Modelling one-dimensional reactive transport of toxic contaminants in natural rivers

Kim, Byunguk; Seo, Il Won; Kwon, Siyoon; Jung, Sung Hyun; Choi, Yongju

doi:10.1016/j.envsoft.2021.104971

Cited by 11 publications

(9 citation statements)

References 18 publications

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“…The spatial–temporal concentration variation of a tracer in a stream involves the information of both the flow dynamics and complex storage effects of the stream. To acquire such information, a tracer test was carried out at the 4.85 km reach of Gam Creek, South Korea, in October 2019 (Kim et al., 2021a, 2021b, 2022). The test reach of Gam Creek had a sandy bed with little vegetation and potential storage zones, such as shoals, dunes, side pockets, and natural banks (see Figure 4).…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, by assuming ideal storage zones, the NRTD can be explicitly defined with the mass exchange rate

\alpha

and retention time distribution

\varphi

, and Equation becomes equivalent to the TSM with the exponential

\varphi

of Equation . In this study, the optimal four parameters;

U

{D}_{L}

{\epsilon}

, and

\alpha

were determined by finding the best‐fitted breakthrough curve to observations, which is the classical technique for transient storage parameter determination (Choi et al., 2020; Femeena et al., 2020; Jackson et al., 2013; Kim et al., 2021a, 2021b; Rana et al., 2017; Rivord et al., 2014; Rowiński & Piotrowski, 2008; Zaramella et al., 2016). For the non‐convex multi‐parameter optimization, the global optimization scheme, suggested and validated with the TSM model by Noh et al.…”

Section: Methodsmentioning

confidence: 99%

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Estimating Net Retention Time of Solute in Storage Zones of a Stream

Kim

Seo

Kwon

et al. 2023

Water Resources Research

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Because of the influence of various storage zones, solute transport in a stream channel cannot be interpreted by advection and dispersion processes alone. Thus, in recent decades, various models that incorporate storage-zone effects have been proposed to characterize anomalous storage mechanisms. The validity of these models has been predominantly demonstrated using tracer breakthrough curves measured in surface flow. However, the storage effect is usually less influential on the breakthrough curve behavior than in-stream flow dynamics. Thus, for model validation, the tracer behavior within the storage zone should be investigated separately. The present study aims to quantify the time-dependent storage effect, herein termed the net retention time distribution (NRTD), from tracer measurements in the flow zone using a deconvolution technique with manipulation in the Fourier domain. The results demonstrated that the deconvolved NRTDs successfully represented the temporal behavior of the tracer in the storage zones without significant distortion in the primary information of the observed breakthrough curves. Using estimates of NRTD, we evaluated the simulations of the transient storage model, and found that the storage effects were underestimated as much as an average 18.5% in this study. The deconvolved NRTDs were also utilized to predict the biodegradation losses of organic chemicals flowing along a stream at confidence intervals.

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Section: Methodsmentioning

confidence: 99%

“…Therefore, by assuming ideal storage zones, the NRTD can be explicitly defined with the mass exchange rate

\alpha

and retention time distribution

\varphi

, and Equation becomes equivalent to the TSM with the exponential

\varphi

of Equation . In this study, the optimal four parameters;

U

{D}_{L}

{\epsilon}

, and

\alpha

Section: Methodsmentioning

confidence: 99%

Estimating Net Retention Time of Solute in Storage Zones of a Stream

Kim

Seo

Kwon

et al. 2023

Water Resources Research

Self Cite

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“…Take the mean concentration over the finite static surface layer as an overall C s , then the two-zone model can be approximated by a one-zone problem given the boundary condition (2.1b) (Khan 1962;Horn 1971). A further simplification is that the transport in the bulk can also be modelled by a one-dimensional effective equation with an exchange term C s , which is widely used in chemical and environmental applications (Nordin & Troutman 1980;Balakotaiah & Chang 1995;Kim et al 2021).…”

Section: Formulationmentioning

confidence: 99%

“…A further simplification is that the transport in the bulk can also be modelled by a one-dimensional effective equation with an exchange term , which is widely used in chemical and environmental applications (Nordin & Troutman 1980; Balakotaiah & Chang 1995; Kim et al. 2021).…”

Section: Formulationmentioning

confidence: 99%

Analytical solutions for reactive shear dispersion with boundary adsorption and desorption

Jiang

Zeng

et al. 2022

J. Fluid Mech.

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Surface reactions such as the adsorption and desorption at boundaries are very common for solute dispersion in many applications of chemistry, biology, hydraulics, etc. To study how reversible adsorption affects the transient dispersion, Zhang, Hesse & Wang (J. Fluid Mech., vol. 828, 2017, pp. 733–752) have investigated the temporal evolution of moments using the Laplace transform method. Owing to difficulties introduced by the adsorption–desorption boundary condition, great challenges arise from the inverse Laplace transform: dealing with the singularities by the residue theorem can tremendously increase complexities. This work provides a much simpler analytical method to derive solutions in a more compact form that is valid for the entire range of the reactive transport process. Such a progress demonstrates that the classic framework of separation of variables can be extended and applied to this more general adsorption–desorption condition, based on which higher-order statistics including skewness and kurtosis can be explicitly explored in practice. Also extended is Gill's generalised dispersion model for solute concentration distributions, which can now address the entire transient dispersion characteristics, instead of just applied for the long-time asymptotic reactive process as done previously. Regarding the most classic Taylor dispersion problem, we investigate the influence of the reversible adsorption–desorption on the solute cloud in a tube flow. Not only the transient dispersion characteristics of transverse-average concentration distribution but also those of the bulk, surface and total-average distributions are discussed. We further investigate the influence of initial conditions on the non-uniformity of the transient dispersion over the cross-section.

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“…where In this study, MATLAB-based TSM code was employed [48]. This model used the finite difference method and the Crank-Nicolson method, similar to the OTIS by Runkel [37].…”

Section: Contaminant Accident Scenarios (Cas) 211 Transient Storagmentioning

confidence: 99%

Identification Framework of Contaminant Spill in Rivers Using Machine Learning with Breakthrough Curve Analysis

Kwon

Noh

Seo

et al. 2021

IJERPH

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To minimize the damage from contaminant accidents in rivers, early identification of the contaminant source is crucial. Thus, in this study, a framework combining Machine Learning (ML) and the Transient Storage zone Model (TSM) was developed to predict the spill location and mass of a contaminant source. The TSM model was employed to simulate non-Fickian Breakthrough Curves (BTCs), which entails relevant information of the contaminant source. Then, the ML models were used to identify the BTC features, characterized by 21 variables, to predict the spill location and mass. The proposed framework was applied to the Gam Creek, South Korea, in which two tracer tests were conducted. In this study, six ML methods were applied for the prediction of spill location and mass, while the most relevant BTC features were selected by Recursive Feature Elimination Cross-Validation (RFECV). Model applications to field data showed that the ensemble Decision tree models, Random Forest (RF) and Xgboost (XGB), were the most efficient and feasible in predicting the contaminant source.

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Modelling one-dimensional reactive transport of toxic contaminants in natural rivers

Cited by 11 publications

References 18 publications

Estimating Net Retention Time of Solute in Storage Zones of a Stream

Estimating Net Retention Time of Solute in Storage Zones of a Stream

Analytical solutions for reactive shear dispersion with boundary adsorption and desorption

Identification Framework of Contaminant Spill in Rivers Using Machine Learning with Breakthrough Curve Analysis

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