Full Title: Machine Learning Predicts Which Rivers, Streams, and Wetlands the Clean Water Act Regulates
Author(s): Simon Greenhill, Hannah Druckenmiller, Sherrie Wang, David A. Keiser, Manuela Girotto, Jason K. Moore, Nobuhiro Yamaguchi, Alberto Todeschini, and Joseph S. Shapiro
Publisher(s): Haas School of Business at University of California, Berkeley
Publication Date: February 19, 2024
Full Text: Download Resource
Description (excerpt):
They assess which waters the Clean Water Act protects and how Supreme Court and White House rules change this regulation. They 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 over half of wetlands; under a 2020 White House rule, it protects under 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. Their framework can support permitting, policy design, and use of machine learning in regulatory implementation problems.