![]() |
![]() |
|||
Analysis Techniques: Flood Analysis Tutorial with Daily Data (Log-Perason Type III Distribution)
Download DataView and print this webpage as a pdf file.Step 1: Obtain streamflow data
Step 2: Organize the information in a table.
Step 3: Rank the data from largest discharge to smallest discharge. Add a column for Rank and number each streamflow value from 1 to n (the total number of values in your dataset).
Step 4: Create a column with the log of each max or peak streamflow using the Excel formula {log (Q)} and copy command.
Step 5: Calculate the Average Max Q or Peak Q and the Average of the log (Q)
Step 6: Create a column with the excel formula {(log Q – avg(logQ))^2}
Step 7: Create a column with the excel formula {(log Q – avg(logQ))^3
Step 8: Create a column with the return period (Tr) for each discharge using Excel formula {(n+1)/m}. Where n = the number of values in the dataset and m = the rank.
Step 9: Complete the table with a final column showing the exceedence probability of each discharge using the excel formula {=1/Return Period or 1/Tr} and the copy command.
Step 10: Calculate the Sum for the {(logQ – avg(logQ))^2} and the {(logQ – avg(logQ))^3} columns.
Step 11: Calculate the variance, standard deviation, and skew coefficient as follows:variance = standard deviation = skew coefficient =
Step 12: Calculate k values
Show Me
Step 13: Using the general equation, list the discharges associated with each recurrence intervalgeneral equation =
Step 14: Create table of Discharge values found using the log – Pearson analysis
Step 15: Create Plot
|
This website was developed by Oregon State University's Civil, Construction, and Environmental Engineering Department with support from the state water institutes program of the U.S. Geological Survey. | |
Copyright © 2002-2005 Oregon State University -
Web Disclaimer Web Address: http://water.oregonstate.edu/streamflow/ Send Comments to: Peter Klingeman |