Sensitivity Analysis of Transient Storage Parameters in Mathematical Modeling of Pollution Transport in Rivers Containing Storage Zone

Abstract

Hydrologists studying rivers must determine the relative importance of in-river processes to understand the fate of pollutants. Storage processes are one of the most of this. Currently, the most reliable method for determining the importance of storage processes in the solute transfer is to estimate the stream-storage exchange coefficient (α) and the cross-sectional area ratio (AS/A) in the transient storage model (TSM) with tracer experiment data (Wallis and Manson, 2019). Calibrating the parameters depends on the reciprocal coverage between parameter effects on BTCs and the model's sensitivity to each parameter (Zaramella et al., 2016). Previous studies have quantified the sensitivity of the TSM in inverse modeling (Kelleher et al., 2013; Wlostowski et al., 2013). Due to tracer test data for these studies, their results cannot provide a comprehensive picture of the model behavior. In this study, using Monte Carlo-based methods, an attempt has been made to investigate the effect of different pollutant transfer circumstances in the river by defining a framework with Peclet and Damkohler numbers and pollutant injection time series on storage parameters sensitivity.

Keywords

• transient storage model
• uncertainty analysis
• monte carlo method
• damkohler number
• peclet number