Flooding: Devastating Floods and Heavy Rains
Climate change has contributed to a rise in extreme weather events - including higher-intensity hurricanes in the North Atlantic and heavier rainfalls across the country. Scientists project that climate change will increase the frequency of heavy rainstorms, putting many communities at risk for devastation from floods.
Flooding can cause a range of health impacts and risks, including: death and injury, contaminated drinking water, hazardous material spills, increased populations of disease-carrying insects and rodents, moldy houses, and community disruption and displacement.
As rains become heavier, streams, rivers, and lakes can overflow, increasing the risk of water-borne pathogens flowing into drinking water sources. Downpours can also damage critical infrastructure like sewer and solid waste systems, triggering sewage overflows that can spread into local waters.
Cities like New York City and Chicago, where older sewer systems carry sewage and rain water in the same pipes, are at greater risk for sewage spills. During heavy rains, these pipes cannot handle the volume of stormwater and wastewater, and untreated sewage is often discharged into local waters where people swim and play.
Exposure to pathogens from sewage and unclean water can sicken vulnerable communities with illnesses like cryptosporidiosis, giardiasis, and norovirus (which cause diarrhea, abdominal pain, nausea, vomiting, headache, and fever).
Local communities across the country can prevent floods and heavy rains from devastating their homes and buildings by updating infrastructure, improving drinking water safeguards, and creating public plans for what to do in case disaster strikes.
Eight states and various local governments have developed public health preparedness measures to address increased flooding risks associated with climate change. These measures are a good start at addressing some of the risks but comprehensive response plans addressing the multiple threats and hazards highlighted above are lacking.
How are states addressing the threat of flooding?
- California's plan includes a measure to improve emergency response plans to respond to increased risks of flooding due to climate change. Find out more >>
- Florida's plan addresses the potential for flooding to damage drinking water infrastructure. Find out more >>
- Maryland's plan includes measures to monitor, model, and create risk maps for areas potentially most affected by flooding. Find out more >>
- New York's plan identifies flooding as a health-related threat due to increasingly frequent extreme storms and sea level rise with climate change, and it includes measures to update infrastructure. New York City's plan includes specific measures to update flood insurance maps, taking sea level rise and climate changes into account. Find out more >>
- Oregon's plan includes measures to inventory past flood conditions and map future flood conditions. Find out more >>
- Pennsylvania's plan includes a general recommendation to implement measures to prevent and control adverse health-effects caused by flooding. Find out more >>
- Washington's plan includes a measure to research flood threats over various timeframes. King County's plan includes specific measures to incorporate climate change impacts into floodplain management programs and improve stormwater and wastewater systems to prevent exposures to toxic and bacterial contaminants. Find out more >>
- Wisconsin's plan includes a measure to minimize threats to public health and safety by anticipating and managing impacts resulting from extreme weather events like floods. Find out more >>
Background: Global warming is projected to alter precipitation patterns, increase the frequency and intensity of major storm events, and increase risks of floods throughout the U.S. and particularly the Midwest and Northeast.1 Flooding can cause a range of health impacts and risks, including: death and injury, contaminated drinking water, hazardous material spills, increased populations of disease-carrying insects and rodents, moldy houses, and community disruption and displacement. In recent years, a higher percentage of rainfall in the U.S. has come in the form of intense single-day events.2
Flooding Vulnerability Indicators: Vulnerability to flooding is indicated by the frequency of extreme high flow days and the frequency of days where flood conditions were recorded, consistent with the USGS WaterWatch program.3 Extreme high streamflow is defined as above the 95th percentile for each monitoring station. Flood conditions are indicated by days above flood stage, which is defined by the Nation Weather service as the level of surface water where there is a hazard to lives, property, or commerce. Current conditions (2000 -2009) were compared to historical conditions using a 30-year reference period (1961-1990 in this case), consistent with other climate change-related studies.
Data Source: Data from all streamflow gauging stations for all years historically from the United States Geological Survey was collected. The data through 2009 was purchased from EarthInfo, a private vendor that collects USGS data and makes it available on DVDs. Watershed data also comes from the USGS (http://water.usgs.gov/GIS/huc.html). The original watershed data was at the HUC12-level (high resolution). These watersheds were aggregated to HUC4 based on HUC ID.
Data Preparation: Data was assembled in an SQL data base. Each record represented a single site-month of data. The total was 7 million site-months, or a total of more than 210 million site-days of data.
Calculations: A 95th and 5th percentile value for the reference period (1961-1990) was calculated for each site for each day of the year using a moving average of 7 days before and after the day. For example, the reference period percentiles for June 15th would be calculated by selecting all days June 8-22 for the years 1961-1990 (15 x 30 possible days = 450 days contribute to the percentile calculations). June 16th would be based on all days June 9-June 23 and so on. For the first and last 6 days of the year (Jan 1-6 and Dec 26-31) the reference period moving average included days from 1960 and 1991. Current flows at a site were then compared against the reference period percentiles day by day. For example, the ten possible June 15th values from 2000-2009 would be compared against the 95th and 5th percentiles for that day from the reference period. Watershed-level averages were then computed by averaging site-level data within the watersheds.
Analysis was limited to stations that make up the Hydro-Climatic Data Network a subset of stations that are unaffected by artificial diversions. See appendix for a description of these sites below.
Sites were excluded from the analysis if A) they had less than 75% of possible reference days; B) two entire years from the 2000-2009 period were missing; or C) they had less than 75% of possible current period days.
Map: Color gradations reflect terciles of the data distribution.
Flood Stage Data
Data Source: Data was collected from the USGS WaterWatch website (http://waterwatch.usgs.gov?/new/?id=wwdp2_2).
Data Preparation: We developed Python scripts to iterate through all states and download/format all available flood data 2000-2009. Tabular data was converted to geographic data by linking to the dataset described above on USGS station number.
Calculations: No additional calculations were performed. Graduated circles were mapped based on the "No. of days above flood stage" variable from USGS.
Map: Graduated circles reflect natural data breaks in the distribution. Note: flood stage information is not currently available for all Hydro-Climatic Data Network (HCDN) streamflow gauge sites.
Appendix: Definition of HCDN sites
HCDN Description: Pasted from USGS Hydro-Cliatic Data Network: Streamflow Data Set 1874-1988 by By J.R. Slack, Alan M. Lumb, and Jurate Maciunas Landwehr. USGS Water-Resources Investigations Report 93-4076
The potential consequences of climate change to continental water resources are of great concern in the management of those resources. Critically important to society is what effect fluctuations in the prevailing climate may have on hydrologic conditions, such as the occurrence and magnitude of floods or droughts and the seasonal distribution of water supplies within a region. Records of streamflow that are unaffected by artificial diversions, storage, or other works of man in or on the natural stream channels or in the watershed can provide an account of hydrologic responses to fluctuations in climate. By examining such records given known past meteorologic conditions, we can better understand hydrologic responses to those conditions and anticipate the effects of postulated changes in current climate regimes. Furthermore, patterns in streamflow records can indicate when a change in the prevailing climate regime may have occurred in the past, even in the absence of concurrent meteorologic records.
A streamflow data set, which is specifically suitable for the study of surface-water conditions throughout the United States under fluctuations in the prevailing climatic conditions, has been developed. This data set, called the Hydro-Climatic Data Network, or HCDN, consists of streamflow records for 1,659 sites throughout United States and its Territories. Records cumulatively span the period 1874 through 1988, inclusive, and represent a total of 73,231 water years of information.Development of the HCDN Data Set: Records for the HCDN were obtained through a comprehensive search of the extensive surface- water data holdings of the U.S. Geological Survey (USGS), which are contained in the USGS National Water Storage and Retrieval System (WATSTORE). All streamflow discharge records in WATSTORE through September 30, 1988 were examined for inclusion in the HCDN in accordance with strictly defined criteria of measurement accuracy and natural conditions. No reconstructed records of "natural flow" were permitted, nor was any record extended or had missing values "filled in" using computational algorithms. If the streamflow at a station was judged to be free of controls for only a part of the entire period of record that is available for the station, then only that part was included in the HCDN, but only if it was of sufficient length (generally 20 years) to warrant inclusion. In addition to the daily mean discharge values, complete station identification information and basin characteristics were retrieved from WATSTORE for inclusion in the HCDN. Statistical characteristics, including the monthly mean discharge, as well as the annual mean, minimum and maximum discharge values, were derived for the records in the HCDN data set. For a full description of the development and content of the Hydro-Climatic Data Network, please take a look at the HCDN Report.
- Climate and Your Health: Addressing the Most Serious Health Effects of Climate Change
- Rising Tide of Illness: How Global Warming Could Increase the Threat of Waterborne Diseases
- Thirsty for Answers: Preparing for the Water-related Impacts of Climate Change in American Cities
- U.S. Global Change Research Program: Climate Impacts on Human Health
- Karl TR, Melillo JM, Peterson TC, editors. Global climate change impacts in the United States. New York: Cambridge University Press; 2009.
- EPA "Climate Change Indicators in the United States (2010)", EPA 430-R-1â€"007. www.epa.gov/climatechange/indicators.html
- US Geological Survey (USGS) WaterWatch: Flood conditions website. http://waterwatch.usgs.gov/new/index.php?id=ww_flood
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