Vermont EPSCoR Publications and Products


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Arnoldy F, Garrido M, Wong A, Pratt S, Braddish T, Brown G, Reblin M, Rizzo DM, Gramling R. Protocol for a Scalable StoryListening Intervention for Grief-Related Loneliness During COVID-19. Palliative Medicine Reports [Internet]. 2023 ;4(1):208 - 213. Available from: https://www.liebertpub.com/doi/full/10.1089/pmr.2023.0009
Hamshaw SD, Underwood KL, Rizzo DM, Bomblies A. Prediction of suspended sediment in rivers using artificial neural networks and future climate scenarios. NOAA 14th Annual Climate Prediction Applications Science Workshop [Internet]. 2016 . Available from: http://www.uvm.edu/~cpasw/agenda/CPASW_2016_Agenda.pdf
Hamshaw SD, Underwood KL, Rizzo DM, Wemple B, Dewoolkar MM. Prediction of suspended sediment in rivers using artificial neural networks: Implications for development of sediment budgets. In: 2013 AGU (American Geophysical Union) Fall Meeting. 2013 AGU (American Geophysical Union) Fall Meeting. San Francisco, CA: American Geophysical Union (AGU); 2013.
Wiegman A, Augustin IC, Kubow ML, Fein-Cole M, Meyers GHarrison, Ross DS, Wemple BC, Diehl RM, Rizzo DM, Underwood KL, et al. Predicting Post-Restoration Risk of Soil Legacy Phosphorus Release in Historically Drained and Farmed Riparian Wetlands. 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/Paper680719.html
Porterfield KK, Faulkner J, Joblin R, Neher D, Curtis M, Dvorak S, Rizzo DM, Roy ED. Phosphorus recovery and reuse from anaerobically digested dairy manure. AEES 2020 Virtual Poster Symposium [Internet]. 2020 . Available from: https://2020aeesposters.com/phosphorus-recovery-and-reuse-from-anaerobically-digested-dairy-manure/
Doran EMB, Zia A, Rizzo DM, Tsai Y-S, Koliba C. A phase space approach to understanding the efficacy of agricultural BMP adoption on water quality under a range of socio-ecological scenarios using a watershed scale, feed-forward integrated assessment model. 2018 AGU (American Geophysical Union) Fall Meeting [Internet]. 2018 . Available from: https://agu.confex.com/agu/fm18/meetingapp.cgi/Paper/454283
Gramling CJ, Macha N, Lawrenz A, Milukas L, Graber T, Gerson NW, Rizzo DM, Gramling R, Alexander SC. Patient Expressions of Loneliness and Human Connection in Palliative Care Consultations. In: ICCH 2023 (International Conference on Communication in Healthcare). ICCH 2023 (International Conference on Communication in Healthcare). Rio Grande, Puerto Rico: Academy of Communication in Healthcare (ACH); 2023. Available from: https://www.achonline.org/ICCH2023
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Javed A, Hamshaw SD, Lee BSuk, Rizzo DM. Multivariate event time series analysis using hydrological and suspended sediment data. Journal of Hydrology [Internet]. 2021 ;593:125802. Available from: https://www.sciencedirect.com/science/article/pii/S0022169420312634
Pechenick AM, Rizzo DM, Morrissey LA, Garvey KM, Underwood KL, Wemple B. A multi-scale statistical approach to assess the effects of connectivity of road and stream networks on geomorphic channel condition. Earth Surface Processes and Landforms [Internet]. 2014 ;39(11):1538 - 1549. Available from: http://onlinelibrary.wiley.com/doi/10.1002/esp.3611/epdf
Nguyen L, Hamshaw SD, Javed A, Rizzo DM. A Monitoring Tool for Analyzing Sediment Dynamics Using Water Turbidity Sensor Data. 2020 AGU (American Geophysical Union) Fall Meeting [Internet]. 2020 . Available from: https://agu.confex.com/agu/fm20/webprogram/Paper748005.html
Hamshaw SD, Dewoolkar MM, O'Neil-Dunne J, Engel T, Rizzo DM, Frolik J, Bryce TG. Monitoring Fluvial Geomorphic Change Using Unmanned Aircraft System (UAS) Photogrammetry and Laser Scanning. In: 2018 GSA (Geological Society of America) Northeastern Section 53rd Annual Meeting. 2018 GSA (Geological Society of America) Northeastern Section 53rd Annual Meeting. Burlington, VT: Geological Society of America (GSA); 2018. Available from: https://gsa.confex.com/gsa/2018NE/meetingapp.cgi/Paper/309724
Xu Y, Rizzo DM, Schroth AW. A modified framework for trophic status assessment of large lake ecosystems using existing water quality datasets: Application to Lake Champlain. In: New England Association of Environmental Biologists (NEAEB) Annual Conference. New England Association of Environmental Biologists (NEAEB) Annual Conference. ; 2014. Available from: http://www.epa.gov/region1/neaeb2014/pdfs/NEAEB2014ConferenceAbstracts.pdf
Hecht JS, Zia A, Clemins PJ, Schroth AW, Winter JM, Oikonomou PD, Rizzo DM. Modeling the sensitivity of cyanobacteria blooms to plausible changes in precipitation and air temperature variability. Science of The Total Environment [Internet]. 2021 ;812:151586. Available from: https://www.sciencedirect.com/science/article/pii/S004896972106664X
Ren Q, Zia A, Rizzo DM, Mathews N. Modeling the Influence of Public Risk Perceptions on the Adoption of Green Stormwater Infrastructure: An Application of Bayesian Belief Networks Versus Logistic Regressions on A Statewide Survey of Households in Vermont. Water [Internet]. 2020 ;12(10):2793. Available from: https://www.mdpi.com/2073-4441/12/10/2793
Isles PDF, Rizzo DM, Xu Y, Schroth AW. Modeling the drivers of interannual variability in cyanobacterial bloom severity using self-organizing maps and high-frequency data. Inland Waters [Internet]. 2017 . Available from: http://www.tandfonline.com/doi/full/10.1080/20442041.2017.1318640
Shakun JD, Corbett LB, Bierman PR, Underwood KL, Rizzo DM, Zimmerman SR, Caffee MW, Naish T, Golledge NR, Hay CC. Minimal East Antarctic Ice Sheet retreat onto land during the past eight million years. Nature [Internet]. 2018 ;558:284 - 287. Available from: https://www.nature.com/articles/s41586-018-0155-6
Sanders JJ, Blanch-Hartigan D, Ericson J, Tarbi E, Rizzo DM, Gramling R, vanVliet L. Methodological innovations to strengthen evidence-based serious illness communication. Patient Education and Counseling [Internet]. 2023 ;114:107790. Available from: https://www.sciencedirect.com/science/article/abs/pii/S0738399123001702
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

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