Assessment of VIC model in surface runoff simulation and flow routing Case study: Lake Urmia west watersheds

Document Type : Research Article

Authors

1 Ph.D. urban climatology shahid Beheshti University of Tehran

2 Professor of Natural Geography, Shahid Beheshti University

3 Department of Water Engineering, Faculty of Agriculture, Urmia University, Urmia, Iran

Abstract

One of the semi-distributed models that has been considered by researchers in the last decade is the hydrological model of variable infiltration capacity (VIC). The study aim was evaluating the efficiency of VIC model in simulated runoff and flow of rivers in Urmia city overlooking Lake Urmia, including Nazlochyi, Rozeh Chay, Shahrchay and Barandozchay. ERA5 meteorological data was used to achieve this goal. The indices used in the present study to validate the rainfall input data include (R2, TRMSE, NSE). The results of satellite meteorological data surveys with observational data have acceptable results. More precisely, the probability index of POD detection in all stations in the region is above %80. The Khoy synoptic station in the north of the study area is more than %95. Also, the correlation between maximum and minimum temperature data is above %93. After forming the hydrological and mathematical model of the area, the calibration of the observed runoff of the sub-basins with the runoff simulated by the VIC model was investigated. The surveying showed that in all major rivers in the region, the NSE value was above %72 and the R2 coefficient of all basins was more than %64. Also, for validation between observational and simulated data, the maximum flow rate (2010-2000) was used and the results showed that the model was more accurate in simulating maximum runoff, so that the NSE coefficient in the Nazlochay basin was %80 and the coefficient R2 was %78 for daily observational data.

Keywords

References

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Iranian journal of Ecohydrology
Volume 9, Issue 1
April 2022
Pages 243-257

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History

  • Receive Date: 23 October 2021
  • Revise Date: 04 February 2022
  • Accept Date: 11 March 2022

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