Effect of curve number changes on flood hydrograph in a rapid response watershed (Case study: Ardabil Khiavchai Watershed)

Document Type : Research/Original/Regular Article

Authors

1 Associate Professor/Water Engineering Dept., Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili

2 Department of Water Engineering, Faculty of Agriculture and Natural Resources, Water Management Research Center, University of Mohaghegh Ardabili, Ardabil, Iran

3 Associate Professor/Department of Natural Resources, Water Management Research Center, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili

4 Department of Water Engineering, Moghan Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran

5 Natural Resources dept, Faculty of Agriculture and Natural Resources, University Tarbiat Modarres, Tehran, Iran

Abstract

Introduction
Runoff and the rainfall-runoff relationship are one of the most fundamental research topics in hydrology. Due to the increasing trend of flood occurrence and the resulting damages, it is necessary to determine the flood-producing priority areas and prioritize the sub-watersheds in terms of flood control projects and integrated management of watersheds. The primary contributing areas in runoff generation and the affecting factors should be identified in a flood management project. Understanding the flood occurrence potential of watersheds can be useful in formulating different flood management plans, allocating necessary funds, water resources management, watershed management, and erosion control programs. Watershed Modeling System (WMS) as an integrated flood modeling software can simulate flood hydrographs considering the required parameters. Among the common runoff estimation methods, the SCS curve number method is the most common in estimating flood volume and flood runoff height. Land use changes as an important factor in the alteration of watershed hydrologic response can accelerate soil erosion and biodiversity loss. Land use change affects the curve number and consequently, discharge and flood hydrographs, as assessed in the current study.
 
Materials and Methods
The Khiavchai Watershed, with an area of about 134 km2 has been chosen as the study area. The annual rainfall of the study area is 343.8 mm. Toward the hydrologic modeling in the study area, the slope map of the watershed has been derived from the DEM of the study area using the ArcMap software. The maximum daily rainfall of 11 rating gauge stations has been obtained and the raw data has been processed using a common statistical test to check the data quality and homogeneity of SPSS software. The maximum 24-h rainfall data were analyzed using Easy Fit software to select the best statistical distribution. The 3-parameter Pearson distribution (as the best probability distribution function), has been used to calculate the rainfall values in 2 to 100-year return periods. The maximum daily rainfall values were entered into the ArcGIS software and the spatial distribution mapping was done using the IDW method. The average maximum daily precipitation with different return periods was converted to 6-h precipitation. The SCS and WMO rainfall patterns were compared in the study area, and the WMO rainfall patterns were selected as the appropriate input for the model. The maximum annual instantaneous discharge values have been used in estimating the flood discharge in 2, 5, 10, 25, 50, and 100-year return periods using EasyFit software. The input model parameters (slope map, slope direction, curve number, and soil hydrological group) were prepared in ArcGIS and Arc-Hydro software.
 
Results and Discussion
The results showed that the maximum flood discharge increases intensely with an increase in the return period. The average CN value of the basin was obtained at 76, the initial loss coefficient was obtained at 0.202, and the STRTL value was obtained at 16.203. According to the increasing curve number values, the infiltration time and the time to reach the peak are reduced. Therefore, by increasing the curve number by 5, 15, and 25%, respectively, the time to reach the peak is 240, 180, and 135 min, and the base time of the hydrograph has decreased by 1035, 885, and 750 min. Meanwhile, the peak value of the simulated flood hydrograph has increased from 1.74 to 6.466, 27.491, and 109.694 m3 s-1. With an increase of 25% curve number, the peak discharge in the return period of 10, 25, 50, and 100 years has increased to 13, 9, 7.5, and 6.3, respectively. The results show that the effect of changes in curve number values on the flood discharge, in the low return period is much more than the high return period. So in the return period of 100 years with 25% changes in curve number, the peak flood discharge value is 6.38 times in the 2-year return period. The results indicate that the least change in the type of land use (in order to reduce permeability) causes a considerable increase in flood discharge in the region.
 
Conclusion
The effects of changes in CN values have been assessed in the current research in a modeling framework to estimate the flood hydrograph components. Comparison of the estimated flood hydrograph components against observation values has been evaluated using relative error and root mean square error. The values of these statistical indices were obtained with the least error related to the 3-parameter lognormal distribution of about 10.32% and 8.68 m3 s-1. By comparing the results of the maximum flood analysis and the WMS model, it can be concluded that the simulated data are consistent with the observed flood records in the Pole-Solatani river gauge station located at the outlet of the Khiavchai Watershed.

Keywords

Main Subjects

References

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.2017.04.218
Water and Soil Management and Modelling
Volume 4, Issue 1
January 2024
Pages 248-261

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History

  • Receive Date: 06 February 2023
  • Revise Date: 25 February 2023
  • Accept Date: 25 February 2023

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