Proposed Objectives of the Project:
Use artificial intelligence algorithms to inform Clean Water Act regulation; measure costs of Clean Water Act regulation of land use; study how water quality policy affects human health; study efficiency of groundwater extraction; investigate efficiency of spending on water infrastructure projects.

Summary of Results:

1. A substantially advanced paper builds a machine learning model, WOTUS-ML, to describe what the Clean Water Act (CWA) regulates. The paper has maps of 4 million points across the US and describes CWA regulation at each point under three recent Clean Water Act rules (Obama’s Clean Water Rule, Trump’s Navigable Waters Protection Rule, and the Supreme Court’s Rapanos rule), in addition to describing whether these points are adjacent, abutting, or isolated wetlands; ephemeral, intermittent, or perennial streams; or other water resource types. I hope the paper will be submitted and published in 2023.
2. This paper is in progress, the analysis has preliminary results using Zillow land transaction data (ztrax) that find large costs of CWA regulation (on a parcel that is 10 percent wetlands, CWA regulation decreases the parcel’s value by several percentage points). The analysis has now incorporated both results from NWPR in 2019 and SWANCC in 2000. The analysis needs some extra sensitivity tests, e.g., to account for differences in land use classes over time and space and wetland categories, but hopefully will be ready to start moving from tables and figures to a draft paper later this calendar year.
3. This water quality research is developing rapidly. It received an NIH R01 grant focused on drinking water pollution, and with the goal of preparing the drinking water pollution data to be available to other researchers. This paper has a complete draft that is being polished but has been presented a few times and should be ready for submission to a journal later this year.
4. The groundwater sustainability paper now has a working dynamic programming model to measure the sustainability of groundwater extraction in all major aquifers around the world. The analysis is seeking to incorporate some important hydrological features (e.g., porosity of underground aquifers and pressure).
5. I obtained initial results describing how discontinuities in local ballot initiative vote shares affect water investment. The number of usable initiatives in readily available data is fairly small, so I have put this project on hold while I consider additional ways to approach it.

Specific Objectives of the Project:
The project includes four components:
1. Write analysis re-evaluating the economic logic that the Environmental Protection Agency used to justify the Navigable Waters Protection Rule.
2. Drawing on 2021 keynote I gave to Association of Environmental & Resource Economists, write summary article for Review of Environmental Economics and Policy
3. Use computer vision and artificial intelligence algorithms determining the scope of these water quality regulations
4. Study how drinking water policy affects human health

Summary of Results:
1. This was published at REEP (Keiser et al., listed at bottom), discussed with EPA staff, and the underlying report is cited extensively in the economic analysis of the Biden Administration’s new Clean Water Act rule (the revised definition of the ‘Waters of the United States’), cited below.
2. This was published as a separate article at REEP (citation listed at bottom of this report).
3. I have substantially advanced the research using computer vision and artificial intelligence algorithms. The EPA’s Economic Analysis includes text specifically calling for this analysis, which EPA staff told us they included to give more time for us to finish the analysis and so they could then use it in their new rulings. The status as of 8/29/22 is that this research has a convolutional neural network that uses near-infrared wavelengths from the National Agriculture Imagery Program (NAIP); rasterized data from the National Wetlands Inventory; and it is in the process of adding rasterized data from the National Hydrography Dataset, Soil Survey data (SSURGO), Sentinel satellite data, and others. The Supreme Court will hear hearings on Sackett v. EPA, a very related case, on October 3, 2022, and our goal is to publish a high-quality scholarly journal article before the Supreme Court’s decision is released in spring 2023, so a revised EPA rule could use our analysis as a potential input. While the analysis is moving forward rapidly every week, completing it carefully and fully with all these data takes a good amount of time in total.
4. This work has advanced substantially; the analysis has a working panel micro database of drinking water pollution measures for over 35 US states including many pesticides, linked to census blocks where people who drink the water live, health outcomes, and investments made through the Safe Drinking Water Act.

Specific Objectives of the Project:
Re-examine the economic logic that the US Environmental Protection Agency used to justify the Navigable Waters Protection Rule; use machine learning and artificial intelligence algorithms to determine the scope of these water quality regulations.

Project Report/Summary of Results:
The first component resulted in a published publicly available report that received media coverage. It also resulted in a peer-reviewed journal article in Science.

The second component trailed a number of graduate students, and resulted in a preliminary set of results and series of meetings with senior staff at the US Environmental Protection Agency to convey the approach and initial results. This is an ongoing project that will involve research and policymaker outreach over multiple years as the EPA revises the Clean Water Act.

Specific Objectives of the Project: Assess the efficiency of water quality regulation over the last 50 years, the importance of the weak regulation for water pollution for agriculture, and the potential of new regulatory tools to efficiently regulate water pollution.

Project Report/Summary of Results:
With support from this grant, this project resulted in two papers published in high-impact journals. These papers investigate the effectiveness and efficiency of US water quality policy, including soil and water conservation programs sponsored by the U.S. Department of Agriculture. The research reviews the last 50 years, discusses differences between regulation of point (primarily industrial and municipal) and non-point (primarily agricultural) source regulation, including data analysis from records in California and other states. The research discusses some new regulatory efforts, including Total Maximum Daily Load requirements, cap-and-trade markets for water pollution, and recent debates over regulating water quality in agriculture through debates following the Supreme Court’s SWANCC and Rapanos decisions, including the Obama Administration’s Waters of the United States rule.

This and related research has been widely discussed in the media, including over 20
(mostly national) news stories, received 800 comments and 45,000 views as the top science story on Reddit, and was featured in a Voxeu article.

This project also compiled extensive drinking water data for research on drinking water quality regulation. Extensive cleaning has been undertaken of the drinking water data, and ongoing research is linking this to other datasets for use in ongoing research on drinking water quality and agriculture.