Derivation of nondimensional synthetic unit hydrograph of ITS-2 using the 2-parameter gamma distribution

I. Gede Tunas, Nadjadji Anwar, Umboro Lasminto, Sukandi Samatan

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

ITS-2 is one of the latest synthetic unit hydrograph-based flood estimation models in Indonesia. Developed at the Institut Teknologi Sepuluh Nopember (ITS) Surabaya in 2017, the basic parameters of the model were formulated using fractal and morphometric charac-teristics of eight observed river basin in Central Sulawesi, Indonesia. The fundamental concern with developing this model is how to derive a curve equation which illustrates the shape of the hydrograph. This paper aims to formulate this equation using the 2-parameter Gamma distribution, one of the statistical distribution model that is widely used for hydrological modeling especially hydrographs. The derivation of the equation was carried out by simplifying the parameters of the Gamma function which corresponds to the shape of the hydrograph such as the rising limb, peak and, recession limb. This research has succeeded in formulating an equation of dimensionless synthetic unit hydrograph curve expressed by the ratio of time (T) and peak time (Tp) of the hydrograph. A coefficient of C3 states that the hydrograph shape parameters can be optimized to improve model performance, when a series of observation discharge is available for calibration. The performance of the synthetic unit hydrograph equation was assessed using Mean Absolute Percentage Error (MAPE) and the Coefficient of correlation (r). The analysis results based on a series of verification indicated that the performance of the hydrograph equation was very high with MAPE below 20% and a r above 0.8.

Original languageEnglish
Pages (from-to)827-838
Number of pages12
JournalInternational Journal of Mathematics and Computer Science
Volume15
Issue number3
Publication statusPublished - 2020

Keywords

  • Hydrograph
  • Hydrology model
  • Performance
  • Statistical distribution

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