Sensitivity of the SMA HEC-HMS Model for Continuous Hydrological Modeling in Beheshtabad Basin

Document Type : Research Article

Authors

1 M.Sc Student in Watershed Management, Sharekord University, Shahrkord, Iran

2 Associate professor, Department of Watershed Management, Faculty of Natural Resources and Geosciences, Shahrekord University, Iran

3 Assitant professor, Department of Watershed Management, Faculty of Natural Resources and Geosciences, Shahrekord University, Iran

Abstract

Sensitivity analysis is a common tool to study how changes due to uncertainty in the inputs or parameters affect on the output of the simulating model. The aim of this study is to perform sensitivity analysis and model calibration for the HEC-HMS model with soil moisture accounting (SMA) algorithm. In this research manual and automatic parameter sensitivity analysis was used to calibrate and validate the model in the Beheshtabad Basin. The data (1998 to 2015) was separated into 2 parts, the first 13 years daily data set including discharge, rainfall, temperature and evapotranspiration were used for calibration. While, the second period of 2012 to 2015 was used to test the model validation. The evaluation was based on model efficiency coefficient and root mean square error indexes. The model efficiency coefficient values 0.696 and 0.63 were resulted for both calibration and validation respectively.The root mean square error were found to be 13.2 m3/s and 7 m3/s for corresponding stages.The results of performed sensitivity analysis in both form of automatic and manual have showed the parameters soil storage, tension storage and recession constant have highest sensitivity. This is an indicator for the importance of these factors in continuous modeling in specified catchment.

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References

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Iranian journal of Ecohydrology
Volume 4, Issue 4
January 2018
Pages 1117-1127

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History

  • Receive Date: 25 March 2017
  • Revise Date: 06 July 2017
  • Accept Date: 11 August 2017
  • First Publish Date: 22 December 2017
  • Publish Date: 22 December 2017

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