How to Distribute Water Fairly in Times of Scarcity

A Participatory and Simulation-Based Process towards Distribution Policies for Guadalajara’s Aquapheric with a Distributive Justice and Deep Uncertainty Approach

Master thesis (2024)

Authors

A. Goldin Marcovich Technology, Policy and Management

Contributors

J. Zatarain Salazar Policy Analysis - TPM (mentor)
N. Doorn (graduation committee member)
Edmundo Molina-Perez Tecnologico de Monterrey (graduation committee member)
Faculty
Technology, Policy and Management
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Published Date

27-09-2024

Language

English

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Faculty

Technology, Policy and Management

Abstract

The city of Guadalajara, Mexico, is facing increasing challenges in supplying enough water to its five million inhabitants. To adapt the city’s water supply system to worsening drought conditions, some key vulnerabilities need to be addressed. The city’s water supply system is compartmentalised, meaning that each one of its four main sources supplies a specific area of the city. Thus, if one source underperforms, one area of the city will not have enough water, and the other sources cannot compensate. This situation happened in 2021, when one of its sources reached critical levels leaving around 500,000 inhabitants without water supply for over 3 months. To combat this vulnerability the city built the Aquapheric: a circular aqueduct that interconnects the supply areas and can pump up to 1m3/s in both directions in each segment independently. However, the government has not developed a distribution policy for this infrastructure.

This project proposes a participatory and simulation-based process for designing a Decision Support Tool (DST) that could serve as the basis for a Distribution Policy for the Aquapheric. Such policy would determine how much water should flow in each segment of the Aquapheric under the current drought conditions based on a set of objectives selected by policymakers. The pool of objectives available was defined via an in-person participatory workshop that was conducted with over 26 members of the local government and academia. The Distributive Justice Principles framework was used to guide the ethical discussion during the workshop and to develop the mathematical formulations of the objectives. A problem formulation for a Multi-Objective Optimization algorithm was designed to find the best performing and best compromise policies for the objectives that policy-makers select on the DST.

The theoretical discussions in this research focus on how deep uncertainty, particularly that related to values, can be tackled by offering tools based on simple models, built with participatory knowledge co-creation processes and that enable learning and flexibility as opposed to robustness.