Norwalk River and Harbor Bacterial Data Analysis Technical Report F Norwalk Harbor Management Commission

Norwalk Harbor

Calf Pasture Point

Manresa Island

Norwalk Islands

Norwalk River and Harbor Bacterial Data Analysis Technical Report F Norwalk Harbor Management Commission

Thomas Hart Geoffrey Steadman

June 2015

Norwalk River and Harbor Bacterial Data Analysis Technical Report

Norwalk Harbor Management Commission

Norwalk, Connecticut

Prepared By:

Thomas Hart & Geoffrey Steadman

June 2015 ii

NORWALK HARBOR MANAGEMENT COMMISSION

Jose Juan Cebrian (Chairman)

Anthony Aitoro

William Gardella

Anthony Mobilia (Vice Chairman)

John T. Pinto, Ph.D.

John C. Romano

Dennis Santella (Secretary)

Jan Schaefer

Richard J. Stumpf

Ex-Officio Member:

Michael Griffin State of Connecticut Harbor Master for Norwalk

Commission Planning Consultant:

Geoffrey Steadman

NORWALK HARBOR MANAGEMENT COMMISSION:

Norwalk City Hall 125 East Avenue P.O. Box 5125 Norwalk, Connecticut 06856-5126 (203) 854-7780

www.norwalkct.org

iii

FOREWORD

This report presents an analysis by the Norwalk Harbor Management Commission (NHMC) of historical data concerning water quality conditions in the Norwalk River and Harbor. Norwalk Harbor is a center of recreational boating activity in western Long Island Sound and the location of arguably the most valuable shellfish resources in the Sound.

The analysis provides a scientific demonstration of the relationship among bacteria in the river and harbor, rainfall amounts, and river flow; reinforces the need for continued stormwater best management practices (BMPs) as called for in the Norwalk Harbor Management Plan and Norwalk River Watershed Action Plan; and confirms the current practice of using rainfall amounts as predictive pollution events for managing harvest closures in shellfish growing areas.

Since rainfall measurements in the lower, most urbanized part of the watershed show a strong relationship with Harbor bacterial levels, implementing BMPs in locations near the harbor should have the greatest benefit. In addition, capability to identify relationships in the data may be improved if existing monitoring programs are coordinated so that water samples from the river and harbor are taken within a day of each other. Application of microbial source tracking (MST) methods to identify the major sources of bacterial contamination entering the river and harbor is recommended. If the relative bacterial contributions of waterfowl, dogs, and humans, for example, are discerned, pollution abatement measures more specific to the sources may be developed.

The Norwalk Harbor Management Plan, adopted by the Norwalk Common Council and approved by the State of Connecticut, establishes a vision for safe and beneficial use of the harbor and protection of the harbor’s environmental quality, including water quality. Achievement of that vision is based on the concept of perpetual stewardship whereby the agencies, organizations, governmental officials, residents, and visitors with an interest or authority pertaining to the harbor recognize their responsibilities for care of the harbor in the public interest. That care—or stewardship—is for the purpose of ensuring that the coastal resources and environmental quality of the harbor are sustained for the future.

The Harbor Management Plan also encourages a “water quality partnership” of all stakeholders. That partnership is reflected in the work of the Harbor Management Commission, Mayor’s Water Quality Committee, and Norwalk River Watershed Initiative.

CONTENTS

Page

Introduction and Background ...... 1

Norwalk Harbor on Long Island Sound ...... 1 Norwalk River Watershed ...... 4 Harbor Management Plan ...... 7 Problem Statement ...... 8 Study Goals ...... 9 Data Sources ...... 9 Hypotheses ...... 13

Methods ...... 14

Review and Selection of Data ...... 14 Pairing Samples by Date and Rainfall Events ...... 17 Data Transformations...... 18 Development of Precipitation and Flow Measures ...... 19 Statistical Methods ...... 21

Analysis ...... 22

Hypothesis Testing Results ...... 23 Summary of Findings ...... 24 Conclusions ...... 25 Next Steps ...... 26

Appendix ...... 27

Project Team ...... 36

LIST OF FIGURES, MAPS AND TABLES

Figure 1: Norwalk Harbor estuary on Long Island Sound (Calf Pasture Point at right) ...... 2 Figure 2: The view south over the Norwalk River and Harbor to Long Island Sound ...... 4 Figure 3: Norwalk River, upstream in the watershed ...... 7 Figure 4: Average bacterial levels in harbor (orange, transformed) and river (blue) by date ...... 19 Figure 5: River flows for 2011 ...... 20 Figure 6: Single storm flow record with peak flow and monitoring program sample times (flow in cubic feet per second against duration in minutes) ...... 20

Map 1: The City of Norwalk on western Long Island Sound ...... 2 Map 2: Norwalk Harbor, including Inner and Outer Harbors...... 3 Map 3: Norwalk River watershed and river water quality sampling locations ...... 5 Map 3A: Norwalk River watershed and river water quality sampling locations ...... 6 Map 4: Norwalk Harbor water quality sampling locations and shellfish growing area classifications ...... 12 Map 4A: Norwalk Harbor water quality sampling locations and shellfish growing area classifications ...... 15 Map 5: Watershed with up-river and down-river sample groups circled...... 16 Map 6: Harbor sample sites ...... 23

Table 1: Subset of river sample results ...... 10 Table 2: Sample subset for a single harbor sample station ...... 11 Table 3: Paired sample dates ...... 17 Table 4: Example of data pairs combined for two dates ...... 18 Table 5: Flow measure examples ...... 21

Introduction and Background

This report presents findings and conclusions from the “Norwalk River and Harbor Bacterial Data Analysis Study” (the study) conducted for the Norwalk Harbor Management Commission (NHMC) and Mayor’s Water Quality Committee (MWQC) in the period 2013-2014.1 The purpose of the Study was to improve understanding of how the Norwalk River and its watershed influence water quality in Norwalk Harbor (the harbor) and to otherwise improve the NHMC’s ability to protect and improve the harbor’s water quality. The NHMC, guided by the Norwalk Management Plan (the Plan), has a responsibility to protect and improve the harbor’s water quality. Harbor shellfish resources, generally considered the most valuable in the state, depend on clean water, as do safe and enjoyable boating, swimming, and every other water-based recreational activity.

The study continues to advance the NHMC’s understanding of the ecological relationships linking the Norwalk River, its watershed, Norwalk Harbor, and Long Island Sound by investigating the relationship between levels of bacteria found upstream in the river and the quality of water in the harbor.

Norwalk Harbor on Long Island Sound

Norwalk Harbor, located at the mouth of the Norwalk River in southwestern Connecticut, is a center of boating and commercial shellfishing in western Long Island Sound. (See Map 1 and Figure 1.). Southwestern Connecticut is one of the most developed regions of the state. The City of Norwalk, with a population in 2010 of 85,621, is one of the region’s principal population and commercial centers.

Boundaries of the harbor, extending inland from south of the Norwalk Islands to the “head of navigation” on the Norwalk River, are established in the City Charter and Norwalk Harbor Management Plan. (See Map 2.)

At the mouth of the Norwalk River, the harbor is generally one half-mile wide and well-sheltered from coastal storms by Calf Pasture Point on the east, the Manresa Island peninsula on the west, and the Norwalk Islands to the south. Despite the geographic extent of harbor waters, depths throughout much of the harbor are generally shallow except where congressionally authorized federal navigation channels and anchorage basins have been dredged and maintained. Inland from South Norwalk, the harbor is confined and narrowed by the banks of the Norwalk River. The river here is generally 100 to 200 yards wide and winds through intertidal flats and marshes to the “head of navigation” at Wall Street (see Figure 2).

1 The Norwalk Harbor Management Commission is a municipal agency established by City Ordinance in accordance with authority provided by Sections 22a-113k through 22a-113t of the Connecticut General Statutes to plan for the safe and beneficial use and conservation of Norwalk Harbor. Among its powers and duties, the NHMC is charged with preparing and implementing the Norwalk Harbor Management Plan. The Plan calls for the NHMC to provide a leadership role for the Norwalk Mayor’s Water Quality Committee whose members are appointed by the Mayor to analyze pollution problems, recommend measures to protect and improve water quality in the harbor, and increase public awareness of water quality issues. Recommendations of the MWQC are for implementation by the Mayor, Common Council; NHMC, Health Department, Department of Public Works, and other city agencies with authorities and responsibilities to protect water quality. 2

Map 1: City of Norwalk on western Long Island Sound

Figure 1: Norwalk Harbor Estuary on Long Island Sound (Calf Pasture Point at right) 3

Map 2: Norwalk Harbor, including Inner and Outer Harbors 4

Figure 2: The view south over the Norwalk River and Harbor to Long Island Sound

The NHMC recognizes that natural features of the harbor, including its estuarine environment, tidal wetlands, extensive areas of intertidal flats, and the sheltering presence of the Norwalk Islands, provide exceptional shellfish habitat. Principal responsibility for managing the harbor’s shellfish resources rests with the Norwalk Shellfish Commission and the Connecticut Department of Agriculture’s Bureau of Aquaculture (DA/BA).

Norwalk River Watershed

The Norwalk River Watershed - the geographic area from which precipitation drains off the land, pulled downhill by gravity to the river and ultimately into the harbor and Long Island Sound - covers about 64 square miles in parts of seven towns: Norwalk, New Canaan, Redding, Ridgefield, Weston, and Wilton in Connecticut and Lewisboro in New York State (see maps 3 and 3A). The Norwalk River Watershed Initiative (NRWI), a partnership of the seven watershed towns, concerned citizens, local organizations, and state and federal agencies, pursues cooperative and voluntary projects to protect and improve water quality in the watershed. NRWI activities are guided by the Norwalk River Watershed Action Plan endorsed by the seven watershed towns and which includes recommendations and strategies to reduce pollution in the watershed. 5

Within the watershed, two significant tributaries to the Norwalk River are the Silvermine River (approximately eight miles long) and Comstock Brook (about three miles). The Norwalk River begins in an area known as the Great Swamp in Ridgefield, flows north for about a mile, and then south for 20 miles before entering Long Island Sound through the tidal estuary at Norwalk Harbor.

The river’s width ranges from six to 20 feet in its northern half (see Figure 3) where it is generally hidden from public view by vegetation and development, and from 30 to 70 feet in its southern half before it enters the navigable waters of the harbor downstream of Wall Street. Upstream of the harbor, the river’s substrate is primarily composed of cobbles, boulders, and sand. From its highest elevation of 860 feet above sea level, the Norwalk River flows to Long Island Sound at an average gradient of one half of one percent.

Figure 3: Norwalk River, upstream in the watershed

Harbor Management Plan

Protecting and improving the harbor’s water quality is a basic goal of the Norwalk Harbor Management Plan and responsibility of the NHMC. The Plan—prepared by the NHMC, approved by the State of Connecticut in 1989, adopted by the Norwalk Common Council in 1990, and most recently amended in 2009—includes a number of provisions to maintain and improve water quality in the harbor. Included are policies to reduce or eliminate nonpoint sources of pollution2 and encourage the use of suitable best management practices3 to manage, reduce where feasible, or otherwise control storm-water runoff into the harbor.

2 Nonpoint source (NPS) pollution is pollution that does not originate from a specific identifiable source such as a discharge pipe. Types of NPS pollution include storm-water runoff from roads, parking lots, and backyards as well as wet and dry atmospheric deposition. Precipitation can carry pollutants from the air to the ground and then gather more pollutants as the water runs off pavement and land to the nearest waterway.

3 Best management practices (BMPs) are regulatory, structural, or nonstructural techniques applied to prevent and reduce NPS pollution. Some examples of BMPs are buffers of streamside (Continued) 8

It is a policy of the Plan that “Initiatives to improve water quality in Norwalk Harbor that are planned and implemented on a watershed-wide basis in coordination with other communities in the Norwalk River watershed and other coastal watersheds draining into the harbor should be encouraged and supported. Implementation of the water quality initiatives contained in the Norwalk River Watershed Action Plan endorsed by the City of Norwalk should be encouraged and supported.”

It is also a policy of the Plan that “An effective, ongoing program of water quality monitoring in Norwalk Harbor and upstream in the Norwalk River by qualified governmental and nongovernmental organizations should be encouraged and supported to identify existing and potential sources of pollution and to establish and maintain a data base of information to support water quality improvement efforts by city agencies with water quality responsibilities and authorities.”

In addition, the Plan establishes a number of provisions to manage, protect, and where feasible restore harbor shellfish resources.

Problem Statement

Norwalk Harbor is an estuary where saltwater from Long Island Sound mixes with freshwater from the watershed. Much of the flow in the estuary is governed by the tide rising and falling twice a day along the harbor’s shoreline. Occasional and unpredictable precipitation falling in the watershed drains off roads, parking lots, lawns, and other surfaces, adding to the flows in the harbor estuary. As this freshwater runs over the ground and into storm drains it picks up pollutants such as oil, sand, debris, pesticides, bacteria, and nutrients. This nonpoint source pollution, also called runoff pollution, can make its way to the river, harbor, and Sound.

Bacterial pollution is detected in the harbor from time to time at levels that exceed the state’s water quality standards, including standards established by the Connecticut Department of Energy and Environmental Protection (DEEP) for recreational use of the water, and standards established by the Connecticut Department of Agriculture’s Bureau of Aquaculture for harvesting shellfish.4 As a result, swimming from public and private beaches is sometimes prohibited by the Norwalk Health Department, and restrictions on commercial and recreational shellfishing are imposed by the DA/BA. Those restrictions are especially significant as Norwalk Harbor’s shellfish resources provide uncommonly high economic and recreational values in the State of Connecticut and the harbor supports a viable inter-state shellfishing industry generating economic benefits of local and state-wide significance.

Several ongoing programs collect and test water from the river and harbor. Historically, water quality data have been collected for several different purposes, including management of shellfish growing areas and beach recreation areas and identification of possible contamination

vegetation to keep pollutants from entering a watercourse; construction of wetlands to act as natural filters; and improved street-cleaning and catch basin maintenance programs.

4 The DA/BA has an important role in managing shellfish resources in the harbor, particularly with respect to evaluating and classifying Harbor waters for shellfishing, licensing shellfishing activities, and generally working in coordination with the Norwalk Shellfish Commission and other agencies, including the NHMC, to protect and enhance shellfish resources. 9 sources. Since the ongoing monitoring programs have different purposes, they have always been conducted independently. The NHMC wished to determine if consolidating the data from the river and harbor might advance understanding pollution dynamics in the harbor. A broad goal was to provide additional information to help support evidence-based decisions to protect and improve water quality. More specifically, the NHMC wanted to determine if upstream river conditions are related to levels of bacteria found in the harbor.

Study Goals

1. To advance the provisions of the Norwalk Harbor Management Plan to protect and enhance water quality in Norwalk Harbor, including the Plan’s policy to maintain an effective program for water quality monitoring;

2. To conduct an assessment of three separate water quality data sources (from the Norwalk River, Harbor, and city beaches) and develop protocols for data consolidation;

3. To design appropriate analytical methods for evaluating the consolidated data for the purpose of conducting a useful analysis concerning bacterial pollution in the harbor and river;

4. To apply the analytical methods to explore potential relationships between bacterial pollution in the harbor and river and, more specifically, to determine the extent to which bacterial pollution observed in the river may be related to bacterial pollution in the harbor;

5. To present outcomes of data analyses that will illustrate pollution conditions within the analysis year and across the geographic extent of the harbor, river, and beaches;

6. To develop recommendations for improving long-term water quality monitoring in the harbor and river and applying water quality data for harbor management purposes, including shellfish management purposes;

7. To provide an assessment of the anticipated value of an analysis of the complete ten-year period of data; and

8. To identify pertinent natural and anthropogenic factors affecting water quality in the harbor and river, including, but not limited to, precipitation, stream flow, tidal action, and shoreline configuration, and describe how those factors influence water quality.

Data Sources

Historically, water quality data, including data concerning the levels of fecal coliform bacteria in the water column, have been collected from the Norwalk Harbor and River by the Connecticut Department of Agriculture’s Bureau of Aquaculture, the Harbor Watch (HW) program of the non-profit Earthplace The Nature Discovery Center based in Westport, Connecticut, and the Health Department of the City of Norwalk. The bacteria Escherichia coli (E. coli), a type of fecal coliform bacteria commonly found in the intestines of animals and humans, is used as an indicator of fecal contamination by the Connecticut Department of Energy and Environmental Protection for determining compliance with the state’s water quality standards. 10

With funding assistance from the DEEP and City of Norwalk, HW collects and tests water samples for fecal coliform from established in-stream locations in the Norwalk River upstream of the harbor (and therefore upstream of tidal influence) and also from specific storm drains entering the harbor. Much data have been collected to document the level of pollutants that can be found in the river. Each year HW volunteers, including high school students, college interns and adult volunteers supervised by HW environmental science professionals, collect complete rounds of water samples from 12 established locations in the Norwalk River as far upstream as Ridgefield (see Table 1). Using funds provided by the Norwalk Harbor Management Commission and Shellfish Commission, HW tests the samples to identify the presence of bacteria that can degrade environmental quality and adversely affect public health.5

Table 1: Subset of river sample results At the same time, the Norwalk Health Department and the Connecticut DA/BA collect and test water samples from near the city’s beaches and in the harbor, respectively. The Health Department tests the water immediately following rainfall events; prohibits swimming when bacterial levels exceed established criteria; and allows swimming to resume when additional tests show the bacterial level has returned to acceptable levels.

The DA/BA regularly collects and tests water samples from established locations in the harbor for the purpose of monitoring shellfishing areas for commercial and recreational harvesting (see Map 4 and Table 2). To protect public health, the DA/BA may close shellfish growing areas when bacteria are detected in amounts that exceed federal standards for shellfish sanitation and compliance with the National Shellfish Sanitation Program (NSSP) of the U.S. Food and Drug Administration.6 Depending on the harbor shellfishing area affected, the DA/BA considers rainfall events that exceed either one inch or 1.5 inches in a 24-hour period as “predictable pollution events” presumed to introduce excessive NPS bacterial pollution into the harbor.

5 The HW laboratory is certified by the Connecticut Department of Health and operates in accordance with U.S. Environmental Protection Agency Quality Assurance Project Plans.

6 To ensure compliance with the NSSP, the DA/BA tests the quality of coastal waters to determine if those waters are suitable for shellfish harvesting. Following evaluation of water quality, the DA/BA classifies coastal waters for the taking of shellfish. Basic classifications are “Approved,” “Conditionally Approved,” “Restricted,” “Conditionally Restricted,” and “Prohibited.” 11

These events trigger automatic closure of specific shellfishing areas for at least seven days; they remain closed until satisfactory samples are collected by the DA/BA.

Table 2: Sample subset for a single harbor sample station 12

In addition to the data concerning the presence of bacteria in the river and harbor, stream flow and rainfall data for the river and watershed are available. These data were included in the study to investigate the predictive value of stream flow and precipitation on harbor bacterial levels. Two river flow gauges maintained by the U.S. Geological Survey (USGS) are located on the Norwalk River: one in Norwalk just downstream of the Merritt Parkway and the other in Wilton. Data from these gauges provide a good measure of total precipitation in the watershed, and may well reflect rainfall associated with large storm systems with broader areas of rainfall including rainfall in the upper reaches of the watershed and rainfall that produces significant runoff with an associated increase in stream flow. Two other measures of precipitation are found in data available from the National Weather Service (NWS) and from the Norwalk Health Department. The Health Department’s rain gauge data is a direct measure of rainfall amounts nearby the harbor. NWS data combines local rainfall gauge observations with radar data to provide reliable estimates of localized precipitation. Rainfall gauge data can be used to estimate the total volume of precipitation falling within the more densely-developed lower contribution basin for the Norwalk River, potentially providing a good measure of non-point runoff that might be most closely related to observed levels of bacteria in the river.

Hypotheses

The available data sources described above lend themselves to development of the study’s five specific hypotheses concerning potential relationships between Norwalk River water quality conditions and observed levels of bacteria in Norwalk Harbor.

Hypothesis 1: River Bacteria Monitoring. Levels of coliform bacteria measured through the river monitoring program are related to levels of fecal coliform found in harbor monitoring samples.

Analysis of river bacteria monitoring data may answer the question, “Does the level of bacteria in the river provide a good predictive measure of the likely levels of harbor contamination? If it does, what levels of reduction in the river need to be achieved in order to see a corresponding decrease in the harbor levels?”

Hypothesis 2: Beach Bacteria Monitoring. Levels of bacteria measured through the beach monitoring program are related to the levels of fecal coliform bacteria found in harbor monitoring samples.

Analysis of beach bacteria monitoring data may answer the question, “Is the amount and proximity of contamination immediately offshore of swimming beaches a significant contributor to the observed levels of bacteria in the harbor? If it is, what are the sources of beach contaminants and what measures need to be considered to reduce contaminants?”

Hypothesis 3: River Flow. River flow levels are related to of levels of bacteria found in harbor samples.

Analysis of river flow data may answer the question, “How much does river flow account for the amount of bacteria observed in the harbor? If river flow explains a significant portion of the levels of bacteria in the harbor, then general precipitation in the watershed and its associated large scale runoff along with river sediment scouring may influence the level of bacteria observed in the harbor.”

Hypothesis 4: Local Runoff. Local rainfall amounts in the lower watershed are related to levels of bacteria found in harbor samples.

Analysis of local runoff, as measured by modeled rainfall volume in the lower watershed may answer the question, “How much of the observed bacterial levels in the harbor is related to localized runoff and its associated mobilization and flow of surface contaminants adjacent to the river and harbor?”

Hypothesis 5: Total Bacterial Load. The total load of bacteria from the river as determined through the combination of runoff data and River bacteria concentration is related to the observed harbor monitoring.

Analysis of combined river bacteria, river flow, and rainfall data may answer the question; “Does the combination of bacteria, river flow, and precipitation data provide the best measure of observed contaminant levels in the harbor? If it does, then future presentations of contaminant levels in the river should consider precipitation in addition to bacteria concentration in measures of progress to improve water quality.”

Testing of the above hypotheses was accomplished simultaneously to determine which, if any, of these considerations - River bacteria, river flow, and precipitation -are significant contributors to the levels of bacteria found in the harbor.

Methods

Ten years of available data were assembled from beach, river and harbor monitoring programs. After reviewing the volume and structure of the compiled data sets, a test case was designed to develop analytical methods using river and harbor data from 2011, the latest monitoring year available upon initiation of the study. An explanation of the specific means of incorporating data for each environmental measure accompanies the data set description.

Review and Selection of Data

The review of bacterial concentration data sets included development of rules for selection of data. Originally it was thought that the best approach may be to include all up-river data as individual observations and to then find corresponding harbor data observation on the same or nearly the same date. Initial analysis of both river and harbor data did not show a sequence or pattern in the data. That is, no observations of an initial high level of upstream bacteria could be tracked as an independent flow of contamination that appeared at a later time in downstream samples, much as a chemical spill might be observed to move down-river. Rather, bacterial levels were observed to be generally elevated throughout the river on the same sampling event either reflecting a system-wide increase in bacteria or that the sampling resolution in time does not match the time period needed to track individual contributions by site. Similar observations were made for harbor samples.

This observation dictated a different analytical approach whereby multiple sampling stations constituted the replicates for harbor and river observations. Of the data for harbor observations, there were five sample stations with consistent sample results. (See Map 4A.) Of the data for river observations, results for ten sample stations were consistently available, five down-river sites and five up-river sites. This lends to a design using the five harbor sites as replicate 15 observations of harbor conditions and two sets of river data with five replicate observations each: reflecting down-river conditions and one reflecting up-river conditions. (See Map 5.) Beach bacterial data was available for a more limited calendar period, reflecting the shorter swimming season roughly from Memorial Day to Labor Day.

Map 5:

Map 5: Watershed with up-river and down-river sample groups circled

In order for the design to be successful, samples from harbor, beach and river sample stations need to be measuring the same conditions. The overall approach is to find matched data samples for river, beach and harbor data by date. That means the samples data must be:

1) reasonably coincident (measured on the same or nearly the same dates), 2) without intervening rainfall between sample dates, 3) suited to rules to address handling of missing data, and 4) within reasonably similar ranges.

Estimates for missing sample data may add strength to the analysis so that more sample and flow data can be incorporated. It is possible to produce data estimates for use in analysis that are neutral in affecting the analysis so that other data can be included that would benefit analysis. Finally, data transformation may be necessary to make comparisons among the different data sets so that variance of the data is in a reasonably comparable range of values.

Pairing Samples by Date and Rainfall Events Matched Sample Dates How far apart can samples be to be reasonably coincident? We used the shellfish bed closure periods as rough guidance River Harbor for measuring coincident dates. Although it would be 5/5/2011 01/04/11 desirable to have samples all within one day, we applied A 5/12/2011 01/19/11 five days as the maximum difference in sample times. (See 5/19/2011 02/07/11 Table 3.) Any sample taken with an intervening rainfall B 5/26/2011 03/29/11 event within the five-day sample period was not used. 6/2/2011 04/19/11 Using a shorter time period between sample events was C 6/9/2011 04/26/11 considered, but did not produce enough data for analysis. D 6/16/2011 A 05/10/11 6/23/2011 05/23/11 Applying these rules resulted in nine sets of observations 7/7/2011 B 05/26/11 for harbor and river data sets with 5 replicate samples for 7/14/2011 C 06/07/11 harbor data and ten replicate samples for river data resulting E 7/21/2011 D 06/20/11 in 119 observations (see Table 4). One missing sample 7/28/2011 07/06/11 observation in the harbor data was estimated using the F 8/4/2011 07/20/11 average of the remaining four observations on that single 8/11/2011 E 07/21/11 date. One data point in the harbor data set was identified an G 8/18/2011 F 08/08/11 outlier data point (extremely high) and was re-estimated 8/25/2011 G 08/22/11 from the average of the remaining data on that date. 9/1/2011 H 09/12/11 H 9/8/2011 I 09/22/11 Preparation of the beach data proved problematic. The 9/15/2011 09/26/11 purpose of the beach data is to determine if beaches could I 9/22/2011 10/03/11 be open during public use periods, ostensibly biasing the 10/18/11 data collection to before weekends. The shorter season of 10/24/11 the data collection (not during colder spring and fall 11/07/11 months) and the number of intervening rainfall events did 12/01/11 not allow selection of paired sample dates that would reflect 12/06/11 the same conditions measured in river and harbor samples, 12/13/11 both of which used rainfall events as sampling triggers. 12/20/11 Table 3: Paired sample dates 18

Table 4: Example of data pairs combined for two dates

Data Transformations

Harbor and river bacteria data are separated by several orders of magnitude with harbor E. coli numbers being much lower than river fecal coliform numbers. That is, river data may typically be measured in the hundreds of fecal coliform colonies, while harbor samples are more often in the single digits. An exponential reduction of fecal coliform concentration is documented in the literature as the estuarine environment is more hostile to these bacteria. In addition, volume of water in Long Island Sound and the tidal flow of water is substantial in comparison to river volume such that dilution may be a large factor. Add to this the efficiency of shellfish in filtering bacteria from the water column and there is a strong rationale for why sample results are much lower. In order to proceed with an analysis (the range of variance in the data must be somewhat similar), data transformations were performed including: the sum of observations (not averages); direct multiplication of the sum of harbor data values by 100; and exponentiation of the sum of harbor data. (See Figure 4.)

Rainfall data also needed to be scaled by multiplying by 10 to allow for a successful analysis using comparable variance ranges.

Figure 4: Average bacterial levels in harbor (orange, transformed) and river (blue) by date.

Development of Precipitation and Flow Measures

Rainfall gauge data was available from the Health Department for each rainfall event. This is the same data provided in each of the river and harbor monitoring sample data sets and was used to determine which bacteria data could be paired. In addition, how many days rainfall occurred prior to the sample date was used along with the number of days offset between river and harbor sample dates. Both the days prior to sampling and the difference between sampling dates for both river and harbor samples were used to measure the impact of not having sample dates coincident with rainfall events and with each other.

Flow data was collected from the National Weather Service for the lower USGS stream gauge station located below Merritt Parkway for the entire year using their online data site (see Figure 5). River flow data is available for all sample periods allowing each rainfall event preceding each paired set of samples to be characterized. (See Figure 6.)

Figure 5: River flows for 2011

Figure 6: Single storm flow record with peak flow and monitoring program sample times (flow in cubic feet per second against duration in minutes) 21

Several measures were developed to test whether different characterization of flow would be related to harbor bacterial levels. The measures are: total flow volume after a storm, duration of flow, intensity of flow, duration of peak flow, peak flow volume, peak flow intensity, and 24 hour flow volume. Total flow was the river flow volume from the start of flow increase to a point of consistent level flow that captured the entire runoff event. Duration of flow was the time period from start to finish of the total flow. Flow intensity is the total volume divided by the duration, providing a rate of flow.

Peak flow was determined by identifying the start of increased river flow and the maximum river flow, then summing the flow volume for each of the 15 minute periods and converting the units to acre/feet from cubic feet. Duration of peak flow was the time from the start of elevated flow to the maximum flow in hours. Peak flow intensity is the peak volume divided by duration.

Of these measures, those associated with peak flow were easiest to calculate as they avoided the ambiguous determination of when the river returned to a normal state of flow. Each provides a different estimate of storm runoff with volume providing the total amount of runoff entering the river from a storm, duration providing the speed of runoff entering the river, and intensity measuring the possible flushing effect of the combination of volume and time. (See Table 5.)

Rainfall Days_Before Sample Offset XFlow_24Hr PFlow_Duration Pflow_Vol Pflow_Intensity 0.5 1 5 82 11.00 77 7 2.64 1 4 292 40.25 823 20 0.68 2 0 78 9.50 130 14 0.42 4 5 32 5.00 29 6 2.19 0 4 263 2.00 88 44 1.46 2 0 9 4.25 8 2 3.88 3 4 34 13.25 77 6 3.41 0 4 530 59.25 2036 34 Table 5: Flow measure examples

Statistical Methods

The statistical method used in this analysis is based on General Linear Models (GLM), a fundamental method on which many statistical tests are based. In this analysis, GLM is used to perform regression, analysis of variance and analysis of co-variance to test whether any of the independent variables have a significant role in explaining the bacterial levels found in the harbor. The dependent variable is the transformed harbor data set (X or the left side of the statistical equation). The independent variables (Y or the right side of the equation) are: river bacterial levels (sum of all ten stations); down-river bacterial levels (sum of five stations); up- river bacterial levels (sum of five stations); rainfall gauge level (inches); river flow (peak volume (acre-ft), flow duration (hours), and intensity (acre-feet per hour)). Additional analyses were performed to test whether transforming the data changed the analysis, whether the delay in obtaining samples after a rainfall were significant, and whether a delay between sampling in the river and harbor was significant. We also employed a multivariate form of the General Linear 22

Model where we can use the five harbor sample sites all as separate dependent variables (five values on the left side of the equation) to test whether all harbor sample sites were the same with respect to being influenced by river data (bacteria, rainfall or flow measures).

Analysis

A sequential exploratory analysis was performed where different sets of independent variable and combination of variables were analyzed against levels of harbor bacteria. Probability values are only reported for those analyses resulting in statistical significance. Analysis result tables are included in the appendices.

Sample offset from rainfall date, difference in sample collection date between river and harbor sampling, and transformations were tested to determine if these influenced the analysis. None of these variables were statistically significant.

Levels of harbor bacteria showed a significant relationship with the following:

 Rainfall alone (p= 0.004; p=0.006)  Rainfall (p=0.001) in combination with downriver bacteria (p=0.015) and peak volume (p=0.010)

No other combination of variables was able to provide additional explanation or significant predictors of observed levels of harbor bacteria.

Levels of harbor bacteria differed according to the sample site location in the harbor (see Map 6).

 The western most site (103-10.1) was not related to any of the variables.  The center of the harbor (103-15.3) was explained by rainfall alone (p=0.011)  Calf Pasture Point (103-15.6) was related to all three variables: downriver bacteria (p=0.016); rainfall (p=0.001) and peak flow (p=0.002).  The two sites to the east, Calf Pasture Beach (103-16.0) and Shorehaven (103-17.0) only related to peak flow (p= 0.002 and p=0.015, respectively).

See the Appendix for a complete list of 19 analyses and their outcomes. 23

Map 6:

December, 2014

Map 6: Harbor sample sites

Hypothesis Testing Results

Five hypotheses were developed at the initiation of this study. The analysis supports the following findings.

Hypothesis 1: River Bacteria Monitoring. Levels of coliform bacteria measured in river monitoring are related to levels of fecal coliform found in harbor samples. Hypothesis is not supported when river bacteria are considered alone.

Hypothesis 2: Beach Bacteria Monitoring. Levels of bacteria found in adjacent beach monitoring are related to the levels of fecal coliform bacteria found in Harbor monitoring. Data characteristics did not allow for testing this hypothesis.

Hypothesis 3: River Flow. River flow levels are related to of levels of bacteria found in harbor monitoring. Hypothesis is not supported when river flow data is considered alone.

Hypothesis 4: Local Runoff. Local rainfall amounts in the lower river catchment basin are related to levels of bacteria found in harbor monitoring. Rainfall data alone were consistent predictors of harbor bacterial levels. Hypothesis is accepted.

Hypothesis 5: Total Bacterial Load. The total load of bacteria from the river as determined through the combination of runoff data and river bacterial levels is related to levels of bacteria found in harbor monitoring. The combination of river flow, bacterial levels from downriver samples and rainfall provide the best explanation for levels of bacteria found in the harbor. Hypothesis is accepted.

Summary of Findings

By itself, the level of bacteria in the Norwalk River was not a good predictor of elevated levels of bacteria in the harbor. When rainfall amounts were considered, however, a statistically significant relationship between the river and harbor data was observed. Continuing the analysis, the best predictors were bacterial levels in the lower reaches of the river combined with rainfall and volume of river flow.

Harbor bacterial levels appear related to a complex combination of watershed processes. High bacterial counts from the upstream sampling locations in Wilton and Ridgefield did not appear to adversely affect bacterial levels in the harbor; the influence of runoff from the more developed areas of Norwalk surrounding the lower river was most significant; and the harbor sampling stations closest to the center of the harbor, roughly on a line from Manresa Island to Calf Pasture Point, were most affected by River conditions.

Not surprisingly, sampling stations within the harbor differed in their relationship to the river variables. The center of the harbor (103-15.3) and Calf Pasture Point (103-15.6) sites are closest to the river mouth and the analysis with respect to river variables is strongest for these sites. Calf Pasture Beach (103-16) and Shorehaven (103-17) sites are farther from the river mouth, but were still affected significantly by peak flow in the river. Analysis reflects the complex hydrologic processes involving the interaction of river flow with tidal flow and currents in the harbor and Long Island Sound.

The following findings are supported.

1. The statistical relationship of rainfall to harbor bacterial levels confirms the validity of current shellfish bed closure practices based on rainfall thresholds.

2. Sample stations in the harbor closest to the river have the greatest relationship to the river sample data.

3. River bacterial data alone do not explain levels of bacteria observed in the harbor; the combination of rainfall, river flow, and river bacterial levels does explain observations in the harbor.

4. Since levels of harbor bacteria are related to river bacterial levels, the value of reducing river bacterial pollution levels through existing monitoring and follow-up actions, including stormwater best management practices, are likely to continue to have value in reducing bacterial loads to the harbor.

5. Bacterial loading to the harbor appears to be generated most significantly by local runoff in the lower basin as indicated by the significance of rainfall data (as opposed to river flow data); ; data from upstream river sample stations show no relationship to harbor conditions.

6. Actions to control levels of bacterial loading from local runoff may be most effective in reducing harbor bacterial levels.

7. Adding sampling to existing stations within the restricted shellfishing area in the harbor may extend the availability of data for analysis and measuring change or effectiveness of pollution controls.

8. Since river bacterial levels are able to explain bacterial levels found in the harbor, identifying the origin of the bacteria in the watershed (from human, wildlife, or domestic animal sources, for example) becomes especially important.

9. Analytical methods utilized here have potential applicability to other Connecticut coastal areas where river and shellfish sampling data sets are available.

Conclusions

While results may appear intuitive, the significance of the statistical analysis is that it was able to utilize data collected from two separate monitoring programs and scientifically demonstrate a strong inter-relationship validating current harbor and watershed management programs. Analysis supports the validity of the rainfall “closure triggers” currently in place for the harbor’s conditionally open shellfishing areas. Study reviewer Kristin DeRosia-Banick from the Bureau of Aquaculture agreed, and emphasized that the DA/BA looks for closure triggers that are predictable and readily measured, such as rain amount or river flows. Without predictive tools, or when variables contributing to elevations in bacteria cannot be identified, the DA/BA’s only option for protecting public health is to downgrade the classification of the shellfish growing area. This means that without the benefit of an appropriate predictive measure, some harbor shellfishing areas could be downgraded to “prohibited” status.

The demonstrated relationship between bacteria in the river, rainfall amounts, and river flow reinforces the need for continued stormwater best management practices as called for the Harbor Management Plan and Norwalk River Watershed Action Plan to reduce runoff pollution. Since simple rainfall measurements in the lower, most urbanized part of the watershed show a strong relationship with harbor bacterial levels, the value of focusing stormwater BMPs near the harbor may have the greatest benefit. Ability to identify relationships in the data may be improved if the Harbor Watch and DA/BA monitoring programs in the river and harbor are coordinated so that water samples are taken within a day of each other.

Origin of bacteria in the river and harbor is not known. Application of microbial source tracking (MST) methods to identify the major sources of bacterial contamination is recommended. If the relative bacterial contributions of waterfowl, dogs, and humans, for example, are discerned, pollution abatement measures more specific to the sources may be developed.

Next Steps

1. To confirm the reliability of the findings, additional years of data may be subjected to the study’s method of analysis. The data year selected (2011) appears unusual with respect to storm activity, especially the occurrence of Hurricane Irene. In addition, data at the mid-harbor location (103-15.3) had one outlier observation that may mask relationships. Extending the analysis to a five-year period should be beneficial.

2. Analysis of the two disparate data sources—from the river and harbor sampling programs—was limited by the difficulty in pairing data sets that were both complete and taken at nearly the same time. Opportunities to improve coordination of sampling events should be considered to improve the strength of the analysis by offering more paired sample data.

3. Continued monitoring may be able to detect benefits accrued by reducing levels of bacteria entering the river. Expanded analysis of river and harbor data may contribute to more precise predictions of the levels of bacteria found in the harbor and, if so, document additional benefits derived from stormwater management practices and other measures to manage non-point source pollution.

4. The Norwalk River Watershed may be considered a model watershed for developing and testing Microbial Source Tracking methods suitable for application in southwestern Connecticut watersheds. MST analyses should be conducted to identify dominant sources of fecal contamination in the river and harbor and the relative contribution of each source. Consideration should be given to human sources (sewage disposal), domestic animal sources (including, but not limited to, dogs and horses), and wildlife sources (including, but not limited to, ducks, geese, and deer). Data developed through MST analyses should be utilized to validate or modify the current assumptions regarding pollution sources and loads, and to aid in the development of pollution abatement measures tailored to specific sources.

Appendix

Statistical Analysis Tables

(Significant statistical relationships are indicated by p values of less than 0.05.)

1. Comparing the (Sum of the Harbor Observations x 10) against the (Sum of the Up-River and Down-River Observation Sums) does not demonstrate any relationship.

2. The type of transformation of the data does not influence the analysis (sum multiplied by 10 or the sum squared).

3. If all the River data are combined together, bacterial levels in the river do not explain the Harbor bacterial levels. The statistical p values fall between the up-river and down-river values.

4. Rainfall amounts are significant in explaining observed levels of harbor bacteria using either squared sums or sums multiplied by 100 transformed data.

5. Adding down-river sample results does not show a difference in with bacterial levels in the harbor.

6. Adding river flow data does not show a difference in the relationship with bacterial levels in the harbor.

7. Adding maximum flow (24 hour flow) does not alter the analysis.

8. Flow intensity does not alter the analysis

9. Combining peak flow and intensity with rainfall appears to account for some of the variability in harbor bacterial levels, but does not rise to statistical significance.

10. Combining the most promising bacterial in River sample results with the best of the rain and flow data sets shows that volume of flow joins the rainfall data as a significant explanatory variable and that the Sum of the Down-River samples seems to account for more of the variability than in prior analyses

11. Selecting only the significant variables of flow volume, rainfall and down-river bacteria shows that all three variables contribute to explaining levels of harbor bacteria.

12. The fit between observed and predicted values from the three-variable model is good.

13. The five sample stations in the harbor are not the same. The western-most station doesn’t relate well to the variables.

14. The sample station in the harbor center is closely related to rainfall, but not flow or down- river bacterial levels.

15. Calf Pasture Point site accounts for most of the relationship with the three variables of peak flow, rainfall and sum of down-river bacterial levels.

16. Calf Pasture Beach site bacterial levels are related to peak flow.

17. Shorehaven site is related to peak flow volume.

18. The simplest explanation and fit is provided by rainfall and down-river bacteria at the center of the harbor.

19. The best fit of all data is provided by the three variables of peak flow, rainfall, and down-river bacterial levels at Calf Pasture Point site.

River flow analysis

1. Compilation of river gauge data for single rainfall event

2. Combined flow data for all rainfall events in 2011

3. Peak flow curves derived from flow data (sum values over time for volume)

Project Team

The Project Team for conducting the study consisted of environmental science consultant Thomas F. Hart, Jr., Director, Program Implementation Group and Chief, Information Section (retired), New York State Department of Health, and Geoffrey Steadman, Norwalk Harbor Management Commission Planning Consultant and representative of the NHMC to the Norwalk River Watershed Initiative. Mr. Hart developed and applied the study’s analytical methods and along with Mr. Steadman is co-author of the study report. Other participants who provided information and vital advice and other assistance included: Thomas Closter, Director of Environmental Services, Norwalk Health Department; Tony D’Andrea, former Norwalk Harbor Management Commission member and chairman of the Mayor’s Water Quality Committee; Kristin DeRosia-Bannick, Lead Analyst, Connecticut Department of Agriculture Bureau of Aquaculture, Shellfish Sanitation Program; Richard Harris, Director of Harbor Watch (now retired) at Earthplace, The Nature Discovery Center; John T. Pinto, Ph.D., Norwalk Harbor Management Commission member and past chairman of the Mayor’s Water Quality Committee; and Jan Schaefer, Norwalk Harbor Management Commission member and past chairman of the Mayor’s Water Quality Committee. Computer mapping by Keith Placko; photos by G. Steadman.

Funding for this Study was provided by the Norwalk Harbor Management Commission through the Norwalk Harbor Management Fund.

Thomas F. Hart Jr. 30 Claremont Drive Voorheesville, NY 12186 (518) 229-5627 [email protected]

Geoffrey Steadman 345 Main St. Westport, CT 06880 (203) 226-9383 [email protected]