Precipitation extremes and the impacts of climate change on stormwater infrastructure in Washington State

Abstract

Stormwater management facilities are important elements of the civil infrastructure that can be sensitive to climate change, particularly to precipitation extremes that generate peak runoff flows. The design and anticipated performance of stormwater infrastructure is based on either the presumed characteristics of a "design rainstorm" or the continuous simulation of streamflow driven by a time series of precipitation. Under either approach, a frequency distribution of precipitation is required, either directly or indirectly, together with an underlying assumption that the probability distribution of precipitation extremes is statistically stationary. This assumption, and hence both approaches, are called into question by climate change. We therefore examined both historical precipitation records and simulations of future rainfall to evaluate past and prospective changes in the probability distributions of precipitation extremes across Washington State. The historical analyses were based on hourly precipitation records for the time period 1949-2007 from weather stations surrounding three major metropolitan areas of the state: the Puget Sound region (including Seattle, Tacoma, and Olympia), the Vancouver (WA) region (including Portland, OR), and the Spokane region. Changes in future precipitation were simulated using two runs of the Weather Research and Forecast regional climate model (RCM) for the time periods 1970-2000 and 2020-2050, statistically downscaled from the ECHAM5 and CCSM3 Global Climate Model and biascorrected against the SeaTac Airport rainfall record. Downscaled and bias-corrected hourly precipitation sequences were then used as input to the HSPF hydrologic model to simulate streamflow in two urban watersheds in central Puget Sound. Few statistically significant changes in extreme precipitation were observed in the historical records, with the possible exception of the Puget Sound. RCM simulations generally indicate increases in extreme rainfall magnitudes throughout the state, but the range of projections is too large to predicate engineering design, and actual changes could be difficult to distinguish from natural variability. Nonetheless, the evidence suggests that drainage infrastructure designed using mid-20 th century rainfall records may be subject to a future rainfall regime that differs from current design standards.

Extreme Rainfall Nonstationarity Investigation and Intensity–Frequency–Duration Relationship

“…Therefore, it is essential to perform analysis to confirm stationarity (or detect non-stationarity) of extreme rainfall data. Extreme rainfall trend analysis and non-stationarity tests are commonly used for detection of nonstationarity in hydrological studies (Wang et al 2005;Rosenberg et al 2010). …”

“…Therefore, it is essential to conduct extreme rainfall trend analysis at finer temporal scales, since urban flash flooding is the product of heavy rainfalls over short durations. Studies addressing non-4 stationarity in extreme rainfall events are very rare in the literature for sub-daily temporal scales (Bonaccorso et al 2005, Rosenberg et al 2010, Jacob et al 2011.…”

“…Extreme rainfalls are the essential inputs to develop Intensity-Frequency-Duration (IFD) curves, which are used to derive design rainfalls for infrastructure project designs and flood mitigation works (Rosenberg et al 2010). The Australian Rainfall and Runoff (ARR) has been widely adopted as the guideline for design rainfall estimation in Australia (IEA 1987).…”

Regional climate model projections for the State of Washington

“…Thus, for many applications, some bias correction must be applied to the results, to remove the combined biases of the global and regional model. This approach is used in Rosenberg et al (2010) using data from the WRF simulations presented here. Furthermore, due to the computational demands of regional models, there is a trade-off in using them for impacts studies between long simulations at high model resolution, to better simulate local effects, and a large ensemble of simulations using multiple regional and global models, to better represent the range of uncertainty.…”

Application of PCSWMM to Explore Possible Climate Change Impacts on Surface Flooding in a Peri-Urban Area of Pathumthani, Thailand

“…Semadeni-Davies et al 2008;Rosenberg et al 2010;Hirshman et al 2011;. The probable effects of a changing climate provide a challenge for sustainable water resource management.…”