Joint 60th Annual Northeastern/59th Annual North-Central Section Meeting - 2025

Paper No. 8-5
Presentation Time: 8:30 AM-5:30 PM

COMPARISON OF MODFLOW6 MODELS WITH CROSS-HOLE SLUG, PIEZOMETER, AND PUMPING TEST DATA FOR ESTIMATING HYDRAULIC PARAMETERS IN MAINE PEATLANDS


BELL, Addison, University of Maine, School of Earth and Climate Sciences, Orono, ME 04469

Peatlands store significant amounts of carbon and are an important component of the global carbon cycle. They influence greenhouse gas concentrations by sequestering CO₂ and contributing CH₄ to the atmosphere. Understanding and managing peatlands is crucial for local ecology and predicting their role in global climate change. Reliable data on hydraulic properties, such as hydraulic conductivity and storativity, are important to their management but limited in the literature. The objectives of this research are to evaluate single-well and cross-hole slug testing methods used to measure aquifer parameters, quantify deep peat hydraulic parameters (e.g., specific yield and vertical hydraulic conductivity) that are poorly represented in the peatland literature, and compare these findings with data from piezometer and pumping tests. Fieldwork for cross-hole slug testing was conducted at four peatland sites in Maine, where lightweight tools were used to install wells in soft, deformable peat. These tests were complemented with a traditional pumping test and slug test analysis (e.g., Hvorslev Method) to compare with cross-hole test results. Groundwater models of the pumping and cross-hole tests are being developed to estimate peat’s hydraulic parameters through calibration of groundwater simulations to hydraulic head data. Analysis of pumping test data using the Theis method produces estimates of transmissivity near 1×10-5 m²/sec and storativity near 0.4. Analyses of slug test data produces estimates of hydraulic conductivity ranging from 1×10-7 m/sec in deep (3 m) wells to 1×10-5 m/sec in shallow (1.5 m) wells based on water level response. These values are critical for improving peatland hydrology models and have significant implications for predicting peatland responses to environmental changes. Improved models can guide peatland management to mitigate methane emissions and enhance carbon sequestration efforts, contributing to climate change adaptation.