Enhancing Efficacy of Water Quality Trading with Automation: A Case Study in Virginia's Nutrient Trading Program. (10th February 2021)

• Record Type: Journal Article
• Authors: Saby, Linnea; Goodall, Jonathan L.; Band, Lawrence E.; Bowes, Benjamin D.; Fults, Michelle
• Is Part Of: Journal of the American Water Resources Association. Volume 57:Number 3(2021)
• Page Start: 374
• Page End: 390
• Publication Date: 2021-02-10
• Subjects: water quality trading -- automation -- nutrients -- nonpoint source pollution -- environmental regulations -- data management; Water-supply -- Periodicals; Hydrology -- Periodicals; Water resources development -- Periodicals; Water resources development -- Environmental aspects -- Periodicals; 333.9100973
• DOI: 10.1111/1752-1688.12903
• Languages: English
• ISSNs: 1093-474X

Abstract

Abstract: The complexity of water quality trading (WQT) policy can lead to the promulgation of regulations that are challenging to comply with and to enforce. As a result, transaction costs may be high and administrators have limited ability to monitor the program outcomes. These concerns can be alleviated in part through increased automation of trading compliance procedures. We present a case study of a pilot system designed for the Virginia Department of Transportation that automates compliance and streamlines brokering processes that are a part of the Virginia nonpoint source WQT program. Outcomes of this work reveal opportunities and challenges for implementing automated systems in WQT and suggest a framework for developing automated programs. We conclude that use of automated procedures to facilitate compliance with WQT rules can help identify gaps in data reporting and availability, amend inconsistency in rule interpretation, and reduce transaction costs for credit purchasers by enabling efficient analysis of trading opportunities. Persistent limitations to automation exist, including lack of standardized, machine accessible, and open data sources. Potential long‐term benefits of automating WQT processes include minimizing transaction costs, enabling new environmental data collection and policy analysis, and ultimately yielding improved WQT program efficacy and water resources outcomes. Abstract : Research Impact Statement : Automation of water quality trading compliance and brokering procedures can enable more efficient transactions and increase coherence of data about environmental outcomes.