Getting Physical with Estuaries

National Estuarine Research Reserve System / 9-12 / Life Science, Earth Science



Focus Question

How do physical factors in estuaries vary over time, and how do variations in one factor affect other factors?

Learning Objectives

Links to Overview Essays and Resources for Student Research

http://oceanservice.noaa.gov/topics/coasts/reserves/

Materials

Audio/Visual Materials

None

Teaching Time

One or two 45-minute class period, plus time for student research

Seating Arrangement

Groups of 3-4 students

Maximum Number of Students

30

Key Words

Estuary
Salinity
Dissolved oxygen
Temperature
Physical factors
National Estuary Research Reserve System

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Background Information

Estuaries are bodies of water and adjacent wetlands found in areas where rivers flow into much larger bodies of water. Most estuaries are formed when a river meets the sea, and the water in these estuaries is a mixture of freshwater and saltwater from the ocean. But there are also freshwater estuaries that occur where rivers flow into much larger bodies of freshwater such as the Great Lakes.

Estuaries are some of the most biologically productive systems on Earth and provide food, recreation, and economic opportunities to human communities, as well as habitats, food, and protected breeding areas for many species. Because of these benefits, many human communities are located in or near estuaries; and as a result, many estuaries have been damaged by human activities such as dredging, inappropriate industrial activity, and poor agricultural practices. In addition, estuaries are exposed to a variety of natural disturbances including winds, waves, heavy rainfall, and severe storms.

Threats to estuaries coupled with their importance led to the establishment of the National Estuarine Research Reserve System (NERRS). NERRS protects more than one million acres in 26 estuaries that represent a range of coastal estuarine habitats in the United States and its territories. In addition to protecting representative sites, NERRS conducts research to investigate the effects of natural processes and human activities on estuaries. A key part of this research is the systemwide Monitoring Program (SWMP; pronounced “swamp”), which includes regular measurements of water quality indicators (water temperature, specific conductivity, salinity, dissolved oxygen, depth, pH, and turbidity); meteorological data (air temperature, relative humidity, barometric pressure, wind speed, wind direction, precipitation, and solar radiation); and nutrient data (orthophosphate, ammonium, nitrite, nitrate, nitrite+nitrate and chlorophyll).

This lesson is intended to introduce students to information available from the NERRS SWMP and to simple techniques for analyzing these data to investigate environmental conditions in specific estuaries.

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Learning Procedure

  1. Preparation: Visit the NERRS Centralized Data Management Office Web site at http://cdmo.baruch.sc.edu/. You may want to follow some or all of the directions in the “NERRS Systemwide Monitoring Program Data Base Worksheet” to become familiar with these procedures and the types of information available at this site. If your students will be using a spreadsheet program other than Microsoft Excel® you may need to modify the directions for setting up the spreadsheet and preparing graphs of the data.

  2. Direct students to the Estuaries Tutorial at http://oceanservice.noaa.gov/education/kits/estuaries. You may want to assign different tutorial sections to individual students within each student group.

  3. You may need to review some of the following concepts before students begin working with the SWMP Database:

    • Salinity is defined as the content of dissolved salts in seawater. Since seawater contains a variety of salts (magnesium sulfate, magnesium chloride, calcium carbonate, etc.) in addition to sodium chloride, salinity is not directly equivalent to the concentration of sodium chloride in seawater. Salinity is measured in parts per thousand (ppt or ‰), which is equivalent to grams per kilogram. Freshwater has a salinity of 0 ‰; normal seawater has a salinity of about 35 ‰.

    • Specific Conductivity is a measure of a material’s ability to conduct an electric charge. In water, conductivity is related to salt content and is used to estimate salinity. The units of conductivity are siemens per centimeter (S/cm). Since 1S/cm is a very high level of conductivity for most solutions, conductivity is usually expressed in millisiemens per centimeter (mS/cm). One millisiemen is one-thousandth of a siemen. The specific conductivity of “fresh” water ranges from 0.001 to about 1.000 mS/cm. The specific conductivity of seawater is about 55 mS/cm.

    [Conductivity is the opposite of resistance. The unit of resistance measurements is the ohm, which is the resistance of an electrical circuit in which a voltage of one volt produces a current of one ampere. Conductivity is defined as the reciprocal of resistance and its unit formerly was the mho (ohm spelled backward). Most scientists now use the siemen as the unit of conductivity, but it is equivalent to the mho. Because conductivity of a solution depends upon the distance between the electrodes of the measuring instrument, conductivity is given in siemens per centimeter (S/cm) or millisiemens per centimeter (mS/cm).]

    • Units for dissolved oxygen measurements are usually milligrams per liter or parts per million (ppm; equivalent to mg/kg). Solubility of oxygen (the amount of oxygen that will dissolve in water) depends upon temperature, salinity, and other factors. For this reason, dissolved oxygen may also be expressed as a percentage of saturation, which compares the level of dissolved oxygen in a water sample with the maximum amount of dissolved oxygen that could be contained in water having the same temperature, salinity, etc., as the sample.

    • Solubility of oxygen decreases as salinity and temperature increase. Cold freshwater may have dissolved oxygen concentrations around 17 ppm, while the concentration of dissolved oxygen in cold seawater is around 10 ppm. Dissolved oxygen concentrations less than 5 ppm are generally considered to be low and are particularly harmful to aquatic organisms during summer months when metabolic rates are high.

    • Turbidity is a measurement of the amount of suspended matter in a water sample. Because suspended matter causes light to scatter as it passes through a water sample, turbidity is often estimated with an instrument called a nephelometer, which measures the amount of light that is absorbed and scattered by a water sample. The units for turbidity measured this way are called nephelometric turbidity units (NTU). A clear stream might have a turbidity of 1 NTU, while the turbidity of a large river might be around 10 NTUs during dry weather and several hundred NTUs after heavy rainfall because of particulate material carried into the river by runoff.

  4. Distribute copies of the “NERRS System-wide Monitoring Program Database Worksheet” to each student group. Tell students that their assignment is to use the NERRS SWMP Database to answer the questions on the worksheet.

  5. Have each student group present their charts and lead a discussion of students’ answers to the worksheet questions.

Students should recognize a regular oscillation in water depth and infer that this is due to tidal motion within the estuary. The twice-daily cycles are particularly evident in the charts for a single day’s worth of data. Salinity levels correlate most strongly with water depth variations, and this is particularly striking in data from January 15, 2003. Higher salinity levels correlate with higher water levels, and students should infer that this is due to the influx of seawater. Oscillations in dissolved oxygen and temperature levels also resemble water depth variations, particularly in the latter half of the November 8 - 18, 2002, period. Since peaks in temperature coincide with higher water levels during this period, students may infer that seawater was warmer than inflowing freshwater at this time. Peaks in dissolved oxygen show a similar correlation, suggesting that ocean waters may have been more aerated than freshwaters, perhaps as a result of wave action.

Dissolved oxygen levels are highest during colder months, and lowest during the hottest months. This obviously suggests a relationship between dissolved oxygen and temperature, and students should realize that the capacity of water for dissolved gases is reduced as water temperature increases. Encourage students to speculate on other processes that could contribute to the observed relationship. You may want to remind them that metabolic processes in living organisms are generally more active during warmer months and that oxygen consumption of aerobic organisms increases with increasing metabolic activity; so dissolved oxygen might be depleted by an increase in metabolic activity associated with increased temperature. Higher temperatures may also encourage the rapid growth of aquatic plants. When these plants die, decomposition of large masses of decaying vegetation consumes oxygen and lowers the level of dissolved oxygen.

Students should recognize that salinity levels dropped during the latter portion of the November 8 - 18, 2002, period following heavy precipitation a day or so earlier. Oscillations in dissolved oxygen levels also became more pronounced at the same time, suggesting that the influx of freshwater from heavy rains resulted in increased oxygen consumption perhaps because the resulting runoff carried additional organic matter into the estuary. Metabolism of this organic matter could results in increased oxygen consumption and consequently lower levels of dissolved oxygen.

Students should identify the following maximum daily and annual ranges:

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The Bridge Connection

The Bridge is a growing collection online marine education resources. It provides educators with a convenient source of useful information on global, national, and regional marine science topics. Educators and scientists review sites selected for the Bridge to insure that they are accurate and current.

www.vims.edu/bridge/ - Click on “Ocean Science Topics” in the navigation menu to the left, then “Habitats,” then “Coastal,” then “Estuary.”

The “Me” Connection

Have students write a brief essay describing three things that they could personally do to help protect and enhance one or more estuaries, and how these actions would be personally important.

Extensions

Have students select other estuaries included in the NERRS and prepare brief reports about these systems, including information on variations in environmental factors based on information in the SWMP Database.

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Resources

http://cdmo.baruch.sc.edu/ – National Estuarine Research Reserve System Centralized Data Management Office website

http://www.epa.gov/owow/estuaries/kids/ – Games and activities about estuaries produced through the National Estuary Program

http://www.northinlet.sc.edu/estnetweb/estnet.html – “Estuary-Net Project;” an online project to develop collaborations among high schools, community volunteer water quality monitoring groups, local officials, state Coastal Zone Management (CZM)  programs and National Estuarine Research Reserves  (NERRS) to help solve non-point source pollution problems in estuaries and their watersheds

National Science Education Standards

Content Standard A: Science as Inquiry

Content Standard C: Life Science

Content Standard D: Earth and Space Science

Content Standard F: Science in Personal and Social Perspectives

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Ocean Literacy Essential Principles and Fundamental Concepts

Essential Principle 1. The Earth has one big ocean with many features.

Essential Principle 5. The ocean supports a great diversity of life and ecosystems.

Essential Principle 6. The ocean and humans are inextricably interconnected.

Essential Principle 7. The ocean is largely unexplored.

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Getting Physical with Estuaries

NERRS System-wide Monitoring Program Data Base Student Worksheet

Long-term environmental monitoring is a key activity of NOAA’s National Estuarine Research Reserve System (NERRS). The NERRS System-wide Monitoring Program (SWMP; pronounced “swamp”) includes regular measurements of water quality indicators, meteorological data and nutrient data. Water quality indicators include water temperature, specific conductivity, salinity, dissolved oxygen, depth, pH, and turbidity.

Meteorological data include air temperature, relative humidity, barometric pressure, wind speed, wind direction, precipitation, and solar radiation. Nutrient data include orthophosphate, ammonium, nitrite, nitrate, nitrite+nitrate and chlorophyll. The NERRS Centralized Data Management Office (CDMO) provides technical support to monitoring programs in each of the 26 NERRS estuaries, and also provides access to data from these programs to researchers and anyone else who is interested in this information.

Your assignment is to retrieve data from the CDMO database for a specific estuary, and analyze these data to make inferences about some of the processes that affect environmental conditions in this estuary.

The easiest way to do this analysis is to import the data into a spreadsheet program that will allow you to sort, summarize, and graph them. Here’s how to retrieve SWMP data and import them into Microsoft Excel® using the ACE Basin estuary as an example:

  1. Open the CDMO Home page at http://cdmo.baruch.sc.edu/. Click on "Get Data" on the left side of the page, then click on “Search Data.” A map will appear showing the Estuarine Research Reserves for which data are available. Click “Map” or “Hybrid” to display place names and state outlines. Click on the red dot on the South Carolina coast between Charleston and Savannah, or click the link to "ACE Basin, SC" on the list found on the right side of the page. A new window will appear that includes a satellite view of the reserve area showing the locations of sampling stations, the types of data collected at each station, and links to each station.

  2. Click on sampling station link for “3. Mosquito Creek,” then on “Water Data” in the pop-up window that appears. Click on “Export Data.” A new window will appear with directions for exporting data. Be sure “ACE Basin, SC: acemcwq - Mosquito Creek” is highlighted, select “2002” in the “Range” window, and click on the “Export data” button.

  3. You will see a new page titled “ Data/Metadata Download” and a messaging stating the the files are being generated. When this process is complete, another page will appear with a user information form. Fill out the form, including the email address to which the data file should be sent. Click “Submit.” A new page will appear stating that downloading instructions have been sent to the email address you provided, that a link to the exported data will be provided in those instructions, and you should  click on the link to download your data. Check your email for these instructions and click on the link. A compressed (“zip”) file will download to your computer.

    Unzip the file (either by clicking on the file icon or by using an “unstuffing” utility. You should now have a folder containing five files. Open the file named  “acemcwq01012002-01012003.csv” in a spreadsheet program such as Microsoft Excel® to simplify graphing and manipulating the data. To open the file in Microsoft Excel®:

    • Launch Microsoft Excel® and select “Open” from the “File” menu. Select “acemcwq01012002-01012003.csv” and click “Open” (if the file name is dimmed, select “All documents” in the “Enable” window). You should now have a spreadsheet containing 20 columns (A through T) and 3,721 rows with titles of each column in row 1. If a column contains “#” symbols, increase the width of that column until data appear.

    • Select column B (“TimeDateStamp”). Under the “Format” menu select “Cells.” Click on the “Number” tab, and select “Date” in the window next to “Category” then choose “3/14/01 13:30” in the “Type:” window. Click “OK.”

  4. Prepare data summary graphs for temperature, salinity, dissolved oxygen (mg/L), and depth as follows:

    1. Highlight the cells in columns E, I, M, and O (temperature, salinity, dissolved oxygen (mg/L), and depth) for the interval November 8 – 18, 2002 (rows 1130 – 1657).

    2. b. Click on the Chart Wizard icon. Select “Line” under “Chart type” and the upper left icon under “Chart subtype.” Click “Next.”

    3. Be sure the button next to “Columns” is selected under “Series in.” Click the “Series” button at the top of the window. Notice that the four data sets are named, “Series 1,” “Series 2,” etc. You can replace these names by highlighting the name in the lefthand box, then typing a new name in the “Name:” box. Replace “Series 1” with “Temperature”. Replace “Series 2” with “Salinity”. Replace “Series 3” with “Dissolved Oxygen”. Replace “Series 4” with “Depth”. Set the X-axis labels by typing in the reference for the “TimeDateStamp” cells in the window next to “Category (X) axis labels:” The reference for these cells is:
    4.      =‘acemcwq01012002-01012003.csv’!$B$1130:$B$1657

      Click “Next.”

    5. Click the “Titles” tab. Enter a title for your chart. Enter “Sample Interval (30 minutes)” in the “Category (X) axis:” box and “Temp (°C), Sal (ppt), DO (ppt), Depth (m)” in the “Value (Y) axis:” box. Click the “Axes” tab. Click the button next to “Category”. Click “Next.”

    6. Click the button next to “As new sheet” and enter “Temp, Sal, DO, Depth”. Click “Finish.” You now have a chart that shows variations in temperature, salinity, dissolved oxygen, and depth at the Mosquito Creek monitoring station during the November 8 – 18, 2002 interval.

    7. If you want to print your chart and do not have a color printer, you may want to modify the line patterns and background. To do this, double click on the background area of your chart. The “Format Plot Area” dialogue box will open. Select “No Fill” button for the Fill color. Click “OK.” Now double click on one of the plotted lines on your chart. The “Format Data Series” dialogue box will open. Select the solid line or one of the patterned lines in the window next to “Dashed:” and black in the window next to “Color:” You may also want to select a heavier line in the window next to “Weight.” Click “OK.” Repeat these steps for the other lines on your chart.

  5. Return to the ACE Basin Site Map page. Click on the link for the Bennett’s Point sampling station, then on “Weather Data” in the pop-up window that appears. Click on “Export Data” (near the bottom of the page). A new window will appear with directions for exporting data. Be sure “ACE Basin, SC: acebpmet - Bennett’s Point (Real Time)” is highlighted, select “2002” in the “Range” window, and click on the “Export data” button.
  6. Continue as directed in step 2, above. The information form should contain the same entries that you made before, so you don’t need to enter anything new unless you want the data file to be sent to a different email address. Download and unzip the file as directed above.

    Open the file named “acebpmet01012002-01012003.csv” in Microsoft Excel® as directed above. You should now have a spreadsheet containing 23 columns of weather data from the Bennett’s Point station for the year 2002. If a column contains “#” symbols, increase the width of that column until data appear.

    We need a graph that shows rainfall for the period November 8 – 18, 2002. For this graph, you will use data in column R (“TotPrcp” = total precipitation). Notice that most of the entries in this column are either “0” or “-99”. These entries show that no rain fell during the sampling period. If you try to graph these data with all those “-99”s, the actual rainfall events will be hard to see. So what we need to do is to filter out any entry that is less than “0.” To do this, click on the “More buttons” arrow on the right side of the lower menu bar at the top of the Excel® window. Next click on “AutoFilter” in the popup menu that appears. Next, click on the two arrows that are now visible on the right side of the title box for column R (“TotPrcp”), then select (Custom Filter . . .) from the popup menu. The “Custom AutoFilter” window should appear. Select “is greater than or equal to” in the upper left box, then type “0” in the upper right box. Click “OK.” Now, the spreadsheet should only contain entries where “TotPrcp” is 0 or greater, and you can proceed to construct the graph:

    1. Highlight the cells in column R for the interval November 8 – 18, 2002.

    2. Click on the Chart Wizard icon. Select “Line” under “Chart type” and the upper left icon under “Chart subtype.” Click “Next.”

    3. Be sure the button next to “Columns” is selected under “Series in.” Click the “Series” button at the top of the window. Rename “Series 1” to “Precipitation”. Set the X-axis labels by typing in the reference for the “TimeDateStamp” cells in the window next to “Category (X) axis labels:” The reference for these cells is:
    4.      =‘acebpmet01012002-01012003.csv’!$B$37631:$B$38957

      Click “Next.”

    5. Click the “Titles” tab. Enter a title for your chart. Enter “Sample Interval (30 minutes)” in the “Category (X) axis:” box and “Precipitation” in the “Value (Y) axis:” box. Click the “Axes” tab. Click the button next to “Category”. Click “Next.”

    6. Click the button next to “As new sheet” and enter “Precipitation”. Click “Finish.” You now have a chart that shows variations in rainfall at the Bennett’s Point monitoring station during the November 8 – 18, 2002 interval.

    7. Modify the line patterns and background if necessary, and print the graph.

  7. Repeat Step 2 to obtain a file of water quality data from Mosquito Creek for 2003, and open the data file in your spreadsheet program. Prepare graphs of temperature, salinity, dissolved oxygen, and depth for January 15, 2003; April 15, 2003; July 15, 2003; and October 15, 2003.

  8. Use your graphs for clues to the following questions:

    1. What pattern do you see in variations in water depth? What do you think causes these variations?

    2. What other factors (temperature, salinity, and/or dissolved oxygen) seem to have variations that coincide with variations in water depth? Why do they coincide?

    3. How do the overall values of dissolved oxygen vary at different times of the year? Does there seem to be a relationship between dissolved oxygen levels and temperature, salinity, and/or water depth?

    4. Are there any indications that precipitation affected water depth, temperature, salinity, and/or dissolved oxygen between November 8 - 18, 2002? If so, how do you explain the observed effects?

    5. Organisms living in estuaries are subjected to long- and short-term variations in temperature, salinity, dissolved oxygen, and other important environmental conditions. Based on your charts for January 15, April 15, July 15, and October 15, 2003, what is the maximum daily range of temperature, salinity, and dissolved oxygen experienced by estuarine organisms living in Mosquito Creek? What is the annual range of these factors?

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