ANALYSIS ОЕ DRY WEATHER TESTING FOR MUNICIPAL STORM WATER RUNOFF IN THE SOUTHERN SAN DIEGO REGION
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Authors
Muhl, Richard W.
Issue Date
1999
Type
Capstone
Language
en
Keywords
Alternative Title
Abstract
Urban stormwater runoff contains measurable levels of heavy metals, petroleum hydrocarbons, pesticides, pathogens, nutrients, sediments and other pollutants which reduce water quality іп receiving water bodies.
In order to minimize the impact of urban storm water National Pollutant Discharge Elimination System (NPDES) permits have been issued. In San Diego, a region wide NPDES permit has been issued for all of the incorporated cities in San Diego County, the County of San Diego, and the San Diego Unified Port District. These permits require co-permittees to control potential pollutants by prohibiting non-storm water discharges and developing and implementing a comprehensive storm water management program. One component of the storm water management program Is the Illicit Connection/ illegal Discharge elimination program. In order to eliminate illicit connections and illegal discharges co-permittees are required to implement a dry weather field screening program. The dry weather field screening program requires each co-permittee to implement; a BMP program, a storm water ordinance and funding source, and set up a monitoring and reporting program.
This study evaluates the dry weather testing data stored at the Regional Water Quality Control Board in San Diego. This information has been analyzed to determine which of the co-permittees have performed dry weather testing during the study period. The statistical analysis data for the southern San Diego region has been analyzed for the five main constituents found in storm water. These constituents are chlorine, copper, detergents, phenols, and ammonia. pH was also analyzed for this study. Using this analyzed information the maximum level , median level, average level, minimum level, and standard deviation for each constituent was identified. Then, potential patterns were analyzed, hot spots were identified, and observations and suggestions were made. Data from the study area was then compared to data from the County of San Diego to identify patterns between urban and rural areas.