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An empirical-stochastic, event-based program for simulating inflow from a tributary network: Framework and application to the Sacramento River basin, California

Singer, Michael Bliss and Dunne, Thomas 2004. An empirical-stochastic, event-based program for simulating inflow from a tributary network: Framework and application to the Sacramento River basin, California. Water Resources Research 40 (7) 10.1029/2003WR002725

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Abstract

A stochastic streamflow program was developed to simulate inflow to a large river from a network of gauged tributaries. The program uses historical streamflow data from major tributary gauges near their confluence with the main stem and combines them stochastically to represent spatial and temporal patterns in flood events. It incorporates seasonality, event basis, and correlation in flood occurrence and flood peak magnitude between basins. The program produces synchronous tributary inflow hydrographs, which when combined and routed, reproduce observed main stem hydrograph characteristics, including peak, volume, shape, duration, and timing. Verification of the program is demonstrated using daily streamflow data from primary tributary and main stem gauges in the Sacramento River basin, California. The program is applied to simulating flow at ungauged main stem locations, assessing risk in fluvial systems, and detecting bed level change.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Earth and Ocean Sciences
Publisher: American Geophysical Union (AGU)
ISSN: 0043-1397
Date of Acceptance: 20 May 2004
Last Modified: 01 Sep 2017 11:09
URI: http://orca.cf.ac.uk/id/eprint/104167

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