Kalman Filter in Real-Time Hydrologic Forecasting: A Tutorialby Harold R. Henry, Univ of Alabama, United States,
Abstract: The Kalman filter provides an algorithm by which measured streamflow can be used to update the estimated hydrologic state of the watershed as determined from the application of a hydrologic model. This updated state is then the basis for the computation of an updated streamflow. In order to use the Kalman filter it is necessary that the hydrologic model be expressed in state-space format which is defined herein. It is also necessary that the equations be linearized. To illustrate the Kalman filter relationships, a detailed example of a hypothetical flow from a parking lot is presented. The discussion and hydrographs include consideration of sensitivity of the filter to system and measurement noises. Results from application of the Kalman filter in ARRM, the Alabama Rainfall-Runoff Model, illustrate its use in a practical hydrologic case.
Subject Headings: Hydrology | Filters | Hydrologic models | Kalman filters | Forecasting | Streamflow | Rainfall-runoff relationships | Mathematical models | Hydrographs | North America | Alabama | United States
Services: Buy this book/Buy this article
Return to search