Get valuable legal information effortlessly with APISCRAPY's services – USA Court Data, USA Litigation Data, and US County Legal Data. Our user-friendly offerings include a handy Court Data API, providing you with all the legal details you need for your decision-making.

This data package aims to pilot an approach for providing usable data for analyses related to drought planning and management for urban water suppliers--ultimately contributing to improvements in communication around drought. This project was convened by the California Water Data Consortium in partnership with the Department of Water Resources (DWR) and the State Water Resources and Control Board (SWB) and is one of two use cases of this working group that aim to improve data submitted by urban water suppliers in terms of accessibility and useability. The datasets from DWR and the SWB are compiled in a standard format to allow interested parties to synthesize and analyze these data into a cohesive message. This package includes a data management plan describing its development and maintenance. All code related to preparing this data package can be found on GitHub. Please note that the "org_id" (DWR's Organization ID) and the "pwsid" (SWB's Public Water System ID) can be used to connect to the various data tables in this package.

We acknowledge that data quality issues may exist. Making these data available in a usable format will help identify and address data quality issues. If you identify any data quality issues, please contact the data steward (see contact information). We plan to iteratively update this data package to incorporate new data and to update existing data with quality fixes. The purpose of this project is to demonstrate how data from two agencies, when made publicly available, can be used in relevant analyses; if you found this data package useful, please contact the data steward (see contact information) to share your experience.

This record is for Approval for Access (AfA) product AfA445. The Water Resource Availability and Abstraction Reliability Cycle 2 dataset indicates whether, and for what percentage of time, additional water may be available for consumptive abstraction (subject to assessment of local risks) for each Water Framework Directive Cycle 2 water body. Each water body is colour coded as follows: • Green - Water available for licensing • Yellow - Restricted water available for licensing • Red - Water not available for licensing • Grey - Heavily Modified Waterbodies (and /or discharge rich water bodies) This data is not raw, factual or measured. It comprises of estimated or modelled results showing expected outcomes based on the data available to us. Attribution statement: © Environment Agency copyright and/or database right 2015. All rights reserved.

The OPERA_L3_DIST-ALERT-HLS Version 0 data product was decommissioned on April 25, 2025. Users are encouraged to use the OPERA_L3_DIST-ALERT-HLS V1 data product which was released on March 14, 2024, and has achieved stage 1 validation.

The Observational Products for End-Users from Remote Sensing Analysis (OPERA) Land Surface Disturbance Alert from Harmonized Landsat Sentinel-2 (HLS) provisional data product Version 0 maps vegetation disturbance alerts from data collected by Landsat 8 and Landsat 9 Operational Land Imager (OLI) and Sentinel-2A, Sentinel-2B, and Sentinel-2C Multi-Spectral Instrument (MSI). Vegetation disturbance alert is detected at 30 meter (m) spatial resolution when there is an indicated decrease in vegetation cover within an HLS pixel. The product also provides auxiliary generic disturbance information as determined from the variations of the reflectance through the HLS scenes to provide information about more general disturbance trends. HLS data represent the highest temporal frequency data available at medium spatial resolution. The combined observations will provide greater sensitivity to land changes, whether of large magnitude/short duration, or small magnitude/long duration.

The OPERA_L3_DIST-ALERT-HLS (or DIST-ALERT) data product is provided in Cloud Optimized GeoTIFF (COG) format, and each layer is distributed as a separate file. There are 19 layers contained within in the DIST-ALERT product: vegetation disturbance status, current vegetation cover indicator, current vegetation anomaly value, historical vegetation cover indicator, max vegetation anomaly value, vegetation disturbance confidence layer, date of initial vegetation disturbance, number of detected vegetation loss anomalies, and vegetation disturbance duration. See the Product Specification for a more detailed description of the individual layers provided in the DIST-ALERT product.

Known Issues * Additional usage constraints are provided under Section 5 of the Algorithm Theoretical Basis Document (ATBD).

About this dataset

Context

This list ranks the 4 cities in the Fayette County, OH by Taiwanese population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Taiwanese Population: This column displays the rank of city in the Fayette County, OH by their Taiwanese population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• Taiwanese Population: The Taiwanese population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as Taiwanese. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Fayette County Taiwanese Population: This tells us how much of the entire Fayette County, OH Taiwanese population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

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/.

About this dataset

Context

This list ranks the 18 cities in the Nevada by Vietnamese population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Vietnamese Population: This column displays the rank of city in the Nevada by their Vietnamese population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• Vietnamese Population: The Vietnamese population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as Vietnamese. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Nevada Vietnamese Population: This tells us how much of the entire Nevada Vietnamese population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

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/.

The table NE- Demographic Data is part of the dataset Demographic Data, available at https://columbia.redivis.com/datasets/fh74-90v3ge9m2. It contains 1182076 rows across 699 variables.

This table presents the water accounts, being part of the environmental accounts compiled by Statistics Netherlands annually. This Water Accounting table includes the (physical) water use by the Dutch economy. A distinction is made between the use of tap water, use and abstraction (withdrawal) of groundwater and of surface water. The water used is allocated to the industries and households. Alternatively, tables selections can be made that show break down by economic activity (including households), by water type and annual use. Values are shown in million cubic meters of water (mln m³).

With tap water, a distinction is made between tap water of drinking water quality and industrial water. Industrial water is tap water with a less quality than drinking water, or sometimes with a better quality, like demineralized water. This industrial water is mainly used by the industry and electricity producers. For surface water a distinction is made between fresh surface water and seawater. Within all water types (except drinking water) a distinction is made between use for cooling and use for other purposes. The distinction between use for cooling and use for other purposes is recently added from 2022. Therefore, the trend between 2022 and 2023 can be volatile. The data are derived from a diverse set of sources, more about those sources can be found in chapter 4.

Data in the environmental accounts directly correspond to the economic data in the national accounts, that allows assessment of the impact of the economic activities of the Netherlands for the use of water taken from the natural environment in quantitative terms. From the water accounts bills, environmental indicators can be derived. As an example the water use intensity for the different types can be determined for the Netherlands as a whole or for the break down by industry.

Data available from: 2003

Status of the figures: The data for the respective years in the full time series in this table are final and the last three years are provisional. The entire time series from 2003 onwards, if necessary, is to be adjusted to reflect the updated source information. Part of the tapwater (drinking water and industrial water) data is not yet available for the year 2022 and 2023. The missing values are specified as dots and will be updated in the next year in 2026. The whole time series will be updated in 2026 due to improved data sources and improvements in the time series.

Changes as of April 2025: Figures for 2023 have been added.

When will new figures be published? The next publication will be in September 2026.

🇺🇸 미국 English This dataset of U.S. mortality trends since 1900 highlights the differences in age-adjusted death rates and life expectancy at birth by race and sex. Age-adjusted death rates (deaths per 100,000) after 1998 are calculated based on the 2000 U.S. standard population. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years between 2000 and 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Data on age-adjusted death rates prior to 1999 are taken from historical data (see References below). Life expectancy data are available up to 2017. Due to changes in categories of race used in publications, data are not available for the black population consistently before 1968, and not at all before 1960. More information on historical data on age-adjusted death rates is available at https://www.cdc.gov/nchs/nvss/mortality/hist293.htm. SOURCES CDC/NCHS, National Vital Statistics System, historical data, 1900-1998 (see https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm); CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov). REFERENCES 1. National Center for Health Statistics, Data Warehouse. Comparability of cause-of-death between ICD revisions. 2008. Available from: http://www.cdc.gov/nchs/nvss/mortality/comparability_icd.htm. 2. National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. 3. Kochanek KD, Murphy SL, Xu JQ, Arias E. Deaths: Final data for 2017. National Vital Statistics Reports; vol 68 no 9. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_09-508.pdf. 4. Arias E, Xu JQ. United States life tables, 2017. National Vital Statistics Reports; vol 68 no 7. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_07-508.pdf. 5. National Center for Health Statistics. Historical Data, 1900-1998. 2009. Available from: https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm.

This data set contains estimated teen birth rates for age group 15–19 (expressed per 1,000 females aged 15–19) by county and year.

DEFINITIONS

Estimated teen birth rate: Model-based estimates of teen birth rates for age group 15–19 (expressed per 1,000 females aged 15–19) for a specific county and year. Estimated county teen birth rates were obtained using the methods described elsewhere (1,2,3,4). These annual county-level teen birth estimates “borrow strength” across counties and years to generate accurate estimates where data are sparse due to small population size (1,2,3,4). The inferential method uses information—including the estimated teen birth rates from neighboring counties across years and the associated explanatory variables—to provide a stable estimate of the county teen birth rate.
Median teen birth rate: The middle value of the estimated teen birth rates for the age group 15–19 for counties in a state.
Bayesian credible intervals: A range of values within which there is a 95% probability that the actual teen birth rate will fall, based on the observed teen births data and the model.

NOTES

Data on the number of live births for women aged 15–19 years were extracted from the National Center for Health Statistics’ (NCHS) National Vital Statistics System birth data files for 2003–2015 (5).

Population estimates were extracted from the files containing intercensal and postcensal bridged-race population estimates provided by NCHS. For each year, the July population estimates were used, with the exception of the year of the decennial census, 2010, for which the April estimates were used.

Hierarchical Bayesian space–time models were used to generate hierarchical Bayesian estimates of county teen birth rates for each year during 2003–2015 (1,2,3,4).

The Bayesian analogue of the frequentist confidence interval is defined as the Bayesian credible interval. A 100*(1-α)% Bayesian credible interval for an unknown parameter vector θ and observed data vector y is a subset C of parameter space Ф such that
1-α≤P({C│y})=∫p{θ │y}dθ,
where integration is performed over the set and is replaced by summation for discrete components of θ. The probability that θ lies in C given the observed data y is at least (1- α) (6).

County borders in Alaska changed, and new counties were formed and others were merged, during 2003–2015. These changes were reflected in the population files but not in the natality files. For this reason, two counties in Alaska were collapsed so that the birth and population counts were comparable. Additionally, Kalawao County, a remote island county in Hawaii, recorded no births, and census estimates indicated a denominator of 0 (i.e., no females between the ages of 15 and 19 years residing in the county from 2003 through 2015). For this reason, Kalawao County was removed from the analysis. Also , Bedford City, Virginia, was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. For consistency, Bedford City was merged with Bedford County, Virginia, for the entire 2003–2015 period. Final analysis was conducted on 3,137 counties for each year from 2003 through 2015. County boundaries are consistent with the vintage 2005–2007 bridged-race population file geographies (7).

SOURCES

National Center for Health Statistics. Vital statistics data available online, Natality all-county files. Hyattsville, MD. Published annually.

For details about file release and access policy, see NCHS data release and access policy for micro-data and compressed vital statistics files, available from: http://www.cdc.gov/nchs/nvss/dvs_data_release.htm.

For natality public-use files, see vital statistics data available online, available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm.

National Center for Health Statistics. U.S. Census populations with bridged race categories. Estimated population data available. Postcensal and intercensal files. Hyattsville, MD. Released annually.

For population files, see U.S. Census populations with bridged race categories, available from: https://www.cdc.gov/nchs/nvss/bridged_race.htm.

REFERENCES

1. Khan D, Rossen LM, Hamilton B, Dienes E, He Y, Wei R. Spatiotemporal trends in teen birth rates in the USA, 2003–2012. J R Stat Soc A 181(1):35–58. 2017. Available from: http://onlinelibrary.wiley.com/doi/10.1111/rssa.12266/abstract.

2. Khan D, Rossen LM, Hamilton BE, He Y, Wei R, Dienes E. Hot spots, cluster detection and spatial outlier analysis of teen birth rates in the U.S., 2003–2012. Spat Spatiotemporal Epidemiol 21:67–75. 2017. Available from: http://www.sciencedirect.com/science/article/pii/S1877584516300442.

3. Rue H, Martino S, Lindgren F. INLA: Functions which allow to perform a full Bayesian analysis of structured additive models using Integrated Nested Laplace Approximation. R package, version 0.0. 2009.

4. Rue H, Martino S, Chopin N. Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. J R Stat Soc B 71(2):319–92. 2009.

5. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Mathews TJ. Births: Final data for 2015. National Vital Statistics Reports; vol 66 no 1. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_01.pdf (1.9 MB).

6. Carlin BP, Louis TA. Bayesian methods for data analysis. Boca Raton, FL: CRC Press, 2009.

7. National Center for Health Statistics. County geography changes: 1990–2012. Available from: http://www.cdc.gov/nchs/data/nvss/bridged_race/County_Geography_Changes.pdf (39 KB).

Country Population (Admin0) using aggregated Facebook high resolution population density data (https://data.humdata.org/organization/facebook).The world population data sourced from Facebook Data for Good is some of the most accurate population density data in the world. The data is accumulated using highly accurate technology to identify buildings from satellite imagery and can be viewed at up to 30-meter resolution. This building data is combined with publicly available census data to create the most accurate population estimates. This data is used by a wide range of nonprofit and humanitarian organizations, for example, to examine trends in urbanization and climate migration or discover the impact of a natural disaster on a region. This can help to inform aid distribution to reach communities most in need. There is both country and region-specific data available. The data also includes demographic estimates in addition to the population density information. This population data can be accessed via the Humanitarian Data Exchange website.

About this dataset

Context

This list ranks the 2 cities in the Knox County, TN by Japanese population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Japanese Population: This column displays the rank of city in the Knox County, TN by their Japanese population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• Japanese Population: The Japanese population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as Japanese. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Knox County Japanese Population: This tells us how much of the entire Knox County, TN Japanese population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

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/.

About this dataset

Context

This list ranks the 16 cities in the Brevard County, FL by Taiwanese population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Taiwanese Population: This column displays the rank of city in the Brevard County, FL by their Taiwanese population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• Taiwanese Population: The Taiwanese population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as Taiwanese. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Brevard County Taiwanese Population: This tells us how much of the entire Brevard County, FL Taiwanese population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

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/.

Displacement risk indicator showing the distribution of renter households and renter units between different income brackets, covering the entire city from 2006 to the most recent year of data available.

About this dataset

Context

This list ranks the 17 cities in the Cache County, UT by Finnish population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Finnish Population: This column displays the rank of city in the Cache County, UT by their Finnish population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• Finnish Population: The Finnish population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as Finnish. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Cache County Finnish Population: This tells us how much of the entire Cache County, UT Finnish population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

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/.

About the Dataset This dataset contains contact and program participation information for each site participating in the Seamless Summer Option (SSO) for summer 2019 (SNP program year 2018-2019). The active application period for summer program participants runs January through April. Changes in participant information can occur through August. Summer meals programs operate mid-May through the end of August. New Data Fields Available! CE and site status (active/inactive), termination status, termination as of date, and application cycle (new/renewal) are now available on this dataset. These fields have been added to the last columns of the report and data descriptions have been added to the column metadata. An overview of all Summer Meal Program data available on the Texas Open Data Portal can be found at our TDA Data Overview - Summer Meals Programs page. An overview of all TDA Food and Nutrition data available on the Texas Open Data Portal can be found at our TDA Data Overview - Food and Nutrition Open Data page. More information about accessing and working with TDA data on the Texas Open Data Portal can be found on the SquareMeals.org website on the TDA Food and Nutrition Open Data page. About Dataset Updates TDA aims to post new program participation data by April 1 of the active program year. Due to the short duration of the summer meal programs, updates to the program participation dataset will occur every two weeks until the end of August. All TDA datasets will have a final active update 90 days after the close of the program period. Datasets will be updated at six months and one year from the close of program period before becoming archived. Any data posted during the active update schedule is subject to change. A detailed list of TDA Food and Nutrition datasets and data fields available on the Texas Open Data Portal can be downloaded as a PDF here. About the Agency The Texas Department of Agriculture administers 12 U.S. Department of Agriculture nutrition programs in Texas including the National School Lunch and School Breakfast Programs, the Child and Adult Care Food Program (CACFP), and summer meal programs. TDA’s Food and Nutrition division provides technical assistance and training resources to partners operating the programs and oversees the USDA reimbursements they receive to cover part of the cost associated with serving food in their facilities. By working to ensure these partners serve nutritious meals and snacks, the division adheres to its mission — Feeding the Hungry and Promoting Healthy Lifestyles. For more information on these programs, please visit our website.

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. The Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) in cooperation with the Massachusetts Office of Coastal Zone Management, has compiled reliable historical shoreline data along open-facing sections of the Massachusetts coast under the Massachusetts Shoreline Change Mapping and Analysis Project 2013 Update. Two oceanfront shorelines for Massachusetts (approximately 1,800 km) were (1) delineated using 2008/09 color aerial orthoimagery, and (2) extracted from topographic LIDAR datasets (2007) obtained from NOAA's Ocean Service, Coastal Services Center. The new shorelines were integrated with existing Massachusetts Office of Coastal Zone Management and USGS historical shoreline data in order to compute long- and short-term rates using the latest version of the Digital Shoreline Analysis System (DSAS).

Groundwater levels have declined since the 1940s in the Wailuku area of central Maui, Hawaiʻi, on the eastern flank of West Maui volcano, mainly in response to increased groundwater withdrawals. Available data since the 1980s also indicate a thinning of the freshwater lens and an increase in chloride concentrations of pumped water from production wells. These trends, combined with projected increases in demand for groundwater in central Maui, have led to concerns over groundwater availability and have highlighted a need to improve understanding of the hydrologic effects of proposed groundwater withdrawals in the Waiheʻe, ʻĪao, and Waikapū areas of central Maui. A three-dimensional, variable-density solute-transport model (SUTRA) was developed to evaluate the effects of seven selected withdrawal/recharge scenarios on water levels and salinity of groundwater in central Maui, Hawaiʻi. The model was constructed using water-level and salinity data available for the period from 1926 to 2012. Groundwater recharge for the model was estimated using a daily water budget for the period of interest. Inflow of groundwater at the model boundaries was estimated from an existing island-wide numerical groundwater-flow model (Izuka and others, 2021, available at https://doi.org/10.3133/sir20205126). The data release also includes the SUTRA source code and executable file used to run the simulations. The SUTRA code was modified to include a simplified representation of water-table storage (Gingerich, 2008, available at https://pubs.usgs.gov/sir/2008/5236/; Gingerich and Engott, 2012, available at https://pubs.usgs.gov/sir/2012/5010/). This USGS data release contains all of the input and output files for the simulations described in the associated model documentation report (https://doi.org/10.3133/sir20215113).

About this dataset

Context

This list ranks the 5 cities in the Putnam County, FL by Sudanese population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Sudanese Population: This column displays the rank of city in the Putnam County, FL by their Sudanese population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• Sudanese Population: The Sudanese population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as Sudanese. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Putnam County Sudanese Population: This tells us how much of the entire Putnam County, FL Sudanese population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

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/.