Paper No. 25-7
Presentation Time: 4:10 PM
MASSACHUSETTS TOP OF ROCK PROJECT: ONE APPROACH
MABEE, Stephen, 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 PONTRELLI, Marshall, McPhail Associates, 2269 Massachusetts Avenue, Cambridge, MA 02140
The bedrock surface is recognized as an important surface in many geological and engineering applications. Yet the depth to the bedrock surface is not well known everywhere, particularly where glacial sediments of variable thickness cover the bedrock. Creation of a model of the “top of rock” surface is an essential ingredient in supporting the development of a 2D/3D geologic framework. Here we report on one approach used in Massachusetts to create maps of the altitude of the bedrock surface and overburden thickness at 100-meter resolution. Starting in 2020, we collected drill hole and geophysical data from 28 different easily accessible data sources, including gathering our own horizontal-to-vertical spectral ratio (HVSR) survey data in areas of sparse well coverage. We also discretized bedrock outcrop and shallow-to-bedrock area polygons contained in the statewide surficial materials geodatabase. Together, these sources produced a data set of 711,317 measurements each with a bedrock altitude value, depth to bedrock value and location. In addition, we assigned each record a depth to bedrock measurement uncertainty based on the data source and method of data acquisition.
We modeled the bedrock surface using kriging and iterated the procedure for the final maps. The first step used empirical Bayesian kriging to generate a continuous bedrock altitude raster. The next step identified areas where overburden wells indicated the bedrock is deeper than the initial bedrock surface generated in the model. These overburden wells were incorporated into a new kriging run to depress the bedrock altitude at those locations. We also created corresponding kriging prediction standard error, measurement uncertainty, and combined prediction error and uncertainty maps to accompany the modeled data layers.
The results are already being used. The Massachusetts Department of Transportation is using the information to reduce uncertainty in planning subsurface investigations for transportation projects. A new Hydrogeologic Atlas of Massachusetts is in progress that uses the information to develop a statewide groundwater flow model and hydraulic conductivity and transmissivity maps. Future plans include developing an app to query the maps and provide users with an estimate of the depth to bedrock and accompanying uncertainty.