Dr. Shortridge is an Assistant Professor and Extension Specialist in the Department of Biological Systems Engineering at Virginia Tech. Her research focuses on making water resource systems more sustainable, robust, and resilient through the use of systems engineering methodologies, such as risk and decision analysis, machine learning, and statistical modeling. Management of water scarcity and pollution generally relies heavily on engineered infrastructure that can store, transfer, and treat water. However, effective design and management of this infrastructure demands that we account for the natural, ecological, and social systems in which it resides. Dr. Shortridge’s work is aimed at understanding the interactions between different components of coupled water resource systems and developing methodologies for infrastructure planning that can account for these complexities.
Dr. Shortridge is also interested in refining traditional methods for risk assessment and management so that they are better suited to emerging, “wicked” challenges such as climate change, invasive species, and emerging diseases. She holds a B.S. from U.C. Berkeley in Environmental Engineering Science and an M.S.E. and Ph.D. from the Johns Hopkins University in Geography and Environmental Engineering. Prior to conducting her graduate studies, she spent six years working as an engineer focused on groundwater contamination and remediation, and as a consultant for the United Nations Environment Program on disaster preparedness.
Shortridge, J.E., Guikema, S.D., and Zaitchik, B.F. (2017) Robust decision making in data scarce contexts: addressing data and model limitations for infrastructure planning under transient climate change. Climatic Change 140, 323-337. doi:10.1007/s10584-016-1845-4
Shortridge, J.E., Aven, T., and Guikema, S.D. (2017) Risk assessment under deep uncertainty: a methodological comparison. Reliability Engineering and System Safety 159, 12-23. doi: 10.1016/j.ress.2016.10.017
Shortridge, J.E., Guikema, S.D, and Zaitchik, B.F. (2016) Machine learning methods for empirical streamflow simulation: a comparison of model accuracy, interpretability, and uncertainty in seasonal watersheds. Hydrology and Earth Systems Sciences 20, 2611-2628. doi:10.5194/hess-20-2611-2016.
Shortridge, J.E., and Guikema, S.D. (2016) Scenario discovery with multiple criteria: an evaluation of the robust decision making framework for climate change adaptation. Risk Analysis. Early view published online in February 2016. DOI: 10.1111/risa.12582
Shortridge, J.E., Falconi, S.M., Zaitchik, B.F., and Guikema, S.D. (2015). Climate, Agriculture, and Hunger: Statistical prediction of undernourishment using non-linear regression and data mining techniques. Journal of Applied Statistics. 42(11), 2367-2390.
Shortridge, J.E., and Guikema, S. D. (2014). Public health and pipe breaks in water distribution systems: analysis with internet search volume as a proxy. Water Research. 53(15), 26-34.
For a complete list of publications, see Dr. Shortridge’s Google Scholar page.