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


Journal

Science (New York, N.Y.)
ISSN: 1095-9203
Titre abrégé: Science
Pays: United States
ID NLM: 0404511

Informations de publication

Date de publication:
26 Jan 2024
Historique:
medline: 25 1 2024
pubmed: 25 1 2024
entrez: 25 1 2024
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 38271507
doi: 10.1126/science.adi3794
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

406-412

Auteurs

Simon Greenhill (S)

Department of Agricultural and Resource Economics, University of California, Berkeley, Berkeley, CA 94720, USA.
Goldman School of Public Policy, University of California, Berkeley, Berkeley, CA 94720, USA.

Hannah Druckenmiller (H)

Resources for the Future, Washington, DC 20036, USA.
Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA 91125, USA.

Sherrie Wang (S)

Goldman School of Public Policy, University of California, Berkeley, Berkeley, CA 94720, USA.
Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

David A Keiser (DA)

Department of Resource Economics, University of Massachusetts, Amherst, Amherst, MA 010013, USA.
Center for Agricultural and Rural Development, Iowa State University, Ames, IA 50011, USA.
National Bureau of Economic Research, Cambridge, MA 02139, USA.

Manuela Girotto (M)

Department of Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, CA 94720, USA.

Jason K Moore (JK)

US Department of Energy, Washington, DC 20585, USA.

Nobuhiro Yamaguchi (N)

School of Information, University of California, Berkeley, Berkeley, CA 94720, USA.

Alberto Todeschini (A)

School of Information, University of California, Berkeley, Berkeley, CA 94720, USA.

Joseph S Shapiro (JS)

Department of Agricultural and Resource Economics, University of California, Berkeley, Berkeley, CA 94720, USA.
National Bureau of Economic Research, Cambridge, MA 02139, USA.
Department of Economics, University of California, Berkeley, Berkeley, CA 94720, USA.

Classifications MeSH