Comparative assessment of conventional and calibrated curve number models in flood and runoff estimation (Studied Catchments: Galikesh, Tamer, Nodeh, Kechik and Vatana in Golestan province)

Authors

1 MSc. of Water Resources Engineering, Faculty of Water and Soil Engineering, Gorgan University of Agricultural Sciences and Natural Resources

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

3 Associate Professor, Department of Water Science and Engineering, Gorgan University of Agricultural Sciences and Natural Resources

4 Soil & Water Dep. university of Grgan natural resources & Agricultural science, gorgan,Iran;

Abstract

 The conventional curve number (SCS-CNT) model, which is based on the application of the proposed table by US Soil Conservation Service (SCS), is widely used by researchers and engineers. However, characteristics of the study catchment may be completely different from the conditions for the extraction of SCS-CNT model. Calibrated curve number model (SCS-CNC) can be a solution in this problem. In this study, 37 rainfall-runoff events were investigated in Tamer, Galikesh, Nodeh, Vatna and Kechik catchments (with area 1527, 401.45, 789.65, 10.77 and 36 square kilometers respectively) located in Golestan province, Iran, and 14 events were used for SCS-CNT and SCS-CNC models’ comparison. Results were compared based on root mean square error (RMSE), Nash-Sutcliffe (NSE) and peak discharge estimation error (PEP). The RMSE and NSE criteria in 79% and PEP criterion in 86% of the cases confirmed improvement of the hydrograph and peak discharge estimations in SCS-CNC compared to SCS-CNT model. The SCS-CNC and SCS-CNT models resulted in peak discharge underestimation in 8 and 7 events and overestimation in 6 and 7 events, respectively. Results indicated that application of the calibrated curve number model improves the simulation results in all five studied catchments.

Keywords

References

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Iranian Journal of Irrigation & Drainage
Volume 12, Issue 1 - Serial Number 67
May and June 2018
Pages 143-152

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