Exploring The Application Of Good Neighbor Agreements As Legal Mech
Presenter: David Morales1
Co-Author(s): -
Advisor(s): Dr. P.A. Ty Ferré
1Department of Hydrology and Atmospheric Sciences, University of Arizona
Hydrogeologists commonly inform decision makers by predicting the impacts of proposed activities on future water resources. In many cases, one stakeholder hires them to perform analyses that are most relevant to their decisions, leaving other stakeholders to make decisions based on a model that is less well-suited—or even inappropriate—to account for the concerns that are central to their decision context. One approach to address this disconnect and provide predictions relevant to all stakeholders is to build an ensemble of models that span the range of plausible conditions. This ensures that all stakeholders can make better-informed decisions; but it raises a difficult practical question. How can all stakeholders come to consensus decisions based on multiple, possibly conflicting models? One path forward may be through Good Neighbor Agreements (GNAs) which are legally binding agreements developed between a business and another party to direct concerns and expectations regarding the potential impacts of business’ operations on the local environment and community. With these agreements, stakeholders can agree upon a course of action, possibly based on one model or a combination of models, with caveats that account for the predictions of other models in the ensemble. This allows all parties to make decisions based on the best available science with contingencies to address uncertainties. My work will use artificial intelligence to conduct an initial analysis of the structure of GNAs and then propose a GNA that supports water-resources negotiations that will achieve more fair, equitable, and positive outcomes in Southern Arizona.