Kristen’s academic and professional experience in water resources, bridges fields of aquatic ecology, fluvial geomorphology, hydrogeology and environmental engineering. Her current research involves the application of advanced computational tools to address environmental challenges in water resource management and to support pragmatic solutions within an adaptive management framework. She has used machine-learning algorithms and Bayesian inference to evaluate catchment dynamics and biogeochemical processing in rivers. Kristen has applied smart classifiers and Bayesian statistics, to better understand spatial and temporal variability in sediment and nutrient flux, to inform sustainable design of infrastructure for geomorphic and ecological compatibility, and to direct river corridor conservation and restoration activities for reduced flood losses.
Gund Affiliate, Research Assistant Professor, College of Engineering and Mathematical Sciences
- Underwood, K. L., Rizzo, D.M., Dewoolkar, M.M., and Kline, M. (2020). Analysis of Reach-scale Sediment Process Domains in Glacially-conditioned Catchments Using Self-Organizing Maps. Geomorphology (Accepted).
- Shakun, J. D., L. B. Corbett, P. R. Bierman, K. Underwood, D. M. Rizzo, S. R. Zimmerman, M. W. Caffee, T. Naish, N. R. Golledge, C. C. Hay. (2018). Minimal East Antarctic Ice Sheet retreat onto land during the past 8 million years. Nature, 558, 284- 287, doi:10.1038/s41586-018-0155-6.
- Underwood, K. L., D. M. Rizzo, A. W. Schroth, M. M. Dewoolkar. (2017). Evaluating Spatial Variability in Sediment and Phosphorus Concentration-Discharge Relationships Using Bayesian Inference and Self-Organizing Maps. Water Resources Research, 53, doi:10.1002/2017WR021353.
- Galford , G. L., J. Nash, A. K. Betts, S. Carlson, S. Ford, A. Hoogenboom, D. Markowitz, A. Nash, E. Palchak, S. Pears, A. Thompson, K. L. Underwood. (2015). Bridging the climate information gap: a framework for engaging knowledge brokers and decision makers in state climate assessments. Climatic Change. doi:10.1007/s10584-016-1756-4.
- Besaw, L. E., D. M. Rizzo, M. Kline, K. L. Underwood, J. J. Doris, L. A. Morrissey and K. Pelletier. (2009). Stream classification using hierarchical artificial neural networks: A fluvial hazard management tool. J. Hydrol., doi:10.1016/j.hydrol.2009.04.007.
Areas of Expertise and/or Research
Water resources, fluvial geomorphology, smart classifiers, infrastructure & hazard mitigation
- PhD, Environmental Engineering, University of Vermont
- MS, Geosciences, Pennsylvania State University