Josh Woda Jason Finkelstein John Williams 20220502 Data Release Troy, NY U.S. Geological Survey https://doi.org/10.5066/P96R5K5R Nicholas Corson-Dosch Michael N. Fienen Jason S. Finkelstein Andrew T. Leaf Jeremy T. White Joshua C. Woda John H. Williams 2022 publication n/a US Geological Survey https://doi.org/10.3133/sir20215112 This dataset includes "smoothing points" used in the creation of the Cincinnatus hydrogeologic framework. Smoothing points were manually added by the project team and were used to enhance interpolated layers using geologic assumptions and include: valley edge points, centerline bedrock points (and where applicable L1 and L2 points), and upland bedrock SSURGO points. The purpose of this dataset was to guide the raster generation models using sound geologic assumptions. 2019 2020 ground condition Complete None planned -76.03 -75.75 42.65 42.45 USGS Thesaurus Sourcewater Valley Fill Bedrock Mapping Aquifer mapping Glacial geology USGS Metadata Identifier USGS:5fc54c74d34e4b9faad8882f Getty Thesaurus of Geographic Names Cincinnatus New York Cortland County Chenango County none none Joshua C Woda NORTHEAST REGION: NEW YORK WATER SCI CTR Hydrologist mailing and physical

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Troy NY 12180 US 518-285-5606 jwoda@usgs.gov Values were quality checked multiple ways, including outlier detection and physical examination of the data. A check was performed for duplication. Supplementary point elevation data were checked to ensure for logical geologic sense (i.e. bedrock elevation is not above land surface). Dataset is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details. No formal positional accuracy tests were conducted Values were quality checked multiple ways, including outlier detection and physical examination of the data. The United States Geologic Survey 2020 Database table https://waterdata.usgs.gov/nwis The United States Geologic Survey https://waterdata.usgs.gov/nwis Database table 19760916 20190729 incomplete NWIS well log data This data was used to help define the depth to bedrock The New York Department of Environmental Conservation 2020 Well logs and spreadsheet Albany, NY The New York Department of Environmental Conservation https://webapps.usgs.gov/geologlocator/#!/search Well Logs 19300201 20190630 incomplete NY DEC well logs This data provided by the NY DEC was used to help define hydrogeologic layers, surficial geology, and better understand the subsurface in general The New York Department of Transportation 2020 Boring logs provided as shapefile N/A The New York Department of Transportation https://waterdata.usgs.gov/nwis Boring logs provided as shapefile 19660908 20180328 incomplete NY DOT Boreholes This data provided by the NY DOT was used to help define hydrogeologic layers, surficial geology, and better understand the subsurface in general United States Department of Agriculture 2014 shapefile Data Fort Worth, Texas United States Department of Agriculture https://cugir.library.cornell.edu/catalog/cugir-007903 shapefile Data 20140914 20141014 Complete SSURGO Soil Survey Geographic Database for Cortland County, NY Axis geospatial LLC 2015 point data Easton, Maryland Axis geospatial LLC ftp://ftp.gis.ny.gov/elevation/LIDAR/County_Cortland2005/BareEarth/ point data 20150401 20150630 Complete LIDAR coverage LIDAR was used as a benchmark to: help define hydrogeologic layer elevations and, adjust and create surficial geology, and provide understanding about the hydrogeologic framework. A raster was generated from point data available online. U.S. Department of Agriculture, Natural Resources Conservation Service 2015 Shapefile Fort Worth, Texas U.S. Department of Agriculture, Natural Resources Conservation Service https://cugir.library.cornell.edu/catalog/cugir-007902 Shapefile 20150101 20151231 Complete SSURGO Soil Survey Geographic Database for Chenango County, NY Axis GeoSpatial, LLC 2015 Points Easton, MD Axis GeoSpatial, LLC ftp://ftp.gis.ny.gov/elevation/LIDAR/NYSGPO_MadisonOtsego_2015/ Points 20150416 20150606 Complete New York Tiled LIDAR: Madison and Otsego Counties 1-meter resolution LIDAR The below processes are described for each unique point type, unique point types are combined when process are similar: Casing - Minimum Depth Bedrock Uplands: The casing method primarily conducted on wells originating from NWIS. Thus the first step was to bring all groundwater NWIS wells in the study area into ArcGIS. Drillers commonly set casing lengths to go 10 ft into bedrock. Thus, the assumption was made that in wells where the total well depth was at least 20 ft greater than the casing depth, the unconsolidated thickness was estimated to be 10 ft less than casing length. This subtraction was performed within ArcGIS. 2019 DOT - Minimum Depth Bedrock Valley: New York Department of Transportation (DOT) wells were provided to the USGS by the DOT in a ready to view shapefile. The shapefile contained an image of geologic layers, description of geologic layers and sediment types at depth. When used, points were manually added to the location of the borehole and geologic layers were added as depths and thicknesses within the point dataset. When data was lacking and in an area and DOT logs did not have a BR depth, it was assumed that the depth of the borehole was the bedrock depth (to ensure that bedrock was not modeled excessively shallow). 2019 Minimum Depth Bedrock Valley: Minimum bedrock depths for DEC wells were used when data was lacking. DEC wells were provided to the USGS by the NY DEC. Every log within the study area was looked at and geologic layers pertaining to the hydrogeologic framework were recorded in an excel spreadsheet before being uploaded into ArcGIS as a point dataset. When available, point datasets eventually contained elevations of the bottom of the unconfined aquifer (L1), bottom of the confining unit (L2), and top of bedrock (L3). When data was lacking in an area, but a relatively deep well was present, it was assumed that the depth of the well was the bedrock depth (to ensure that bedrock was not modeled excessively shallow). 2019 Smoothing points: smoothing points were added for both bedrock and valley fill hydrogeologic layers to help guide the interpolation in areas where data was lacking, or to mimic known valley fill shapes (i.e. the U shape of typical valley fill valleys). For bedrock, equidistant smoothing points (200 feet) were generated in a straight line down the center of the valley. Smoothing points nearby known bedrock elevations (i.e a bedrock elevation derived from a well log or cross section) were assigned the known value. Points in between these were assigned values calculated from the linear difference between the two known points. These points assure that valley shape (i.e deep part of valley typically in the center of the valley) is preserved. Smoothing points were also added within select regions of the study area for defining the bottom of L1 and L2 where data was extremely sparse. Smoothing point values were assigned in a similar manner as bedrock, but with larger spacing between points. 2019 Valley Edge Points: Valley edge points were first generated by creating points spaced 200 feet apart placed along the aquifer boundary (assumed to be the valley edge). Bedrock was assumed to be close to the surface at these points (3.35 meters) in order to give the valley a clear U shape (common in valley fill aquifers). If strong upland bedrock data (i.e multiple well logs near the valley edge) was present that indicated a thickness greater than 3.35 meters, that data was incorporated into the nearby points. 2019 SSURGO - Bedrock Uplands: In order to add these points, SSURGO polygons were downloaded from the NY GIS Clearinghouse. Specific polygons were isolated based on known soil types that were shallow to bedrock or based on keywords that indicated that bedrock was at or near the surface. Next, a point grid (spaced 300 feet apart) was added over the entire study area and points were selected that fell within shallow bedrock SSURGO polygons. These points were assigned a depth to bedrock indicative of the minimum thickness used within this study area (i.e. 3 meters). 2019 Bedrock elevation values were calculated by first extracting surface elevation from the LIDAR at each well point location. The extracted LIDAR value was subtracted by the depth to bedrock value for each supplemental point, which would equal the bedrock elevation. Other layer elevations were also calculated in this manner. 2019 1.0E-5 1.0E-5 Decimal degrees D_North_American_1983 NAD_1983 6378137.0 298.257222101 North American Vertical Datum of 1988 0.01 meter Explicit elevation coordinate included with horizontal coordinates Cincinnatus_Supplementary_Points This shapefile contains data points with values that are inferred or interpreted based on associated data or geologic assumptions. These data are used to help guide and improve the corresponding interpolations in ways that best represent valley fill aquifers and till covered uplands. The authors of this dataset conceived these values WellNO This column only applies to 12 wells and/or DOT boreholes. For these wells, a casing method (extensively defined in Finkelstein and others, 2022) was used to establish the minimum depth to bedrock. This column serves to identify the name of these wells/boreholes Producer defined This column describes names, and thus does not have a set defined value or variable Latitude The latitude in decimal degrees of the associated point Producer defined 42.488559 42.636438 Decimal degrees Longitude The longitude in decimal degrees of the associated point Producer defined -76.00454 -75.732029 Decimal degrees Point_Type Describes what kind of supplemental point the row is describing. For ease, multiple point types were compiled into one shapefile rather than having multiple datasets. The name and description of what each point type represent are further described below Producer defined Casing - Minimum Depth Bedrock Uplands These points predict the depth to bedrock, calculated using the casing method described in Finkelstein and others, 2022 Producer-defined DOT - Minimum Depth Bedrock Valley These points predict the minimum possible depth to bedrock, calculated using bridge boring logs provided by the New York Department of Transportation. This approach was only used in area where bedrock data was extremely sparse. Thus using a minimum bedrock depth provided better information for the model Producer-defined Minimum Depth Bedrock Valley These points predict the minimum possible depth to bedrock, calculated using DEC well logs. This approach was only used in area where bedrock data was extremely sparse. Thus using a minimum bedrock depth provided better information for the model Producer-defined Smoothing - Bedrock Valley These are equidistant (200 feet) points generated in a straight line down the center of the valley. Points nearby known bedrock elevations are assigned the known value. Points in between these are assigned values based on the linear difference between the two known points. These points assure that valley shape (i.e deep part of valley typically in the center of the valley) is preserved Producer-defined Smoothing - Layer 1 Smoothing points were added in data sparse regions between two known points to help guide the interpolation Producer-defined Smoothing - Layer 2 Smoothing points were added in data sparse regions between two known points to help guide the interpolation Producer-defined SSURGO - Bedrock Uplands Points spaced 200 feet apart (grid fashion) within SSURGO polygons deemed to have bedrock within 3 meters of the surface. These points allowed better constraint to upland bedrock surface where data was sparse Producer-defined Valley edge - Bedrock Uplands and Valley Points spaced 200 feet apart placed along the aquifer boundary (assumed to be the valley edge). Bedrock was assumed to be close to the surface at these points (3.35 meters) in order to give the valley a clear U shape (common in valley fill aquifers). If strong upland bedrock data was present that indicated a thickness greater than 3.35, that data was incorporated into the nearby points. Producer-defined Comments Assorted comments pertaining to select points, used to provide additional clarity about the smoothing point (when provided) Producer defined Assorted comments pertaining to select points, used to provide additional clarity about the smoothing point (when provided) Elev_Meter The surface elevation of various geologic layers (identified in the "Point_Type" column) in meters. Producer defined 270.669006 569.369995 Meters DTB_Meters The depth to bedrock calculated from the land surface elevation minus the bedrock surface elevation. Any value of 0 is a NULL value within the provided shapefile. This is not applicable for the accompanying feature class, as the NULL values will be shown. Producer defined 0.441007 39.878908 Meters ScienceBase U.S. Geological Survey mailing and physical

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Denver CO 80225 USA 1-888-275-8747 sciencebase@usgs.gov Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. Not for navigational use. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. 20260424 Josh Woda The United States Geologic Survey Hydrologist mailing and physical

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Troy New York 12180 The United States 518-285-5606 jwoda@USGS.gov Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998