Fitting of Time Series Models to Forecast Streamflow and Groundwater Using Simulated Data from Swat
Publication: Journal of Hydrologic Engineering
Volume 13, Issue 7
Abstract
Time series models provide a valuable tool for simulation and forecasting hydrologic variables. However, time series models require fitting long series of records. This study explores the applicability of soil water assessment tool (SWAT), a deterministic hydrologic model, to generate long data series to fit autoregressive and autoregressive moving average models, in order to perform short-term forecasting of monthly streamflow and groundwater table depth in areas that lack long historical records. SWAT performed well in reproducing the statistical structure of the variables making it possible to fit time series models to simulated series. Time series models fitted to SWAT simulated data and to historical records showed a similar but poor performance to forecast monthly streamflow in all watersheds. However, time series fitted to SWAT data for groundwater table depth showed good performance for forecasting this variable with correlation coefficients between 0.58 to 0.70 and Nash-Sutcliffe model efficiencies from 0.22 to 0.46 in the validation period.
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Acknowledgments
The writers are very grateful to Dr. Ramachandra Rao from the Civil Engineering Department, and Dr. Rabi Mohtar from the ABE Department at Purdue University for their wise advice and critical assistance in this research.
References
Arnold, J. G., Srinavasan, R., Muttiah, R. S., and Williams, J. R. (1998). “Large area hydrologic modeling and assessment. Part I: Model development.” J. Am. Water Resour. Assoc., 34(1), 73–89.
Box, G. E., and Jenkins, G. M. (1976). Time series analysis: Forecasting and control, Holden-Day, Oakland, Calif.
Di Luzio, M., Srinavasan, R., and Arnold, J. G. (2001). “ArcView interface for SWAT2000, user’s guide.” Blackland Research Center-Texas Agricultural Experiment Station, Temple, Tex., http://www.brc.tamus.edu/swat/swatdoc.html (Mar. 31, 2002 ).
Haan, C. T. (1982). Statistical methods in hydrology, 3rd Ed., Iowa State University Press, Ames, Iowa.
Haltiner, J. P., and Salas, J. D. (1988). “Short-term forecasting of snowmelt. Runoff using ARMAX models.” Water Resour. Bull., 24(5), 1083–1089.
Hirsch, R. M., Helsel, D. R., Cohn, T. A., and Gilroy, E. J. (1993). “Statistical analysis of hydrologic data.” Handbook of hydrology, D. R. Maidment, ed., McGraw-Hill, New York, 23–26.
Jenkinson, B. J. (1998). “Wet soil monitoring project on two till plains in south and west central Indiana.” MS thesis, Purdue Univ., West Lafayette, Ind.
Knotters, M., and Bierkensr, M. F. P. (2001). “Predicting water table depths in space and time using a regionalized time series model.” Geoderma, 103, 51–77.
Knotters, M., and van Walsum, P. E. V. (1997). “Estimating fluctuation quantities from time series models of water-table depths.” J. Hydrol., 197, 25–46.
Law, A. G. (1974). “Stochastic analysis of groundwater level time series in the western United States.” Hydrology Paper 68, Colorado State Univ., Fort Collins, Colo.
Nash, J. E., and Sutcliffe, J. E. (1970). “River flow forecasting through conceptual models. Part 1: A discussion of principles.” J. Hydrol., 10, 282–290.
Navulur, K. C. S., and Engel, B. A. (1998). “Groundwater vulnerability assessment to non-point source nitrate pollution on a regional scale using GIS.” Trans. ASAE, 41(6), 1671–1678.
Neitsch, S. L., Arnold, J. G., Kiniry, J. R., and Williams, J. R. (2001). “Soil and water assessment tool theoretical documentation version 2000.” Blackland Research Center–Texas Agricultural Experiment Station, Temple, Tex., http://www.brc.tamus.edu/swat/swatdoc.html .
Nicks, A. D. (1974). “Stochastic generation of the occurrence, pattern and location of maximum amount of daily rainfall.” Proc., Symp. Statistical Hydrology, USDA Miscellaneous Publication 1275, U.S. Government Printing Office, Washington, D.C., 154–171.
R Development Core Team. (2004). “R: A language and environment for statistical computing.” R Foundation for Statistical Computing, Vienna, Austria, http://www.R-project.org (Feb. 15, 2005 ).
Rao, A. R., Rao, R. G. S., and Kashyap, R. L. (1975). “Stochastic models for ground water levels.” Water Resources Research Center, Purdue Univ., West Lafayette, Ind.
Richardson, C. W., and Wright, D. A. (1984). WGEN: A model for generating daily weather variables.” ARS-8, U.S. Dept. of Agriculture, Agricultural Research Service.
Salas, J. D. (1992). “Analysis and modeling of hydrologic time series.” Handbook of hydrology, D. R. Maidment, ed., McGraw-Hill, New York, 42–43.
Salas, J. D., Delleur, J. W., Yevjevich, V., and Lane, W. L. (1997). Applied modeling of hydrologic time series, 4th Ed., Water Resources Publications, Fort Collins, Colo.
Sharpley, A. N., and Williams, J. R. (1990). “EPIC-erosion productivity impact calculator. 1: Model documentation.” Tech. Bull. No. 1768, U.S. Dept. of Agriculture, Agricultural Research Service.
Vazquez-Amabile, G. G. (2005). “Hydrologic and non-point source pollution risk analysis on agricultural watersheds.” Ph.D. thesis, Purdue Univ., West Lafayette, Ind.
Vazquez-Amabile, G. G., and Engel, B. A. (2005). “Use of SWAT to compute groundwater table depth and stream flow in Muscatatuck River Watershed.” Trans. ASAE, 48(3), 991–1003.
Wilcox, B. P., Rawls, W. J., Brakensiek, D. L., and Wright, J. R. (1990). “Predicting runoff from rangeland catchments: A comparison of two models.” Water Resour. Res., 26 2401–2410.
Yevjevich, V. (1972). “Structural analysis of hydrologic time series.” Paper No. 56, Colorado State Univ., Fort Collins, Colo.
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© 2008 ASCE.
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Received: Jun 26, 2006
Accepted: Aug 21, 2007
Published online: Jul 1, 2008
Published in print: Jul 2008
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