Item talk:Q317858
From geokb
{
"DOI": {
"doi": "10.5066/p9ful880",
"identifiers": [],
"creators": [
{
"name": "Carol L Luukkonen",
"nameType": "Personal",
"affiliation": [
"United States Geological Survey"
],
"nameIdentifiers": [
{
"schemeUri": "https://orcid.org",
"nameIdentifier": null,
"nameIdentifierScheme": "ORCID"
}
]
},
{
"name": "Ayman H Alzraiee",
"nameType": "Personal",
"affiliation": [
"United States Geological Survey"
],
"nameIdentifiers": [
{
"schemeUri": "https://orcid.org",
"nameIdentifier": null,
"nameIdentifierScheme": "ORCID"
}
]
},
{
"name": "Joshua D Larsen",
"nameType": "Personal",
"affiliation": [
"United States Geological Survey"
],
"nameIdentifiers": [
{
"schemeUri": "https://orcid.org",
"nameIdentifier": null,
"nameIdentifierScheme": "ORCID"
}
]
},
{
"name": "Donald Martin",
"nameType": "Personal",
"affiliation": [
"United States Geological Survey"
],
"nameIdentifiers": [
{
"schemeUri": "https://orcid.org",
"nameIdentifier": null,
"nameIdentifierScheme": "ORCID"
}
]
},
{
"name": "Deidre M Herbert",
"nameType": "Personal",
"affiliation": [
"United States Geological Survey"
],
"nameIdentifiers": [
{
"schemeUri": "https://orcid.org",
"nameIdentifier": null,
"nameIdentifierScheme": "ORCID"
}
]
},
{
"name": "Cheryl A Buchwald",
"nameType": "Personal",
"affiliation": [
"United States Geological Survey"
],
"nameIdentifiers": [
{
"schemeUri": "https://orcid.org",
"nameIdentifier": "https://orcid.org/0000-0001-8968-5023",
"nameIdentifierScheme": "ORCID"
}
]
},
{
"name": "Natalie A Houston",
"nameType": "Personal",
"affiliation": [
"United States Geological Survey"
],
"nameIdentifiers": [
{
"schemeUri": "https://orcid.org",
"nameIdentifier": "https://orcid.org/0000-0002-6071-4545",
"nameIdentifierScheme": "ORCID"
}
]
},
{
"name": "Kristen J Valseth",
"nameType": "Personal",
"affiliation": [
"United States Geological Survey"
],
"nameIdentifiers": [
{
"schemeUri": "https://orcid.org",
"nameIdentifier": "https://orcid.org/0000-0003-4257-6094",
"nameIdentifierScheme": "ORCID"
}
]
},
{
"name": "Scott Paulinski",
"nameType": "Personal",
"affiliation": [
"United States Geological Survey"
],
"nameIdentifiers": [
{
"schemeUri": "https://orcid.org",
"nameIdentifier": null,
"nameIdentifierScheme": "ORCID"
}
]
},
{
"name": "Lisa D Miller",
"nameType": "Personal",
"affiliation": [
"United States Geological Survey"
],
"nameIdentifiers": [
{
"schemeUri": "https://orcid.org",
"nameIdentifier": "https://orcid.org/0000-0002-3523-0768",
"nameIdentifierScheme": "ORCID"
}
]
},
{
"name": "Richard Niswonger",
"nameType": "Personal",
"affiliation": [
"United States Geological Survey"
],
"nameIdentifiers": [
{
"schemeUri": "https://orcid.org",
"nameIdentifier": "https://orcid.org/0000-0001-6397-2403",
"nameIdentifierScheme": "ORCID"
}
]
},
{
"name": "Jana S Stewart",
"nameType": "Personal",
"affiliation": [
"United States Geological Survey"
],
"nameIdentifiers": [
{
"schemeUri": "https://orcid.org",
"nameIdentifier": "https://orcid.org/0000-0002-8121-1373",
"nameIdentifierScheme": "ORCID"
}
]
},
{
"name": "Cheryl A Dieter",
"nameType": "Personal",
"affiliation": [
"United States Geological Survey"
],
"nameIdentifiers": [
{
"schemeUri": "https://orcid.org",
"nameIdentifier": "https://orcid.org/0000-0002-5786-4091",
"nameIdentifierScheme": "ORCID"
}
]
}
],
"titles": [
{
"title": "Public supply water use reanalysis for the 2000-2020 period by HUC12, month, and year for the conterminous United States (ver. 2.0, August 2024)"
}
],
"publisher": "U.S. Geological Survey",
"container": {},
"publicationYear": 2023,
"subjects": [
{
"subject": "water resources"
}
],
"contributors": [],
"dates": [
{
"date": "2024-08-27",
"dateType": "Updated"
}
],
"language": null,
"types": {
"ris": "DATA",
"bibtex": "misc",
"citeproc": "dataset",
"schemaOrg": "Dataset",
"resourceType": "Dataset",
"resourceTypeGeneral": "Dataset"
},
"relatedIdentifiers": [],
"relatedItems": [],
"sizes": [],
"formats": [],
"version": null,
"rightsList": [
{
"rights": "Creative Commons Zero v1.0 Universal",
"rightsUri": "https://creativecommons.org/publicdomain/zero/1.0/legalcode",
"schemeUri": "https://spdx.org/licenses/",
"rightsIdentifier": "cc0-1.0",
"rightsIdentifierScheme": "SPDX"
}
],
"descriptions": [
{
"description": "The U.S. Geological Survey is developing national water-use models to support water resources management in the United States. Model benefits include a nationally consistent estimation approach, greater temporal and spatial resolution of estimates, efficient and automated updates of results, and capabilities to forecast water use into the future and assess model uncertainty. The term \u201creanalysis\u201d refers to the process of reevaluating and recalculating water-use data using updated or refined methods, data sources, models, or assumptions. In this data release, water use refers to water that is withdrawn by public and private water suppliers and includes water provided for domestic, commercial, industrial, thermoelectric power, and public water uses, as well as water that is consumed or lost within the public supply system. Consumptive use refers to water withdrawn by the public supply system that is evaporated, transpired, incorporated into products or crops, or consumed by humans or livestock.\n\nThis data release contains data used in a machine learning model (child item 2) to estimate monthly water use for communities that are supplied by public-supply water systems in the conterminous United States for 2000-2020. This data release also contains associated scripts used to produce input features (child items 4 - 8) as well as model water use estimates by 12-digit hydrologic unit code (HUC12) and public supply water service area (WSA). HUC12 boundaries are in child item 3. Public supply delivery and consumptive use estimates are in child items 1 and 9, respectively.\n\nFirst posted: November 1, 2023\nRevised: August 8, 2024\n\nThis version replaces the previous version of the data release:\nLuukkonen, C.L., Alzraiee, A.H., Larsen, J.D., Martin, D.J., Herbert, D.M., Buchwald, C.A., Houston, N.A., Valseth, K.J., Paulinski, S., Miller, L.D., Niswonger, R.G., Stewart, J.S., and Dieter, C.A., 2023, Public supply water use reanalysis for the 2000-2020 period by HUC12, month, and year for the conterminous United States: U.S. Geological Survey data release, https://doi.org/10.5066/P9FUL880\n\nVersion 2.0\nThis data release has been updated as of 8/8/2024. The previous version has been replaced because some fractions used for downscaling WSA estimates to HUC12 did not sum to one for some WSAs in Virginia. Updated model water use estimates by HUC12 are included in this version. A change was made in two scripts to check for this condition. Output files have also been updated to preserve the leading zero in in the HUC12 codes. Additional files are also included to provide information about mapping the WSAs and groundwater and surface water fractions to HUC12 and to provide public supply water-use estimates by WSA. The 'Machine learning model that estimates total monthly and annual per capita public supply water use' child item has been updated with these corrections and additional files. A new child item 'R code used to estimate public supply consumptive water use' has been added to provide estimates of public supply consumptive use.\n\nThis page includes the following files:\nPS_HUC12_Tot_2000_2020.csv - a csv file with estimated monthly public supply total water use from 2000-2020 by HUC12, in million gallons per day\nPS_HUC12_GW_2000_2020.csv - a csv file with estimated monthly public supply groundwater use for 2000-2020 by HUC12, in million gallons per day\nPS_HUC12_SW_2000_2020.csv - a csv file with estimated monthly public supply surface water use for 2000-2020 by HUC12, in million gallons per day\nPS_WSA_Tot_2000_2020.csv - a csv file with estimated monthly public supply total water use from 2000-2020 by WSA, in million gallons per day\nPS_WSA_GW_2000_2020.csv - a csv file with estimated monthly public supply groundwater use for 2000-2020 by WSA, in million gallons per day\nPS_WSA_SW_2000_2020.csv - a csv file with estimated monthly public supply surface water use for 2000-2020 by WSA, in million gallons per day\n Note: 1) Groundwater and surface water fractions were determined using source counts as described in the 'R code that determines groundwater and surface water source fractions for public-supply water service areas, counties, and 12-digit hydrologic units' child item. 2) Some HUC12s have estimated water use of zero because no public-supply water service areas were modeled within the HUC.\nchange_files_format.py - A Python script used to change the water use estimates by WSA and HUC12 files from wide format to the thin and long format version_history.txt - a txt file describing changes in this version\n\nThe data release is organized into these items:\n1. Machine learning model that estimates public supply deliveries for domestic and other use types - The public supply delivery model estimates total delivery of domestic, commercial, industrial, institutional, and irrigation (CII) water use for public supply water service areas within the conterminous United States. This item contains model input datasets, code used to build the delivery machine learning model, and output predictions.\n2. Machine learning model that estimates total monthly and annual per capita public supply water use - The public supply water use model estimates total monthly water use for 12-digit hydrologic units within the conterminous United States. This item contains model input datasets, code used to build the water use machine learning model, and output predictions.\n3. National watershed boundary (HUC12) dataset for the conterminous United States, retrieved 10/26/2020 - Spatial data consisting of a shapefile with 12-digit hydrologic units for the conterminous United States retrieved 10/26/2020.\n4. Python code used to determine average yearly and monthly tourism per 1000 residents for public-supply water service areas - This code was used to create a feature for the public supply model that provides information for areas affected by population increases due to tourism.\n5. Python code used to download gridMET climate data for public-supply water service areas - The climate data collector is a tool used to query climate data which are used as input features in the public supply models.\n6. Python code used to download U.S. Census Bureau data for public-supply water service areas - The census data collector is a geographic based tool to query census data which are used as input features in the public supply models.\n7. R code that determines buying and selling of water by public-supply water service areas - This code was used to create a feature for the public supply model that indicates whether public-supply systems buy water, sell water, or neither buy nor sell water.\n8. R code that determines groundwater and surface water source fractions for public-supply water service areas, counties, and 12-digit hydrologic units - This code was used to determine source water fractions (groundwater and/or surface water) for public supply systems and HUC12s.\n9. R code used to estimate public supply consumptive water use - This code was used to estimate public supply consumptive water use using an assumed fraction of deliveries for outdoor irrigation and estimates of evaporative demand. This item contains estimated monthly public supply consumptive use datasets by HUC12 and WSA.\n\nThis page includes the following files:\nPS_HUC12_Tot_2000_2020.csv - a csv file with monthly public supply reanalysis of withdrawals from 2000-2020 by HUC12.\nPS_HUC12_GW_2000_2020.csv -a csv file with estimated monthly public supply groundwater use for 2000-2020 by HUC12\nPS_HUC12_SW_2000_2020.csv - a csv file with estimated monthly public supply surface water use for 2000-2020 by HUC12\n Note: 1) Groundwater and surface water fractions were determined using source counts as described in the 'R code that determines groundwater and surface water source fractions for public-supply water service areas, counties, and 12-digit hydrologic units' child item. 2) Some HUC12s have estimated water use of zero because no public-supply water service areas were modeled within the HUC.\n\nThe data release is organized into these items:\n1. Machine learning model that estimates public supply deliveries for domestic and other use types - The public supply delivery model estimates total delivery of domestic, commercial, industrial, institutional, and irrigation (CII) water use for public supply water service areas within the conterminous United States. This item contains model input datasets, code used to build the delivery machine learning model, and output predictions.\n2. Machine learning model that estimates total monthly and annual per capita public supply withdrawals - The public supply water use model estimates total monthly water withdrawals for 12-digit hydrologic units within the conterminous United States. This item contains model input datasets, code used to build the water use machine learning model, and output predictions.\n3. National watershed boundary (HUC12) dataset for the conterminous United States, retrieved 10/26/2020 - Spatial data consisting of a shapefile with 12-digit hydrologic units for the conterminous United States retrieved 10/26/2020.\n4. Python code used to determine average yearly and monthly tourism per 1000 residents for public-supply water service areas - This code was used to create a feature for the public supply model that provides information for areas affected by population increases due to tourism.\n5. Python code used to download gridMET climate data for public-supply water service areas - The climate data collector is a tool used to query climate data which are used as input features in the public supply models.\n6. Python code used to download U.S. Census Bureau data for public-supply water service areas - The census data collector is a geographic based tool to query census data which are used as input features in the public supply models.\n7. R code that determines buying and selling of water by public-supply water service areas - This code was used to create a feature for the public supply model that indicates whether public-supply systems buy water, sell water, or neither buy nor sell water.\n8. R code that determines groundwater and surface water source fractions for public-supply water service areas, counties, and 12-digit hydrologic units - This code was used to determine source water fractions (groundwater and/or surface water) for public supply systems and HUC12s.",
"descriptionType": "Abstract"
}
],
"geoLocations": [],
"fundingReferences": [],
"url": "https://www.sciencebase.gov/catalog/item/65f86970d34e97daac9ff4c8",
"contentUrl": null,
"metadataVersion": 2,
"schemaVersion": "http://datacite.org/schema/kernel-4",
"source": "mds",
"isActive": true,
"state": "findable",
"reason": null,
"viewCount": 0,
"downloadCount": 0,
"referenceCount": 0,
"citationCount": 0,
"partCount": 0,
"partOfCount": 0,
"versionCount": 0,
"versionOfCount": 0,
"created": "2023-11-01T14:26:17Z",
"registered": "2023-11-01T14:26:18Z",
"published": null,
"updated": "2024-08-27T15:54:58Z"
}
}
