Multicriteria Evaluation Approach for Assessing Parametric Uncertainty during Extreme Peak and Low Flow Conditions over Snow Glaciated and Inland Catchments

Abstract

This paper examines model uncertainties associated with streamflow by characterizing it into extreme high (peak) flows and low flows in two different catchments, viz. a snowmelt-induced hilly catchment (Satluj) and an inland catchment (Tungabhadra). The streamflow was initially simulated and calibrated using the soil and water assessment tool (SWAT) model and SWAT CUP (calibration and uncertainty program) based sequential uncertainty fitting approach (SUFI2) by analyzing 14 different hydrological parameters. The multiple criteria evaluation was based on the multiple linear regression equations and noncommensurable measures of information derived from river flow series by means of a number of sequential time-series processing tasks, including separation of the river flow series into extreme peak flows and low-flow hydrograph periods. A reliable set of rules for model calibration was applied to all linear-regression-based objective functions. The authors found that extreme peak flow conditions were more critical than low-flow conditions and that the streamflow corresponding to the snowmelt process was more uncertain. Factors such as temperature (p-value∼0.027) and snowmelt (p-value∼0.000) were identified as sensitive parameters which showed large influence on the calibration parameters for mountainous hilly terrain conditions. Overall, calibration of the SWAT modeling was found more reliable for the Tungabhadra catchment in both extreme peak flow and low flow simulations whereas the model performance was slightly complex for the snowmelt-induced Satluj catchment, especially during extreme peak flow events.