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.
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Information & Authors
Information
Published In
Journal of Hydrologic Engineering
Volume 13 • Issue 7 • July 2008
Pages: 554 - 562
Copyright
© 2008 ASCE.
History
Received: Jun 26, 2006
Accepted: Aug 21, 2007
Published online: Jul 1, 2008
Published in print: Jul 2008
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