Point locations of domestic wells reported to the Maine Geological Survey. This dataset is based on an original survey of well drillers in the 1970s, a voluntary well driller reporting program in the mid-1980s, and the present mandatory reporting program which relies on the submission of well information by drillers. Wells have been located using GPS coordinates submitted by the drillers, e911 address information submitted by the drillers and/or ownership data and tax records.

The table contains the domestic wells reported to the Maine Geological Survey that don't have spatial coordinates. This dataset is based on an original survey of well drillers in the 1970s, a voluntary well driller reporting program in the mid-1980s, and the present mandatory reporting program which relies on the submission of well information by drillers.

A dataset of well information and geospatial data was developed for 426 U.S. Geological Survey (USGS) observation wells in Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont. An extensive list of attributes is included about each well, its location, and water-level history to provide the public and water-resources community with comprehensive information on the USGS well network in New England and data available from these sites. These data may be useful for evaluating groundwater conditions and variability across the region. The well list and site attributes, which were extracted from USGS National Water Information System (NWIS), represent all of the active wells in the New England network up to the end of 2017, and an additional 45 wells that were inactive (discontinued or replaced by a nearby well) at that time. Inactive wells were included in the database because they (1) contain periods of water-level record that may be useful for groundwater assessments, (2) may become active again at some point, or (3) are being monitored by another agency (most discontinued New Hampshire wells are still being monitored and the data are available in the National Groundwater Monitoring Network (https://cida.usgs.gov/ngwmn/index.jsp). The wells in this database have been sites of water-level data collection (periodic levels and/or continuous levels) for an average of 31 years. Water-level records go back to 1913. The groundwater-level statistics included in the dataset represent hydrologic conditions for the period of record for inactive wells, or through the end of water year 2017 (September 30, 2017) for active wells. Geographic Information Systems (GIS) data layers were compiled from various sources and dates ranging from 2003 to 2018. These GIS data were used to calculate attributes related to topographic setting, climate, land cover, soil, and geology giving hydrologic and environmental context to each well. In total, the data include 90 attributes for each well. In addition to site number and station name, attributes were developed for site information (15 attributes); groundwater-level statistics through water year 2017 (16 attributes); well-construction information (9 attributes); topographic setting (11 attributes); climate (2 attributes); land use and cover (17 attributes); soils (4 attributes); and geology (14 attributes). Basic well and site information includes well location, period of record, well-construction details, continuous versus intermittent data collection, and ground altitudes. Attributes that may influence groundwater levels include: well depth, location of open or screened interval, aquifer type, surficial and bedrock geology, topographic position, flow distance to surface water, land use and cover near the well, soil texture and drainage, precipitation, and air temperature.

This resource contains Aqueous Chemistry observation data for water quality of domestic water wells compiled by the Maine Geological Survey. (This represents the 1.9 version of this service data, and is superseded by http://repository.stategeothermaldata.org/repository/resource/50ec3aefb656b70647f32e38bc0acf0d/.) The data is available in the following formats: web feature service, web map service, ESRI service endpoint, and an Excel workbook for download. The workbook contains 12 worksheets, including information about the template, notes related to revisions of the template, resource provider information, the data (see the 5 tabs representing the analyte layers in service), a field list (data mapping view), an analyte dictionary, and vocabularies (data valid terms) used to populate the data worksheet. This resource was provided by the Maine Geological Survey and made available for distribution through the National Geothermal Data System.

In fall 2001, researchers from the Wells National Estuarine Research Reserve, Virginia Institute of Marine Science, and the NOAA Office for Coastal Management conducted a project to map benthic habitats in the York and Webhannet rivers in southern Maine. The team completed two weeks of fieldwork in September 2001, collecting sediment profile images at 382 stations and sediment grab samples at 93 stations. This data set represents the information gathered from sediment profile imagery sampling. Original contact information: Contact Name: Dr. Michele Dionne Contact Org: Wells National Estuarine Research Reserve Phone: (207) 646-1555

The U.S. Geological Survey (USGS), in cooperation with the U.S. Centers for Disease Control and Prevention and the Maine Center for Disease Control and Prevention, assessed the physical and chemical characteristics and the occurrence, distribution, and oxidation state of inorganic arsenic in drinking water from selected domestic well-water supplies in Maine in 2001–2 and 2006–7. The data collected provide support for evaluating arsenic-removal efficiencies of household water-purification systems and provide information to State and local officials that can be used in determining a water-treatment approach for the removal of arsenic from drinking water.

This resource contains Heat Flow observation data for Maine provided by the Maine Geological Survey. The data are published in the Heat Flow schema version 1.3 as a Web feature service, a Web map service, an ESRI service endpoint, and as an Excel workbook for download. The Excel workbook contains six worksheets including information about the template, notes related to revisions of the template, resource provider information, the data, and a field list (data mapping view). The Excel workbook contains header features for Thermal Conductivity, Gradient, Heat Flow, and Heat Flow Correction Method for each observation. This resource was provided by the Maine Geological Survey and made available for distribution through the National Geothermal Data System.

Dataset contains point data describing the textures of surficial sediments, independent of interpretations regarding their origin mapped at a scale of 1;24,000, from the Maine Geological Survey. Thickness of gravel, sand, silt, clay, and diamicton is shown. Data comes from auger holes, test pits, well logs, test borings, and gravel pits. Mapped at a scale 1:24,000. Printed maps published by the Maine Geological Survey on USGS 7.5' quadrangle bases. Point data compiled and digitized by the Maine Geological Survey from data compiled on USGS 7.5' quadrangle bases. Point attribute table contains information on the type of data point and, where appropriate, depth to bedrock, depth to water table, well yield, and/or material type and thickness.

In fall 2001, researchers from the Wells National Estuarine Research Reserve, Virginia Institute of Marine Science, and the NOAA Office for Coastal Management conducted a project to map benthic habitats in the York and Webhannet rivers in southern Maine. The team completed two weeks of fieldwork in September 2001, collecting sediment profile images at 382 stations and sediment grab samples at 93 stations. This data set represents the benthic community information gathered from grab sampling. Original contact information: Contact Name: Dr. Michele Dionne Contact Org: Wells National Estuarine Research Reserve Phone: (207) 646-1555

Data from "Schools as Sources of PFAS Contamination of private wells in Rural Maine communities"

   In a community-engaged research project near Mount Desert Island High School in Bar Harbor, Maine, efforts were made to understand potential well contamination. This involved attending public meetings, distributing PFAS drinking water sample kits to homeowners, and collaborating on sample collection protocols. Surface water samples were collected from wetlands adjacent to the school, while drinking water samples were obtained from eight property owners, with careful adherence to sampling procedures to prevent contamination. Samples were analyzed for PFAS content and data are reported here.

no abstract provided

In July 1979, the Maine Office of Energy Resources, in conjunction with the Maine Geological Survey, began the Maine Peat Resource Evaluation Program. The Program, which was funded by the US Department of Energy (DOE), was undertaken to determine the amount and location of fuel-grade peat in Maine. Similar DOE/State Peat Resource Evaluation Programs are also being carried out in thirteen other states, including Alaska, Michigan, Minnesota, North Carolina, and South Carolina, whose programs began in 1979. Two hundred thirty-three areas containing peat deposits were evaluated under the Program. A total of 48 deposits covering 14,988 acres and containing 32,114,800 short tons (dry weight) of peat in Washington County have been evaluated under the Maine Peat Resource Evaluation Program. These deposits range in size from 40 to 2645 acres and in estimated resources from 40,000 to 6,953,000 short tons. Maps of individual deposits showing the distribution and depth of peat, core sites, and the surficial geology of the area adjacent to the deposits are shown in Figures 4 to 50. Cores showing the vertical distribution of peat and sediment as well as sample locations, and the results of laboratory analyses are also included. 22 references, 50 figures, 3 tables.

Point locations of domestic wells reported to the Maine Geological Survey. This dataset is based on an original survey of well drillers in the 1970s, a voluntary well driller reporting program in the mid-1980s, and the present mandatory reporting program which relies on the submission of well information by drillers. Wells have been located using GPS coordinates submitted by the drillers, e911 address information submitted by the drillers and/or ownership data and tax records.

In July 1979, the Maine Office of Energy Resources, in conjunction with the Maine Geological Survey, began the Maine Peat Resource Evaluation Program. The Program, which was funded by the US Department of Energy (DOE), was undertaken to determine the amount and location of fuel-grade peat in Maine. Two hundred thirty-three areas containing peat deposits were evaluated under the Program. A total of 47 deposits covering 21,666 acres and containing 40,923,000 short tons (dry weight) of peat in Penobscot County have been evaluated under the Maine Peat Resource Evaluation Program. These deposits range in size from 35 to 3301 acres and in estimated resources from 45,000 to 6,994,000 short tons. Maps of individual deposits showing the distribution and depth of peat, core sites, and the surficial geology of the area adjacent to the deposits are shown in Figures 4 to 46. Cores showing the vertical distribution of peat and sediment as well as sample locations, and the results of laboratory analyses are also included. 22 references, 46 figures, 3 tables.

The Digital Surficial Geologic-GIS Map of Mount Desert Island and Vicinity, Acadia National Park, Maine is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (acad_surficial_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (acad_surficial_geology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (acad_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (acad_surficial_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (acad_surficial_geology_metadata_faq.pdf). Please read the acad_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Maine Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (acad_surficial_geology_metadata.txt or acad_surficial_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual _location as presented by this dataset. Users of this data should thus not assume the _location of features is exactly where they are portrayed in Google Earth, ArcGIS Pro, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

About this dataset

Context

The dataset tabulates the population of Wells town by race. It includes the population of Wells town across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Wells town across relevant racial categories.

Key observations

The percent distribution of Wells town population by race (across all racial categories recognized by the U.S. Census Bureau): 91.93% are white, 2.24% are Black or African American, 0.02% are American Indian and Alaska Native, 2.58% are Asian, 0.39% are some other race and 2.84% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Wells town
• Population: The population of the racial category (excluding ethnicity) in the Wells town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Wells town total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Wells town Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the data for the Wells, Maine population pyramid, which represents the Wells town population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Wells, Maine, is 26.3.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Wells, Maine, is 52.4.
• Total dependency ratio for Wells, Maine is 78.7.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Wells, Maine is 1.9.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Wells town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Wells town for the selected age group is shown in the following column.
• Population (Female): The female population in the Wells town for the selected age group is shown in the following column.
• Total Population: The total population of the Wells town for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Wells town Population by Age. You can refer the same here

The Digital Surficial Geologic-GIS Map of the Schoodic Head Area, Acadia National Park, Maine is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (sche_surficial_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (sche_surficial_geology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (acad_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (acad_surficial_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (sche_surficial_geology_metadata_faq.pdf). Please read the acad_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Maine Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (sche_surficial_geology_metadata.txt or sche_surficial_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:62,500 and United States National Map Accuracy Standards features are within (horizontally) 31.8 meters or 104.2 feet of their actual _location as presented by this dataset. Users of this data should thus not assume the _location of features is exactly where they are portrayed in Google Earth, ArcGIS Pro, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

About this dataset

Context

The dataset tabulates the Wells town median household income by race. The dataset can be utilized to understand the racial distribution of Wells town income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Wells, Maine median household income breakdown by race betwen 2011 and 2021
• Median Household Income by Racial Categories in Wells, Maine (2021, in 2022 inflation-adjusted dollars)

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Wells town median household income by race. You can refer the same here