This research was aimed to model transition from rainfall to flow and then calibrate and validate the model in a tropical watershed. The location of this research was in Kahayan River located in the Kahayan watershed, Central Kalimantan. Land cover in 2022 was used as the input model, while topographic data was extracted from Digital Elevation Model Nasional (DEMNAS). 10 years of measured rainfall data (2013–2022) was converted to flow using a physical-based model named Arc-SWAT. The model was calibrated using data from 2015 to 2018 after being warmed up using measured rainfall and discharge data from 2013 to 2014. Then, the resulting calibration parameters were used to validate the 2019–2022 simulation period. Result shows that the calibration parameter with the lowest deviation was the Curve Number (CN) value of 60 and alpha_bf of 0.005. The Nash Sutcliffe Efficiency (NSE) value during model calibration was 0.72, while during validation the NSE increased to 0.78.

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Modeling Rainfall-Flow in the Kahayan Watershed Central Kalimantan Province

  • Nomeritae,
  • Darmae Nasir,
  • Salonten

摘要

This research was aimed to model transition from rainfall to flow and then calibrate and validate the model in a tropical watershed. The location of this research was in Kahayan River located in the Kahayan watershed, Central Kalimantan. Land cover in 2022 was used as the input model, while topographic data was extracted from Digital Elevation Model Nasional (DEMNAS). 10 years of measured rainfall data (2013–2022) was converted to flow using a physical-based model named Arc-SWAT. The model was calibrated using data from 2015 to 2018 after being warmed up using measured rainfall and discharge data from 2013 to 2014. Then, the resulting calibration parameters were used to validate the 2019–2022 simulation period. Result shows that the calibration parameter with the lowest deviation was the Curve Number (CN) value of 60 and alpha_bf of 0.005. The Nash Sutcliffe Efficiency (NSE) value during model calibration was 0.72, while during validation the NSE increased to 0.78.