Abstract

Understanding the effects of best management practices (BMPs) on nitrate reduction in karst aquifers is critical for spring restoration. In this study, Conduit Flow Process (CFPv2) and Conduit Mass Three-Dimensional (CMT3D) models were applied to evaluate nitrate removal for Silver Springs in Florida using blanket filters composed of biosorption-activated media (BAM). As the inputs of the model, the spatial and temporal variability of nitrate-N concentration in groundwater recharge was estimated as a function of population and land use, reflecting both point and non-point sources of nitrate. Additionally, the spatial heterogeneity of nitrate removal efficiency in the soil was considered in the evaluation. The model estimates that conduit flow accounts for 48% of spring discharge and 47% of nitrate-N mass transport on average, and the contributions of conduit to flow and nitrate mass transport are higher during wet years. The net effect of nitrate reduction in spring discharge was evaluated for two BMP scenarios, i.e., implementing BAM-based blanket filters in 26 stormwater retention basins and 50% of the urban area. The net effect of the BMP on nitrate reduction for Scenario 1 is limited; whereas, for Scenario 2, the nitrate-N concentration will be reduced to 1.08 mg/L in 2026 for a nitrate removal efficiency of 74% (i.e., a 4.9% reduction relative to the baseline condition). This study suggests that the BAM-based blanket filters benefit is likely to scale with penetration (i.e. greater water quality benefits can be expected with greater BMP implementation). Further, this study shows that whether BAM-based blanket filters leads to net water quality improvements or degradation depends on whether BAM removes more or less nutrients from stormwater than the unaltered soil profile. The simulated effects of the BMP on nitrate reduction may serve as an additional guidance for water resources managers to make decisions on investments in nutrient reduction technologies for spring restorations in karst systems.

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