Ensemble Stream Flow Prediction (ESP) Using Hybrid Rainfall Runoff Model (Case study: Roud Zard Basin)

Document Type : Research Paper

Authors

Abstract

     One of the most important information which is effective in desirable utilization of water resources is the information related to predicting the future available water in the catchment. Considering the existing uncertainty it is of significant importance when streamflow forecasting information is used. The ensemble stream flow prediction (ESP) is one of the methods in considering the forecast uncertainty. The goal of this research is to develop and evaluate monthly ESP for Roud Zard basin in Iran. Two models have been used to produce ESP: A conceptual river flow model based on Tank method (CRFM), and Combining the CRFM model with the adaptive neuro fuzzy inference system (ANFIS) to develop a hybrid model. Following, the Event bias correction method is employed on generated ESP’s and the results of the three predictions have been evaluated. The results show that the precision of base stream flow simulation model had considerable effects in the quality of the ensemble prediction as far as RPS in hybrid model that had higher precision than CRFM model has decreased from 0.56 to 0.38 and the months with suitable prediction (positive skills score) increased from 82 to 115 months and in case of employing bias correction, there will be an increase to 119 months from the total 182 months of simulation period.

Keywords

References

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Irrigation Sciences and Engineering
Volume 40, 1-1
Special Issue
June 2017
Pages 1-12

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History

  • Receive Date: 06 October 2013
  • Revise Date: 07 June 2017
  • Accept Date: 16 September 2015
  • Publish Date: 01 January 1970

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