Calculated Series

WRDB Graph is able to calculate new series and add them to the graph. The types of available calculations depend on the type of graph. The new series is generally formatted or calculated based on one or two selected series; calculated data are stored in the .graph file:

Calculation

Graph Type

Description

Constant Value

Time Series,
Longitudinal, Depth & Width Profiles

Based on constant value that you specify

PCode Criteria Limit

Time Series,
Longitudinal, Depth & Width Profiles

For WRDB tables, extracts the Criteria Limit value for the selected series' PCode and plots the constant value.

Moving Average

Time Series

After prompting for the number of periods in the moving average, computes the series; data points are plotted at the center point of the number of periods. Available periods are:

Number of Adjacent Points Averaged

Purpose

24

Hourly Data to Daily Average

168

Hourly Data to Weekly Average

7

Daily Data to Weekly Average

30

Daily Data to Monthly Average

3

Monthly Data to Quarter-year Average

6

Monthly Data to Half-year Average

12

Monthly Data to Annual Average

Please note that the moving average plot is based upon the number of consecutive numbers averaged. A true daily average will be computed from hourly data only if there are no missing data points and the data start at 12:00 a.m. Nevertheless, the moving average plots can be very helpful for screening out the "noise" in the data and help you see underlying trends and relationships.

Daily Averages

Time Series

Calculates average daily values for all data found within each day and plots them at noon.

Sine Curve Fit

Time Series

Uses a non-linear curve fitting tool to fit a sine curve to the observed data. This is most useful when applied to daily, weekly, or monthly average data to discern annual periodicities. When you click this button, a non-linear fit routine is started which determines the sine curve coefficients which best fit the data:

This is the same equation used by Dyar and Alhadeff in Stream-Temperature Characteristics in Georgia, USGS WRI Report 96-4203. The resulting sine curve are thereafter displayed like this:

 

Adjust by Constant Value

Time Series,
Longitudinal, Depth & Width Profiles

Creates a new series by performing an arithmetic calculation on the selected series; you can specify the operator (+,-,*,/) and a constant to be used.

Add Two Series

Time Series,
Longitudinal, Depth & Width Profiles

Presents the Add Selected Series form in which you can select the two series to be added:

Subtract Two Series

Time Series,
Longitudinal, Depth & Width Profiles

See Add Two Series, above.

Linear Fit

Scatter Plot

Fit least-squares linear fit to data in the form y=Ax + B

Power Fit

Scatter Plot

Fit least-squares linear fit to data in the form y=Ax^B

Exponential Fit

Scatter Plot

Fit least-squares linear fit to data in the form y=A Ln(x) + B

Normal Distribution

Probability

Fit normal distribution to observed data.

Log-normal Distribution

Probability

Fit log-normal distribution to observed data.

Log-Pearson III Distribution

Probability

Fit Log-Pearson III distribution to observed data.