Sponsor
Portland State University. Department of Civil Engineering
First Advisor
Roy Koch
Date of Publication
11-8-1991
Document Type
Thesis
Degree Name
Master of Science in Civil Engineering (MSCE)
Department
Civil Engineering
Language
English
Subjects
Hydrology -- Mathematical models, Hydrology -- Statistical methods
DOI
10.15760/etd.6464
Physical Description
1 online resource (2, vi, 134 p.)
Abstract
The basic concepts of hydrologic forecasting using the Streamflow Synthesis And Reservoir Regulation Model of the U.S. Army Corps of Engineers, auto-regressive-moving-average time series models (including Greens' functions, inverse functions, auto covariance Functions, and model estimation algorithm), and the Kalman filter (including state space modeling, system uncertainty, and filter algorithm), were explored. A computational experiment was conducted in which the Kalman filter was applied to update Mehama local basin model (Mehama is a 227 sq. miles watershed located on the North Santiam River near Salem, Oregon.), a typical SSARR basin model, to streamflow measurements as they became available in simulated real time. Among the candidate AR and ARMA models, an ARMA(l,l) time series model was selected as the best-fit model to represent the residual of the basin model. It was used to augment the streamflow forecasts created by the local basin model in simulated real time. Despite the limitations imposed by the quality of the moisture input forecast and the design and calibration of the basin model, the experiment shows that the new stochastic methods are effective in significantly improving the flood forecast accuracy of the SSARR model.
Rights
In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
Persistent Identifier
https://archives.pdx.edu/ds/psu/26584
Recommended Citation
Tang, Philip Kwok Fan, "Stochastic Hydrologic Modeling in Real Time Using a Deterministic Model (Streamflow Synthesis and Reservoir Regulation Model), Time Series Model, and Kalman Filter" (1991). Dissertations and Theses. Paper 4580.
https://doi.org/10.15760/etd.6464
Comments
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