An Assessment of Time Series and Autoregressive Artificial Neural Network Models, Support Vector Machine and Gene Expression Programming Models Performance in Monthly River Flow Simulation (Case Study: Kherkherechi River Basin)

Document Type : Research Paper


1 M.Sc. of Water Resources Engineering, Faculty of Agriculture, University of Tabriz.

2 Ph.D. Student of Water Resources Engineering, Faculty of Agriculture, University of Tabriz.

3 Associate Professor, Water Engineering Department, Faculty of Agriculture, University of Tabriz.


Selecting a model that simulate the runoff with high accuracy and less error, can be helpful in favorable management of water resources plans and increasing the performance of these plans. Also, increasing the accuracy of runoff simulation in the basins with no meteorological data, is of great significance in efficient management of water resources in these basins.


Main Subjects

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Volume 40, Issue 4
February 2018
Pages 91-107
  • Receive Date: 20 February 2016
  • Revise Date: 02 May 2016
  • Accept Date: 04 July 2016
  • Publish Date: 21 January 2018