Linked Rainfall and Runoff Intensity-Duration-Frequency in the Face of Climate Change and Uncertainty

Dr. Yonas Demissie | Washington State University

RC-2514

Objective

The Department of Defense (DoD) recognizes the effects of climate change as a growing national security threat with potential impacts on critical military installations and operations. One of the anticipated effects of climate change is the increase in intensity and frequency of extreme precipitation and subsequent flood events. Adaptation to this change requires proper design and management of stormwater facilities using improved and updated characterization of the intensity-duration-frequency (IDF) of storms. The primary objective of this project was to revise and update storm and flood IDF relationships (or curves) for selected military installations by considering changes in the past and future storm and flood events, effect of snowmelt, and modeling and data uncertainties. Regional frequency analysis coupled with Bayesian uncertainty quantification were used to update rainfall IDF curves, which are then used by site-specific hydrologic models to develop runoff IDF curves that can be used to assess the vulnerability of military installations to flooding. The resulting rainfall and runoff IDF curves provide reliable, forward-looking, and spatially resolved characteristics of storm events and flooding risks for thorough review and update of the current stormwater design standards at the selected installations. An interactive web-based geographic information system (GIS) interface was developed, which contains tabulated and geo-referenced IDF data and figures.

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Technical Approach

The IDF curves describing the probabilistic relationship between rainfall intensity, duration, and frequency (return period) – are commonly used for designing and managing hydrologic and hydraulic infrastructures. This project utilized statistical and modeling approaches to develop rainfall and runoff IDF curves that consider the potential changes in extreme precipitation and watershed, effects of snow on both extreme precipitation and runoff, modeling, and data uncertainties. A new framework was developed using (1) a modified L-moment algorithm to regionalize IDF curves and improve the representation of spatial variations of rainfall for various durations, (2) a Bayesian model averaging to quantify the uncertainty in the IDF curves resulting from the selection of probability distribution models and estimation of the model parameters, (3) a dynamic downscale and bias correction approaches to generate high-resolution spatial and temporal precipitation and temperature projections, 4) a recursive Bayesian analysis algorithm to update the IDF curves using recently observed and projected extreme precipitation, (5) a hydrologic, snowmelt and hydraulic models to develop the runoff IDF curves and directly assess flood risk, (6) an interactive web-based GIS tool and a geodatabase to facilitate construction and an update to the rainfall and runoff IDF curves for any military installation and region of interest to DoD.

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Results

Small percentage (less than 20%) of stations exhibited statistically significant trends in historical precipitation extremes, while more than 50% of the stations show statistically significant positive trends when future precipitation projections (from two climate models and two emission scenarios) append the past data. Stationary and nonstationary IDF curves with 95% confidence intervals were developed and compared for rainfall durations from one-hour to 10-days and return periods from two years to 500 years for 13 military installations across the United States. The difference in IDF values range from a 25% decrease at Yuma Proving Ground to a 50% increase at Ft. Hood. When future precipitation is considered for the rainfall IDF curves, the storm magnitudes corresponding to longer durations increased for most of the installations with the increase being higher for the installations located in the central and eastern parts of the country. While the trends for sub-daily storms are mixed, some of the installations (e.g., those located in the south and two in the southwest) showed a negative trend. Consequently, flooding risk may increase in the Midwest and Northwest, but decrease in the southern installations because of future storm trends. The snowmelt effect may change the season of annual maximum precipitation to early spring at Ft. Drum, leading up to a 22% and 25% increase in the 10-year and 100-year storm event magnitudes, respectively. A project website and web-based mapping tool (https://bogi.evs.anl.gov/dodewa/tool/index.html) were created to provide access to all the IDF results.

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Benefits

The final report provides a qualitative assessment and scientific foundation to provide an understanding of flood vulnerability at selected military installations. This work contributes to the DoD’s larger goal of improving military readiness for future environmental conditions. Understanding how the intensity and frequency of extreme precipitation events are changing is important for regional risk assessments and adaptation planning. The study provides new understanding of how the frequency and intensity of storm and associated flooding risk may be affected by past and projected changes in extreme precipitation. All methodologies, datasets, and the interactive web-based GIS tool developed during the study will be provided to DoD for use in decision-making and planning exercises.

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Points of Contact

Principal Investigator

Dr. Yonas Demissie

Washington State University

Phone: 509-372-7344

Program Manager

Resource Conservation and Resiliency

SERDP and ESTCP

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