Work

Real-time Runoff Forecasting Characteristics of Urban Storage Function Model Using Kalman Filter

Year: 2013

Type: article

Abstract: The Kalman filter (KF) is a mathematical power tool that is used for real-time forecasting. In this paper, we implement KF on Urban Storage Function (USF) model which is a nonlinear lumped model considering urban runoff process. USF model using KF is applied to a virtual catchment where rainfall-runoff characteristics are known. The model parameters are updated with 1-minute river discharge data by KF. The characteristics of real-time forecasting of the model using KF is discussed by comparison with the model using a particle filter. The results show that KF forecasted in a very short computation time with performs comparable to the particle filter.

Source: Journal of Japan Society of Civil Engineers Ser B1 (Hydraulic Engineering)

DOI: 10.2208/jscejhe.69.i_475

Authors: Tadakatsu TAKASAKI, Akira KAWAMURA, Hideo AMAGUCHI, Shigeyuki ISHIHARA

Institutions: Civil Engineering Center Tokyo Metropolitan Government, Tokyo Metropolitan University

Language: English

Topic: Hydrology and Watershed Management Studies

Subfield: Water Science and Technology

Field: Environmental Science

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Clean water and sanitation

Open Access status: diamond

OpenAlex ID: W4234019026

FWCI:

Cites: 1

Cited by: 2

Related to: 10