You are here:
Estimating Impaired Waters on a County Level for Public Health Analysis
Citation:
JAGAI, J. S., B. J. ROSENBAUM, S. PIERSON, L. Messer, K. Rapazzo, E. Naumova, AND D. T. LOBDELL. Estimating Impaired Waters on a County Level for Public Health Analysis. Presented at 43rd Annual Meeting of the Society of Epidemiologic Research (SER), Seattle, WA, June 23 - 26, 2010.
Impact/Purpose:
We utilize data collected by the Environmental Protection Agency (EPA), under Section 303(d) of the Clean Water Act, from each state regarding the intended use of each stream and whether it is impaired for that use. Each state establishes the intended use and impairment of stream waters individually and streams may be allocated to more than one use.
Description:
Assessing the population-level impact of water quality on health can be difficult. Water quality data are measured at a watershed level and health data are organized at different levels of aggregation. To address this discrepancy and enable the consideration of water quality for health research, we have developed a method to estimate impaired waters at the county level. We utilize data collected by the Environmental Protection Agency (EPA), under Section 303(d) of the Clean Water Act, from each state regarding the intended use of each stream and whether it is impaired for that use. Each state establishes the intended use and impairment of stream waters individually and streams may be allocated to more than one use. We merged stream hydrology information from the National Hydrography Dataset Plus and EPA's Reach Attribute Database to estimate percent of stream length intended for drinking water and recreational water that is impaired per county in the U.S. For example, in 2002 Wake County, North Carolina had 2064 streams representing a total of 2131 kilometers (km); 476km of stream were intended for drinking water of which 35km (7.4%) were impaired and 104km of stream were intended for recreational water of which 35km (34%) were impaired. We assessed variability across states and considered implications for missing data for states which do not report intended stream use. Our goal is to use these estimates to calculate correlation between percent of impaired waters and rates of hospitalization for gastrointestinal diseases in the elderly. County-level water quality modeling will enable improved public health monitoring and more nuanced health-related assessments. (This abstract does not necessarily reflect EPA policy.)