| Main Title |
Stochastic Analysis of Monthly Flow Data Application to Lower Ohio River Tributaries. |
| Author |
McKercha, A. I. ;
Delleu, J. W. ;
|
| CORP Author |
Purdue Univ., Lafayette, Ind. Water Resources Research Center. |
| Year Published |
1972 |
| Report Number |
TR-26; DI-14-31-0001-3585; OWRR-B-036-IND; 04063,; B-036-IND(2) |
| Stock Number |
PB-214 115 |
| Additional Subjects |
( Hydrology ;
Stochastic processes) ;
( Surface water runoff ;
Forecasting) ;
Mathematical models ;
Watersheds ;
Flow rate ;
Regression analysis ;
Time series analysis ;
Reviews ;
Computer programs ;
FORTRAN ;
Rivers ;
Indiana ;
Illinois ;
Kentucky ;
Ohio ;
Synthetic hydrology ;
Ohio River
|
| Holdings |
| Library |
Call Number |
Additional Info |
Location |
Last
Modified |
Checkout
Status |
| NTIS |
PB-214 115 |
Some EPA libraries have a fiche copy filed under the call number shown. |
|
07/26/2022 |
|
| Collation |
116p |
| Abstract |
Past works in the stochastic analysis of runoff data are briefly reviewed. A summary of a recent technique for developing stochastic models for forecasting seasonal time-series is given. This technique, which applies a combination of autoregression and moving-average processes to represent differenced series which minimizes the uncertainties in the model by minimizing the number of parameters that need to be estimated is called the autoregression integrated moving-average (ARIMA) method. This method is applied to monthly flow data of 14 watersheds contributing to the Ohio River within the states of Indiana, Illinois, Kentucky and Ohio. Two models of monthly flow data were developed. (Author) |
