Vermont EPSCoR Publications and Products


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2018
Underwood KL, Rizzo DM, Perdrial JN, Li L, Wen H, Adler T. Application of machine-learning tools to extract patterns in long-term DOC monitoring data: an integrated, multi-scale approach. In: 2018 AGU (American Geophysical Union) Fall Meeting. 2018 AGU (American Geophysical Union) Fall Meeting. Washington, DC: American Geophysical Union (AGU); 2018. Available from: https://agu.confex.com/agu/fm18/meetingapp.cgi/Paper/411757
Perdrial JN, Cincotta MM, Armfield J, Adler T, Shanley JB, Underwood KL, Rizzo DM, Wen H, Li L, Harpold A, et al. Combining long-term observations with experiments to test hypotheses on stream water dissolved organic carbon dynamics at the Sleepers River Research Watershed. In: 2018 AGU (American Geophysical Union) Fall Meeting. 2018 AGU (American Geophysical Union) Fall Meeting. Washington, DC: American Geophysical Union (AGU); 2018. Available from: https://agu.confex.com/agu/fm18/meetingapp.cgi/Paper/407615
2020
Perdrial JN, Adler T, Bristol C, Underwood KL, Rizzo DM, Wen H, Li L, Harpold AA, Sterle G, Hanley J. Combining complex systems analyses with process observations to understand stream dissolved organic carbon across scales. Goldschmidt 2020 [Internet]. 2020 . Available from: https://goldschmidtabstracts.info/2020/2060.pdf
Perdrial JN, Rizzo DM, Underwood KL, Lee BSuk, Toolin R, Seybold EC, Harpold AA, Boisrame G, Abbott BW, Li L, et al. Critical Zone network cluster research: Using Big Data approaches to assess ecohydrological resilience across scales. In: 2020 AGU (American Geophysical Union) Fall Meeting. 2020 AGU (American Geophysical Union) Fall Meeting. Virtual: American Geophysical Union (AGU); 2020. Available from: https://agu.confex.com/agu/fm20/webprogram/Paper748076.html
Wen H, Perdrial JN, Abbott BW, Bernal S, Dupas R, Godsey SE, Harpold A, Rizzo DM, Underwood KL, Adler T, et al. Temperature controls production but hydrology regulates export of dissolved organic carbon at the catchment scale. Hydrology and Earth System Sciences [Internet]. 2020 ;24(2):945 - 966. Available from: https://www.hydrol-earth-syst-sci.net/24/945/2020/hess-24-945-2020.html
Underwood KL, Hanley J, Rizzo DM, Sterle G, Harpold AA, Adler T, Li L, Wen H, Perdrial JN. Use of machine learning to extract patterns from long-term monitoring data across the US. ESA2020 (Harnessing the Ecological Data Revolution) [Internet]. 2020 . Available from: https://eco.confex.com/eco/2020/meetingapp.cgi/Paper/86651
2021
Adler T, Underwood KL, Rizzo DM, Harpold A, Sterle G, Li L, Wen H, Stinson L, Bristol C, Stewart B, et al. Drivers of Dissolved Organic Carbon Mobilization From Forested Headwater Catchments: A Multi Scaled Approach. Frontiers in Water [Internet]. 2021 ;3. Available from: https://www.frontiersin.org/articles/10.3389/frwa.2021.578608/full
2022
Stewart B, Shanley JB, Kirchner JW, Norris D, Adler T, Bristol C, Harpold AA, Perdrial JN, Rizzo DM, Sterle G, et al. Streams as Mirrors: Reading Subsurface Water Chemistry From Stream Chemistry. Water Resources Research [Internet]. 2022 ;58(1). Available from: https://onlinelibrary.wiley.com/doi/10.1029/2021WR029931
2023
Underwood KL, Rizzo DM, Hanley JP, Sterle G, Harpold A, Adler T, Li L, Wen H, Perdrial JN. Machine‐Learning Reveals Equifinality in Drivers of Stream DOC Concentration at Continental ScalesAbstractKey Points. Water Resources Research [Internet]. 2023 ;59(3). Available from: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2021WR030551