Participatory Design for Water Quality Monitoring of Highly Decentralized Water Infrastructure Systems

Project funded by National Science Foundation Division of Behavioral and Cognitive Sciences, Award 2120829 (January 2022 -- December 2023). In collaboration with Alicia Cooperman (TAMU), Alex Mayer (UTEP), and Shane Walker (UTEP).

Aging infrastructure, increasing droughts, groundwater depletion, and contamination of water supplies all challenge America’s drinking water infrastructure. Water typically is treated at central facilities and then piped to users, but recent technological advances could enable water treatment at the point of use (e.g., a house). In theory, this approach can make water systems more resilient to extremes, reduce the need for pipes and pumping, help water systems scale up or down as populations change, and filter contaminants that existing plants cannot treat cost-effectively. However, point of use water treatment also shifts the burden of maintaining water treatment infrastructure, monitoring water quality, and governing water systems onto end users, creating new vulnerabilities for water infrastructure systems. In this project, we are working with residents of colonias in El Paso County, Texas, to codevelop an iterative, collaborative frame­work to stress test strategies for water quality monitoring in decentralized water treatment systems. Many residents of these communities lack access to safe drinking water, and efforts to improve water security are hampered by financial constraints, socio-political marginalization of residents, and lack of surface water sources (see this video).

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The Mississippi River drains a continent, gathering water from as far as Pennsylvania and Montana and discharging it into the Gulf of Mexico. The channeling of so much water into a single river naturally raises the stakes for flooding, and the river has one of the most extensive flood mitigation systems in the world. However, the performance of this infrastructure under a changing climate remains uncertain. Previous studies suggest that the net effect of warming on Mississippi River flood risk is determined by a balance between competing effects: warming accelerates evaporation and reduces snowpack, but on the other hand warmer air generally holds more moisture. This projects seeks to determine the net effect of these competing influences on Mississippi River discharge, which serves as a broad-brush proxy for flood risk, using a combination of weather and streamflow observing networks, paleoclimate reconstructions, and ensembles of present-day and last millennium climate model simulations.

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Fast-growing coastal megacities around the world, including Houston, rely on aging and often inadequate infrastructure to manage evolving weather and climate risks such as flooding. Yet although climate-driven changes in extreme precipitation are already evident in Texas and beyond, current NOAA Atlas 14 frequency analysis methods assume stationarity in both the historical data used in making the estimates and in the future conditions. Thus, infrastructure built today is likely to be underprepared for future climate. In this research, we are combining leverage Earth system observations at multiple timescales (recent radar observations, station observations, and paleoclimate reconstructions) with novel space-time statistical approaches to model the probability distributions of extreme rainfall. This work can inform how existing or alternative engineering codes will perform under actual and anticipated climates.

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