Machine learning predicts which rivers, streams, and wetlands the Clean Water Act regulates.

Journal: Science (New York, N.Y.)
Published Date: Jan 25, 2024

Abstract

We assess which waters the Clean Water Act protects and how Supreme Court and White House rules change this regulation. We train a deep learning model using aerial imagery and geophysical data to predict 150,000 jurisdictional determinations from the Army Corps of Engineers, each deciding regulation for one water resource. Under a 2006 Supreme Court ruling, the Clean Water Act protects two-thirds of US streams and more than half of wetlands; under a 2020 White House rule, it protects less than half of streams and a fourth of wetlands, implying deregulation of 690,000 stream miles, 35 million wetland acres, and 30% of waters around drinking-water sources. Our framework can support permitting, policy design, and use of machine learning in regulatory implementation problems.

Authors

  • Simon Greenhill
    Department of Agricultural and Resource Economics, University of California, Berkeley, Berkeley, CA 94720, USA.
  • Hannah Druckenmiller
    Resources for the Future, Washington, DC 20036, USA.
  • Sherrie Wang
    Goldman School of Public Policy, University of California, Berkeley, Berkeley, CA 94720, USA.
  • David A Keiser
    Department of Resource Economics, University of Massachusetts, Amherst, Amherst, MA 010013, USA.
  • Manuela Girotto
    Department of Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, CA 94720, USA.
  • Jason K Moore
    US Department of Energy, Washington, DC 20585, USA.
  • Nobuhiro Yamaguchi
    School of Information, University of California, Berkeley, Berkeley, CA 94720, USA.
  • Alberto Todeschini
    School of Information, University of California, Berkeley, Berkeley, CA 94720, USA.
  • Joseph S Shapiro
    Department of Agricultural and Resource Economics, University of California, Berkeley, Berkeley, CA 94720, USA.

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