8.5 Applying Climate Change Information to Hydrologic and Hydraulic Design of Transportation Infrastructure

Wednesday, 15 January 2020: 11:30 AM
152 (Boston Convention and Exhibition Center)
Jennifer M. Jacobs, Univ. of New Hampshire, Durham, NH; and R. Kilgore, A. Stoner, K. Hayhoe, C. J. Anderson, W. Thomas, and D. B. Thompson

Increasingly, engineers must make estimates of discharge associated with a particular risk (or set of risks) to design a hydraulic structure or stormwater management facility considering impending climate change. The National Cooperative Highway Research Program (NCHRP) project “Applying Climate Change Information to Hydrologic and Hydraulic Design of Transportation Infrastructure” was initiated to develop national guidance for transportation engineering hydrologic and hydraulic design practice. The authors examined issues and proposed strategies for adapting Global Climate Model (GCM) precipitation output as inputs to rainfall/runoff models used in hydrologic design. This presentation describes the recommendations for estimating projected precipitation based on the downscaled projections of GCMs.

Engineers typically rely on the assumption of nonstationarity to apply historical information to future periods during which the transportation infrastructure will serve its intended purpose. However, with projections of a changing climate, transportation agencies and policy makers are asking engineers to consider future scenarios without relying on nonstationarity. To accomplish this, engineers using rainfall/runoff models need estimates of future daily and sub-daily precipitation as inputs at watershed-level spatial scales.

This presentation addresses the research project findings and recommendations for actionable guidance for estimating projected daily precipitation data for use in rainfall/runoff modeling, including a 10-step procedure that involves selection of a portfolio of downscaled GCM outputs using a range of future scenarios. The procedure describes a method for using GCM-based information in conjunction with historical precipitation for estimating projected precipitation and estimating mean values and confidence limits for each scenario.

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