Sciences in Cold and Arid Regions ›› 2016, Vol. 8 ›› Issue (4): 297-310.doi: 10.3724/SP.J.1226.2016.00297

• ARTICLES • Previous Articles    

Uncertainty analysis of runoff and sedimentation in a forested watershed using sequential uncertainty fitting method

Tanveer Abbas1, Ghulam Nabi1, Muhammad W. Boota1, Fiaz Hussain1, Muhammad I. Azam1, HuiJun Jin2, Muhammad Faisal1   

  1. 1. Centre of Excellence in Water Resources Engineering, University of Engineering and Technology Lahore, Lahore 54890, Pakistan;
    2. State Key Laboratory of Frozen Soils Engineering, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China
  • Received:2016-04-09 Revised:2016-06-01 Published:2018-11-23
  • Contact: Tanveer Abbas, Centre of Excellence in Water Resources Engineering, University of Engineering and Technology Lahore. G.T. Road, Lahore 54890, Pakistan.
  • Supported by:
    The research work was supported by the Centre of Excellence in Water Resources Engineering, Univer-sity of Engineering and Technology Lahore, and local authorities in Pakistan. The authors would like to ex-press appreciation to the Pakistan Meteorological Department (PMD) and the Capital Development Authority (CDA), Islamabad, for providing valuable data to conduct this research.

Abstract: The Soil and Water Assessment Tool (SWAT) was implemented in a small forested watershed of the Soan River Basin in northern Pakistan through application of the sequential uncertainty fitting (SUFI-2) method to investigate the associated uncertainty in runoff and sediment load estimation. The model was calibrated for a 10-year period (1991-2000) with an initial 4-year warm-up period (1987-1990), and was validated for the subsequent 10-year period (2001-2010). The model evaluation indices R2 (the coefficient of determination), NS (the Nash-Sutcliffe efficiency), and PBIAS (percent bias) for stream flows simulation indicated that there was a good agreement between the measured and simulated flows. To assess the uncertainty in the model outputs, p-factor (a 95% prediction uncertainty, 95PPU) and r-factors (average wideness width of the 95PPU band divided by the standard deviation of the observed values) were taken into account. The 95PPU band bracketed 72% of the observed data during the calibration and 67% during the validation. The r-factor was 0.81 during the calibration and 0.68 during the validation. For monthly sediment yield, the model evaluation coefficients (R2 and NS) for the calibration were computed as 0.81 and 0.79, respectively; for validation, they were 0.78 and 0.74, respectively. Meanwhile, the 95PPU covered more than 60% of the observed sediment data during calibration and validation. Moreover, improved model prediction and parameter estimation were observed with the increased number of iterations. However, the model performance became worse after the fourth iterations due to an unreasonable parameter estimation. Overall results indicated the applicability of the SWAT model with moderate levels of uncertainty during the calibration and high levels during the validation. Thus, this calibrated SWAT model can be used for assessment of water balance components, climate change studies, and land use management practices.

Key words: hydrological modeling, uncertainty analysis, SWAT model, the Soan River Basin, SUFI-2 method

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