Vermont EPSCoR Publications and Products


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Hanley JP, Jackson E, Morrissey LA, Rizzo DM, Sprague BL, Sarkar IN, Carr FE. 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
Hanley JP, Stevens-Goodnight S, Kulkarni S, Bustamante DM, Fytilis N, Goff P, Monroy MC, Morrissey LA, Orantes L, Stevens L, et al. 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.
Hanley JP, Rizzo DM, Buzas JS, Eppstein MJ. 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
Hamshaw SD, Javed A. Hydrological Event Detection & Analysis (HEDA) tool for streamflow and water quality time series. CUAHSI Conference on Hydroinformatics [Internet]. 2019 . Available from: https://www.cuahsi.org/uploads/pages/img/2019_Conference_on_Hydroinformatics_Program.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.
Hamshaw SD, Rizzo DM, Underwood KL, Wemple B, Dewoolkar MM. High Frequency Turbidity Monitoring to Quantify Sediment Loading in the Mad River. 2014 NEAEB Conference. 2014 [cited 0BC].
Hamshaw SD, Javed A. HEDA: Hydrological Event Detection & Analysis. 2019 .
Hamshaw SD, Denu D, Holthuijzen M, Wshah S, Rizzo DM. Automating the Classification of Hysteresis in Event Concentration-Discharge Relationships. In: SEDHYD 2019. SEDHYD 2019. Reno, NV: SEDHYD, INC.; 2019. Available from: https://www.sedhyd.org/2019/openconf/modules/request.php?module=oc_program&action=view.php&id=70&file=1/70.pdf
Hamshaw SD, Underwood KL, Rizzo DM, O'Neil-Dunne J, Dewoolkar MM. 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
Hamshaw SD, Engel T, Rizzo DM, O'Neil-Dunne J, Dewoolkar MM. Application of unmanned aircraft system (UAS) for monitoring bank erosion along river corridors. Geomatics, Natural Hazards and Risk [Internet]. 2019 ;10(1):1285 - 1305. Available from: https://www.tandfonline.com/doi/full/10.1080/19475705.2019.1571533
Hamshaw SD, Rizzo DM, Javed A, Nguyen L. 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
Hamshaw SD. 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/
Hamshaw SD, Dewoolkar MM, Rizzo DM, O'Neil-Dunne J, Frolik J, Underwood KL, Bryce TG, Waldron AY. Quantifying streambank erosion: a comparative study using an unmanned aerial system (UAS) and a terrestrial laser scanner. 2015 AGU (American Geophysical Union) Fall Meeting [Internet]. 2015 . Available from: https://agu.confex.com/agu/fm15/webprogram/Paper85568.html
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. Suspended Sediment Prediction Using Artificial Neural Networks and Local Hydrometeorological Data (M.S. Thesis). Burlington VT: University of Vermont; 2014.
Hamshaw SD, Rizzo DM, Underwood KL, Wemple B, Dewoolkar MM. Suspended Sediment Prediction. In: 2014 NEAEB. 2014 NEAEB. Burlington VT; 2014.
Hamshaw SD, Denu D, Dewoolkar MM, Holthuijzen M, Wshah S, Rizzo DM. 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
Hamshaw SD. Identification of patterns of hysteresis in suspended sediment-discharge relationships to infer watershed sediment dynamics. In: Lake Champlain Research Conference. Lake Champlain Research Conference. Burlington, VT: Lake Champlain Basin Program; 2018. Available from: http://www.lcbp.org/water-environment/data-monitoring/lake-champlain-research-conference/
Hamshaw SD. Using unmanned aircraft system (UAS) photogrammetry to monitor bank erosion along river corridors. In: Lake Champlain Research Conference. Lake Champlain Research Conference. Burlington, VT: Lake Champlain Basin Program; 2018. Available from: http://www.lcbp.org/water-environment/data-monitoring/lake-champlain-research-conference/
Hamshaw SD, Underwood KL, Rizzo DM, Dewoolkar MM. 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
Hamshaw SD, Dewoolkar MM, Bryce TG, Rizzo DM, O'Neil-Dunne J, Frolik J, Engel T. Comparison of Unmanned Aircraft Systems (UAS) to LIDAR for Streambank Erosion Measurement at the Site-Specific Scale. Vermont Geospatial Forum 2017 [Internet]. 2017 . Available from: http://vcgi.vermont.gov/event/forum_2017/poster_gallery
Hamshaw SD, Bryce TG, Rizzo DM, O'Neil-Dunne J, Frolik J, Dewoolkar MM. Quantifying streambank movement and topography using unmanned aircraft system photogrammetry with comparison to terrestrial laser scanning. River Research and Applications [Internet]. 2017 ;33(8):1354 - 1367. Available from: http://doi.wiley.com/10.1002/rra.3183http://onlinelibrary.wiley.com/wol1/doi/10.1002/rra.3183/fullpdfhttp://api.wiley.com/onlinelibrary/chorus/v1/articles/10.1002%2Frra.3183https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Frra.3183
Hamshaw SD, Underwood KL, Rizzo DM, Wemple B, Dewoolkar MM. 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 .
Hamshaw SD, Dewoolkar MM, Schroth AW, Wemple B, Rizzo DM. A new machine-learning approach for classifying hysteresis in suspended-sediment discharge relationships using high-frequency monitoring data. Water Resources Research [Internet]. 2018 ;54(6):4040-4058. Available from: https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2017WR022238
Hamshaw SD. Fluvial Processes in Motion: Measuring Bank Erosion and Suspended Sediment Flux using Advanced Geomatics and Machine Learning. Burlington, VT: University of Vermont; 2017.

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