Date of Award

2009

Degree Type

Thesis

Degree Name

Master of Science in Civil and Environmental Engineering

Department

Civil and Environmental Engineering

First Advisor

Raymond M. Wright

Abstract

The Ponaganset River Basin consists of an area of 14.4 mi2 located in the town of Foster, Rhode Island. This area is located within the northwest region of the Scituate Watershed. The source of this river comes from the Ponaganset Reservoir with an area of 2.1 mi2 and a storage capacity of 742 MG. Water quality samples were collected at United States Geological Survey (USGS) site (01115187) which is approximately 5 miles down stream from the reservoir and 0.4 miles upstream from Barden Reservoir. The Ponaganset River has the largest mean daily discharge of all the sampling locations in the Scituate Reservoir watershed.

The concept of this analysis originated with the 1995 Water Quality Protection Plan which sited a lack of wet weather data on the Scituate Reservoir Watershed. No wet weather data was collected from the watershed between 1995 and 2003. In 2003, the Water Quality Protection Plan again sited a lack of wet weather data on the Scituate Reservoir Watershed as one of the major weaknesses. The plan recommended the need to determine potential wet weather impacts as well as the potential sources of those impacts on the environment.

The objective of this analysis was to determine non-point sources of pollutants which contribute to the river and establish a preliminary wet weather monitoring program to determine pollutant loads contributed by stormwater runoff. In addition, this analysis was intended to establish a procedure to extrapolate wet and dry weather data from a characteristic sub watershed to the entire Scituate Watershed. In this study, the Ponaganset River site was selected based upon preliminary research, historical water data, and range of flows for the selected site. The data collected during wet weather sampling provided insight into the behavior of the sources during various storm events as well as storm characteristics. The information acquired for use in this analysis was used to explore load characteristics using linear and multiple regression models to predict loads then apply them to monthly and annual parameter data to determine if the site is either influenced more with dry weather or wet weather.

As more stringent water quality standards continue to increase, monitoring the health of the watershed will increase as well. Evaluating the water quality under dry and wet weather conditions seems fitting to answer some of these questions in addition to fulfilling the requirements of this thesis. In this study, water quality results, loads, and linear/multiple regression models are used to determine load characteristics that exist at this site and to relate this information to the entire watershed.

The field data used to develop the statistical models was conducted solely by the investigator and all samples were tested by Premier Laboratory in Dayville, Connecticut. Sampling and monitoring for the analysis occurred for a period of approximately two years during the months from April to September in 2005 and 2006. Three wet weather events were successfully captured for the wet weather program: Storm 1 (May 2-4, 2006), Storm 2 (July 12-14, 2006), and Storm 3 (September 19-20, 2006). A total of twelve dry weather samples were collected between April through August 2005 and May through September 2006. The initial samples collected consisted of total suspended solids (TSS), biological oxygen demand (BOD), inorganic constituents, total trace metals, and nutrients. During sample collection the introduction of errors was always a concern and careful consideration was taken to avoid any contamination to the water samples. A strict regimen of water sample collection techniques, preservation, and laboratory analysis were carefully adhered to avoid any contamination.

Concentration data and flow data were used to calculate the mass load. With the use of the water quality data collected at the site, it allowed for the development of empirical equations used to determine dry and wet weather loads. _ Linear regression models were developed for dry weather and multiple linear regression models were developed for wet weather conditions for selected constituents. The six primary constituents included barium, manganese, aluminum, iron, sodium, and chloride. A limited amount of total coliform bacteria data was also included in the analysis. The largest loads observed at the site included sodium and chloride during wet weather conditions. The equations were later applied to hydrograph data which had been generated for a period of a year that occurred from October 1, 2003 to September 30, 2004. Although the data set used to develop the models was limited to twelve dry weather samples and three storm events, the data showed that it could be applied to the monthly and annual parameter data used to describe dry and wet weather load characteristics for this sub-watershed. The application of the mathematical models indicates that the Ponaganset River watershed is both dry and wet weather influenced. Finally, the analysis provides a procedure to determine annual loads and provide recommendations for future wet weather assessment for the entire Scituate Reservoir.

Further evaluations of wet weather monitoring within the Scituate Reservoir Complex will be needed to access the overall health of the watershed. A team effort is needed as planning is crucial in order to gather accurate data. The findings of this analysis may lead to a more extensive wet and dry weather analysis encompassing the entire watershed.

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