1 Executive Summary

This document presents an analysis conducted by the Mystic River Watershed Association (MyRWA) to evaluate indicator bacteria levels in the Mystic River basin. The goals of this analysis are to:

  1. better understand the spatial and temporal variability in compliance with state water quality standards
  2. evaluate a quantitative methodology for assigning letter grades based on the previous EPA grading system
  3. explore alternative methods for computing the compliance and for evaluating individual water bodies

Compliance rates for each sampling location and waterbody are based on the state water quality standards for boating and swimming. The E. coli (ECOLI) data and standards will be used to evaluate freshwater locations, and Enterococcus (ENT) will be used for saltwater locations. The following table lists the numeric criteria for each standard and parameter.

Location Type Parameter Boating (#/100mL) Swimming (#/100mL)
Saline ENT 350 104
Fresh ECOLI 1260 235

MyRWA recommends the following grades for each waterbody in 2014. These grades are based on data collected over a 3-year period (2012-2014) by both MyRWA and the Massachusetts Water Resources Authority (MWRA). Multiple years of data are used to reduce uncertainty and increase stability in the year-to-year grade. The grade is directly related to the mean of the individual swimming and boating compliance rates. This mean compliance rate is shown as red points in the figure below.

For each waterbody, the compliance rate is computed as the mean of all locations within the waterbody. For each standard (swimming and boating), the compliance rate is based on a weighted average of dry and wet weather compliance using weights of 0.75 and 0.25, respectively. Individual samples are classified as wet or dry weather using a threshold precepitation amount of 0.25" over the previous 48 hours from when the sample was collected. Details of this methodology are described in the sections below.

The following table lists the grade and numeric values for each waterbody, and includes the individual compliance rates for the swimming and boating standards under dry and wet weather.

Water Type Waterbody Grade Average Avg Swim Avg Boat Swim/Dry Swim/Wet Boat/Dry Boat/Wet
Fresh Upper Mystic Lake A+ 96.2% 92.4% 100.0% 95.5% 83.3% 100.0% 100.0%
Fresh Mystic River (Fresh) B+ 84.8% 74.9% 94.7% 85.3% 43.7% 99.4% 80.4%
Fresh Aberjona River C+ 65.3% 43.5% 87.2% 53.5% 13.5% 96.9% 58.1%
Fresh Malden River C- 58.8% 42.1% 75.6% 51.5% 13.9% 88.3% 37.2%
Fresh Meetinghouse Brook D 46.9% 26.2% 67.6% 27.3% 23.1% 77.3% 38.5%
Fresh Alewife Brook D 46.4% 16.9% 75.8% 21.7% 2.5% 84.7% 49.3%
Fresh Mill Brook D- 43.1% 17.0% 69.1% 22.7% 0.0% 72.7% 58.3%
Fresh Little River D- 40.4% 11.8% 69.0% 14.9% 2.5% 78.7% 40.0%
Fresh Winns Brook F 33.0% 9.2% 56.8% 9.5% 8.3% 61.9% 41.7%
Saline Mystic River (Salt) A 90.2% 85.9% 94.5% 93.9% 62.1% 99.0% 80.8%
Saline Chelsea River A- 87.4% 81.9% 92.9% 92.4% 50.4% 99.0% 74.6%
Saline Belle Isle Inlet C 63.9% 48.3% 79.5% 51.9% 37.5% 85.2% 62.5%
Saline Island End River F 33.2% 21.1% 45.4% 24.0% 12.5% 48.0% 37.5%
Saline Mill Creek F 32.3% 16.7% 47.9% 22.2% 0.0% 55.6% 25.0%

2 Dataset Summary

The water quality data used in this analysis was extracted from the MyRWA Water Quality Database, which has been developed over the past few years. The database was designed to store water quality data collected for multiple sample programs managed by MyRWA as well as other agencies and organizations. The database contains important metadata such as field and lab methods as well as quality assurance information to ensure all data are properly characterized and used appropriately.

The analysis is also facilitated by the myrwaR R package, which is currently under development by MyRWA. This package contains R functions for loading data from the MyRWA Database, merging percipitation and computing wet/dry conditions. Using this package improves reproducibility and transparency of MyRWA’s data analyses and is becoming an integral part of the organization’s capabilities for exploring, reporting and understanding datasets collected in the watershed.

2.1 Precipitation Data

An hourly precipitation dataset was obtained for Logan Airport from the Northeast Regional Climate Center and the NOAA Climate Data Online warehouse. The precipitation dataset is continuous (i.e. no gaps) and spans from 1982 - 2014.

The precipitation dataset can be downloaded here: logan_hourly.csv

Precipitation data is used to characterized each water quality sample as either dry or wet weather. This classification is based on a threshold of 48-hour antecedent precipitation > 0.25".

The following figure shows the fraction of hours for each weather category by year.

Overall, the annual mean fraction of Wet weather hours from 1982-2014 was 25.1%.

This figure shows the weather fractions for only the summer (May-Oct) of each year. Although there is more year-to-year variability than the plot above, the overall mean fraction is about the same indicating no major seasonal differences in the occurance of wet and dry weather. However, note that “Wet” conditions during winter months may contribute to snowpack, and thus not immediately generate runoff that could affect the instream bacteria concentrations. An improved classification might consider snowmelt during winter months for characterizing wet events.

2.2 Bacteria Data

Bacteria data were extracted from the MyRWA Water Quality Database for three sampling programs from two organizations (MyRWA and MWRA):

Agency ProjectID
MyRWA BASE
MWRA CSORWM
MWRA BHWQM

The raw dataset can be downloaded in csv format here: bacteria.csv

The corresponding locations table can be downloaded in csv format here: locations.csv

Two types of bacteria indicators were measured:

  • E. coli (ECOLI)
  • Enterococcus (ENT)

The E. coli measurements are used to assess compliance in freshwater locations (above Amelia Earhart Dam), and the Enterococcus measurements are used for saltwater locations (below the dam).

The dataset has been filtered to include only samples that passed all QAQC tests. As a result, 9 samples (for MyRWA Baseline data only) were excluded due to failing the lab RPD (Relative Percent Difference) test.

2.2.1 Station Locations

The following map shows the location of each sampling station.

2.2.2 Sampling Counts

This figure shows the number of samples for each location (grouped by program) and year for 2002-2014 (note that some MWRA stations go back to 1989, but the MyRWA baseline program began in 2002). The freshwater MyRWA stations all span the period 2002-2014. Additional baseline stations were added in 2008-2009 in the saltwater portion of the watershed. The MWRA locations include more samples per year (approximately 1 sample every 1-2 weeks) than MyRWA locations that are sampled monthly. A number of samples from May 2010 - Dec 2011 are missing for the saltwater MyRWA stations due to methodological errors that were identified with the lab analysis.

This figure shows the number of samples at each location by month. The MyRWA Baseline program (BASE) contains samples evenly distributed across the year. The MWRA CSORWM program focuses on May-Oct, and BHWQM is more evenly distributed but with fewer samples in Jan-Mar.

2.2.3 Distributions

This figure shows the distribution of bacteria concentrations at each site under Dry and Wet weather for 2010-2014. At nearly all sites, there is a significant difference between Dry and Wet weather.

This figure shows the distributions of concentrations by waterbody for 2010-2014. The data are grouped by simpling combining all samples from individual locations. Therefore, locations with more samples have greater weight in the distribution.

This figure compares the bacteria distributions under dry and wet weather conditions between Summer (May-Oct) and Winter (Nov-Apr) for the MyRWA stations from 2002-2014. The distributions under dry weather are fairly similar at most locations between the two seasons. However, under wet weather, winter samples tend to be lower than summer samples at some of the locations (especially Aberjona River, Mill Creek). These results are likely due to precipitation falling as snow and thus not generating runoff that would contribute to elevated bacteria levels. During winter, the wet/dry classification could instead by determined by changes in streamflow. However, new thresholds for defining wet and dry would be required. Therefore, for this analysis the 48-hour antecedent precipitation threshold will be used in all seasons.

3 Compliance Rates

The compliance of each location and waterbody is computed as a weighted mean of the compliances under dry and wet weather. This weighting scheme removes the year-to-year variability due to weather as well as the proportion of samples collected under each weather condition in a given year. As shown above, the long-term average fraction of the year under wet and dry conditions are 25% and 75%, respectively. Therefore, these fractions will be used to aggregate the compliances under dry/wet weather into an average compliance for a given year.

The mean compliance for standard \(s\) at location \(l\) is computed by the following equation:

\[Y_{l,s} = 0.75 Y_{l,s,dry} + 0.25 Y_{l,s,wet}\]

The mean compliance for standard \(s\) in waterbody \(w\) is computed as the mean of \(n_w\) locations within the waterbody:

\[Y_{w,s} = \frac{1}{n_w}\sum_{l \in w}{Y_{l,s}}\]

Finally, the overall compliance rate for waterbody \(w\) that is used to assign a grade is the mean of the boating and swimming compliance rates:

\[Y_w = \frac{Y_{w,swim}+Y_{w,boat}}{2}\]

3.1 Compliance By Location

This figure shows the compliance rates for each location undery dry and wet weather in 2014.

For each location, the compliance rates for dry and wet weather are then averaged using weights of 75% and 25%, respectively. These weights are based on the long-term average fraction of the year corresponding to each weather condition.

3.2 Compliance By Water Body

3.2.1 Locations Equally Weighted

The primary approach to the waterbody aggregation is to assign equal weight to each location. This calculation is performed by first computing the compliance rate for each location, and then taking the arithmetic mean of compliance rates for all locations within each water body. The following figure shows the resulting compliance rates for each waterbody in 2014.

3.2.2 Locations Weighted by Sample Number

An alternative approach is to compute a weighted mean compliance rate for each waterbody by weighting each location by its number of samples. Locations with more samples thus have a great influence on the waterbody compliance rates.

3.2.3 Comparison

This figure compares the overall mean compliance rate (average of swimming and boating compliance) for each waterbody between the two weighting schemes. The results show relatively small differences between weighting all locations within each waterbody equally or by the number of samples for each location.

3.2.4 Remarks

The two methods for aggregating the compliance rates by water body yield similar results. The waterbodies that contain both MyRWA and MWRA locations (e.g. Alewife Brook, Malden River, and Mystic River (Fresh)) show only minor differences between the two methods.

3.3 Year-to-Year Stability

The previous EPA grades were based on only one year of data. However, this limits the amount of data used to compute the compliance rate (and thus the grade) especially for MyRWA baseline stations where 12 samples are collected at most each year. In some years, all samples happen to occur during dry weather and thus there is no estimate of the compliance under wet weather, which invalidates the 25/75% weighting by weather condition.

With fewer samples, the compliance for each location and waterbody varies from year to year due to high uncertainty in the compliance under dry and wet conditions. For the purpose of assigning an annual set of grades, a more stable metric would be preferred that is not subject to large changes from year to year.

One method for smoothing the annual compliance rates of each waterbody is to use a rolling window containing multiple years of data. For example, a 2-year window would use data from 2013 and 2014 to compute the compliance rate and assign the grade for 2014.

The choice of rolling window length involves some tradeoffs:

  • Shorter rolling windows better represent short-term variability in annual compliance and response to infrastructure improvements. However, shorter windows also contain higher uncertainty, greater variability, and less year-to-year stability due to smaller sample sizes
  • Longer rolling windows are more stable from one year to the next due to the large sample size and because the data used for each year includes overlapping samples across multiple years. The grade for each year also reflects the average conditions for multiple years in addition to the assessment year.

3.3.1 Freshwater MyRWA Locations

The following figure shows the change in annual compliance rates between windows of 1-5 years for the MyRWA stations in the freshwater portion of the basin. Note that the 1 year window includes only data collected in each given year, and thus there is no overlap in the datasets used to compute the compliance rates. Compliances are not shown in 2009 for the 1 Year window because no wet samples were collected, and thus the mean compliance rate could not be computed.

3.3.2 Freshwater MWRA Locations

This figure shows same results for MWRA freshwater locations on the Mystic River mainstem (Mystic River (Fresh)). Note that the MWRA locations tend to have many more samples per year than the MyRWA stations, and thus have a larger sample size for each year. Nevertheless, using a multi-year rolling window does have a significant smoothing effect on the change in annual compliance rates.

3.3.3 Remarks

Using a rolling window greater than 1 year reduces the year-to-year variability in the annual compliance rate and effectively smooths the general trends in compliance of each water body. By doing this, the sample size for each year and location is increased thus yielding a more stable estimate of the annual compliance rates.

An alternative method to increase the sample size is to use bootstrap methods that resample the data for each year. However, for locations with only monthly data (MyRWA Baseline), there is still a good chance that no wet events are sampled in a given year, which would require a different method to address.

A rolling window of 3 years will be used for all subsequent analyses and to assign the recommended grades for 2014. The figures above show that 3 years is sufficient to achieve a stable year-to-year change in grades and compliance at most locations. It also captures short-term variability better than the longer windows as shown for the MyRWA station MAR036 on the Malden River.

4 Grade System

4.1 Previous EPA Grade Method

In previous years, USEPA used the following method to assign the annual grade for the Mystic River based on MyRWA Baseline Sampling Data (excerpt from 2012 Grade Announcement).

…when assessing water quality to assign a grade to the Mystic River Watershed, EPA uses an average between the overall percentages that water quality met the state criteria for swimming and boating (for 2012, it is 61%) as well as qualitative criteria that are similar to those developed for the Charles River Initiative, as follows:

A - met swimming and boating standards nearly all of the time

B - met swimming and boating standards most of the time

C - met swimming standards some of the time, and boating standards most of the time

D - met swimming and boating standards some of the time

F - fail swimming and boating standards most of the time

The grade is thus a combination of a quantitative evaluation using the mean of swimming and boating compliance, and a qualitative evaluation using the descriptions above. Note, however, the meaning of “nearly all”, “most of”, and “some of the time” are not defined. The compliance rates are also computed by pooling all samples collected in the watershed. Thus the grade is heavily weighted towards reflecting conditions in the tributaries since there is only one freshwater station on the Mystic River mainstem.

4.2 Revised Grading Method

The revised grading method is similar to the EPA method, except that it uses a strictly quantitative approach as well as distinguishes between the individual waterbodies.

Similar to the EPA method, the grade is based on the mean of the swimming and boating compliance rates, each of which is computed as the weighted average for wet and dry weather using weights of 25% and 75%. This value is then assigned to individual grades in 5% increments

Grade Compliance Range
A+ 95% - 100%
A 90% - 95%
A- 85% - 90%
B+ 80% - 85%
B 75% - 80%
B- 70% - 75%
C+ 65% - 70%
C 60% - 65%
C- 55% - 60%
D+ 50% - 55%
D 45% - 50%
D- 40% - 45%
F 0% - 40%

5 Results

To review, the methodology used to compute the final grades for each waterbody includes:

  1. Annual compliance for swimming and boating is computed as the weighted mean of the compliances under dry and wet weather using weights of 75% and 25%, respectively.
  2. Locations are equally weighted when computing the mean annual compliance rates for each waterbody.
  3. A 3-year rolling window is used to increase the sample size for computing the annual compliance of each year.
  4. The grading system uses a strictly quantitative scale for assigning grades as defined above.

5.1 2014 Results

5.1.1 By Location

This figure shows the annual compliance rate of each location for 2014 (note that this includes data from 2012-2014 due to the 3-year rolling window). The red points are the mean of the swimming and boating compliance, and thus the value used to assign each grade.

5.1.2 By Waterbody

This figure shows the annual compliance rate of each waterbody for 2014 (data from 2012-2014) using all MyRWA and MWRA data and by assigning equal weights to the locations with each waterbody.

The following table lists the grade and individual compliance rates for each waterbody corresponding to the previous figure.

Water Type Waterbody Grade Average Avg Swim Avg Boat Swim/Dry Swim/Wet Boat/Dry Boat/Wet
Fresh Upper Mystic Lake A+ 96.2% 92.4% 100.0% 95.5% 83.3% 100.0% 100.0%
Fresh Mystic River (Fresh) B+ 84.8% 74.9% 94.7% 85.3% 43.7% 99.4% 80.4%
Fresh Aberjona River C+ 65.3% 43.5% 87.2% 53.5% 13.5% 96.9% 58.1%
Fresh Malden River C- 58.8% 42.1% 75.6% 51.5% 13.9% 88.3% 37.2%
Fresh Meetinghouse Brook D 46.9% 26.2% 67.6% 27.3% 23.1% 77.3% 38.5%
Fresh Alewife Brook D 46.4% 16.9% 75.8% 21.7% 2.5% 84.7% 49.3%
Fresh Mill Brook D- 43.1% 17.0% 69.1% 22.7% 0.0% 72.7% 58.3%
Fresh Little River D- 40.4% 11.8% 69.0% 14.9% 2.5% 78.7% 40.0%
Fresh Winns Brook F 33.0% 9.2% 56.8% 9.5% 8.3% 61.9% 41.7%
Saline Mystic River (Salt) A 90.2% 85.9% 94.5% 93.9% 62.1% 99.0% 80.8%
Saline Chelsea River A- 87.4% 81.9% 92.9% 92.4% 50.4% 99.0% 74.6%
Saline Belle Isle Inlet C 63.9% 48.3% 79.5% 51.9% 37.5% 85.2% 62.5%
Saline Island End River F 33.2% 21.1% 45.4% 24.0% 12.5% 48.0% 37.5%
Saline Mill Creek F 32.3% 16.7% 47.9% 22.2% 0.0% 55.6% 25.0%

5.1.2.1 MyRWA Only

This figure shows the grades for each waterbody based only on the MyRWA data to evaluate the effect of including MWRA data in the compliance calculations.

This figure compares the overall mean compliance rate for each waterbody using only MyRWA data vs using both MyRWA and MWRA data. The waterbodies that contain MWRA stations (Mystic River (Fresh), Alewife Brook, Malden River, Mystic River (Salt)) do show some significant differences of 10% or more.

5.2 Historical Grades

This figure shows the compliance rates and grades for each freshwater waterbody since 2006 using a 3-year rolling window.

This figure shows the historical compliance rates and grades for saltwater waterbodies. Note that some waterbodies show fewer years since sampling did not begin after 2006.

5.3 Comparison to Historical Charles River Grades

In addition to the Mystic River, the USEPA also assigns annual grades for the Charles River watershed. However, there are significant differences in how these grades are assigned that invalidates any direct comparison of the grades. The primary difference is that the Charles River grade is based on sampling from the mainstem only, whereas the Mystic River grade has historically been based on all locations which are primarily within tributaries to the Mystic. The grades are also based on different quantitative and qualitative criteria.

For comparison, the following figure shows the historical grades and compliance rates from 2006-2014 between the Charles River and the freshwater portion of the Mystic River mainstem. The Charles River grades and compliance rates are those reported by EPA in its annual grade announcements. For the Mystic River (Fresh) mainstem, the grades are based on both MyRWA and MWRA data using only samples collected in 2014 and based on the revised grading method described above. Although the grades presented in previous sections were based on a 3-year rolling window of data, a 1-year window is used for this comparison to be consistent with the Charles River grades.

The figure indicates that the revised grading system developed by MyRWA is very consistent with the historical grades reported by USEPA for the Charles River. It also shows that the rate of swimming compliance in the freshwater portion of the Mystic River mainstem has historically been greater than that in the Charles River mainstem in all years from 2006-2014, and that the rate of boating compliance is similar between the two rivers although less variable in the Mystic River.

This table shows the corresponding compliance rates and grades for each river.

Waterbody Year Grade Average Avg Swim Avg Boat Swim/Dry Swim/Wet Boat/Dry Boat/Wet
Charles River 2006 B+ 76.0% 62.0% 90.0% 80.0% 51.0% 100.00% 84.0%
Charles River 2007 B++ 81.5% 63.0% 100.0% 84.0% 50.0% 100.00% 100.0%
Charles River 2008 B+ 71.5% 48.0% 95.0% 58.0% 42.0% 91.00% 92.0%
Charles River 2009 B+ 77.5% 62.0% 93.0% 69.0% 58.0% 92.00% 94.0%
Charles River 2010 B+ 76.0% 66.0% 86.0% 86.0% 54.0% 94.00% 82.0%
Charles River 2011 B 68.0% 54.0% 82.0% 89.0% 35.0% 96.00% 74.0%
Charles River 2012 B+ 77.0% 67.0% 87.0% 93.0% 53.0% 99.00% 81.0%
Charles River 2013 A- 83.0% 70.0% 96.0% 84.0% 63.0% 97.00% 95.0%
Charles River 2014 B+ 78.0% 65.0% 91.0% 86.0% 53.0% 100.00% 86.0%
Mystic River (Fresh) 2006 B+ 84.4% 74.5% 94.3% 83.5% 47.5% 98.89% 80.6%
Mystic River (Fresh) 2007 B+ 80.4% 69.9% 90.8% 87.4% 17.4% 95.41% 76.9%
Mystic River (Fresh) 2008 B+ 84.4% 73.5% 95.2% 84.7% 40.0% 98.56% 85.2%
Mystic River (Fresh) 2009 B+ 84.0% 70.1% 97.9% 77.4% 49.8% 98.69% 95.8%
Mystic River (Fresh) 2010 B+ 82.5% 70.9% 94.0% 78.1% 49.3% 98.11% 81.7%
Mystic River (Fresh) 2011 B+ 82.0% 70.5% 93.4% 81.6% 37.3% 99.49% 75.2%
Mystic River (Fresh) 2012 B+ 82.6% 70.0% 95.2% 83.4% 29.7% 99.42% 82.6%
Mystic River (Fresh) 2013 A- 89.2% 81.6% 96.8% 91.7% 51.1% 100.00% 87.2%
Mystic River (Fresh) 2014 B+ 82.0% 71.5% 92.6% 79.6% 47.0% 98.79% 74.0%

6 Conclusions

The following conclusions were reached from this analysis:

The source code for this analysis is available on Github: https://github.com/walkerjeffd/myrwa-epa-grade

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