadings in the Chesapeake Bay," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 37(2), pages 1-16.
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    Cited by:

    1. Hood, Raleigh R. & Shenk, Gary W. & Dixon, Rachel L. & Smith, Sean M.C. & Ball, William P. & Bash, Jesse O. & Batiuk, Rich & Boomer, Kathy & Brady, Damian C. & Cerco, Carl & Claggett, Peter & de Mutse, 2021. "The Chesapeake Bay program modeling system: Overview and recommendations for future development," Ecological Modelling, Elsevier, vol. 456(C).
    2. Fleming, Patrick & Lichtenberg, Erik & Newburn, David A., 2018. "Evaluating impacts of agricultural cost sharing on water quality: Additionality, crowding In, and slippage," Journal of Environmental Economics and Management, Elsevier, vol. 92(C), pages 1-19.
    3. Chai, Yuan & J. Pannell, David & G. Pardey, Philip, 2023. "Nudging farmers to reduce water pollution from nitrogen fertilizer," Food Policy, Elsevier, vol. 120(C).
    4. Ribaudo, Marc & Savage, Jeffrey, 2014. "Controlling non-additional credits from nutrient management in water quality trading programs through eligibility baseline stringency," Ecological Economics, Elsevier, vol. 105(C), pages 233-239.
    5. Uchida, Emi & Swallow, Stephen K. & Gold, Arthur J. & Opaluch, James & Kafle, Achyut & Merrill, Nathaniel H. & Michaud, Clayton & Gill, Carrie Anne, 2018. "Integrating Watershed Hydrology and Economics to Establish a Local Market for Water Quality Improvement: A Field Experiment," Ecological Economics, Elsevier, vol. 146(C), pages 17-25.
    6. Duke, Joshua M. & Liu, Hongxing & Monteith, Tyler & McGrath, Joshua & Fiorellino, Nicole M., 2020. "A method for predicting participation in a performance-based water quality trading program," Ecological Economics, Elsevier, vol. 177(C).

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