Assessing Flooding from Changes in Extreme Rainfall: Using the Design Rainfall Approach in Hydrologic Modeling
Citation:
Jalowska, A., D. Line, T. Spero, J. Kirki-Fox, B. Doll, J. Bowden, AND G. Gray. Assessing Flooding from Changes in Extreme Rainfall: Using the Design Rainfall Approach in Hydrologic Modeling. WATER. MDPI, Basel, Switzerland, 17(15):2228, (2025). https://doi.org/10.3390/w17152228
Impact/Purpose:
Extreme precipitation events result in major floods affecting human life, health, ecosystems, agriculture, infrastructures, and the economy. With climate change we observe an increasing trend in the frequency and intensity of extreme precipitation events of different durations. Intensification of rainfall extremes may lead to increase in flood events, such as flash flooding and large-scale river flooding that are among the most significant consequences of anthropogenic climate change. With intensifying rainfall extremes, we observe increase in flood magnitude and extent.The design, operation, and maintenance of water infrastructure are based on precipitation intensity?duration?frequency (PIDF) curves. PIDF curves graphically represent the probability that extreme events will occur based on the historical record of observed precipitation events. PIDF data are fundamental for the adequate and economical design of urban storm water systems, farm?terrace and drainage systems, highway and railway culverts, municipal storm?sewer systems, and other engineering works that must care for storm runoff. The PIDFs are also used by the EPA in the process of National Pollutant Discharge Elimination System (NPDES) permits issuance. Currently available PIDF data is incomplete and outdated and does not account for changing climate. Using model?based, historical and future data provides us with insights in upcoming changes. In this study we will use dynamically downscaled (DD) climate data to develop IDF data for the U.S. The methodology behind the DD allows for exploration of extreme events.
Description:
Extreme rainfall events have been increasing in frequency and intensity over the past few decades, exacerbating flooding throughout the eastern U.S. This trend is expected to amplify throughout the 21st century. Quantification of future changes in extreme events and associated flooding is challenging, yet fundamental for watershed and storm-water managers. In this study we present a novel approach of utilizing rainfall data from five, dynamically and statistically downscaled global climate models under two greenhouse gas emission scenarios (RCP4.5 and 8.5) to visualize a potential future extent of flooding. We guide the readers through the merits of dynamically and statistically downscaled rainfall data, and modelled data application into hydrological models (HEC-HMS and HEC-RAS) in Eastern North Carolina. In recent years Eastern North Carolina experienced numerous catastrophic floods resulting from extreme rainfall from tropical storms. The projected changes in local rainfall (~50%, with the maximum of 112%) exceed values published for U.S. regions; however, they do not exceed historical changes in extreme rainfall events in the U.S. in the last decades. Dynamically downscaled data showed to be more representative of historical changes in extreme rainfall than statistically downscaled datasets. Here we use data from dynamically downscaled projections to compute future changes in Precipitation-Intensity-Duration-Frequency (PIDF) curves for the Neuse River Basin in North Carolina. The calculated PIDF changes by the end of 21st century were then applied to observed rainfall associated with Hurricane Matthew (2017). Created Hurricane Matthew “2100” rainfall intensities were then used in hydrologic models (HEC-HMS and HEC-RAS) to simulate “2100” discharges and flooding extents in the Neuse River. The results suggest that peak discharges for Matthew “2100” in the Neuse River Basin could increase by 23–39% under RCP 4.5 scenario and by 50–69% under RCP 8.5 scenarios. The projected discharges resulted in increases in water surface elevation 0.4–3m and 8–57% increases in flooded area relative the observed from Matthew. The projected increases in extreme rainfall and resulting flooding would cause even more devastating impacts in Eastern North Carolina, threatening populated, often underserved areas not yet directly impacted by recent observed hurricanes.
URLs/Downloads:
DOI: Assessing Flooding from Changes in Extreme Rainfall: Using the Design Rainfall Approach in Hydrologic Modeling