Using Data Science to Investigate Climate Resilient Strategies Along US Inland Waterways (DSI-SRP)
This DSI-SRP fellowship funded Tyler Revering to work in the laboratory of Dr. Hiba Baroud, Ph.D. and Paul Johnson in the Department of Civil and Environmental Engineering during the summer of 2023. Tyler is a rising junior with a major in Economics and minors in Data Science and Scientific Computing.
Tyler and his mentors have leveraged exploratory data analysis, network analysis, and economic modeling to analyze the inland waterway commodity flows across the Upper Mississippi River and trends in regional economic production. Their work is part of a project evaluating financial tools to invest in climate adaptation strategies for critical infrastructure systems with an application to inland waterways. They have done a comprehensive literature review on discounting and valuation practices, specifically decoupled net present value (DNPV), a financial framework that distinguishes between physical risk and climate risk in infrastructure development projects. Through their data exploration and literature review, valuable insights have been gained on commodity flow, waterborne commerce traffic, and economic production in the region. Their analysis revealed how different commodity groups are shipped in and out of twelve states surrounding the Upper Mississippi River, and how certain states serve as significant nodes both for inland trade and for the regional economy. They examined trends in economic production and commodity flow and found that agricultural commodities dominate the region in terms of commodity flow. Their analysis identified Illinois as the lead in the region in cumulative economic production. By gaining understanding of economic insights along inland waterways and the surrounding region, their research helps emphasize the significance posed by potential economic loss due to climate induced weather events. Phase two of this research will incorporate a multidisciplinary modeling approach including Monte Carlo simulations and climate projections to analyze the regional economic effects of future severe weather events. This research aims to inform risk-transparent investment strategies into infrastructure, along with utilizing the DNPV framework to facilitate investments into infrastructure given a better idea of the risk posed to a project.
In addition to receiving support through a DSI-SRP fellowship, this project was supported and facilitated by the DSI Data Science Team through their regular summer workshops and demo sessions.