A pilot study for an enhanced algal spatial pattern prediction using RS images

Hong Li*, Mijail Arias, Anouk Blauw, Steef Peters, Arthur E. Mynett

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)

Abstract

Accurate and reliable flow forecasting form an important basis for efficient real-time river management, including flood control, flood warning and so on. In order to improve the accuracy of flow forecasting, gain matrix of Kalman filter was applied to real-time correction of hydraulic model for spatial distributing the system deviation (called expected value of system noise in Kalman filter). That means Kalman gain matrix is used to distribute model system deviation from measurement cross sections to the entire state of the river system. State functions of Kalman filter were set up based on discretization and linearization Saint-Venant equations by adopting four-point linear implicit form, and the spatial distribution system deviation method (SDM) was used for real-time correction. The calculation of flood forecasting for river section from Cuntan to Fengjie of Yangtze River verifies that SDM is useful in promoting the accuracy of real-time flood forecasting.

Original languageEnglish
Title of host publicationAdvances in Water Resources and Hydraulic Engineering - Proceedings of 16th IAHR-APD Congress and 3rd Symposium of IAHR-ISHS
PublisherSpringer
Pages738-743
Number of pages6
ISBN (Print)9783540894643
Publication statusPublished - 1 Jan 2009
Event16th Congress of Asia and Pacific Division of International Association of Hydraulic Engineering and Research, APD 2008 and the 3rd IAHR International Symposium on Hydraulic Structures, ISHS 2008 - Nanjing, China
Duration: 20 Oct 200823 Oct 2008

Conference

Conference16th Congress of Asia and Pacific Division of International Association of Hydraulic Engineering and Research, APD 2008 and the 3rd IAHR International Symposium on Hydraulic Structures, ISHS 2008
Country/TerritoryChina
CityNanjing
Period20/10/0823/10/08

Keywords

  • Expected value of system noise
  • Gain matrix
  • Kalman filter
  • Real-time correction

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