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Mapping Coastal Vulnerability to Sea-Level Rise at Point Reyes National Seashore

Len VacherDepartment of Geology, University of South Florida, Tampa, FL 33620© 2010 University of South Florida Libraries. All rights reserved.

SSACgnp.GB450.LV1.8

Core Quantitative Literacy TopicsRank scales

Supporting Quantitative Literacy TopicsAverageSquare root

Core Geoscience SubjectGlobal Warming: Sea-Level Rise

This material is based upon work supported by the National Science Foundation under Grant Number NSF DUE-0836566.

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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Getting started

After completing this module you should be able to:

•Know that sea level is rising, it’s rate, and why. •Describe what controls how a shoreline responds to sea-level rise.•Describe how the U.S. Geological Survey’s coastal vulnerability index is calculated.•Know what a minute is in terms of longitude and latitude.•Describe how a quantitative ranking scheme is set up and carried out.

You should also know where Point Reyes National Seashore is.

California

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The setting – Point Reyes National Seashore

Point Reyes National Seashore is a short drive north along the San Andreas Fault from San Francisco Bay. Along the coast are high, rocky headlands and broad, sandy beaches Inland are forested, shrubby and grassy hills and valleys. Streams cascade down to feed quiet estuaries. At the lighthouse, visitors often see fog and seabirds. On clear days they see sea lions and, depending on the season, migrating humpback whales. Inland there are elk, bobcats and scattered cattle ranches.

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Sea level is rising globally, and in California

At San Diego, the rate is 2.06 0.20 mm/yr (101 years of record). At Los Angeles it is 0.83 0.27 mm/yr (84 years). At San Francisco, it is 2.01 0.21 (110 years).

Ocean temperatures are rising. That process alone would make sea level rise, because water expands with increasing temperature. Glaciers and ice caps are melting, and so there is more water in the ocean basins. That process too should make sea level rise. So it is not surprising that sea level is indeed rising globally. The global rate is about 1.8 mm/yr (18 cm in the past 100 years).

Looks like the land at the survey station rose a bit with the 1906 earthquake.

Here’s the trend at Crescent City. What do you suppose is going on there?

Source: Tides and Currents Website of the Center for Operational Oceanographic Products and Services (CO-OPS)

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Relative sea level is rising at Point Reyes, National Seashore

The graphs on the preceding slide are from four of the 16 stations in the CO-OPS data base.

For the complete table from which the one on this slide was extracted.

For national, regional and global maps.

For information about CO-OPS’s National Water Level Observation Network (NWLON).

For a report by the Pacific Institute on the impact to California’s coast of a 1.4-m sea-level rise.

With the sole exception of Crescent City, relative sea level is rising at all of them. Note, we are saying relative sea level now. Why?

Relative sea level is rising at Point Reyes NS too.

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The problem

According to the US Geological Survey’s report, Coastal Vulnerability Assessment of Point Reyes National Seashore (PORE) to Sea-Level Rise by Pendleton, Thieler and Williams, the effect of sea-level change on a coastline depends in part on three geological variables. The first is geomorphology, which accounts for the coastline’s relative resistance to erosion. The second is the historic rate of sea-level change, which speaks to the coastline’s long-term trend of erosion vs. accretion. The third is coastal slope, which affects susceptibility to flooding.

In addition to the three geologic variables, the report continues, there are three variables relating to physical oceanographic processes: the height of the waves, the rate of sea-level rise, and the tide range. These three processes contribute to the potential and frequency of inundation.

These geologic variables and physical processes change dramatically from place to place along PORE’s shoreline. Consequently, we can expect some places to be more vulnerable than others to physical changes brought about by rising sea level. Taking all six variables into account, what parts of the shoreline are most vulnerable? Which are least vulnerable?

We will use the method described by Pendleton et al. in their USGS report to find out.

Compared to the rest of the Point Reyes shoreline, how vulnerable is the point where the lighthouse is?

Strategy

Divide the shoreline into squares, each covering one minute of latitude and one minute of longitude. Each square is about 1.5 km on a side.

Score each of the one-minute squares from 1 (least vulnerable) to 5 (most vulnerable) on each of six variables.

Original map

Calculate a final score for each square by aggregating the six single-variable scores in some way.

What is the north-south distance in minutes of latitude from the northenmost to southernmost square? In km? What is the west-east distance in minutes of longitude from the westernmost to easternmost square? In km? 7

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Laying out the grid

Here is a spreadsheet version of the USGS map of one-minute squares on the preceding slide. The shoreline crosses a piece of each cell as it extends from cell number 1 in Cell H8 to cell number 64 in Cell T23.

The 64 cells are listed in Column V. “Count” refers to the number in which the cell is encountered if one traveled counter-clockwise around the shoreline from H8 to T23. The corresponding addresses are given in Column W (only the first 24 are shown in this view).

Imagine flying in a helicopter close to shore and 500 ft above the water along the entire coast of California, taking photographs of the coastline along the way. Such a collection of photos is actually available online thanks to the California Coastal Records Project. Visit the site, click on Point Reyes Lighthouse (which is in Cell 33 of this grid), and explore the coastline to familiarize yourself with it from Cell H8 to Cell T23. Notice the location of the helicopter when you move from image to image.

From the California Coastal Records Project Web site

The variables

The five-point scale is color-coded with red (hot) at the very high vulnerability extreme and blue (cold) at the very low vulnerability extreme.

For the geomorphology variable, low coastal landforms such as barrier beaches and mudflats are rated red, and rocky cliffed coasts are rated blue. For historical shoreline change, strongly eroding beaches (negative accretion) are red, and strongly accreting shorelines are blue. For the third variable, low slopes are red, and steep slopes are blue.

The three oceanographic process variables are rated according to their numerical values as listed in this table from the USGS report. High rates of relative sea-level change and large wave heights rate as red, and high tide ranges rate as blue.

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Getting started: the active grid of cells

Click on the icon to open the workbook containing this spreadsheet (it’s on the tab, “setting up grid”). Immediately save the file. You will be doing a variety of things with the spreadsheets in this workbook. (Only the first 25 rows of this spreadsheet are shown here.)

First, pick a cell in Column X and change the number from the 1 that is there now to 5. The corresponding cell on the map will change from grey to red.

Your active grid uses conditional formatting. Each of the map cells refers to the corresponding cell in Column X and is coded so that it turns red if the X cell is 5 (indicating very high vulnerability), orange for 4 (high), and yellow for 3 (moderate). The map cell remains grey (default) for any other number, (including 2 and 1 for low and very low vulnerability, respectively).

In case you would like to make a map like this, we describe how we did this one in an Endnote. Googling “conditional formatting” finds a lot more good information.

Point Reyes Sea Level Student

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Getting started: the data

Now select the tab on your workbook labeled “Data table.” Here are the first 18 rows.

This spreadsheet shows how the USGS study rated each of the one-minute square areas on a scale of 1 to 5 for each of the six variables (Columns C through H).

For example, the first one-minute area (located at H8) is rated low vulnerability for geomorphology (C), moderate for historical shoreline change (D), low for slope (E), very low for sea-level change (F), very low for wave height (G), and high for tide range (H).

Return to Slide 19

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Getting your map ready to map the scores

Now select the tab on your workbook labeled “Grid plus data.” Here are the first 25 rows.

This spreadsheet combines the spreadsheets of the previous two slides. Columns Y – AD give the data again. This spreadsheet is the one you are going to work with to map the scores of the six variables.

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Mapping the geomorphology variable

With your spreadsheet of the previous slide: In Cell X2 enter =Y2. Then copy the formula in Cell X2 down Column X (last row is 65).

Here is the map your spreadsheet should show for the geomorphology variable.

The USGS map

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Mapping the slope variable

Now in Cell X2 enter =AA2 and copy the formula down through Column X.

Here is your map for the slope variable.

The USGS map

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Mapping the wave height variable

Now in Cell X2 enter =AC2 and copy that formula down through Column X.

Here is your map for the wave height variable.

The USGS map

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Mapping the other three variables

You can do the same for the other three variables: historical erosion/accretion; rate of sea-level change, and tidal range.

Here are those three maps.

None of those variables differ from place to place. None of them will contribute to the place-to-place variation of the final vulnerability grade.

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Mapping the average

Add column AE to your spreadsheet and title it Average. In Cell AE2, enter = AVERAGE(Y2:AD2) , center it, and format it to one decimal place. Copy the equation down the column.

Now we can average the ratings for each cell and map them.

Then, in Cell X2 enter =ROUND(AE2,0) (which means to round the value in Cell AE2 to zero decimal places), and copy the equation down the column.

Here is what you should get.

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Ranking the areas

Add column AF to your spreadsheet and title it Rank (avg). In Cell AF2, enter =RANK(AE2,AE$2:AE$65,0).This equation finds the rank of Cell AE2 within the block AE2:AE65 by ranking in descending order (0); any number other than zero means ascending order.

We can also rank the cells from most vulnerable to least vulnerable.

Then center the result and copy the equation down the column. Finally, use Column X to retrieve the information in Column AF as you did before.

We turned off the conditional formatting and colored the cells individually (otherwise all the cells would be grey except for the 5s, which would be red).

Here is what you should get for the numbers. The cells are colored to organize them into four nearly equal-size groups (as close to 16 cells as possible).

This table summarizes the results. Four cells scored highest (rank=1), and eight cells were next highest (rank=5). The highest-vulnerability group (red) includes four ranks (1, 5, 13, 14), containing 15 cells. Eleven cells are tied for 16th place and compose the second group (orange). The third and fourth (lowest vulnerability) groups are colored yellow and green respectively.

R ank Number S ize of G roup

1 4

5 8

13 1

14 2 15

16 11 11

27 9

36 13 22

49 9

58 7 16

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The Coastal Vulnerability Index

The USGS Report used a different method to aggregate the scores. Instead of the average of the six scores, they used the square root of the product of the six scores; in other words for each cell they multiplied the six scores together and then took the square root. They call this the Coastal Vulnerability Index (CVI).

Add Column I to your spreadsheet from Slide 11, label it “CVI” and calculate the CVI for each cell. One way is to use an equation of the form =SQRT(PRODUCT (C2:H2))

Add Column J and label it “Rank CVI.” Then determine the rank of each cell’s CVI (use a formula comparable to what you used in Column AF of the spreadsheet ranking the averages). Compare the two ranks. It might be helpful to reproduce Columns AE and AF of the previous spreadsheet in Columns K and L in this one and subtract Column L from Column J to spot the differences.

One thing that you can conclude from this is that the results of a ranking depend on the method used to aggregate the scores. This concept is likely familiar to you from your experiences with calculating a final score for a course grade.

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End-of-module assignment (p. 1 of 2)

1. Find these images in the California Coastal Records Project database, look at the position of the helicopter, find the location of the coast on your maps, and report the ratings of the six variables and the CVI for each of the six locations.

Image 200505138: Tomales Point, the northernmost point in the Park and the point that separates the Pacific Ocean from Tomales Bay.

Image 200505230: Abbot’s Lagoon, which provides critical nesting habitat for Western Snowy Plovers, one of the Threatened Species that use the Park.

Image 200505323: Pt. Reyes Lighthouse and Lighthouse Rock, perhaps the best-known features found in the Park.

Image 200505335: Sea Lion Overlook, where sea lions haul out and congregate on the rocks and rocky shorelines.

Image 200505421: Limantour Spit and Estero de Limantour, a beach-estuary complex maintained by longshore drift of sand in Drake’s Bay.

Image 200808737: Wildcat Campground, one of two beachfront campsites available for public use in the Park.

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End-of-module assignment (p. 2 of 2)

2. While the results of a ranking system may depend on the method of calculation, the differences may or may not affect conclusions. If the conclusions are affected, one can say that they are sensitive to the method of calculation. If they are not affected, one says they are robust. Look at the map of the CVI produced by the USGS; it was created in much the same way that we did ours for the average, namely, the top quartile of CVI scores was colored red; the second quartile, orange; the third, yellow; and the fourth, green. Would you say the map is sensitive or robust with respect to the calculation. Then look at the conclusions that the NPS drew from the study. Are those conclusions sensitive or robust?

3. Why should the CVI differ from the average? Consider this: if you start with six scores of 3 each, the average is 3 and the CVI is 27. If you change one of the scores to 4 and another to 2, the average is unaffected, as is the case also if you change one of the scores to 5 and one to 1, or two to 2. How do the CVIs change? Does the CVI bias toward high scores, or low ones? Put it this way: which aggregation method would you prefer for final grades in this course?

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Step 1. Laid out Columns V, W, and X, using the map in Slide 7 to determine the order of cell addresses in Column X.

Step 2 (the most tedious step). Referred the cells of the map one-by-one to the corresponding value in Column X. For example, the equation in Cell E7 is = X20.

Step 3. Colored all the cells in the block from B2 and T23 grey and then did the conditional formatting of that block as follows (Excel 2007):

a. highlighted the block of cells.

b. clicked on “Conditional Formatting,” then “Highlight Cell Rules,” then “Equal to.”

c. on the prompt box, typed 5, then clicked the drop down, selected “Custom Format,” clicked on the red square, and clicked “OK,” and “OK” again when the prompt box reappeared.

d. with the block still highlighted, clicked on “Conditional Formatting” again and repeated all the steps, this time for 4 and orange.

e. with the block still highlighted, clicked on “Conditional Formatting” a third time and repeated for 3 and yellow.

Step 4. We cleared the grey color from the cells without numbers (i.e., cells that are not in the shoreline roster of Columns V, W, and X) and removed the conditional formatting from those cells, as follows:

a. highlighted selected cells to remove conditional formatting

b. clicked on “Conditional Formatting,” then “Clear Rules.” then “Clear Rules for Selected Cells.”

Return to Slide 10

Endnote