Improvement of streamflow simulation for gauge site of hydrological model

• Main Authors: Jeevaragagam, Ponselvi, Simonovic, Slobodan P.
• Format: Article
• Language: English
• Published: 2013
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.utm.my/id/eprint/40356/1/PonselviJeevaragagam2013_ImprovementofStreamflowSimulationforGauged.pdf; http://eprints.utm.my/id/eprint/40356/; http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:125977
• Institution: Universiti Teknologi Malaysia

The paper presents an improvement procedure for streamflow simulation at gauged site of a semi-distributed river basin model. In addition to streamflow and precipitation, meteorological observations that are not employed in the HEC-HMS model calibration are used as inputs in the procedure. Some of the available meteorological variables may be of limited values in calibrating a large range of streamflow hydrographs for obtaining the optimum state variables and parameters of a river basin model. This study presents the integration of the Bayesian regularization neural network with the HEC-HMS model to provide most accurate streamflow simulations at gauged site, for a wide range of streamflow hydrographs pertinent to the hydrometeorological conditions. The artificial neural network is capable of generating a good generalization with given hydrometeorological patterns.