Paper Information

Journal:   IRAN-WATER RESOURCES RESEARCH   FALL 2005 , Volume 1 , Number 3; Page(s) 29 To 40.
 
Paper: 

IMPROVED HYDROLOGIC MODEL CALIBRATION BASED ON COUPLED MONTE CAIRO AND BAYESIAN METHODS

 
 
Author(s):  HEYDARI ALI, SAGHAFIAN B., MAKNOUN R.
 
* 
 
Abstract: 

In this paper, uncertainty of a rainfall-runoff (RR) model is analyzed based on combination of Monte Carlo (MC) procedure and Bayesian theory, which is known as GLUE framework. The rainfall-runoff transformation was performed by Mod Clark distributed- conceptual model. In this model, the basin's hydrograph is determined by the superposition of runoff generated by individual cells in a raster-based discretization. Application of MC in uncertainty analysis introduces convenient parameter variation range, which is not adjustable based on new data. In GLUE method, however, Bayesian theory is applied to update prediction limits and distribution of parameter as new data becomes available. Goodness of fit criteria is selected such that higher discharges of hydrograph are given larger weights compared to other parts of the hydrograph. Uncertainty of RR model parameters was assessed in Gharasoo basin, a subbasin of the great Karkheh river basin. The results show that GLUE has a good performance in updating model parameters in comparison with MC method alone.

 
Keyword(s): RAINFALL- RUNOFF MODEL, MONTE CALRO METHOD, BAYESIAN THEORY, UNCERTAINTY
 
References: 
  • ندارد
 
  Persian Abstract Yearly Visit 45
 
Latest on Blog
Enter SID Blog