TECHNICAL NOTES
Aug 1, 1992

Conceptual Basis of Seasonal Streamflow Time Series Models

Publication: Journal of Hydraulic Engineering
Volume 118, Issue 8

Abstract

Conceptual models of watershed processes and stochastic models of precipitation and streamflow processes are often needed in the planning and management of hydraulic systems. A number of such models have been proposed in the literature, and many of them are actually used in current practice. This paper focuses on identification of stochastic models for representing storage and streamflow processes of a natural watershed subject to a stochastic precipitation input. More specifically, a natural watershed is considered in which all inputs, state variables, outputs, and parameters vary with the season. Assuming that the precipitation input is uncorrelated with periodic mean and periodic variance, that the ground-water storage is the only significant storage in the watershed, and under further linear reservoir assumptions, it has been shown that the seasonal ground-water storage is represented by a periodic autoregressive moving average process of order (1,0), i.e., a PARMA(1,0) process, and the seasonal streamflow is a PARMA(1,1) process. If surface storage is considered, in addition to ground-water storage, then for the same periodic uncorrelated precipitation input, the seasonal ground water becomes a PARMA(2,0) process, and the model of seasonal streamflow becomes a PARMA(2,1) process. Furthermore, extensions have been made considering the general case of PARMA(p,q) precipitation inputs.

Get full access to this article

View all available purchase options and get full access to this article.

References

1.
Alley, W. M. (1984). “On the treatment of evapotranspiration, soil moisture accounting, and aquifer recharge in monthly water balance models.” Water Resour. Res., 20(8), 1137–1149.
2.
Bartolini, P., and Salas, J. D. (1985). “Properties of multivariate periodic ARMA(1, 1) models.” Proc. Int. Symp. on Multivariate Analysis in Hydrologic Processes, Colorado State University, Fort Collins, Colo.
3.
Burnash, R. J. C., Ferral, R. L., and McGuire, R. A. (1973). “A generalized streamflow simulation system conceptual modeling for digital computers.” Joint Federal‐State River Forecast Center, National Weather Service, California Dept. of Water Resources.
4.
Box, G. E. P., and Jenkins, G. (1970). Time series analysis, forecasting and control. 1st Ed., Holden‐Day, San Francisco, Calif.
5.
Cline, T. B. (1981). “Selecting seasonal streamflow models.” Water Resour. Res., 17(4), 975–984.
6.
Eagleson, P. S. (1978). “Climate, soil and vegetation, 1, introduction to water balance dynamics.” Water Resour. Res., 14(5), 705–712.
7.
Fiering, M. B. (1967). Streamflow synthesis. Harvard University Press, Cambridge, Mass.
8.
Freeze, R. A. (1980). “A stochastic‐conceptual analysis of rainfall‐runoff processes on a hillslope.” Water Resour. Res., 16(2), 391–408.
9.
Hannan, E. J. (1955) “Test for singularities in Sydney rainfall.” Aust. J. Phys., 8(2), 289–297.
10.
Hipel, K. W., McLeod, A. I., and Lennox, W. C. (1977). “Advances in Box‐Jenkins modeling, 1, model construction.” Water Resour. Res., 13(3), 567–575.
11.
Hirsch, R. M. (1979). “Synthetic hydrology and water supply reliability.” Water Resour. Res., 15(6), 1603–1615.
12.
Johanson, R. C., Imhoff, J. C., Kittle, J. L., Jr., and Donigian, A. S., Jr. (1984). “Hydrological simulation program—Fortran, user's manual for release 8.0.” U.S. Environmental Protection Agency, Athens, Ga.
13.
Klemes, V. (1978). “Physically based stochastic hydrologic analysis.” Advances in hydroscience, V. T. Chow, ed., Academic Press, New York, N.Y., 285–352.
14.
Koch, R. W. (1985). “A stochastic streamflow model based on physical principles.” Water Resour. Res., 21(4), 545–553.
15.
Kuczera, G. (1982). “On the relationship between the reliability of parameter estimates and hydrologic time series data used in calibration.” Water Resour. Res., 18(1), 146–154.
16.
Lettenmaier, D. P., and Burges, S. J. (1979). “Operational assesment of hydrologic models of long‐term persistence.” Water Resour. Res., 13(1), 113–124.
17.
Matalas, N. C. (1967). “Mathematical assessment of synthetic hydrology.” Water Resour. Res., 3(4), 937–945.
18.
McKerchar, A. I. M., and Delleur, J. W. (1974). “Application of seasonal parametric linear stochastic models to monthly flow data.” Water Resour. Res., 10(2), 246–255.
19.
McLeod, A. I., and Hipel, K. W. (1978). “Developments in monthly autoregressive modeling.” Tech. Rep. 45‐XM‐011178, Dept. of Systems Design Engrg., University of Waterloo, Ontario, Canada.
20.
Moss, M. E., and Bryson, M. C. (1974). “Autocorrelation structure of monthly streamflows.” Water Resour. Res., 10(4), 737–744.
21.
Obeysekera, J. T. B., and Salas, J. D. (1986). “Modeling of aggregated hydrologic time series.” J. Hydro., 86, 197–219.
22.
O'Connell, E. (1971). “A simple stochastic modeling of Hurst's law.” Int. Symp. On Mathematical Models in Hydrology, IAHS Press, Wallingford, U.K., 327–358.
23.
Rao, A. R., Kashyap, R. L., and Mao, L. (1982). “Optimal choice of type and order of river flow time series models.” Water Resour. Res., 18(4), 1097–1109.
24.
Salas, J. D., Delleur, J. W., Yevjevich, V., and Lane, W. L. (1980). Applied modeling of hydrologic time series. 1st Ed., Water Resources Publications, Littleton, Colo.
25.
Salas, J. D., Obeysekera, J. T. B., and Smith, R. A. (1981). “Identification of streamflow stochastic models.” J. Hydr. Div., ASCE, 107(7), 853–866.
26.
Spolia, S. K., and Chander, S. (1974). “Modeling of surface runoff systems by an ARMA model.” J. Hydro., 22, 317–332.
27.
Sorooshian, S., and Dracup, J. A. (1980). “Stochastic parameter estimation procedures for hyrlrologic rainfall‐runoff models: Correlated and heteroscedastic error cases.” Water Resour. Res., 16(2), 430–442.
28.
Stedinger, J. R., Lettenmaier, D. P., and Vogel, R. M. (1985). “Multisite ARMA(1, 1) and disaggregation models for annual streamflow generation.” Water Resour. Res., 21(4), 497–510.
29.
Stedinger, J. R., and Taylor, M. R. (1982). “Synthetic streamflow generation 1. Model verification and validation.” Water Resour. Res., 18(4), 909–918.
30.
Tao, P. C., and Delleur, J. W. (1976). “Seasonal and nonseasonal ARMA models in hydrology.” J. Hydr. Div., ASCE, 102(10), 1541–1559.
31.
Thomas, H. A., Jr., and Fiering, M. B. (1962). “Mathematical synthesis of streamflow sequences for analysis of river basis by simulation.” The design of water resources system, A. Maas, M. M. Hufschmidt, R. Dorfman, H. A. Thomas, Jr., S. A. Margolin, and G. M. Fair, eds., Harvard University Press, Cambridge, Mass., 459–493.
32.
Thompstone, R. M. (1983). “Topics in hydrological time series modeling,” Ph.D. Thesis, Univ. of Waterloo, Waterloo, Ontario, Canada.
33.
Vecchia, A. V., Obeysekera, J. T. B., Salas, J. D., and Boes, D. C. (1983). “Aggregation and estimation for low‐order periodic ARMA models.” Water Resour. Res., 19(5), 1297–1306.
34.
Yevjevich, V. (1963). “Fluctuations of wet and dry years, part I, research data assembly and mathematical models.” Hydrology Paper 1, Colorado State University, Fort Collins, Colo.

Information & Authors

Information

Published In

Go to Journal of Hydraulic Engineering
Journal of Hydraulic Engineering
Volume 118Issue 8August 1992
Pages: 1186 - 1194

History

Published online: Aug 1, 1992
Published in print: Aug 1992

Permissions

Request permissions for this article.

Authors

Affiliations

Jose D. Salas, Member, ASCE
Prof., Hydro. Sci. and Engrg. Program, Dept. of Civ. Engrg., Colorado State Univ., Fort Collins, CO 80523
J. T. B. Obeysekera
Sr. Water Resour. Engr., South Florida Water Mgmt. Dist., West Palm Beach, FL 33416

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share