Science Inventory

Assessing and Managing Design Storm Variability and Projection Uncertainty in a Changing Coastal Environment

Citation:

Liang, M., S. Julius, Z. Dong, J. Neal, AND Y. Yang. Assessing and Managing Design Storm Variability and Projection Uncertainty in a Changing Coastal Environment. JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, 264:110494, (2020). https://doi.org/10.1016/j.jenvman.2020.110494

Impact/Purpose:

This paper describes research results on how to assess and manage the design storm variability and uncertainties in future projections. The results can help reduce water infrastructure and water program vulnerability starting from engineering design basis. It proposes a new approach to evaluate and redefine design storm attributes for improved resilience of the water infrastructure and programs. In this paper, the findings are documented and shared to technical communities and water managers who are in charge of coastal water programs.

Description:

Coastal urban infrastructure and water programs are vulnerable to the impacts of long-term hydroclimatic changes and to the flooding and physical destruction of disruptive cyclones and storm surge. Water resilience or, inversely, vulnerability depends on design specifications of storm and inundation, against which water infrastructure and environmental assets are planned and operated. These design attributes are commonly derived from statistical modeling of historical measurements. Here we argue for the need to carefully examine the approach and associated design vulnerability in coastal areas because of future changes and large variability at local coastal watersheds. Using a case study in the Chesapeake Bay of eastern U.S. coast, we show significant spatiotemporal variations particularly in low-frequency high-intensity precipitation that responds differentially to the tropical cyclones and local orographic effects at locations. Average and gust wind speed exhibited much greater spatial, but far less temporal variability, both in the calibration period (~1993-2015) and projected future until 2100. Regional gridded precipitation used in CMIP5 downscaling and regional design guide in NOAA’s Atlas-14, inadequately describe these local variabilities leading to design vulnerability. Up to 46.4% error in the gridded precipitation for the calibration period 1950-1999 is inherited and exacerbated in the future design values by the ensemble of 132 CMIP5 projections. The total model projection error (δ_M) up to -61.8% primarily results from precipitation regionalization (δ_1), climate downscaling (δ_2), and a fraction from empirical data modeling (δ_E). Post-bias correction as a temporary fix is necessary to reduce the design uncertainties. For the Chesapeake Bay region, the post-bias corrected design wind speed at 10-yr to 30-yr storms would have small changes <20% by year 2100 but large spatial variations even for stations of close proximity. Future design precipitations are characteristic of large spatial variability and a notable increase of 2-5 year precipitation along the western shores of Lower and Middle Bay. The mean and variance, both important to the planning and design, are sensitive to the calibration period used in statistical downscaling. Nevertheless, for reliable future projections to better manage the design vulnerability, better climate modeling of oceanic-atmospheric processes underpinning the spatiotemporal variability of design storms in mid-Atlantic are recommended.