Joint 72nd Annual Southeastern/ 58th Annual Northeastern Section Meeting - 2023

Paper No. 52-1
Presentation Time: 8:00 AM-12:00 PM

UPDATE ON MASSACHUSETTS’ CONTRIBUTION TO THE GOALS FOR A SEAMLESS, NATIONAL 2D/3D GEOLOGIC FRAMEWORK MODEL FOR THE UNITED STATES: TOP OF ROCK


MABEE, Stephen B., Massachusetts Geological Survey, University of Massachusetts, 627 North Pleasant Street, Amherst, MA 01003, DUNCAN, Christopher C., GISmatters, Inc., 199 North Valley Road, Pelham, MA 01002, CLEMENT, William P., Department of Earth, Geographical and Climate Sciences, University of Massachusetts, 627 North Pleasant Street, Amherst, MA 01003 and STONE, Byron, U.S. Geological Survey, 101 Pitkin Street, East Hartford, CT 06108

The bedrock surface is important in many geological and engineering disciplines, but its depth is poorly known in some locations, particularly where glacial sediments cover it. We report progress in creating a top of rock map for Massachusetts, an essential step in developing a 2D/3D geologic framework. We collected drill hole and geophysical data from 28 different sources, including our own horizontal-to-vertical spectral ratio survey data in areas of sparse well data, for a total of 107,702 depth observations, of which 43% are wells ending in overburden giving only a minimum depth constraint. We combined these data with depths based on the statewide surficial materials geodatabase (Stone and others, 2018): 111,495 points of zero depth on bedrock outcrops and 492,120 estimated depths within shallow bedrock areas. We developed a state-wide top of rock model on a 100 m grid using the following steps: 1) Compute bedrock altitude at each point by subtracting bedrock depth from surface elevation; 2) Generate a continuous bedrock altitude raster using empirical Bayesian kriging on all points except overburden wells; 3) Identify overburden wells indicating bedrock below the altitude from step 2 and include them in a second kriging to obtain an altitude model honoring their constraints; 4) Identify areas where model bedrock is above topography, errors occurring where data are sparse and topographic relief is high; 5) Generate a continuous bedrock depth raster by kriging on the depth values of points used in step 3; 6) Subtract this depth raster from topography to obtain an alternate model of bedrock altitude guaranteed not to exceed topography; 7) Replace the erroneous areas from step 4 with altitudes from step 6, and smoothly blend the two altitude models in the cells immediately surrounding these areas; 8) Identify areas of excessive bedrock depth, errors occurring where data are absent and relief is low; 9) replace these depressions by interpolation of their perimeter altitudes. This final composite bedrock altitude model is everywhere at or below topography, minimizes imprinting of surface topography, eliminates closed depressions lacking two or more data points, and allows for close inspection and revision of contours by experienced geologists through extension of parallel contours in valley fills.