epa region 9 water quality assessment report tutorial 2011 1

EPA Region 9

Water Quality Assessment Report Tutorial

2011

1

Clean Water Act Section 106

Annual Assessment ReportTribes receiving Section 106 grants must submit an annual Water Quality

Assessment Report (WQAR), which gives an overview of the total and monitored water on Tribal land and an assessment of water quality based on monitoring data.

Purpose

• To provide an analysis of water quality on tribal lands

• To organize water quality data and assessment in a standardized format through which tribes and the EPA can track changes in water quality over time, to understand changing environmental and man-made conditions

• To help make decisions about management steps that could be taken to protect or improve on the water quality of tribal lands

2

Clean Water Act Section 106

Annual Assessment Report

The WQAR consists of three sections:

1. A description of your monitoring strategy-included in your QAPP and discussed in the WQAR narrative

2. A water quality assessment report-WQAR template and data analysis

3. Electronic copies of surface water quality data -entered into WQX-STORET format

To download a blank Region 9 WQAR template, at the link below:> Under “2. Water Quality Assessment Report”> Under “Region 9 Water Quality Assessment Report Pilot”> Click: Assessment Template, 2010 (.xls file, 6 pp. 544K)

http://www.epa.gov/region09/water/tribal/cwa-reporting.html#two

(explained in this tutorial)

3

http://www.epa.gov/region09/water/tribal/cwa-reporting.html#two

Please make sure you view this tutorial on slide show mode, to ensure the slides and animations advance properly.

Throughout the tutorial, you can click on links for additional information. When you mouse over a link, your mouse should turn into a small hand cursor.

Click on these orange boxes for additional instructions for filling out the WQAR template

This tutorial will guide you through an example of filling out the WQAR template. Click on these green boxes for answers and explanations related to to this example. These links contain important analysis tips, so it is highly recommended you click on them.

In some cases, a text box will pop up on your slide when you click on these links. Once you are done reading the information, click on the text box (your mouse should look like a small hand pointer) to make it disappear.

Try clicking on the links/boxes above. Make sure your mouse looks like when you place your mouse over the link, to make sure you are clicking on the link and not the slide itself.

If a text box does not pop up, click anywhere on the slide (your mouse will look like an arrow) or press the right arrow to move to the next slide (in some cases, you may need to click twice).

Additional examples of data analysis can be found at the end of the tutorial. A table of contents will link you to specific examples that are mentioned throughout this tutorial

Tips for using this Tutorial

Additional tips usually appear in textboxes outlined in black. Click on the textbox (including this one) to make it disappear

Additional explanations relating to the example in the tutorial will often appear in textboxes outlined in green, such as this one. In other cases, the green question mark link will be placed over a cell on the WQAR template. Clicking on it will reveal what should be entered into the cell. Try to guess what you think the correct answer should be before clicking on the link.

Again, you can click on the textbox to make it disappear.

4

You are the newly appointed Water Quality Monitoring Specialist for the Spring River Tribe. It is your task to monitor the water bodies affecting the Tribe's reservation for the purpose of protecting, maintaining or improving the health of this vital resource, which the Tribe uses for a variety of reasons.

As part of your responsibilities, you must fill out a Water Quality Assessment Report Template to submit to your Region 9 EPA Project Officer. The template will help you document impaired parameters, and possible sources of pollutants, and will prompt you to answer basic questions about the quality of your water.

This tutorial will guide you through the process of filling out a WQAR Template . It will also help you determine what type of environmental analysis you’ll need to make based upon any monitoring data you have collected in order to complete the template.

Water Quality Assessment ExampleSpring River Tribe

5

A map of the Spring River Reservation is illustrated below.

6

Reservation size: 70 square milesReservation boundaries outlined in black

Spring River Salmon Run Tributary

Main Reservoir

Irrigation Ditch

Groundwater Wells

• Four major water bodies • 2 groundwater wells (drinking water)• Spring River flows from N S• All water bodies flow into Spring River

7

Reservation size: 70 square milesReservation boundaries outlined in black


Main Reservoir

Irrigation Ditch

Groundwater Wells

SRV-01

SRV-02

SRV-03

SRTR-01

SRTR-02

IRG-01 GWW-01MR-01

MR-02

• Four major water bodies • 2 groundwater wells (drinking water)• Spring River flows from N S• All water bodies flow into Spring River

Designated Uses• Agricultural Irrigation; Livestock watering• Aquatic Life and Wildlife• Cultural; Secondary Contact• Primary contact (drinking water wells)

Issues of Tribal Concern• Nonpoint source pollution from residential areas• Agricultural/livestock pollution• Logging industry• Maintaining salmon spawning habitat

Nine monitoring stations (one off-reservation)Monitoring frequency (year-round or seasonal) and parameters monitored (defined in QAPP) will vary

8

R9 Water Quality Assessment Report

OutlineThe WQAR is made of 6 sections

Tab 1: Instructions

4 sections you must complete:

Tab 2: WQAR Template (data analysis and assessment)

Tab 3: Tribal Atlas (overview of water existing in and being monitored on

Tribal lands)

Tab 4: Restoration Projects (CWA 319)

Tab 5: Narrative (written report, attached)

Tab 6: Definitions

9

The WQAR is made of 6 sections

Tab 1: Instructions




Tribal lands)



Tab 6: Definitions


Outline

10

Monitoring Strategy (using QAPP)

Water Quality Assessment/ Data Analysis

(using WQX-STORET data)

Additional Analysis/ Information

11

There are nine monitoring locations on the Spring River reservation. Each monitoring location/station (not water body) constitutes one entry, or one row in the template. [See the red box below] for a total of nine rows. For each entry, you will fill out 17 columns of information about the location and its water quality, based on your assessment of monitoring data.


Main Reservoir

Irrigation Ditch

Groundwater Wells

SRV-01

SRV-02

SRV-03

SRTR-01

SRTR-02

IRG-01 GWW-01MR-01

MR-02

You will begin by filling in one row for the IRG-01 monitoring station

12

Irrigation Ditch

Section 1: Basic Monitoring Information

13

Column 1: enter the name of your waterbody

Irrigation Ditch

To enter information into an empty cell on your WQAR template, simply click on the cell and begin typing.

When you click on any text box, a light yellow box will pop-up and give you additional instructions about what to put in each box.

Click on the green box to see what you should enter in column 1

Click for additional tips(make sure your cursor is in the shape of a hand when you mouseover)

14


Column 2: choose the type of your waterbody (river, reservoir,

wetland, groundwater well, etc.)



Irrigation Ditch

Cells labeled “Choose…” can only be filled in by choosing from a list of options in a drop-down list.

When you click on the cell, a small grey arrow will appear at the top right corner of the cell. Clicking on this arrow will give you a list of options to choose from.

(Click this textbox to remove and allow other links to appear)

Click on the green box to see what you should enter in column 2

15




Column 3: choose Yes or No: is your monitoring station located on

your reservation (including trust and fee lands)



Irrigation Ditch




If you refer back to the original reservation map, one monitoring station (SRV-01) is located outside the reservation boundaries, which are outlined in black.

Monitoring locations outside reservation boundaries are most commonly upstream of reservation waters. These help check the water quality of waters before they flow onto the reservation.


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Column 3: choose Yes or No: is your monitoring station located on

your reservation (including trust and fee lands)

Column 4: enter the Monitoring Station ID. This should match the

code or name on your WQX (also under the column “Monitoring

Station ID”)

Irrigation Ditch






If you refer back to the original reservation map, one monitoring station (SRV-01) is located outside the reservation boundaries, which are outlined in black.

Monitoring locations outside reservation boundaries are most commonly upstream of reservation waters. These help check the water quality of waters before they flow onto the reservation.


17

Irrigation Ditch

Section 1: Basic Monitoring Information continued

18

Click on the green box to see what you should enter in column 5 (and an explanation of this answer)

Use this scale and map to estimate the distance of the irrigation ditch that is monitored/assessed by IRG-01 (the exact location of IRG-01 is marked in red)

Columns 5 and 6: How much water is represented by the water quality data collected at the monitoring station?*

Various factors may change a water body’s water quality, so that data collected at the monitoring station is no longer representative.

Factors to keep in mind:• Point or nonpoint source inputs• Changes in watershed characteristics (ex: land use)• Changes in riparian vegetation, stream banks, slope or

channel morphology, flow rate, stream width• Stream confluence or diversions• Hydrologic modifications (ex: channelization or dams)

*some regions of water on your reservation may be left unmonitored

Irrigation Ditch

Some of the column titles are underlined in blue. Click on these links for more information about how to fill out the column, or for definitions of the choices given in the drop-down menu. Clicking on the links will bring you to Tab 6. You can move between the colored tabs yourself at the bottom of the excel page as well.

The water quality at IRG-01 is primarily affected by runoff from agriculture and livestock operations.

Your water quality assessment using data collected from IRG-01 will not accurately assess water quality outside the livestock operation area (shaded in brown), because different (fewer) factors are affecting water quality there.

19


20

**Information for these three columns can be found in your EPA-approved QAPP**

Column 7: How frequently was data collected at

this monitoring station? • find in the sampling methods in your QAPP

• use the parameter most frequently monitored

Column 8: Which water quality parameters were

monitored? • find in the sampling methods in your QAPP• EPA’s 9 fundamental parameters listed• You can type in up to 5 additional parameters

Column 9: What is the water body used for?• find in the problem statement in your QAPP• if these are not officially or clearly written in your

QAPP, use your own knowledge of the water body

and tribal activities• You can type in up to 5 additional goals or uses

For each parameter, choose “Yes” or “No” in the

adjacent cell (if “No,” you also just leave the cell at

“Choose…”)

Note that the parameters for which you choose “Yes”

will pop up in columns 12

(the same is true for columns 9 and 13)


21

WQX-STORET Data AnalysisYou are now ready to analyze your monitoring data and make water quality assessments

(columns 10-13)

22

WQX-STORET Data AnalysisYou are now ready to analyze your monitoring data and make water quality assessments

(columns 10-13)

You have gathered together your:WQX-STORET monitoring dataEPA-approved QAPP (monitoring parameters, tribal

goals/designated uses and Water Quality criteria for each monitoring location)

WQAR template

At the end of this tutorial, you will find more examples of choices on the WQAR template, more complex examples you might experience, and additional statistical analyses.

23

Analyzing Data at IRG-01Example 1A: Total Phosphorous Status

You have collected data on total phosphates at IRG-01 twice a month between April and October, when the irrigation ditch is flowing, and organized this data in a WQX-STORET worksheet.

First, you will evaluate whether or not TP is impaired at this monitoring station.

You will compare your monitoring data to the water quality criteria for TP in your QAPP.

Irrigation Ditch

24

Date Total phosphorous (mg/L)

4/1/2011 0.024

4/15/2011 0.027

5/1/2011 0.037

5/15/2011 0.040

6/1/2011 0.063

6/15/2011 0.057

7/1/2011 0.081

7/15/2011 0.079

8/1/2011 0.076

8/15/2011 0.079

9/1/2011 0.082

9/15/2011 0.078

10/1/2011 0.083

10/15/2011 0.091

Step 3. Conduct some basic statistical analyses on your whole data set. This will help you get a better feel for your data and what results to expect

Summary Statistics:Mean: 0.064 mg/LSt. dev: 0.023 mg/LMinimum: 0.024 mg/LMaximum: 0.091 mg/L

What preliminary conclusions can you make from this data?

Water Quality Criteria:“Total phosphorous: means should not exceed 0.035 mg/L in any 30 day period (at least 2 samples)”

Step 2. Find the water quality criteria for this parameter in your QAPP and/or WQS

Step 1. Organize your data from your WQX-STORET worksheet (include date and monitoring data)

• Mean TP level is much higher than the WQ criteria (0.064 mg/L) • Variation in the data is large (0.023 mg/L, compared to the

maximum threshhold of 0.035 mg/L) M• Minimum TP is below criteria, but the maximum is much, much

higher.

Preliminary Conclusion: TP frequently above the max WQ criteria parameter is impaired

Graphs will help you visualize the spread of data and make a more confident conclusion.

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No. Your monitoring data was collected every two weeks, but you are comparing this against a WQ criteria for monthly TP averages (“means…in any 30 day period”)

Assess the impairment of this parameter by comparing monitoring data to the WQ criteria in your QAPP.

Can you compare your data in its current format with the WQ criteria?

How should you modify your monitoring data so you can compare it to the criteria?

Date Total phosphorous (mg/L)

4/1/2011 0.024

4/15/2011 0.027

5/1/2011 0.037

5/15/2011 0.040

6/1/2011 0.063

6/15/2011 0.057

7/1/2011 0.081

7/15/2011 0.079

8/1/2011 0.076

8/15/2011 0.079

9/1/2011 0.082

9/15/2011 0.078

10/1/2011 0.083

10/15/2011 0.091

Date TP monthly means (mg/L)

4/2011 0.026

5/2011 0.039

6/2011 0.060

7/2011 0.080

8/2011 0.078

9/2011 0.080

10/2011 0.087

Monitoring data Monthly Means Step 4: Prepare/modify your data, according to WQ criteria

Water Quality Criteria (QAPP):“Total phosphorous: means should not exceed 0.035 mg/L in any 30 day period (at least 2 samples)”

For each month during your monitoring period, take the average of all the TP data collected.

Then you can compare these modified data points to the WQ criteria (0.035 mg/L) in a graph.

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4/2011 0.026

5/2011 0.039

6/2011 0.060

7/2011 0.080

8/2011 0.078

9/2011 0.080

10/2011 0.087

Step 5. Graph your data. Include on the same graph: [1] prepared monitoring data (scatterplot), and [2] water quality criteria (line graph)

Water Quality criteria for TP (mg/L)

0.035

0.035

0.035

0.035

0.035

0.035

0.035

Monthly Means

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2/26/2011 4/17/2011 6/6/2011 7/26/2011 9/14/2011 11/3/20110.000.010.020.030.040.050.060.070.080.090.10

Total Phosphorous, IRG-01

TP monthly means

Date

Tota

l Pho

spha

tes (

mg/

L)

2/26/2011 4/17/2011 6/6/2011 7/26/2011 9/14/2011 11/3/20110.000.010.020.030.040.050.060.070.080.090.10


TP monthly means

WQ criteria

Date

Tota

l Pho

spha

tes (

mg/

L)



4/2011 0.026 0.035

5/2011 0.039 0.035

6/2011 0.060 0.035

7/2011 0.080 0.035

8/2011 0.078 0.035

9/2011 0.080 0.035

10/2011 0.087 0.035

Step 6. Analyze your data. Questions to consider: -Do any of the data points exceed the minimum or maximum criteria allowed? (Yes suggests impairment)

Monthly Means

28

2/26/2011 4/17/2011 6/6/2011 7/26/2011 9/14/2011 11/3/20110.000.010.020.030.040.050.060.070.080.090.10


TP monthly means

WQ criteria

Date

Tota

l Pho

spha

tes (

mg/

L)



4/2011 0.026 0.035

5/2011 0.039 0.035

6/2011 0.060 0.035

7/2011 0.080 0.035

8/2011 0.078 0.035

9/2011 0.080 0.035

10/2011 0.087 0.035


Yes. All of the data points above the red line have exceeded the maximum TP levels set by the WQ criteria-Are there any trends in your data points? What is causing these trends? [decreased/increased inputs,

seasonal pollutant input changes , other conditions?]

Monthly Means

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2/26/2011 4/17/2011 6/6/2011 7/26/2011 9/14/2011 11/3/20110.000.010.020.030.040.050.060.070.080.090.10


TP monthly means

WQ criteria

Date

Tota

l Pho

spha

tes (

mg/

L)



4/2011 0.026 0.035

5/2011 0.039 0.035

6/2011 0.060 0.035

7/2011 0.080 0.035

8/2011 0.078 0.035

9/2011 0.080 0.035

10/2011 0.087 0.035



seasonal pollutant input changes , other conditions?] TP levels appear to be increasing over time. However, this is likely because the amount of phosphorous in the soil builds up over the growing season, so higher levels are present in the runoff later in the year. This is a seasonal effect that occurs every year, and does not necessarily mean that water quality is degrading.

-Do any of the data points look like outliers that do not follow the trend of the graph (and should be ignored)?

Monthly Means

30

2/26/2011 4/17/2011 6/6/2011 7/26/2011 9/14/2011 11/3/20110.000.010.020.030.040.050.060.070.080.090.10


TP monthly means

WQ criteria

Date

Tota

l Pho

spha

tes (

mg/

L)



4/2011 0.026 0.035

5/2011 0.039 0.035

6/2011 0.060 0.035

7/2011 0.080 0.035

8/2011 0.078 0.035

9/2011 0.080 0.035

10/2011 0.087 0.035



seasonal pollutant input changes , other conditions?] TP levels appear to be increasing over time. However, this is likely because the amount of phosphorous in the soil builds up over the growing season, so higher levels are present in the runoff later in the year. This is a seasonal effect that occurs every year, and does not necessarily mean that water quality is degrading.

-Do any of the data points look like outliers that do not follow the trend of the graph (and should be ignored)? Not in this example. In some (other) cases, however, if most data points are below the criteria line but one exceeds it, this may simply be an outlier due to some unique event, and may not mean that the water quality is actually impaired

Conclusion:Water quality is impaired

Monthly Means

31

2/26/2011 4/17/2011 6/6/2011 7/26/2011 9/14/2011 11/3/20110.000.010.020.030.040.050.060.070.080.090.10


TP monthly means

WQ criteria

Date

Tota

l Pho

spha

tes (

mg/

L)

There are three common types of analyses of water quality:1. Status: impairment of a parameter or water body at any one time

2. Trends: change in water quality (for a parameter or waterbody) over time

3. Site comparison: difference in water quality (for a parameter or water body) between two monitoring stations, often upstream and downstream of a possible pollutant input or restoration project.*

You just finished an analysis of water quality status.

Next, you will do an analysis of trends in water quality, using the same data set.

*Example 3 at the end of this tutorial goes through an example of site comparison analysis

Data Analysis

32

2/26/2011 4/17/2011 6/6/2011 7/26/2011 9/14/2011 11/3/20110.000

0.010

0.020

0.030

0.040

0.050

0.060

0.070

0.080

0.090

0.100

R² = 0.858848006591426


TP meansLinear (TP means)

Tota

l Pho

spha

tes (

mg/

L)

Step 1. Add a linear trendline to your data.

Step 2. Look at the R2 value. A high R2 value indicates that the trendline fits the data points well. If the R2 is above about 0.8, then there is a clear trend (up, down, or flat) in your data.

Step 3. Analyze the cause of the trend. Could the trend be caused by seasonal or other effects (such as natural or one-time occurrences)? Is water quality actually changing over the long-term?

The trend apparent from this year’s data is due at least in part to seasonal effects (increased fertilizer in soil over the year). As a result, we cannot be sure that the water quality is actually degrading over time (long-term).

To do a more complete analysis of change in water quality, we will compare this data to previous years’ data.

Analyzing Data at IRG-01Example 1B: Total Phosphorous Trends

What is an R2 value? An R2 value is an indicator of how well the trendline correlates with the data points (or how well the equation of the trendline predicts real values).

• R2 =1 means the trendline perfectly fits the data (x-values perfectly predict y-values)

• R2 = 0 means the trendline has no correlation with the data (x-values do not predict y-values)

• R2 = 0.8 means 80% of the data can be explained by the trendline (x-values predict 80% of the variation in y-values)

R2 > 0.8 is an okay model; R2 > 0.9 is excellentR2 < 0.5 generally indicates no clear trend

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2/26/2011 4/17/2011 6/6/2011 7/26/2011 9/14/2011 11/3/20110

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

Total Phosphorous status, IRG-01

WQ criteria

TP means

Date

Tota

l Pho

spha

tes (

mg/

L)

12/18/2008 7/6/2009 1/22/2010 8/10/2010 2/26/2011 9/14/2011 4/1/20120

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

Total Phosphorous over time, IRG-01

WQ criteria

TP monthly means

Tota

l Pho

spha

tes (

mg/

L)


Water Quality criteria (mg/L)

4/1/2011 0.026 0.0355/1/2011 0.039 0.0356/1/2011 0.060 0.0357/1/2011 0.080 0.0358/1/2011 0.078 0.0359/1/2011 0.080 0.035

10/1/2011 0.087 0.035


Water Quality criteria (mg/L)

4/2009 0.004 0.0355/2009 0.021 0.0356/2009 0.026 0.0357/2009 0.025 0.0358/2009 0.027 0.0359/2009 0.030 0.035

10/2009 0.022 0.0354/2010 0.011 0.0355/2010 0.028 0.0356/2010 0.042 0.0357/2010 0.062 0.0358/2010 0.060 0.0359/2010 0.055 0.035

10/2010 0.069 0.0354/2011 0.026 0.0355/2011 0.039 0.0356/2011 0.060 0.0357/2011 0.080 0.0358/2011 0.078 0.0359/2011 0.080 0.035

10/2011 0.087 0.035

Repeat Steps 1-5 of example 1A to make a graph, using additional monitoring data from (recently) previous years, if available

To make it easier to see trends over time (and see the effects of seasonality), draw lines to separate different monitoring periods.

Monthly Means, 2011Monthly Means, 2009-2011

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Methods of data analysis

1. Visually analyze trends (all data points)

Monitoring period TP Yearly mean (mg/L)

2009 0.022

2010 0.047

2011 0.064

12/18/2008 7/6/2009 1/22/2010 8/10/2010 2/26/2011 9/14/2011 4/1/20120

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1


WQ criteria

TP monthly means

Tota

l Pho

spha

tes (

mg/

L)

1. Overall, TP levels appear to be increasing over time, even though not all data points from one year are higher than those from the year before.

Click on the green box to see suggested analysis conclusions/ explanations

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2. Compare the TP yearly means (and st.dev) over time


TP Standard deviation (mg/L)

2009 0.022 0.008075

2010 0.047 0.02044

2011 0.064 0.022899

12/18/2008 7/6/2009 1/22/2010 8/10/2010 2/26/2011 9/14/2011 4/1/20120

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1


WQ criteria

TP monthly means

Tota

l Pho

spha

tes (

mg/

L)

12/18/2008 7/6/2009 1/22/2010 8/10/2010 2/26/2011 9/14/2011 4/1/20120

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1


TP yearly means

WQ criteria

TP monthly means

Tota

l Pho

spha

tes (

mg/

L)


2. TP yearly means are increasing each year, and for the past two years they are above the max WQ criteria. The standard deviation is also increasing, indicating wider fluctuations in water quality, or greater increases in TP inputs over time during one year.

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2. Compare the TP yearly means (and st.dev) over time

3. Compare the number of exceedances of the WQ criteria over time


TP Standard deviation (mg/L)

Number of exeedances of WQ criteria

2009 0.022 0.008075 0

2010 0.047 0.02044 5

2011 0.064 0.022899 6

Conclusion:Water quality has further degraded (over time)

12/18/2008 7/6/2009 1/22/2010 8/10/2010 2/26/2011 9/14/2011 4/1/20120

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1


WQ criteria

TP monthly means

Tota

l Pho

spha

tes (

mg/

L)

12/18/2008 7/6/2009 1/22/2010 8/10/2010 2/26/2011 9/14/2011 4/1/20120

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1


TP yearly means

WQ criteria

TP monthly means

Tota

l Pho

spha

tes (

mg/

L)


2. TP yearly means are increasing each year, and for the past two years they are above the max WQ criteria. The standard deviation is also increasing, indicating wider fluctuations in water quality, or greater increases in TP inputs over time during one year.

3. The number of months during which TP levels have exceeded the WQ criteria has consistently increased each year.

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Data Analysis

You have found that total phosphorous levels are impaired (too high) and further degrading (getting worse over time, compared to TP in previous years) at IRG-01

Is this enough for us to determine what the water quality in the irrigation ditch is?

What other information do we need?

The next step is to repeat these two analyses for all the parameters that were monitored at that monitoring station (the irrigation ditch)

Water quality is affected by many different parameters. You will need to know the impairment levels of all monitored parameters before you can judge the overall water quality of any water body.

No!

38

WQ Assessment from Data AnalysisTransferring Data Analysis to WQAR template

After making and analyzing graphs for all the parameters monitored at IRG-01, you combine all your results/conclusions into a table, pictured below.

From this table, you will be able to make big-picture decisions about overall water quality at the monitoring station. Let’s take a look at the WQAR template to see how we can use these results to fill it in.

Parameter monitored

Current impairment status

Change in status (trend)

pH No Maintained

Temperature Yes Maintained

Dissolved Oxygen Yes Degraded

Turbidity Yes Improved

Total Phosphorous Yes Degraded

Total Nitrogen Yes Degraded

E. Coli No Improved

Arsenic No Maintained

Conductivity Yes Maintained

Monitoring location: IRG-01

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Parameter monitored



pH No Maintained






E. Coli No Improved



Data Analysis Summary Table Section 2: Data Analysis/Assessment

Note that the parameters and tribal goals/uses that you chose in columns 8 and 9 have automatically been entered in columns 12 and 13.

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Parameter monitored



pH No Maintained






E. Coli No Improved



Data Analysis Summary Table

Drop-down list choices:• Improved: at least one parameter improved; no

parameters degraded• Maintained: overall, no substantial change in water

quality all parameters maintained• Some improvement, some degradation: at least one

parameter improved AND at least one parameter degraded

• Further degraded: at least one parameter degraded; no parameters improved

• Unknown: not enough data or confidence in the data to make a judgement/conclusion

COLUMN 10: Change in water quality status

For more detailed definitions of the choices on the drop-down menu (listed here in bullet points), click on the blue underlined title of column 10

In this example, some of the parameters have degraded, and some have improved. The change in water quality status is “some improvement, some degradation”

41

Parameter monitored


Change in stats (trend)

pH No Maintained






E. Coli No Improved



COLUMN 11: Current Water Quality Status

By definition, current water quality status is based on your evaluation of the impairment of tribal goals/designated uses of water at the monitoring station. For now, make your best judgment based on your knowledge of the water body and any impaired parameters.

Drop-down list choices:• Pristine: water quality (WQ) criteria surpass those set

for all tribal goals/designated uses of the water body• Satisfactory: WQ criteria for all tribal goals/designated

uses are met• Impaired: WQ has not met the criteria needed to

support at least one of the tribal goals/designated uses for that water body

• Unknown

If you have any impaired parameters, it is likely that at least one of your tribal goals/designated uses are impaired, and that your water quality status is impaired.

There are impaired parameters at the IRG-01 monitoring station.Thus, you can guess that your current water quality status is “impaired”.


42

In the right-hand part of the column, choose “Yes” or “No” from the drop-down list for each of the monitored parameters, based on conclusions from your data analysis.

COLUMN 12: Impaired parameters

You should be able to transfer conclusions from your summary table straight onto your WQAR template.

Only the parameters that you have chosen in column 8 as monitored at this location will appear in column 12 – some rows will be left blank. For each parameter that is filled in, choose its impairment status as “Yes” or “No”

Parameter monitored



pH No Maintained






E. Coli No Improved




43

COLUMN 13: Impaired Tribal Goals/Designated Uses

You will judge whether your tribal goals/designated uses for this water body (or section of a water body) are impaired based on the impairment of parameters that may affect these goals or uses.

Impaired dissolved oxygen may have a negative impact on aquatic life and wildlife, for example (impaired use), but may not have any impact on recreation, such as boating (not impaired use).

Refer to the additional examples at the end of this tutorial for more examples of of how different parameters affect different designated uses, and for an example in which some designated uses are impaired, but some are not.

EXAMPLE: Irrigation Ditch

Tribal Goal/Designated Use[from QAPP and column 9]

Relevant parameters[may impact the goal/use]

Impaired relevant parameters[from column 12]

Agriculture Irrigation pH, DOTemperatureTurbidity, ConductivityTP, TNE. coli

TemperatureDOTurbidity, ConductivityTP, TN

Livestock Watering TemperatureTurbidity, ConductivityTP, TNE. ColiArsenic

TemperatureTurbidity, ConductivityTP, TN

Impaired Goal/Use?

Yes

Yes

If any of the parameters that affect the goal/use are impaired, then that goal/use is impaired as well. Thus, both goals/uses for IRG-01 are impaired

Parameter monitored



pH No Maintained






E. Coli No Improved




44

COLUMN 13: Impaired Tribal Goals/Designated UsesTribal Goal/Designated Use Impaired Goal/Use?

Agriculture Irrigation Yes

Livestock Watering Yes

COLUMN 11: Current WQ Status (revisited)

Both designated uses are impaired, verifying your original assumption that the current water quality status is impaired

Transfer your conclusions into column 13.

45

Data Analysis

SummaryYou have now finished analyzing and interpreting monitoring data for one of your

monitoring stations.

Again, for more information about this section, refer to additional examples at the end of this tutorial or go to Tab 6 for definitions of the terms on the WQAR template

Data Analysis Strategy• Analyze data for one parameter at a time

(table, basic statistics, graph, trendlines)• Combine & organize conclusions for all

parameters at one monitoring station• Make assessments about water quality for

one location based on all the above data• Repeat for each monitoring station

caternary.files.wordpress.com

46

COLUMN 14 and 15: Source & Frequency of ImpairmentIf your water quality is impaired, it is important to identify the possible sources of impairment. These sources can then be targeted for restoration projects, which will help reduce pollutant inputs in improve water quality.

Section 3: Additional Information

47

COLUMN 14: Source of Impairment

In column 14, you can choose up to three sources of impairment from a drop-down list

Source of Impairment

Find sources of impairment in the image above.

48




1. Agriculture (Land Use)

Fertilizer and pesticide runoff from farmland.

49





2. Agriculture (Livestock)

Manure (containing nutrients, antibiotics, pharmaceuticals) runoff and increased turbidity from cows in the irrigation ditch

50






3. Hydromodifications

Pollution, turbidity and variable flow due to the man-made nature of the irrigation ditch

51

COLUMN 15: Frequency of Impairment (Impairment Status)

Source of Impairment Impairment Status




In column 15, for each source, choose the frequency of impairment for each source

Annual: impairments occur consistently throughout the year

Seasonal: impairments occur consistently, but only during a specific season or part of the year

Intermittent: impairments occur inconsistently, often due to storm events or spills/discharges

52

COLUMN 15: Frequency of Impairment


1. Agriculture (Land Use) Seasonal

2. Agriculture (Livestock) Seasonal






The agricultural season only exists between April and October.

Impairments from agriculture occur consistently during this season, but do not exist at any other time; this impairment is seasonal

53

COLUMN 15: Frequency of Impairment


1. Agriculture (Land Use) Seasonal

2. Agriculture (Livestock) Seasonal

3. Hydromodifications Intermittent





The irrigation ditch may frequently flood after storm events or dry up during droughts, which creates a variety of impairments.

Impairments due to the unstable, man-made nature of the irrigation ditch occur inconsistently, so the impairment is intermittent

54

Columns 16: Do you have a watershed restoration project aimed at restoring water quality at this monitoring station(does not have to be funded through CWA Section 319)?

If you enter “Yes” for any monitoring stations, fill out a row in Tab 4 to explain the restoration project.

Column 17: If you would like to further explain any of your answers, or want to add additional notes about this water body or its surrounding conditions, enter it here.

Section 3: Additional Information (Example 1 continued)

55

Example 2 in the additional examples will lead you through data analysis and assessment for SRTR-02

Additional Example

Congratulations! You have now filled out the WQAR template for one monitoring station, IRG-01.

Before moving on, notice that the water quality at IRG-01 is impaired.

Columns 12-15 (green headings) only need to be filled out if “current water quality” is “impaired”.

At another monitoring location (SRTR-02), water quality is satisfactory.

Columns 12-15 for this monitoring location can be left blank.

Leave blank 56

WQAR Template

Wait -- you’re not done yet! Repeat this data analysis and assessment process for each of your other monitoring stations. Fill out one row on the template for each location.

**Before you submit your WQAR Template, please check your work to make sure you have not made any mistakes or left any boxes blank**

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57


Tab 1: Instructions




Tribal lands)



Tab 6: Definitions


Outline

58


Tab 1: Instructions



Tab 3: Tribal Atlas (summary of water existing in and being

monitored on Tribal lands)



Tab 6: Definitions


Outline

59

Tab 3: Atlas of Tribal Waters

Use the scale on this map to estimate the total length or area of the water bodies on the reservation.

When filling out the atlas, pay attention to the units provided.

TIPS• Include all trust and fee lands in “total waters”• Total waters include those monitored and not monitored• The total distance or area monitored (vs. total) should match what

you entered for Column 5 in Tab 2• When entering distance measurements in Column 5 of Tab 2, it is

helpful to use the same units that are provided here, so you can

use the same measurements or values

60

Tab 3: Atlas of Tribal Waters

61


Tab 1: Instructions




Tribal lands)



Tab 6: Definitions


Outline

62


Tab 1: Instructions




Tribal lands)



Tab 6: Definitions


Outline

63

Tab 4: Watershed Restoration Projects (Clean Water Act Section 319)

In this tab, elaborate about the water restoration projects that are currently being funded on your reservation. If you answered “Yes” in Column 17 of Tab 2, include more detailed information about these restoration projects here. Fill out one row for each restoration project.

Include all projects on your water bodies, whether or not they are being funded by a CWA S319 grant, and including those that are being planned and those that are already complete.

64

Click on the green box for an explanation of the answers shown below

Section 1: Basic Project Information Column A: Is this project funded through

CWA Section 319?

Column B: Name the overall waterbody or

watershed whose water quality is

targeted for improvement

In this case, the main water body targeted is the Salmon Run Tributary.In other cases, however, restoration projects may affect entire watersheds, or water bodies farther away, due to the flow of impacted water between different bodies of water.

65

Section 2: Project Impact Columns C: Name the Best Management

Practices (BMPs) implemented

Column D and E: Estimate the length or

area of the BMP implemented

(length/area of the actual project, not the

area affected)

• Impairment source: logging industry (erosion)• Impairments: high turbidity, low DO, high overall contaminant levels from

soil• BMPs: erosion control

Seeding/Mulching (planting of native vegetation to stabilize soil, replacing tree roots)

Stream Channel Stabilization (rip-rap lining of stream banks to minimize erosion and stream bank widening)

Length of BMPs: Both BMPs line stream banks in the region affected by logging (highlighted in red). Rip-rap is only used to target the weakest areas.

66

Section 3: Project Details continued Column F: Enter the year during which work on the project began (or funding began)

Column G: Choose the current status of the project: Planning, In Progress, or Complete

Column H: Did you collect water quality data for the impacted area before the project began?

Column I: Did you collect water quality data for the impacted area after the project was finished/implemented?

If you have not yet finished the project, select “No.”

• Comparison of WQ data collected before and after BMP implementation is one way of evaluating the project (trend analysis).

• Another method is the comparison of WQ between two sites, upstream and downstream of the BMP (site comparison)

Example 3 in the additional examples illustrates the type of analysis you might do with your pre- and post-project data.

67

Section 3: Project Details continued Column J: Enter the ID of the

monitoring station at or nearest the

affected water body.

Column K: Name any agencies you

are working with to complete this

project

There are two monitoring stations on the Salmon Run Tributary. • SRTR-02 is downstream of the projects, so changes

in WQ in the logging region will affect WQ here• SRTR-01 is upstream of the projects, so it will not be

affected and should not be listed

68


Tab 1: Instructions




Tribal lands)



Tab 6: Definitions


Outline

69


Tab 1: Instructions




Tribal lands)



Tab 6: Definitions


Outline

70

Every reservation is unique in terms of its water bodies, water uses and water quality issues. Not all issues related to WQ monitoring can be covered in the data tables in Tabs 2-4.

We ask that you also submit a more complete overview of your Water Quality Monitoring Program, monitoring and data management strategies, and results in a written narrative.

A detailed outline for the narrative can be found in under Tab 5.

Tab 5: Narrative

Narrative Components• Purpose and Goals of your Water Quality Monitoring Program• Description of collaboration with other groups used to deal with WQ issues• WQ Monitoring Design• Data Management and Analysis/Interpretation Strategy• Results (based on your data analysis and assessment) & Future Directions (based on water

quality or monitoring issues discovered during this monitoring period)

71

Congratulations! You have successfully filled out the R9 Water Quality Assessment Report Template and analyzed water quality on your reservation.

Make sure you submit to your Project Officer:WQX-STORET data (Excel sheet)WQAR Template (Excel sheet)WQAR Narrative (Word Document)

Click to exit this tutorialClick for a list of additional examples (mentioned throughout this

tutorial)

Last Steps!

72

Click to return to the last slide you viewed

Table of Contents

Additional Examples• Example 2: Additional Monitoring Location (SRTR-01)

– Not impaired parameter – Improved water quality (includes brief discussion of outliers)– Satisfactory water quality

• Example 3: Restoration Project (Site Comparison)– Concept: t-tests (site comparison OR trends between two periods over time)– Concept: statistical significance

73


Main Reservoir

Irrigation Ditch

Groundwater Wells

SRV-01

SRV-02

SRV-03

SRTR-01

SRTR-02

IRG-01 GWW-01MR-01

MR-02

Example 2

74

Example 2: SRTR-01In Example 1, we looked at a monitoring station (IRG-01) with impaired and degrading water quality.

In this example, we will look at monitoring station SRTR-01, which has satisfactory water quality that has been maintained at this level over time.

Without even looking at the data, you can get an idea of what water quality level to expect just by looking at the conditions near the monitoring location.

Near IRG-01, there were a number of potential pollutant inputs, including agricultural runoff and pollution from livestock operations.

At SRTR-01, however, there are very few nearby potential sources of impairment. Water flows in the above image fro right to left, so pollution from logging in the forested area does not affect water upstream at SRTR-01. As a result, you might guess that water quality is much better at this monitoring station.

Now, let’s begin more rigorous data analysis.75

Date Turbidity (NTU)

1/3/2011 0.86

1/15/2011 0.77

2/1/2011 2.90

2/15/2011 0.72

3/1/2011 3.00

3/15/2011 0.69

4/1/2011 0.85

4/15/2011 0.77

5/1/2011 0.30

5/15/2011 0.82

6/1/2011 1.74

6/15/2011 0.70

7/1/2011 0.98

7/15/2011 0.78

8/1/2011 2.60

8/15/2011 1.00

Step 3. Conduct some basic statistical analyses on your whole data set.

Summary Statistics:Mean: 1.32 NTUSt. dev: 0.98 NTUMinimum: 0.300 NTUMaximum:4.4 NTU

What preliminary conclusions can you make from this data?

Water Quality Criteria:“Turbidity shall not increase above 7.5 NTU.”

Step 2. Find the water quality criteria

Step 1. Organize your data

• Mean TP level is below the WQ criteria (7.5 NTU)• Variation in the data is relatively small compared to the WQ

criteria• Minimum and maximum turbidity are both below the maximum

WQ criteria

Preliminary Conclusion: Turbidity is in general below the WQ criteria

parameter is NOT impaired

Example 2A: Turbidity status, SRTR-01

…etc. through 12/15/2011 76


1/3/2011 0.86

1/15/2011 0.77

2/1/2011 2.9

2/15/2011 0.72

3/1/2011 3

3/15/2011 0.69

4/1/2011 0.85

4/15/2011 0.77

5/1/2011 0.30

5/15/2011 0.82

6/1/2011 1.74

6/15/2011 0.70

7/1/2011 0.98

7/15/2011 0.78

8/1/2011 2.60

8/15/2011 1.00

…etc. through 12/15/2011


Step 4: Prepare/modify your data, according to WQ criteria

Step 5: Graph your data

Step 6: Analyze your data-Are there any exceedances of the WQ criteria? -Are there any apparent trends over time? -Are there any outliers?

Your data does not need to be modified further – it can be compared to your WQ criteria in its current form. (Nothing additional is specified in the criteria)

12/8/2

0101/2

7/2011

3/18/2

011

5/7/2

0116/2

6/2011

8/15/2

01110/4

/2011

11/23/2

0111/1

2/2012

0

1

2

3

4

5

6

7

8

Turbidity, SRTR-01

Monitoring Data

WQ criteria

Turb

idity

(NTU

)

77

12/8/2

0101/2

7/2011

3/18/2

011

5/7/2

0116/2

6/2011

8/15/2

01110/4

/2011

11/23/2

0111/1

2/2012

0

1

2

3

4

5

6

7

8

Turbidity, SRTR-01

Monitoring Data

WQ criteria

Turb

idity

(NTU

)


1/3/2011 0.86

1/15/2011 0.77

2/1/2011 2.9

2/15/2011 0.72

3/1/2011 3

3/15/2011 0.69

4/1/2011 0.85

4/15/2011 0.77

5/1/2011 0.30

5/15/2011 0.82

6/1/2011 1.74

6/15/2011 0.70

7/1/2011 0.98

7/15/2011 0.78

8/1/2011 2.60

8/15/2011 1.00

…etc. through 12/15/2011


Step 4: Prepare/modify your data, according to WQ criteria

Step 5: Graph your data

Step 6: Analyze your data-Are there any exceedances of the WQ criteria? No-Are there any apparent trends over time? No – the turbidity level stays

essentially the same all year-Are there any outliers?

No significant outliers. While there are a few points that are higher than others (perhaps due to storm events), none of these are above the WQ criteria

Your data does not need to be modified further – it can be compared to your WQ criteria in its current form. (Nothing additional is specified in the criteria)

Conclusion:Water quality is not impaired

78

12/8/2

0101/2

7/2011

3/18/2

011

5/7/2

0116/2

6/2011

8/15/2

01110/4

/2011

11/23/2

0111/1

2/2012

0

1

2

3

4

5

6

7

8

R² = 0.024082401899593

Turbidity, SRTR-01

Monitoring DataLinear (Monitor-ing Data)

Turb

idity

(NTU

)

Example 2B: Turbidity trends, SRTR-01Step 1. Add a linear trendline to your data.

Step 2. Look at the R2 value.

Step 3. Analyze the cause of the trend.

The low R2 value indicates that there is no real trend in the data. This makes sense in this context, because there are few inputs or environmental conditions that would cause turbidity levels at this monitoring station to change

It is still a good idea to compare this year’s data with previous years’ data to evaluate trends in water quality over a longer period of time. We will do this analysis next.

The R2 value is very low (0.0241), meaning only 2% of the data can be explained by the linear trendline. This means that there is essentially no trend in the data.

79

12/15/2008 7/3/2009 1/19/2010 8/7/2010 2/23/2011 9/11/20110

1

2

3

4

5

6

7

8

9

Turbidity over time, SRTR-01

Series1

Series3

Turb

idity

(NTU

)



2. Compare the yearly means (and st.dev) over time


1. There does not appear to be a significant change in turbidity levels over time. Even though there are a few points that appear to be higher than most (in the 4-5 NTU range), overall there does not appear to be a significant change.

80

12/15/2008 7/3/2009 1/19/2010 8/7/2010 2/23/2011 9/11/20110

1

2

3

4

5

6

7

8

9


Series1

Series3

Turb

idity

(NTU

)






2. There is no consistent trend upwards or downwards in the yearly means over time. There does not seem to be a very large change in the means between years – the variation in yearly means is much smaller than the variation between the actual data points in any year.

12/15/2008 7/3/2009 1/19/2010 8/7/2010 2/23/2011 9/11/20110

1

2

3

4

5

6

7

8

9


Yearly meansMonitoring DataWQ criteria

Turb

idity

(NTU

)

81

What about this point?

12/15/2008 7/3/2009 1/19/2010 8/7/2010 2/23/2011 9/11/20110

1

2

3

4

5

6

7

8

9


Series1

Series3

Turb

idity

(NTU

)






2. There is no consistent trend upwards or downwards in the yearly means over time. There does not seem to be a very large change in the means between years – the variation in yearly means is much smaller than the variation between the actual data points in any year.

3. There are almost no exceedances of the WQ criteria over time, excluding one point in 2010. This can be considered an outlier, and be ignored during our analysis. Other than this point, the turbidity levels are well under the maximum criteria level. This indicates that water quality criteria have been met.

12/15/2008 7/3/2009 1/19/2010 8/7/2010 2/23/2011 9/11/20110

1

2

3

4

5

6

7

8

9


Yearly meansMonitoring DataWQ criteria

Turb

idity

(NTU

)

This is the only point in three years to exceed the maximum criteria for turbidity. It does not appear to be part of a trend, and is not frequently repeated, so it may have simply been due to an unusual circumstance, such as an accidental spill or large storm event.

We can call this point an outlier, meaning it does not reflect the usual water quality at this monitoring station. We can ignore it when interpreting the data/making water quality assessments. -----------------------------------------------------------------------In other cases, such as with bacterial counts, we cannot ignore outliers, because even one exceedance of the WQ criteria can cause serious threats to health. The WQ criteria will specify when there can be no outliers (“one time exceedances cannot be higher than…”)

End of example 2

Conclusion:Water quality is maintained

82


Main Reservoir

Irrigation Ditch

Groundwater Wells

SRV-01

SRV-02

SRV-03

SRTR-01

SRTR-02

IRG-01 GWW-01MR-01

MR-02

Example 3

83

Example 3: T-tests (Site Comparison)Restoration Project, SRTR-01 and SRTR-02

Water flows from the Salmon Run Tributary to Spring River (from monitoring station SRTR-01 to SRTR-02)

There are no major potential sources of impairment upstream of SRTR-01. However, there exists about a 1.3 mile stretch of forested area between SRTR-01 and SRTR-02, and the tribe conducts logging operations. In 2008, the EPA funded a restoration project to reduce the impact of logging operations on water quality in the tributary, which provides a spawning habitat for salmon in the spring.

Problem• Impairment source: logging industry (erosion)• Impairments: high turbidity, low DO, high overall

contaminant levels from soil

Solutions• BMPs: erosion control

Seeding/Mulching (planting of native vegetation to stabilize soil, replacing tree roots)

Stream Channel Stabilization (rip-rap lining of stream banks to minimize erosion and stream bank widening)

Has the restoration project been successful?

84

Has the restoration project been successful?

Two analyses will help answer this question: Site Comparison (upstream-downstream: comparing SRTR-01 and SRTR-02) Before-After comparison (particularly for SRTR-02, the affected monitoring station)

For these analyses, we want to compare two locations or two points in time. To make this comparison clearer, we will not use scatterplots. Instead, we will conduct t-tests, which can be illustrated using bar graphs with error bars.

Note: In the following data analysis it is assumed that water quality at SRTR-01 is good/satisfactory (meets WQ criteria).

Example 3: T-tests (Site Comparison)What is a t-test?A t-test measures whether values from two sets of data are statistically significantly different from each other or not. When comparing data from two monitoring stations or two time periods on Microsoft Excel, you can use the function TTEST. This will give you a p-value, which indicates the level of significance.

• p-value < or = 0.05 means the two data sets are significantly different from each other

• p-value > 0.05 means the two data sets are not significantly different

85

Example 3: T-tests

Location ID Date Turbidity (NTU)SRTR-01 4/15/2007 0.5SRTR-01 5/10/2007 1SRTR-01 6/8/2007 0.9SRTR-01 7/15/2007 2.1SRTR-01 8/11/2007 0.6SRTR-01 9/12/2007 0.3SRTR-01 4/15/2011 0.4SRTR-01 5/10/2011 1.2SRTR-01 6/8/2011 0.8SRTR-01 7/15/2011 1SRTR-01 8/11/2011 1.6SRTR-01 9/12/2011 0.2


Location ID / time Mean Standard dev Max. Min. RangeSRTR-01, 2007 0.9 0.642 2.1 0.3 1.8SRTR-02, 2007 13.9 7.374 23.6 5.1 18.5SRTR-01, 2011 0.867 0.516 1.6 0.2 1.4SRTR-02, 2011 2.3 1.642 5.1 0.6 4.5

Step 1. Organize your dataStep 2. Find WQ criteriaStep 3. Conduct basic statistical analysis

The mean turbidity level only exceeds the WQ criteria at SRTR-02, and only before the restoration project .

This suggests that the restoration project is working, and has reduced turbidity levels since its implementation.

More rigorous statistical analysis is needed to support this conclusion confidently.

Note: SRTR-01 represents natural turbidity levels, because there are no inputs there. WQ here also acts as a “control,” to show that conditions other than logging and the restoration project are affecting WQ.

Location ID Date Turbidity (NTU)SRTR-02 4/15/2009 6.3SRTR-02 5/10/2009 12SRTR-02 6/8/2009 19.2SRTR-02 7/15/2009 23.6SRTR-02 8/11/2009 17.2SRTR-02 9/12/2009 5.1SRTR-02 4/15/2011 0.6SRTR-02 5/10/2011 3.2SRTR-02 6/8/2011 2.2SRTR-02 7/15/2011 5.1SRTR-02 8/11/2011 1.1SRTR-02 9/12/2011 1.6

86



p-value: 0.00568*

p-value: 0.07874

Pre-Project Post-Project0

2

4

6

8

10

12

14

16

Site Comparison

SRTR-01

SRTR-02

Turb

idity

(NTU

) p-value: 0.00568

p-value: 0.07874

*p-values below 0.05 indicate a significant difference between data sets.

Analysis #1

Data Analysis

This graph and related p-values help you compare WQ at the two monitoring stations.

• Pre-project: large, significant difference in turbidity levels between SRTR-01 and SRTR-02

• Post-project: no significant difference between SRTR-01 and SRTR-02 turbidity (p-value > 0.05)

If we assume WQ at SRTR-01 is satisfactory, WQ at SRTR-02 is much more similar to this satisfactory WQ after the project. This suggests that the restoration project has improved water quality over time.

Step 4. Calculate p-values (t-test) that compare the two monitoring stations (both before and after the project)

87



Analysis #2 (Alternative)*

p-value: 0.908336 p-value: 0.0068

*This is an additional/ alternative way of graphing your data, which will help you come to similar conclusions.

Doing both analyses will help you see your data in different ways and gain more confidence in your conclusions.

Step 4. Calculate p-values (t-test) that compare pre- and post- project data for each monitoring station

SRTR-01 SRTR-020

5

10

15

20

25

Site Comparison

Pre-Project Data (2007)Post-Project Data (2011)

p-value: 0.908336

p-value: 0.0068

Data Analysis

This graph helps you better visualize the change in water quality at each monitoring station.

• SRTR-01: No significant change in WQ• SRTR-02: Very significant change in WQ

after project implementation

The lack of change at SRTR-01 verifies that natural levels of turbidity are not changing. The change at SRTR-02 indicates that the restoration project is indeed improving WQ.

What is a p-value?A p-value indicates whether or not the values in two data sets are “significantly different” from each other.

• p-value < or = 0.05 means the two data sets are significantly different from each other

• p-value > 0.05 means the two data sets are not significantly different

Remember that a statistically significant difference does not always mean a significant real-world difference. Judging the difference between an impaired or not impaired parameters, for example, requires different analysis.

88

Additional Notes (t-tests)


2

4

6

8

10

12

14

16

Site Comparison

SRTR-01SRTR-02

Turb

idity

(NTU

) p-value: 0.00568

p-value: 0.07874

SRTR-01 SRTR-020

5

10

15

20

25

Site Comparison


p-value: 0.908336

p-value: 0.0068

T-test are helpful to use when making comparisons between two sets of data, such as • pre- and post-project data, or• upstream and downstream data at two monitoring stations

However, t-tests do NOT help you compare your data to the WQ criteria*, so you cannot use them to determine the actual water quality of any one monitoring station at a certain time.

*Statistical significance does not necessarily mean actual significance. For example:Water quality at SRTR-01 is satisfactory and turbidity is not impaired. However, even though turbidity levels are not significantly different between SRTR-01 and SRTR-02 in 2011, turbidity levels could still be impaired at SRTR-02. You would need to actually compare data values at SRTR-02 to the WQ criteria to determine impairment.

Similarly, even though water quality became not significantly different between the two locations after the restoration project, it does not mean that turbidity levels at SRTR-02 has changed from impaired to not impaired. There is no connection between statistical significance and impairment.

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Site Comparison

SRTR-01SRTR-02

Turb

idity

(NTU

) p-value: 0.00568

p-value: 0.07874

SRTR-01 SRTR-020

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Site Comparison


p-value: 0.908336

p-value: 0.0068

In the above example, the red-boxed comparison is the most important for clearly showing improvement (p-value < 0.05 indicates a significant decrease in turbidity) in water quality over time at a monitoring station affected by a restoration project.

The other t-tests help you visualize your data in different ways. Including an upstream monitoring station helps put your data values in context.


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Site Comparison

SRTR-01SRTR-02

Turb

idity

(NTU

) p-value: 0.00568

p-value: 0.07874

You can also compare water quality between two sites or time periods by comparing your water quality assessment conclusions (for example: if water quality at SRTR-02 was “impaired” before the project but is “satisfactory” after the project, it is likely that the restoration project improved water quality).

HOWEVER, t-tests may be helpful to show incremental improvement in water quality. For example, water quality might still “impaired” after a restoration project. However, your t-tests show that there has still been an improvement in water quality, indicating that your restoration project has had some positive effect.

End of example 3

SRTR-01 SRTR-020

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Site Comparison


p-value: 0.908336

p-value: 0.0068


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epa region 9 water quality assessment report tutorial 2011 1

Documents

assessment of water

analysis of water quality

assessment template

water quality of tribal

tutorial tips

tutorial additional

clean water act section

wqar narrative