Aqua (Apr 2023)

A comparison of the SCS-CN-based models for hydrological simulation of the Aghanashini River, Karnataka, India

  • Harmandeep Singh,
  • Mohammad Afaq Alam,
  • Priyank J. Sharma,
  • Kuldeep Singh Rautela

DOI
https://doi.org/10.2166/aqua.2023.213
Journal volume & issue
Vol. 72, no. 4
pp. 507 – 519

Abstract

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This present study investigates different techniques for estimating the surface runoff using the Soil Conservation Service Curve Number (SCS-CN) method for the Aghanashini River in Karnataka, India. The SCS-CN method is a simplified approach for runoff estimation, but it does not take into account the actual moisture content in the soil. Consequently, insignificant moisture level changes could induce significant variations in the runoff. The study analyzes six different models based on the SCS-CN method, including the original SCS-CN model and several variations with added features (SCS-CN with slope correction, SCS-CN with λ-optimization, Mishra and Singh, Michel-Vazken -Perrin (MVP), Activation Soil Moisture Accounting SCS-CN). The accuracy of each model was compared using several goodness-of-fit statistics. Furthermore, based on the flood frequency analysis, three large flood events were reported in 2005, 2013, and 2014. The results showed that the MVP model was the best-performing method in simulating runoff. The outcomes of this study can provide valuable information to the local authorities in making informed decisions about flood forecasting and water conservation. HIGHLIGHTS Six mathematical models have been prepared on the basis of SCS-CN for a coastal river basin.; The long-term hydrological simulation of the Aghanashini River has been carried out by taking AMC changes.; Seven statistical indices were used to judge the efficiency of the developed models.; The developed models compute surface runoff with the desired accuracy.;

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