Investigation of effect of basin’s physiographic and climatic parameters in seasonal river flow simulation

Document Type : Research Article


1 M.Sc. Graduate, Dept. of Water Resources Engineering, Gorgan University of Agricultural Sciences and Natural Resource

2 Deptartment of Water Engineering, Gorgan University of Agricultural Sciences and Natural Resources


Physiographic characteristics and climatic conditions are factors which contributing to river flow regime and understanding of relations between these factors and river flow in a basin result in its application for the ungauged sub-basins river flow prediction. In this research the relation between physiographic and climatic parameters of Golestan province and rivers flow were examined by application of M5 regression tree model, k-nearest neighbors (KNN) model and multiple linear model (MLR). Daily recorded data for 28 years (1984-2011) including rainfall, temperature and river flow, belonging to hydrometry and meteorological stations of 39 sub-basins were used to extract seasonal series. The average of R and RMSE criteria in different seasons were 0.768 and 0.800 for M5 model, 0.885 and 0.501 for KNN model and 0.693 and 1.205 for MLR model which revealed better results for KNN model. In addition, according to R and RMSE, the accuracy of modeling results in different seasons were respectively as winter, autumn, spring and summer. In other words, the results of predicted river flows in the wet seasons were more accurate than dry seasons. Moreover, the MBE criterion indicated that the KNN model led to underestimation for spring and winter and overestimation for summer and autumn, M5 model led to underestimation in spring and overestimation in other seasons and MLR model had underestimation in winter and overestimation in other seasons.


Main Subjects

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Volume 3, Issue 4
January 2017
Pages 545-555
  • Receive Date: 21 November 2016
  • Revise Date: 13 December 2016
  • Accept Date: 21 December 2016
  • First Publish Date: 21 December 2016
  • Publish Date: 21 December 2016