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Hydrologists and water managers increasingly face challenges associated with extreme climatic events. At the same time, historic datasets for modeling contemporary and future hydrologic conditions are increasingly inadequate. Machine learning is one promising technological tool for navigating the challenges of understanding and managing contemporary hydrological systems. However, in addition to the technical challenges associated with effectively leveraging ML for understanding subsurface hydrological processes, practitioner skepticism and hesitancy surrounding ML presents a significant barrier to adoption of ML technologies among practitioners. In this paper, we discuss an educational application we have developed—Sandtank-ML—to be used as a training and educational tool aimed at building user confidence and supporting adoption of ML technologies among water managers. We argue that supporting the adoption of ML methods and technologies for subsurface hydrological investigations and management requires not only the development of robust technologic tools and approaches, but educational strategies and tools capable of building confidence among diverse users.
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This content will become publicly available on December 1, 2025
Understanding the intersecting social, technical, and ecological systems challenges associated with emerging contaminants in drinking water using cyanotoxins as an example
Abstract This paper investigates toxic algal blooms (TABs) and their management as an example of a complex emerging contaminant (EC) problem through the lens of interconnected social, technical, ecological systems (SETS). We use mixed methods including analysis of a national survey of public drinking water systems and interviews with drinking water managers and state regulators. For the first time, we extend SETS to the drinking water context to advance a holistic understanding of the complexity of TABs as a problem for drinking water systems and identify specific intervention points to ease TABs management difficulty. We find that management challenges arise at the intersection of SET domains, and often coincide with circumstances where water managers and existing technologies are pushed outside of their traditional operating spheres or when new technologies are introduced creating cascading SET challenges. ECs that do not behave like traditional contaminants and pollutants require adapting social and technical systems to be responsive to these differences. Understanding how management difficulties arise within SET domains and their intersections will help drinking water managers and state regulators mitigate management difficulties in the future. These findings have implications for understanding and mitigating other EC management challenges as well.
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- Award ID(s):
- 2108917
- PAR ID:
- 10562292
- Publisher / Repository:
- Springer
- Date Published:
- Journal Name:
- Journal of Infrastructure Preservation and Resilience
- Volume:
- 5
- Issue:
- 1
- ISSN:
- 2662-2521
- Subject(s) / Keyword(s):
- Emerging contaminants cyanotoxins socio-technical systems socio-ecological systems global environmental change SETS
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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