USGS Data Grapher Tutorial - Quick Overview

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Detailed Description

This is a data graphing utility that allows the user to build graphs of data from selected USGS stations.


Date Taken:

Length: 00:04:40

Location Taken: Portland, OR, US


The Data Grapher is a set of
online tools

that allow users to create customized
graphs and tables of

a whole variety a time-series data that are
served up by

U.S. Geological Survey. When you visit the
USGS Data Grapher site for the Oregon

Water Science Center,

this is the first page you will see. In
order to use the USGS Data

Grapher, you need to become familiar with
the navigation system

at the top. These menus provide you with
access to all of the various programs

that allow you to create customized graphs and tables of your data.

If you've never been here before, check
out the options under the Help menu.

Under the Help menu, you can view how-to

that are very useful, and you can also
look at many of the types of graphs that

can be created by the Data Grapher system.

It's a great place to start. If you want
to make time-series graphs, there are

many different ways to do so,

comparing data amongst various sites,
looking at repeating patterns, or

visualizing things with color maps.

You can plot one parameter versus
another with different types of

XY graphs. You can make polar graphs of

wind speed and wind direction data, or
make customized data tables.

Let's start by looking at a time-series

from one site. In this example,

let's take a look at some pH data from
the Clackamas River

near the mouth that river at Oregon City. So,  we've chosen the Clackamas River

Basin sites in step 1 and we've chosen a

at Oregon City in step 2, showing that we
have many parameters

that have been measured at this site.
We've decided to plot a time-series

graph and we're going plot pH

and discharge, where we've chosen to

plot the daily maximum pH instead of all
of the hourly data.

And were going to make this plot for all available data in the year of 2010.

So let's just hit "Make a Graph." The results,
then, show you

some of the inputs that you asked for and the

you have just created. Now this is a time-series graph, so the x-axis represents

an entire year, because that's what we
asked for, for 2010,

and plotted in blue is the daily maximum pH on the left axis,

and in red is the discharge in the river,
or streamflow,

on the right axis. You can see that
the pH values

in mid-summer can reach relatively high
values near 9,

and that the patterns in

pH decrease when the streamflow goes up.

This is because the conditions that
create the higher pHs are when

algae is growing, and the algae are not
able to grow as much

when you have a high flow event.

Another way to visualize those patterns
in the pH data

in the Clackamas River is to use a color.
This color map can be accessed from the

time-series dropdown,

Color Map option. Here we've chosen again
the Clackamas River at Oregon City site.

We've chosen pH. We're going to plot the
unmodified data for all of 2010,

with the date on the x-axis and hour of day
on the y-axis.

You can choose many different color
scales. We're going to choose a relatively


blue to red color scale on a linear axis,

and we choose "Make Color Map." The color
map that results

shows some interesting patterns that we
saw in the time series graph.

Remember that we had higher pH values, as
represented by the redder colors -

we had higher pH values at particular times
in the spring and summer,

and we had a lower pH values for a time
between those

peaks when the discharge was higher. This
spot also shows you

when the algae are most active and what
time of day.

So, this particular plot easily shows us

that the algae are most active creating
higher pH values

in the afternoon only in the afternoon,
and that this pattern is easily broken


by the higher discharge event. So, to sum
things up,

the Data Grapher is a set of 
online programs that allow anyone

to explore and visualize USGS time-series datasets,

make custom graphs and tables, and
compare datasets among sites and years.

We think it's a great tool and we hope
you enjoy using it!