Evaluating the performance of BAM-based blanket filter on nitrate reduction in a karst spring

Gao, Yuan; Libera, D.; Wang, Dingbao; Kibler, Kelly M.; Chang, Ni‐Bin

doi:10.1016/j.jhydrol.2020.125491

Cited by 3 publications

(5 citation statements)

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“…As described in Section 2.4.2, the cells which were given high-K values in the EPM model were represented as conduits. Here some of these cells were replaced with discrete conduits; and because hydraulic conductivity in the matrix around the conduits could be low (i.e., lower than their K values in the EPM model), the hydraulic conductivity values in these cells were in succession of lowering to the average hydraulic conductivity values of the surrounding matrix [22,32]. A tracer study conducted by [29] reported that there were no mature conduits in the upper portion of the springshed; therefore, conduits were assigned mostly in the central-west portion of the domain (Figure 5b).…”

Section: Conversion Of Epm To Cfpv2mentioning

confidence: 99%

“…In the transport model, three parameters are required to be solved to simulate nitrate concentration in Silver Springs: dispersion coefficient in the rock matrix and conduits and nitrate concentration in groundwater recharge (i.e., input nitrate concentration) [32]. A tracer test was conducted to estimate the dispersivity.…”

Section: Development Of Cmt3d Modelmentioning

confidence: 99%

“…The details for the estimation of nitrate-N concentration in groundwater recharge were described in [32]. The nitrate-N concentration in groundwater recharge was set as 4 mg/L for agricultural land and 0.12 mg/L for forested land [28].…”

Section: Nitrate Concentration In Groundwater Rechargementioning

confidence: 99%

“…Further, more impervious areas (i.e., transportation corridors) may be developed as a result of population growth, and more stormwater runoff from these areas may be generated. Therefore, for residential and transportation lands, the nitrate concentration in groundwater recharge was assumed to be linearly proportional to population density [32]. Parameters of the linear function (slope and intercept) were estimated during the calibration of the transport model.…”

Section: Nitrate Concentration In Groundwater Rechargementioning

confidence: 99%

“…Changes in simulated nitrate concentration in spring discharge show weak fluctuations from December 2014 to December 2016, and both of the simulations can capture the main trend of the observed concentration, except for the period from December 2015 to April 2016. In this study, nitrate in the springs is derived from both point and nonpoint sources, which are mostly distributed in non-or slightly karstified areas (agricultural and forested lands) that account for a relatively larger part of the springshed [32]. The slow recession of nitrate in spring discharge is probably due to the slow solute transport from the nonpoint source to the springs via a low hydraulic conductivity medium.…”

Section: Nitrate Transportmentioning

confidence: 99%

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Modeling Monthly Nitrate Concentration in a Karst Spring with and without Discrete Conduit Flow

Gao

Shen

et al. 2022

Water

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Understanding the coupled continuum pipe-flow framework for modeling contaminant transport in karst systems is critical for protecting water resources therein. This study simulated point and non-point source nitrate concentration in a karst spring and investigated the results generated from the flow and transport model with and without discrete conduit flow. CFPv2 and CMT3D models were integrated to address the changes in nitrate concentration at a monthly scale in a karst spring, and the results were compared with that from an equivalent porous media (EPM) model with high-hydraulic conductivity (K) zones set in the main karstified area to represent conduits. The results show that the CFPv2+CMT3D model is able to describe well the recession of nitrate concentration in spring discharge, and the relatively larger deviation (slower nitrate recession) from the observed trend for the EPM model is probably a result of the limitation of utilizing high hydraulic conductivity cells to represent conduit. Moreover, simulated hydraulic heads in poorly karstified areas from the two models both show slight differences from the observations (the head RMSE values of calibration/validation for CFPv2 and MODFLOW models are 0.16 m/0.25 m and 0.26 m/0.17 m, respectively), indicating the inclusion of conduits may not affect the simulation considerably, and the lower the proportion of karstic area, the slight effects brought from the inclusion of conduits in the model. For highly karstified areas, the CFPv2+CMT3D model could provide more accurate results (head RMSE of calibration/validation for CFPv2 and MODFLOW are 0.22 m/0.06 and 0.52 m/0.47 m, respectively), showing the coupled continuum pipe-flow framework may be more appropriate for applying to highly and maturely karstified areas where the variations in the behavior of flow and contaminant transport are more affected by turbulent flow regime.

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Section: Conversion Of Epm To Cfpv2mentioning

confidence: 99%

Section: Development Of Cmt3d Modelmentioning

confidence: 99%