Vermont EPSCoR Publications and Products
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. Unraveling sediment dynamics in the Mad River watershed through event concentration-discharge relationships and multi-temporal UAS surveys. In: 2018 CERM (Catskill Environmental Research & Monitoring) Conference. 2018 CERM (Catskill Environmental Research & Monitoring) Conference. Highmount, NY: Ashokan Watershed Stream Management Program; 2018. Available from: http://ashokanstreams.org/wp-content/uploads/2016/09/5-Hamshaw_CERM2018.pdf
. Watershed data science at the event scale: Revealing insights in watershed function through analysis of concentration-discharge relationships. 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/Paper766889.html
. Quantifying streambank erosion using unmanned aerial systems at the site-specific and river network scales. In: Geo-Congress 2017 (Geotechnical Frontiers). Geo-Congress 2017 (Geotechnical Frontiers). Orlando, FL; 2017.
. Suspended Sediment Prediction Using Artificial Neural Networks and Local Hydrometeorological Data (M.S. Thesis). Burlington VT: University of Vermont; 2014.
. Applying Deep Learning to Event Concentration-Discharge Hysteresis Patterns to Reveal Differences in Sediment Dynamics across Contrasting Watersheds. 2018 AGU (American Geophysical Union) Fall Meeting [Internet]. 2018 . Available from: https://agu.confex.com/agu/fm18/meetingapp.cgi/Paper/355901
. Watershed data science at the event scale: Machine learning for event concentration-discharge analysis. Virtual Summit: Incorporating Data Science and Open Science Techniques in Aquatic Research [Internet]. 2020 . Available from: https://freshwaterecology.wordpress.com/2020/07/08/conference-workshop-virtual-summit-incorporating-data-science-and-open-science-techniques-in-aquatic-research/
. Unmanned Aircraft System (UAS) Photogrammetry for Tracking Streambank Erosion and Geomorphic Change along a Protected River Corridor. In: Eighth International Conference on Case Histories in Geotechnical Engineering. Eighth International Conference on Case Histories in Geotechnical Engineering. Philadelphia, PA: Geo-Institute of ASCE (American Society of Civil Engineers); 2019. Available from: https://ascelibrary.org/doi/10.1061/9780784482070.015
. 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.
. High Frequency Turbidity Monitoring to Quantify Sediment Loading in the Mad River. 2014 NEAEB Conference. 2014 [cited 0BC].
. Suspended Sediment Prediction. In: 2014 NEAEB. 2014 NEAEB. Burlington VT; 2014.
. Suspended Sediment Prediction Using Artificial Neural Networks and Local Hydrometeorological Data. 2014 NEAEB Conference. 2014 .
. Sediment Loading and Sources in the Mad River: Implications for sediment-bound nutrient management. IAGLR 2015 [Internet]. 2015 . Available from: http://www.iaglr.org/conference/downloads/2015_program.pdf
. Using Distributed Continuous Turbidity Monitoring to Inform Sediment and Sediment-bound Nutrient Budgets in a Small Watershed. 2014 AGU (American Geophysical Union) Fall Meeting. 2014 .
. A Tandem Evolutionary Algorithm for Identifying Causal Rules from Complex Data. Evolutionary Computation [Internet]. 2019 :1 - 32. Available from: https://www.mitpressjournals.org/doi/abs/10.1162/evco_a_00252
. Geospatial and Temporal Analysis of Thyroid Cancer Incidence in a Rural Population. Thyroid [Internet]. 2015 ;25(7):812 - 822. Available from: http://online.liebertpub.com/doi/10.1089/thy.2015.0039
. A Novel Evolutionary Algorithm for Mining Noisy Survey Datasets with an Application Toward Combating Chagas Disease. Journal on Policy and Complex Systems. 2017 ;3(2).
. Evolving Probabilistically Significant Epistatic Classification Rules for Heterogeneous Big Data Sets. In: Genetic and Evolutionary Computation Conference (GECCO 2016). Genetic and Evolutionary Computation Conference (GECCO 2016). Denver, CO; 2016. Available from: http://gecco-2016.sigevo.org/index.html/Papers
Training Systems Modelers through the Development of a Multi-scale Chagas Disease Risk Model. In: EOS Transactions, American Geophysical Union, Fall Meeting. EOS Transactions, American Geophysical Union, Fall Meeting. San Francisco, CA; 2012.
. The Vermont STEM Collaborative: Partnerships Within and Beyond the University. In: Association of Public Land Grant Universities 2015 SMTI National Conference. Association of Public Land Grant Universities 2015 SMTI National Conference. New Orleans, LA; 2015. Available from: http://www.aplu.org/projects-and-initiatives/stem-education/science-and-mathematics-teaching-imperative/smti-conferences-meetings/SMTI%202015%20National%20Conference%20Presentations/Toolin_Rizzo_and_Hanning_APLU_SMTI_Presentation.pdf
. Three-Dimensional Modeling of Eutrophication and Cyanobacteria Growth in Two Shallow Bays of Lake Champlain. In: North American Lake Management Society (NALMS 2021). North American Lake Management Society (NALMS 2021). Virtual: North American Lake Management Society (NALMS); 2021. Available from: https://z0ku333mvy924cayk1kta4r1-wpengine.netdna-ssl.com/wp-content/uploads/2021/11/NALMS-2021-Abstracts-20211116.pdf
. Improving Climate Change Literacy and Promoting Outreach in an Undergraduate Atmospheric Sciences Program. Bulletin of the American Meteorological Society [Internet]. 2019 ;100(7):1209 - 1214. Available from: https://journals.ametsoc.org/doi/10.1175/BAMS-D-17-0332.1
. Examining the Climatology of Shortwave Radiation in the Northeastern United States. Journal of Applied Meteorology and Climatology [Internet]. 2017 . Available from: http://journals.ametsoc.org/doi/10.1175/JAMC-D-16-0420.1
. Promoting climate change outreach in an undergraduate atmospheric sciences program. 2018 AGU (American Geophysical Union) Fall Meeting [Internet]. 2018 . Available from: https://agu.confex.com/agu/fm18/meetingapp.cgi/Paper/369818
. Examining the Impacts of Great Lakes Temperature Perturbations on Simulated Precipitation in the Northeastern United States. Journal of Applied Meteorology and Climatology [Internet]. 2021 ;60(7):935 - 949. Available from: https://journals.ametsoc.org/view/journals/apme/60/7/JAMC-D-20-0169.1.xml