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EPA Region 9 Water Quality Assessment Report Tutorial 2011 1.

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1 EPA Region 9 Water Quality Assessment Report Tutorial 2011 1

2 Clean Water Act Section 106 Annual Assessment Report Tribes 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

3 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

4 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

5 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 youll need to make based upon any monitoring data you have collected in order to complete the template. Water Quality Assessment Example Spring River Tribe 5

6 A map of the Spring River Reservation is illustrated below. 6

7 Reservation size: 70 square miles Reservation 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

8 Reservation size: 70 square miles Reservation boundaries outlined in black Spring River Salmon Run Tributary Main Reservoir Irrigation Ditch Groundwater Wells SRV-01 SRV-02 SRV-03 SRTR-01 SRTR-02 IRG-01 GWW-01 MR-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

9 R9 Water Quality Assessment Report Outline The 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

10 The 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 R9 Water Quality Assessment Report Outline 10

11 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.

12 Spring River Salmon Run Tributary Main Reservoir Irrigation Ditch Groundwater Wells SRV-01 SRV-02 SRV-03 SRTR-01 SRTR-02 IRG-01 GWW-01 MR-01 MR-02 You will begin by filling in one row for the IRG-01 monitoring station 12

13 Irrigation Ditch Section 1: Basic Monitoring Information 13

14 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

15 Column 1: enter the name of your waterbody Column 2: choose the type of your waterbody (river, reservoir, wetland, groundwater well, etc.) 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. 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

16 Column 1: enter the name of your waterbody Column 2: choose the type of your waterbody (river, reservoir, wetland, groundwater well, etc.) Column 3: choose Yes or No: is your monitoring station located on your reservation (including trust and fee lands) 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. 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) 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. (Click this textbox to remove and allow other links to appear) 16

17 Column 1: enter the name of your waterbody Column 2: choose the type of your waterbody (river, reservoir, wetland, groundwater well, etc.) 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 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. 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) 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. (Click this textbox to remove and allow other links to appear) 17

18 Irrigation Ditch Section 1: Basic Monitoring Information continued 18

19 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 bodys 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 Section 1: Basic Monitoring Information continued 20

21 **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 EPAs 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) Section 1: Basic Monitoring Information continued 21

22 WQX-STORET Data Analysis You are now ready to analyze your monitoring data and make water quality assessments (columns 10-13) 22

23 WQX-STORET Data Analysis You are now ready to analyze your monitoring data and make water quality assessments (columns 10-13) You have gathered together your: WQX-STORET monitoring data EPA-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

24 Analyzing Data at IRG-01 Example 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

25 DateTotal phosphorous (mg/L) 4/1/20110.024 4/15/20110.027 5/1/20110.037 5/15/20110.040 6/1/20110.063 6/15/20110.057 7/1/20110.081 7/15/20110.079 8/1/20110.076 8/15/20110.079 9/1/20110.082 9/15/20110.078 10/1/20110.083 10/15/20110.091 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/L St. dev: 0.023 mg/L Minimum: 0.024 mg/L Maximum: 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. 25

26 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? DateTotal phosphorous (mg/L) 4/1/20110.024 4/15/20110.027 5/1/20110.037 5/15/20110.040 6/1/20110.063 6/15/20110.057 7/1/20110.081 7/15/20110.079 8/1/20110.076 8/15/20110.079 9/1/20110.082 9/15/20110.078 10/1/20110.083 10/15/20110.091 DateTP monthly means (mg/L) 4/20110.026 5/20110.039 6/20110.060 7/20110.080 8/20110.078 9/20110.080 10/20110.087 Monitoring dataMonthly 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. 26

27 DateTP monthly means (mg/L) 4/20110.026 5/20110.039 6/20110.060 7/20110.080 8/20110.078 9/20110.080 10/20110.087 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 Monthly Means 27

28 DateTP monthly means (mg/L) Water Quality criteria for TP (mg/L) 4/20110.0260.035 5/20110.0390.035 6/20110.0600.035 7/20110.0800.035 8/20110.0780.035 9/20110.0800.035 10/20110.0870.035 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

29 DateTP monthly means (mg/L) Water Quality criteria for TP (mg/L) 4/20110.0260.035 5/20110.0390.035 6/20110.0600.035 7/20110.0800.035 8/20110.0780.035 9/20110.0800.035 10/20110.0870.035 Step 6. Analyze your data. Questions to consider: -Do any of the data points exceed the minimum or maximum criteria allowed? (Yes suggests impairment) 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 29

30 DateTP monthly means (mg/L) Water Quality criteria for TP (mg/L) 4/20110.0260.035 5/20110.0390.035 6/20110.0600.035 7/20110.0800.035 8/20110.0780.035 9/20110.0800.035 10/20110.0870.035 Step 6. Analyze your data. Questions to consider: -Do any of the data points exceed the minimum or maximum criteria allowed? (Yes suggests impairment) 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?] 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

31 DateTP monthly means (mg/L) Water Quality criteria for TP (mg/L) 4/20110.0260.035 5/20110.0390.035 6/20110.0600.035 7/20110.0800.035 8/20110.0780.035 9/20110.0800.035 10/20110.0870.035 Step 6. Analyze your data. Questions to consider: -Do any of the data points exceed the minimum or maximum criteria allowed? (Yes suggests impairment) 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?] 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

32 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

33 Step 1. Add a linear trendline to your data. Step 2. Look at the R 2 value. A high R 2 value indicates that the trendline fits the data points well. If the R 2 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 years 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-01 Example 1B: Total Phosphorous Trends What is an R 2 value? An R 2 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). R 2 =1 means the trendline perfectly fits the data (x-values perfectly predict y-values) R 2 = 0 means the trendline has no correlation with the data (x-values do not predict y-values) R 2 = 0.8 means 80% of the data can be explained by the trendline (x-values predict 80% of the variation in y-values) R 2 > 0.8 is an okay model; R 2 > 0.9 is excellent R 2 < 0.5 generally indicates no clear trend 33

34 DateTP monthly means (mg/L) Water Quality criteria (mg/L) 4/1/20110.0260.035 5/1/20110.0390.035 6/1/20110.0600.035 7/1/20110.0800.035 8/1/20110.0780.035 9/1/20110.0800.035 10/1/20110.0870.035 DateTP monthly means (mg/L) Water Quality criteria (mg/L) 4/20090.0040.035 5/20090.0210.035 6/20090.0260.035 7/20090.0250.035 8/20090.0270.035 9/20090.0300.035 10/20090.0220.035 4/20100.0110.035 5/20100.0280.035 6/20100.0420.035 7/20100.0620.035 8/20100.0600.035 9/20100.0550.035 10/20100.0690.035 4/20110.0260.035 5/20110.0390.035 6/20110.0600.035 7/20110.0800.035 8/20110.0780.035 9/20110.0800.035 10/20110.0870.035 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 34

35 Methods of data analysis 1.Visually analyze trends (all data points) Monitoring periodTP Yearly mean (mg/L) 20090.022 20100.047 20110.064 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 35

36 Methods of data analysis 1.Visually analyze trends (all data points) 2.Compare the TP yearly means (and st.dev) over time Monitoring periodTP Yearly mean (mg/L) TP Standard deviation (mg/L) 20090.0220.008075 20100.0470.02044 20110.0640.022899 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. 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. 36

37 Methods of data analysis 1.Visually analyze trends (all data points) 2.Compare the TP yearly means (and st.dev) over time 3.Compare the number of exceedances of the WQ criteria over time Monitoring periodTP Yearly mean (mg/L) TP Standard deviation (mg/L) Number of exeedances of WQ criteria 20090.0220.0080750 20100.0470.020445 20110.0640.0228996 Conclusion: Water quality has further degraded (over time) 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. 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. 37

38 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

39 WQ Assessment from Data Analysis Transferring 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. Lets 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) pHNoMaintained TemperatureYesMaintained Dissolved OxygenYesDegraded TurbidityYesImproved Total PhosphorousYesDegraded Total NitrogenYesDegraded E. ColiNoImproved ArsenicNoMaintained ConductivityYesMaintained Monitoring location: IRG-01 39

40 Parameter monitored Current impairment status Change in status (trend) pHNoMaintained TemperatureYesMaintained Dissolved OxygenYesDegraded TurbidityYesImproved Total PhosphorousYesDegraded Total NitrogenYesDegraded E. ColiNoImproved ArsenicNoMaintained ConductivityYesMaintained 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. 40

41 Parameter monitored Current impairment status Change in status (trend) pHNoMaintained TemperatureYesMaintained Dissolved OxygenYesDegraded TurbidityYesImproved Total PhosphorousYesDegraded Total NitrogenYesDegraded E. ColiNoImproved ArsenicNoMaintained ConductivityYesMaintained 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

42 Parameter monitored Current impairment status Change in stats (trend) pHNoMaintained TemperatureYesMaintained Dissolved OxygenYesDegraded TurbidityYesImproved Total PhosphorousYesDegraded Total NitrogenYesDegraded E. ColiNoImproved ArsenicNoMaintained ConductivityYesMaintained 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 isimpaired. Data Analysis Summary Table 42

43 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 Current impairment status Change in stats (trend) pHNoMaintained TemperatureYesMaintained Dissolved OxygenYesDegraded TurbidityYesImproved Total PhosphorousYesDegraded Total NitrogenYesDegraded E. ColiNoImproved ArsenicNoMaintained ConductivityYesMaintained Data Analysis Summary Table 43

44 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 IrrigationpH, DO Temperature Turbidity, Conductivity TP, TN E. coli Temperature DO Turbidity, Conductivity TP, TN Livestock WateringTemperature Turbidity, Conductivity TP, TN E. Coli Arsenic Temperature Turbidity, Conductivity TP, TN Impaired Goal/Use? 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 Current impairment status Change in stats (trend) pHNoMaintained TemperatureYesMaintained Dissolved OxygenYesDegraded TurbidityYesImproved Total PhosphorousYesDegraded Total NitrogenYesDegraded E. ColiNoImproved ArsenicNoMaintained ConductivityYesMaintained Data Analysis Summary Table 44

45 COLUMN 13: Impaired Tribal Goals/Designated Uses Tribal Goal/Designated UseImpaired Goal/Use? Agriculture IrrigationYes Livestock WateringYes 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

46 Data Analysis Summary You 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

47 COLUMN 14 and 15: Source & Frequency of Impairment If 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

48 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

49 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 1. Agriculture (Land Use) Fertilizer and pesticide runoff from farmland. 49

50 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 1. Agriculture (Land Use) 2. Agriculture (Livestock) Manure (containing nutrients, antibiotics, pharmaceuticals) runoff and increased turbidity from cows in the irrigation ditch 50

51 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 1. Agriculture (Land Use) 2. Agriculture (Livestock) 3. Hydromodifications Pollution, turbidity and variable flow due to the man-made nature of the irrigation ditch 51

52 COLUMN 15: Frequency of Impairment (Impairment Status) Source of ImpairmentImpairment Status 1. Agriculture (Land Use) 2. Agriculture (Livestock) 3. Hydromodifications 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

53 COLUMN 15: Frequency of Impairment Source of ImpairmentImpairment Status 1. Agriculture (Land Use)Seasonal 2. Agriculture (Livestock)Seasonal 3. Hydromodifications 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 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

54 COLUMN 15: Frequency of Impairment Source of ImpairmentImpairment Status 1. Agriculture (Land Use)Seasonal 2. Agriculture (Livestock)Seasonal 3. HydromodificationsIntermittent 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 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

55 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

56 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

57 WQAR Template Wait -- youre 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** www.semiwisdom.com 57

58 The 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 R9 Water Quality Assessment Report Outline 58

59 The 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 (summary 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 R9 Water Quality Assessment Report Outline 59

60 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

61 Tab 3: Atlas of Tribal Waters 61

62 The 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 R9 Water Quality Assessment Report Outline 62

63 The 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 R9 Water Quality Assessment Report Outline 63

64 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

65 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

66 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

67 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

68 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

69 The 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 R9 Water Quality Assessment Report Outline 69

70 The 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 R9 Water Quality Assessment Report Outline 70

71 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

72 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 tutorial Click for a list of additional examples (mentioned throughout this tutorial) Last Steps! 72

73 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

74 Spring River Salmon Run Tributary Main Reservoir Irrigation Ditch Groundwater Wells SRV-01 SRV-02 SRV-03 SRTR-01 SRTR-02 IRG-01 GWW-01 MR-01 MR-02 Example 2 74

75 Example 2: SRTR-01 In 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, lets begin more rigorous data analysis. 75

76 DateTurbidity (NTU) 1/3/20110.86 1/15/20110.77 2/1/20112.90 2/15/20110.72 3/1/20113.00 3/15/20110.69 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 NTU St. dev: 0.98 NTU Minimum: 0.300 NTU Maximum: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

77 DateTurbidity (NTU) 1/3/20110.86 1/15/20110.77 2/1/20112.9 2/15/20110.72 3/1/20113 3/15/20110.69 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 Water Quality Criteria: Turbidity shall not increase above 7.5 NTU. 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) 77

78 DateTurbidity (NTU) 1/3/20110.86 1/15/20110.77 2/1/20112.9 2/15/20110.72 3/1/20113 3/15/20110.69 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 Water Quality Criteria: Turbidity shall not increase above 7.5 NTU. 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

79 Example 2B: Turbidity trends, SRTR-01 Step 1. Add a linear trendline to your data. Step 2. Look at the R 2 value. Step 3. Analyze the cause of the trend. The low R 2 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 years data with previous years data to evaluate trends in water quality over a longer period of time. We will do this analysis next. The R 2 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

80 Methods of data analysis 1.Visually analyze trends (all data points) 2.Compare the yearly means (and st.dev) over time 3.Compare the number of exceedances of the WQ criteria 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

81 Methods of data analysis 1.Visually analyze trends (all data points) 2.Compare the yearly means (and st.dev) over time 3.Compare the number of exceedances of the WQ criteria 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. 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. 81

82 What about this point? Methods of data analysis 1.Visually analyze trends (all data points) 2.Compare the yearly means (and st.dev) over time 3.Compare the number of exceedances of the WQ criteria 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. 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. 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

83 Spring River Salmon Run Tributary Main Reservoir Irrigation Ditch Groundwater Wells SRV-01 SRV-02 SRV-03 SRTR-01 SRTR-02 IRG-01 GWW-01 MR-01 MR-02 Example 3 83

84 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

85 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

86 Example 3: T-tests Location IDDateTurbidity (NTU) SRTR-014/15/20070.5 SRTR-015/10/20071 SRTR-016/8/20070.9 SRTR-017/15/20072.1 SRTR-018/11/20070.6 SRTR-019/12/20070.3 SRTR-014/15/20110.4 SRTR-015/10/20111.2 SRTR-016/8/20110.8 SRTR-017/15/20111 SRTR-018/11/20111.6 SRTR-019/12/20110.2 Water Quality Criteria: Turbidity shall not increase above 7.5 NTU. Location ID / timeMeanStandard devMax.Min.Range SRTR-01, 20070.90.6422.10.31.8 SRTR-02, 200713.97.37423.65.118.5 SRTR-01, 20110.8670.5161.60.21.4 SRTR-02, 20112.31.6425.10.64.5 Step 1. Organize your data Step 2. Find WQ criteria Step 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 IDDateTurbidity (NTU) SRTR-024/15/20096.3 SRTR-025/10/200912 SRTR-026/8/200919.2 SRTR-027/15/200923.6 SRTR-028/11/200917.2 SRTR-029/12/20095.1 SRTR-024/15/20110.6 SRTR-025/10/20113.2 SRTR-026/8/20112.2 SRTR-027/15/20115.1 SRTR-028/11/20111.1 SRTR-029/12/20111.6 86

87 Location IDDateTurbidity (NTU) SRTR-014/15/20070.5 SRTR-015/10/20071 SRTR-016/8/20070.9 SRTR-017/15/20072.1 SRTR-018/11/20070.6 SRTR-019/12/20070.3 SRTR-014/15/20110.4 SRTR-015/10/20111.2 SRTR-016/8/20110.8 SRTR-017/15/20111 SRTR-018/11/20111.6 SRTR-019/12/20110.2 Location IDDateTurbidity (NTU) SRTR-024/15/20096.3 SRTR-025/10/200912 SRTR-026/8/200919.2 SRTR-027/15/200923.6 SRTR-028/11/200917.2 SRTR-029/12/20095.1 SRTR-024/15/20110.6 SRTR-025/10/20113.2 SRTR-026/8/20112.2 SRTR-027/15/20115.1 SRTR-028/11/20111.1 SRTR-029/12/20111.6 p-value: 0.00568* p-value: 0.07874 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

88 Location IDDateTurbidity (NTU) SRTR-014/15/20070.5 SRTR-015/10/20071 SRTR-016/8/20070.9 SRTR-017/15/20072.1 SRTR-018/11/20070.6 SRTR-019/12/20070.3 SRTR-014/15/20110.4 SRTR-015/10/20111.2 SRTR-016/8/20110.8 SRTR-017/15/20111 SRTR-018/11/20111.6 SRTR-019/12/20110.2 Location IDDateTurbidity (NTU) SRTR-024/15/20096.3 SRTR-025/10/200912 SRTR-026/8/200919.2 SRTR-027/15/200923.6 SRTR-028/11/200917.2 SRTR-029/12/20095.1 SRTR-024/15/20110.6 SRTR-025/10/20113.2 SRTR-026/8/20112.2 SRTR-027/15/20115.1 SRTR-028/11/20111.1 SRTR-029/12/20111.6 Analysis #2 (Alternative)* p-value: 0.908336p-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 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

89 Additional Notes (t-tests) p-value: 0.00568 p-value: 0.07874 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. 89

90 p-value: 0.00568 p-value: 0.07874 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. Additional Notes (t-tests) 90

91 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 p-value: 0.0068 Additional Notes (t-tests) 91

92 Example 4: Multiple WQ criteria 92

93 Other possible examples.. E. coli: single maximum: 120 CFU/100 mL (contact recreation, wildlife, etc.) [SINGLE MAX] DO: 7-day average of the daily minimum: 9.5 mg/L in the water column; 11.0 mg/L minimum during spawning season [MULTIPLE CRITERIA] pH: 6.5 – 8.5 at all times; 5.0 to 9.0 for MUN uses (municipal and domestic uses) [MAX AND MIN] 93

94 ANIMATIONS To add popups: 1. left click > timing > triggers > start on [click the link] (appear) 2. > triggers > start on [click the popup] (disappear) 94


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