Pathogen transport and fate modeling in the Upper Salem River Watershed using SWAT model

Niazi, Mehran; Obropta, Christopher C.; Miskewitz, Robert

doi:10.1016/j.jenvman.2014.12.042

Cited by 31 publications

(5 citation statements)

References 21 publications

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“…Both RWC and RHZ increased with increasing Across (and associated lower water velocities) due to the increase of hydraulic residence time and hyporheic storage. Water column (WC) percentage E. coli removal was most sensitive to the temperature adjustment factor (θ), which was consistent with previous results reported by Coffey et al (2010) [32], Niazi et al (2015) [33], Kondo et al [69], and Sowah et al [70]. RWC was 3% and 16% for θ = 1.12 and θ = 1.02, respectively.…”

Section: Whole River Network E Coli Removal Using Full Removal Scenariosupporting

confidence: 91%

“…Each parameter was changed by +25% and −25% (except for Temperature adjustment factor (θ) and R HZ ) while leaving all others constant and quantifying the change of E. coli removal at the river network scale. Temperature adjustment factor (θ) was adjusted to the maximum and minimum values from the literature [33,34] since 25% changes exceeded the range. R HZ was only tested by −25% because R HZ cannot exceed 1.…”

Section: E Coli Model Parameterization and Testingmentioning

confidence: 99%

“…This study has shown that exchange with the hyporheic zone contributes more than decay in the water column to whole channel removal. While empirical estimates of water column die-off rates have been implemented in watershed scale models, including the Soil and Water Assessment Tool (SWAT), Hydrologic Simulation Program-FORTRAN (HSPF), and Storm Water Management Model (SWMM) [32][33][34][35][36][37][38], few studies have accounted for the role of non-water column removal at watershed scales [28]. The novelty of our study is represented by quantifying the role of hyporheic removal at watershed scales.…”

Section: Introductionmentioning

confidence: 99%

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Removal of Fecal Indicator Bacteria by River Networks

Huang

Wollheim

Jones

2022

Water

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Fecal contamination is a significant source of water quality impairment globally. Aquatic ecosystems can provide an important ecosystem service of fecal contamination removal. Understanding the processes that regulate the removal of fecal contamination among river networks across flow conditions is critical. We applied a river network model, the Framework for Aquatic Modeling in the Earth System (FrAMES-Ecoli), to quantify removal of fecal indicator bacteria by river networks across flow conditions during summers in a series of New England watersheds of different characteristics. FrAMES-Ecoli simulates sources, transport, and riverine removal of Escherichia coli (E. coli). Aquatic E. coli removal was simulated in both the water column and the hyporheic zone, and is a function of hydraulic conditions, flow exchange rates with the hyporheic zone, and die-off in each compartment. We found that, at the river network scale during summers, removal by river networks can be high (19–99%) with variability controlled by hydrologic conditions, watershed size, and distribution of sources in the watershed. Hydrology controls much of the variability, with 68–99% of network scale inputs removed under base flow conditions and 19–85% removed during storm events. Removal by the water column alone could not explain the observed pattern in E. coli, suggesting that processes such as hyporheic removal must be considered. These results suggest that river network removal of fecal indicator bacteria should be taken into consideration in managing fecal contamination at critical downstream receiving waters.

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Section: Whole River Network E Coli Removal Using Full Removal Scenariosupporting

confidence: 91%

Section: E Coli Model Parameterization and Testingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Removal of Fecal Indicator Bacteria by River Networks

Huang

Wollheim

Jones

2022

Water

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“…This is mainly due to the paucity of data needed to adequately parameterize models and describe the processes involved (Cho et al, 2016a). The mechanistic semi-distributed model Soil and Water Assessment Tool (SWAT) (Arnold et al, 2012) has previously been used in a range of environments (Baffaut and Sadeghi, 2010;Bougeard et al, 2011;Chin, 2011;Cho et al, 2012;Coffey et al, 2010;Iudicello and Chin, 2013;Kim et al, 2010;Niazi et al, 2015) and has been shown to be a promising tool for assessing the fate of fecal bacteria in temperate river basins. However, the applicability of this model for tropical regions remains to be evaluated.…”

Section: Introductionmentioning

confidence: 99%

Hydrological modeling of Fecal Indicator Bacteria in a tropical mountain catchment

et al. 2017

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“…Numerous studies have been conducted on surface water samples to reveal multiple relationships between microbial concentrations in surface water and various catchment and hydrological variables [16][17][18][19]. Stormwater runoff is a dynamic process, and the pollutants' concentrations may vary within one storm event and among different storm events.…”

Section: Introductionmentioning

confidence: 99%

Role of Environmental Variables in the Transport of Microbes in Stormwater

Aryal

Sidhu

Chong

et al. 2021

Water

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Microbial pathogens present in stormwater, which originate from human sewage and animal faecal matters, are one of the major impediments in stormwater reuse. The transport of microbes in stormwater is more than just a physical process. The mobility of microbes in stormwater is governed by many factors, such as dissolved organic matter, cations, pH, temperature and water flow. This paper examined the roles of three environmental variables, namely: dissolved organic matter, positive cations and stormwater flow on the transport of two faecal indicator bacteria (FIB), Enterococcus spp. and Escherichia coli. Stormwater runoff samples were collected during twelve wet weather events and one dry weather event from a medium density residential urban catchment in Brisbane. Enterococcus spp. numbers as high as 3 × 104 cfu/100 mL were detected in the stormwater runoff, while Escherichia coli numbers up to 3.6 × 103 cfu/100 mL were observed. The dissolved organic carbon (DOC) in the stormwater samples was in the range of 2.2–5.9 mg/L with an average concentration of 4.5 mg/L in which the hydrophilic carbon constituted the highest mass fraction of 60–80%. The results also showed that the transport of FIB in stormwater was reduced with an increasing concentration of the hydrophilic organic fraction, especially the humic fraction. On the contrary, the concentration of trivalent cations and stormwater flow rate showed a positive correlation with the FIB numbers. These findings indicated the potentiality to make a good use and measurement of simple environmental variables to reflect the degree of microbe transport in stormwater from residential/suburban catchments.

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Pathogen transport and fate modeling in the Upper Salem River Watershed using SWAT model

Cited by 31 publications

References 21 publications

Removal of Fecal Indicator Bacteria by River Networks

Removal of Fecal Indicator Bacteria by River Networks

Hydrological modeling of Fecal Indicator Bacteria in a tropical mountain catchment

Role of Environmental Variables in the Transport of Microbes in Stormwater

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