Geology topics

David J. Hart

Publications and source records attributed to David J. Hart.

2 recordsLinked to original sources

USGS2025

A regional model comparison between MODPATH and MT3D of groundwater travel time distributions

Groundwater quality changes in wells and streams lag behind changes to land use due to groundwater travel times. Two contaminant transport methods were compared to assess differences in their simulated travel time distributions (TTDs) to streams and wells in the Wisconsin Central Sands. MODPATH simulates advective groundwater flow with particle tracking, while MT3D simulates age-mass using a finite difference solution without dispersion to allow for direct comparison of the two methods. MODPATH appropriately simulates groundwater TTDs from the water table to surface discharge but is subject to inaccuracies at weak-sink well cells due to the flow-model grid discretization and imprecise location of well discharge within well cells. MT3D better represents weak-sink well cells since it removes mass in proportion to the prescribed pumping rate, although travel time within well cells is neglected. Conversely, MT3D's treatment of surface water boundary cells is not as accurate as MODPATH because mass should be removed from the water table rather than the full cell volume. MT3D simulations of TTDs can also be confounded by the instantaneous vertical distribution of mass introduced throughout recharge cells instead of at the water table, which initiates mass along deeper flow paths. We evaluated 9 MODPATH and 13 MT3D implementations, generating differences in median travel times of up to 18 years. Both methods have strengths and weaknesses, with MT3D better representing weak-sink well cell behavior and MODPATH better representing surficial recharge and discharge. The effect of these characteristics on simulated TTDs, along with ideas for ameliorating method weaknesses, is discussed.

Wisconsin↗

USGS2023

Evaluation of models for estimating hydraulic conductivity in glacial aquifers from NMR logging

Nuclear magnetic resonance (NMR) logging is a promising method for estimating hydraulic conductivity ( K ). During the past ∼60 years, NMR logging has been used for petroleum applications, and different models have been developed for deriving estimates of permeability. These models involve calibration parameters whose values were determined through decades of research on sandstones and carbonates. We assessed the use of five models to derive estimates of K in glacial aquifers from NMR logging data acquired in two wells at each of two field sites in central Wisconsin, USA. Measurements of K , obtained with a direct push permeameter (DPP), K DPP , were used to obtain the calibration parameters in the Schlumberger-Doll Research, Seevers, Timur-Coates, Kozeny-Godefroy, and sum-of-echoes (SOE) models so as to predict K from the NMR data; and were also used to assess the ability of the models to predict K DPP . We obtained four well-scale calibration parameter values for each model using the NMR and DPP measurements in each well; and one study-scale parameter value for each model by using all data. The SOE model achieved an agreement with K DPP that matched or exceeded that of the other models. The Timur-Coates estimates of K were found to be substantially different from K DPP . Although the well-scale parameter values for the Schlumberger-Doll, Seevers, and SOE models were found to vary by less than a factor of 2, more research is needed to confirm their general applicability so that site-specific calibration is not required to obtain accurate estimates of K from NMR logging data.

Wisconsin↗