Online Resource 5: Additional Methodological Details for
the Estimation of Impacts and Adaptation Costs for Urban
Drainage
Climatic Change article:
Climate Change Risks to US Infrastructure: Impacts on roads,
bridges, coastal development, and urban drainage
James E. Neumann, Jason Price, Paul Chinowsky, Leonard Wright, Lindsay Ludwig, Richard
Streeter, Russell Jones, Joel B. Smith, William Perkins, Lesley Jantarasami, Jeremy Martinich
Corresponding author:
James E. Neumann
Industrial Economics, Inc.
jneumann@indecon.com
Additional Methodological Details for the Estimation of Impacts and
Adaptation Costs for Urban Drainage
Our analysis of climate change impacts and adaptation costs for urban drainage systems
examines whether changes in storm intensity associated with climate change are likely to
overburden these systems, and, in areas where storms become more intense, assesses the cost of
managing the corresponding increase in runoff. We assess these effects as they relate to changes
in the 10-year, 24-hour storm in 19 of the largest cities in the US.1 We focus on storms with a 10year frequency of occurrence to be consistent with the design criteria for most urban drainage
systems. Table 1 lists the 19 cities included in the analysis.
TABLE 1. CITIES INCLUDED IN URBAN DRAINAGE ANALYSIS
CITY
1
LAND AREA
(SQUARE MILES)
Atlanta, GA
132
Boston, MA
48
Charlotte, NC
242
Chicago, IL
227
Columbus, OH
210
Denver, CO
153
Houston, TX
579
Las Vegas, NV
113
Los Angeles, CA
469
Memphis, TN
279
Miami, FL
36
Minneapolis, MN
55
New Orleans, LA
181
New York, NY
303
Oklahoma City, OK
607
Phoenix, AZ
475
San Francisco, CA
47
Seattle, WA
84
Washington, D.C.
61
The 10-year, 24-hour storm is a rainfall event 24 hours in duration that is expected to occur with a frequency of once every 10
years.
To assess capacity exceedence impacts and the associated adaptation costs for urban drainage
systems, we must characterize the baseline capacity of these systems. One approach for
conducting such a characterization would be to obtain capacity data for the urban drainage
networks in each city—if such data are available. A shortcoming of this approach, however, is
that drainage systems in relatively old and established city districts often lack capacity to manage
runoff from the baseline storm event. This implies that a certain level of capacity exceedence
not attributable to climate change occurs in the baseline. If we were to measure impacts as the
capacity exceedence that occurs with climate change, we would overstate impacts because a
portion of this impact is attributable to baseline capacity constraints. Given that the objective of
this analysis is to assess impacts and costs associated with climate change, we assume a design
capacity sufficient to manage runoff from the baseline storm event.
As an initial step in our analysis, we assess the extent to which urban runoff in each city is likely
to be affected by climate change. We estimate such changes as follows:
(1) 𝑉𝑆,𝐺 = (𝑃𝐵 × 𝐹𝑆,𝐺 )𝐴 × 𝑅
Where VS,G = Change in runoff volume under scenario S based on GCM G;
PB = Rainfall associated with the 10-year, 24-hour storm under baseline climate
(i.e., no climate change);
FS,G = Growth factor representing percent change in rainfall associated with the
10-year, 24-hour storm under climate change scenario S and GCM G relative to
the baseline;
A = Land area of the city; and
R = runoff coefficient.
The term (PB × FS,G) in Equation 1 represents the change in rainfall for the 10-year, 24-hour
storm, which we derive from the baseline 10-year, 24-hour storm and the projected change in
this storm, expressed as a percent. We obtained baseline rainfall values (PB) from NOAA Atlas
14, (Bonnin et al. 2006), Wilks and Cember (1993), and Hershfield (1961).2 To estimate the
percent change in the 10-year, 24-hour storm, we used daily climate projections from the CIRA
climate scenarios. Based on these projections, we applied a Log-Pearson Type III distribution to
estimate the 10-year, 24-hour storm implied by each climate scenario. To assess the change in
the 10-year, 24-hour storm relative to a twentieth century baseline, we obtained modeled
precipitation data for scenario for the years 1980 through 19993. For each city and GCM run, we
then calculate the ratio of the rainfall for the future (2050 or 2100) 10-year, 24-hour storm to the
corresponding twentieth century value.
To convert the estimated change in rainfall associated with climate change (PB × FS,G) to a
volumetric measurement of runoff, Equation 2 multiplies this change by the land area of each
city (A) and the runoff coefficient (R). The runoff coefficient is a commonly used metric
representing the portion of rainfall that becomes runoff in a given area (rather than infiltrating
into the ground). We estimate the runoff coefficient for each city examined as a function of
imperviousness:4
(2) 𝑅𝐶 = 0.05 + 0.9𝐼𝐶
Where RC = runoff coefficient for city C, and
IC = imperviousness of city C (measured as a percent of total land area).
We derived imperviousness estimates for each city based on the Multi-resolution Land
Characteristics Consortium 2006 National Land Cover Database.
Applying the runoff coefficient (R) to the change in rainfall volume for each city, we estimate
the change in urban runoff associated with climate change. Not all of this runoff, however, will
necessarily lead to the exceedence of urban drainage network capacity. In particular, microtopography (i.e, the topography of a city district or neighborhood) plays a significant role in
2
We used values from NOAA Atlas 14 for Charlotte, Chicago, Columbus, Las Vegas, Memphis, Phoenix, and Washington, DC;
values from Wilks and Cember (1993) for Boston and New York; and values from Hershfield (1961) for the other ten cities
included in the analysis.
3
Daily results were available from the GCMs for 1960 through 1999, but we used only 20 years of data from this time series
(1980 through 1999) because the 21st-century GCM projections include daily results for 20-year periods (i.e., 2046 through 2065
and 2081 through 2100..
4
This runoff coefficient equation is consistent with guidance published by the New York Department of Environmental
Conservation (see Center for Watershed Protection, 2010) and has also been used by EPA (see ENSR International, 2005). This
equation is also a reasonable approximation of the nonlinear curve linking imperviousness to the runoff coefficient in Maidment
(1993).
determining whether increased runoff will lead to the failure of a local urban drainage system
(Aronica et al. 2005). For example, neighborhoods located at the top of a hill may not
experience flooding from increased runoff, but such an increase may lead to the failure of
drainage systems in neighborhoods located at the bottom of a hill.
To account for this effect and estimate capacity exceedence, we apply a factor to the estimated
change in runoff (VSG) that represents the percent of a city likely to be affected, as shown in
Equation 3.
(3) 𝐶𝑆,𝐺 = 𝑉𝑆𝐺 × 𝑎
Where CS,G = capacity exceedence under scenario S based on GCM G, and
a = percent of city affected.
We would ideally use data for a specific to each of the cities examined in this analysis, but such
information is not readily available. In the absence of these data, we apply low and high values
of a ranging from 50 percent to 100 percent based on the authors’ professional judgment.
To estimate the costs of adapting urban drainage systems to changes in runoff, we assume that
urban areas will utilize a range of urban storm water management practices that focus on limiting
the quantity of runoff instead of expanding formal drainage networks of catch basins and
conveyance systems. These alternative practices are referred to as Best Management Practices
(BMPs) in the U.S. and are now widely used in the industrialized world. The use of BMPs is
consistent with the globally recognized approach that development of robust adaptation options
is a viable adaptation strategy (Lempert and Groves 2010 and Stakhiv, 2010). Flexibility is a
hallmark of such measures. The installation of BMPs as needed affords local drainage network
managers more flexibility than reconfiguring underground drainage conveyance systems as
climate conditions change (Arisz and Burrell, 2006).
BMP volume management techniques generally include temporary storage above or below
ground or infiltration. U.S. EPA (1999) reports that base construction costs for these measures
are approximately $1.31/ft3 of storage or management (converted to year 2005 dollars) plus an
additional 30 percent for design and contingencies. We annualize these capital costs over the 35-
year design life of BMPs.5 Annual maintenance costs are approximately 5 percent of upfront
construction costs.6
References
Arisz, H. and Burrell, B.C., 2006, Urban Drainage Infrastructure Planning and Design
Considering Climate Change, Engineering Institute of Canada Climate Change Technology
Conference Engineering Challenges and Solutions in the 21st Century, Ottawa Canada, May 1012, 2006.
Aronica, G.T. and Lanza, L.G., 2005, Drainage Efficiency in Urban Areas: a Case Study:
Hydrology in the Urban Environment. Hydrological Processes, 19(5), 1105-1119.
Bonnin, G.M., Martin, D., Lin, B., Parzybok, T., Yekta, M. and Riley, D., 2006, PrecipitationFrequency Atlas of the United States NOAA Atlas 14, 1-2. Originally published 2004, revised
2006.
Center for Watershed Protection, 2010, New York State Stormwater Management Design
Manual, prepared for New York Department of Environmental Conservation.
ENSR International, 2005, Pilot TMDL Applications using the Impervious Cover Method,
prepared for U.S. EPA Region 1, October 2005.
Hershfield, D.M., 1961, Technical Paper No. 40 Rainfall Frequency Atlas of the United States,
U.S. Weather Bureau, May 1961.
Lempert, R. and Groves, D., 2010, Identifying and Evaluating Robust Adaptive Policy
Responses to Climate Change for Water Management Agencies in the American West.
Technological Forecasting & Social Change 77, 960–974.
Maidment, D.R., 1993, The Handbook of Hydrology, McGraw-Hill, New York.
Stakhiv, E., 2010, Practical Approaches to Water Management under Climate Change
Uncertainty. In: Olsen, R., J. Kiang and R. Waskom (ed.) Workshop on Nonstationarity,
Hydrologic Frequency Analysis, and Water Management, Colorado Water Institute Information
Series No. 109.
Wilks, D.S. and Cember, R.P., 1993, Atlas of Precipitation Extremes for the Northeastern United
States and Southeastern Canada, Cornell University, Northeast Regional Climate Center. Report
No. RR 93-5.
5
For design life information, see Olson et al. (2010).
6
The cost of land not already owned by a municipality is not included in these estimates.