Tyler Smith

Biography

Tyler Smith joined Clarkson University in 2012 as an assistant professor in the Department of Civil and Environmental Engineering and an affiliate faculty member in the Institute for a Sustainable Environment following the completion of his PhD from Montana State University. He studies hydrology through the lens of water resources engineering and environmental science and his research focuses on improving water resources decision-making by better understanding hydrologic models and their uncertainties. Outside of work, Tyler enjoys spending time with his wife and kids and exploring the beauty of Northern New York.

Education Background

Ecology & Environmental Sciences Ph.D. - 2012 Montana State University
Civil Engineering M.S. - 2008 Montana State University
Civil Engineering, Bio-Resources Engineering Option B.S. - 2006 Montana State University

Experience

Assistant Professor, Department of Civil & Environmental Engineering Clarkson University, Present
Affiliate Faculty, Institute for a Sustainable Environment Clarkson University, Present
Graduate Research Assistant, Department of Land Resources & Environmental Sciences Montana State University, 2012
Visiting Graduate Research Assistant, School of Civil & Environmental Engineering University of New South Wales, 2010

Courses Taught

• CE330 - Water Resources Engineering I, Fall 2012, Fall 2013, Fall 2015, Spring 2017
• CE430 - Water Resources Engineering II, Spring 2014, Spring 2015, Spring 2016, Spring 2017
• CE491 - Senior Design (Water Resources), Spring 2016
• CE569 - Watershed Analysis, Fall 2014, Fall 2016

Research Interests

• Integrative watershed studies driven by quantitative analysis
• Use of Bayesian statistical approaches to environmental systems modeling
• Collaboration with experimentalists to improve hydrologic model realism
• Hydrologic modeling in data-scarce regions and/or regions under change

Grants

Active Research Grants

• Niagara and St. Lawrence River Operation Forecasting: Present and Future.
• Funding Source: New York Power Authority
• PIs: Tyler Smith (Clarkson), HT Shen (Clarkson)

Publications

Peer-Reviewed Articles

• Smith, T., K. Hayes, L. Marshall, B. McGlynn, and K. Jencso (2016). Diagnostic calibration and cross-catchment transferability of a simple process-consistent hydrologic model, Hydrological Processes, doi: 10.1002/hyp.10955.
• Tang, Y., L. Marshall, A. Sharma, and T. Smith (2016). Tools for investigating the prior distribution in Bayesian hydrology, Journal of Hydrology, doi: 10.1016/j.jhydrol.2016.04.032.
• Smith, T., L. Marshall, and A. Sharma (2015). Modeling residual hydrologic errors with Bayesian inference, Journal of Hydrology, doi: 10.1016/j.jhydrol.2015.05.051.
• Smith, T., L. Marshall, and A. Sharma (2014). Predicting hydrologic response through a hierarchical catchment knowledgebase: A Bayes empirical Bayes approach, Water Resources Research, 50, 1189-1204, doi: 10.1002/2013WR015079.
• Smith, T., L. Marshall, and B. McGlynn (2014). Calibrating hydrologic models in flow-corrected time, Water Resources Research, 50, 748-753, doi: 10.1002/2013WR014635.
• Smith, T., L. Marshall, B. McGlynn, and K. Jencso (2013). Using field data to inform and evaluate a new model of catchment hydrologic connectivity, Water Resources Research, 49, 6834-6846, doi: 10.1002/wrcr.20546.
• Smith, T., A. Sharma, L. Marshall, R. Mehrotra, and S. Sisson (2010). Development of a formal likelihood function for improved Bayesian inference of ephemeral catchments, Water Resources Research, 46, W12551, doi: 10.1029/2010WR009514.
• Smith, T. J. and L. A. Marshall (2010). Exploring uncertainty and model predictive performance concepts via a modular snowmelt-runoff modeling framework. Environmental Modelling & Software, 25(6), 691-701.
• Smith, T. J. and L. A. Marshall (2009). A Conceptual Precipitation-Runoff Modeling Suite: Model Selection, Calibration and Predictive Uncertainty Assessment. In Anderssen, R. S., R. D. Braddock and L. T. H. Newham (eds) 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation. July 2009, pp. 3556-3562. ISBN: 978-0-9758400-7-8. http://www.mssanz.org.au/modsim09/I8/smith_tj.pdf.
• Smith, T. J. and L. A. Marshall (2008). Bayesian methods in hydrologic modeling: A study of recent advancements in Markov chain Monte Carlo techniques, Water Resources Research, 44, W00B05, doi: 10.1029/2007WR006705.

Articles in preparation/review

• Marshall, L., K. Weber, T. Smith, M. Greenwood, and A. Sharma (in review). On the relationship between optimized models and hydrologic signatures towards improved catchment regionalization. Submitted to Journal of Hydrology.
• Jayathilake, D. and T. Smith (in prep). Predicting the temporal transferability of model parameters through a hydrologic signature analysis. To be submitted to Journal of Hydrology.
• Smith, T., L. Marshall, and B. McGlynn (in prep). Catchment classification, directionality, and the pursuit of universality. To be submitted to Hydrology and Earth System Sciences.
• Perera, C., C. Corrigan, T. Smith, A. Baker, V. Peterson, and D. Ding (in prep). Calibrating coupled hydrologic models: Assessing strategies for improved performance and robustness. To be submitted to Water Resources Research.