Simulation of zones of groundwater contribution to wells south of the Naval Weapons Industrial Reserve Plant in Bethpage, New York

Misut, Paul E.

doi:10.3133/sir20175161

Cited by 4 publications

(8 citation statements)

References 11 publications

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“…The lowermost two (Magothy and the confined Lloyd) aquifers are used for water supply in the eastern part of the study area. A rough conceptual model based on previous studies (Misut 2018, Monti et al 2009 consists of partially saturated sand and gravel, silty sand and clay lenses in the uppermost aquifer unconformably overlying the deeper Magothy sandy aquifer which increases in thickness from north to south. Lithological details at the water-table (Figure 1) in the Upper Glacial aquifer, which likely vary across the region, are not generally known due to the lack of information from drillers' records.…”

Section: Hydrogeology Monitoring Wells and Weather Stationsmentioning

confidence: 99%

“…In Nassau County where the other wells are located, values ranged between 711 and 1168 mm/yr. A more recent investigation (Misut 2018) used an areally averaged recharge rate of 635 mm/yr to analyze contaminant transport in the Long Island aquifer system even further east in Nassau County beyond the current study area.…”

Section: Recharge Estimationmentioning

confidence: 99%

“…Values of hydraulic conductivity used for regional modeling analyses average 82 m/day(Misut 2018;Monti et al 2009;Buxton and Smolensky 1999), which is exceeded by local slug testing analyses at the well (Q3810) at Queens College, suggesting that this value may be low and values at the water table may be higher. The analyses for this study correspond to the uppermost part of the Upper Glacial Aquifer at the water table, and this aquifer has an approximate thickness of 33 m(Misut 2018;Buxton and Smolensky 1999). Therefore, as a conservative estimate, the transmissivity value selected for use in the analyses for this study was 150 m 2 /hr, making the diffusivity value T/S Y equal to 1500 m 2 /hr or 36000 m 2 /d for this study.…”

mentioning

confidence: 99%

“…Park (2012) developed a complex method that incorporates a more realistic fillable porosity parameter, but most WTF analyses simply assign an estimated S Y value, and that was the approach used for this study. To minimize the variation in results that could result from unknowable spatial variation in S Y , a value of 0.1 was used for all analyses, at the lower end of the range of values found in USGS regional Long Island aquifer modeling analyses(Misut 2018;Buxton and Smolensky 1999).Hydraulic conductivity in the Upper Glacial Aquifer is known to be high, although the spatial variation in this parameter is also unknown. Values of hydraulic conductivity used for regional modeling analyses average 82 m/day(Misut 2018;Monti et al 2009;Buxton and Smolensky 1999), which is exceeded by local slug testing analyses at the well (Q3810) at Queens College, suggesting that this value may be low and values at the water table may be higher.…”

mentioning

confidence: 99%

“…To minimize the variation in results that could result from unknowable spatial variation in S Y , a value of 0.1 was used for all analyses, at the lower end of the range of values found in USGS regional Long Island aquifer modeling analyses(Misut 2018;Buxton and Smolensky 1999).Hydraulic conductivity in the Upper Glacial Aquifer is known to be high, although the spatial variation in this parameter is also unknown. Values of hydraulic conductivity used for regional modeling analyses average 82 m/day(Misut 2018;Monti et al 2009;Buxton and Smolensky 1999), which is exceeded by local slug testing analyses at the well (Q3810) at Queens College, suggesting that this value may be low and values at the water table may be higher. The analyses for this study correspond to the uppermost part of the Upper Glacial Aquifer at the water table, and this aquifer has an approximate thickness of 33 m(Misut 2018;Buxton and Smolensky 1999).…”

mentioning

confidence: 99%

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Episodic and Continuous Recharge Estimation from High‐Resolution Well Records

Eaton¹

2019

Groundwater

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Section: Hydrogeology Monitoring Wells and Weather Stationsmentioning

confidence: 99%

Section: Recharge Estimationmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Episodic and Continuous Recharge Estimation from High‐Resolution Well Records

Eaton¹

2019

Groundwater

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Improved Prediction of Management‐Relevant Groundwater Discharge Characteristics Throughout River Networks

Barclay

Starn

Briggs

et al. 2020

Water Resources Research

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Groundwater discharge zones connect aquifers to surface water, generating baseflow and serving as ecosystem control points across aquatic ecosystems. The influence of groundwater discharge on surface flow connectivity, fate and transport of contaminants and nutrients, and thermal habitat depends strongly on hydrologic characteristics such as the spatial distribution, age, and depth of source groundwater flow paths. Groundwater models have the potential to predict spatial discharge characteristics within river networks, but models are often not evaluated against these critical characteristics and model equifinality with respect to discharge processes is a known challenge. We quantify discharge characteristics across a suite of groundwater models with commonly used frameworks and calibration data. We developed a base model (MODFLOW-NWT) for a 1,570-km 2 watershed in the northeastern United States and varied the calibration data, control of river-aquifer exchange directionality, and resolution. Most models (n = 11 of 12) fit similarly to calibration metrics, but patterns in discharge location, flow path depth, and subsurface travel time varied substantially. We found (1) a 15% difference in the percent of discharge going to first-order streams, (2) threefold variations in flow path depth, and (3) sevenfold variations in the subsurface travel times among the models. We recalibrated three models using a synthetic discharge location data set. Calibration with discharge location data reduced differences in simulated discharge characteristics, suggesting an approach to improved equifinality based on widespread field-based mapping of discharge zones. Our work quantifying variation across common modeling approaches is an important step toward characterizing and improving predictions of groundwater discharge characteristics.

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