Timeline / Data.gov — Climate Datasets
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Evidence
| Source | Data.gov — Climate Datasets |
|---|---|
| Agency | Data.gov |
| URL | https://api.gsa.gov/technology/datagov/v4/search?q=climate&sort=last_harvested_date&per_page=100&api_key=${DATAGOV_API_KEY} |
| Observed by | Civic Memory, directly, on 2026-10-09T18:22:11+00:00 |
| Content type | application/json |
| Current object |
b4a68542fd83cd7f001668f67500c8ae89457c8a579dead1dab924fe36fe5676
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metadata
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| Previous object |
6b87667a021c060547ca90b90afcac5d8267ad2494f278bc9ac75021d615ce1f
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metadata
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What changed derived
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civic-memory.diff_engine 1.1.0 at
2026-10-09T18:22:11+00:00 by normalizing the two archived objects above. The
objects are authoritative; this reading of them can be regenerated or deleted
without loss. 5144 line(s) added, 5652 line(s) removed.
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In the model, recruitment and mortality of adult bees have substantial social components, with recruitment enhanced and mortality reduced by additional adult bee numbers. The result is an Allee effect, a net per-individual rate of hive increase that increases as a function of adult bee numbers. The Allee effect creates a critical minimum size in adult bee numbers, below which mortality is greater than recruitment, with ensuing loss of viability of the hive. Under ordinary and favorable environmental circumstances, the critical size is low, and hives remain large, sending off viably-sized swarms (naturally or through beekeeping management) when hive numbers approach an upper stable equilibrium size (carrying capacity). However, both the lower critical size and the upper stable size depend on many parameters related to demographic rates and their enhancement by bee sociality. Any environmental factors that increase mortality, decrease recruitment, or interfere with the social moderation of these rates has the effect of exacerbating the Allee effect by increasing the lower critical size and substantially decreasing the upper stable size. As well, the basin of attraction to the upper stable size, defined by the model potential function, becomes narrower and shallower, indicating the loss of resilience as the hive becomes subjected to increased risk of falling below the critical size. Environmental effects of greater severity can cause the two equilibria to merge and the basin of attraction to the upper stable size to disappear, resulting in collapse of the hive from any initial size. The model suggests that multiple proximate causes, among them pesticides, mites, pathogens, and climate change, working singly or in combinations, could trigger hive collapse. This data supplement provides a text file containing 7 scripts written in the R programming language for reproducing Figures 1–7. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: S1 R scripts for figures.</p> <p>File Name: Web Page, url: <a href=\"https://doi.org/10.1371/journal.pone.0150055.s001\">https://doi.org/10.1371/journal.pone.0150055.s001</a> </p><p>Text file containing 7 scripts written in the R programming language for reproducing Figs 1–7 of this article.</p><p>Resource Software Recommended: R programming language,url: <a href=\"https://www.r-project.org/\">https://www.r-project.org/</a> </p></li></ul><p></p>", + "@type": "vcard:Contact", + "fn": "Spatial Analysis Research Section", + "hasEmail": "mailto:nass@nass.usda.gov" + }, + "dataQuality": true, + "description": "VegScape is a geospatial data service which offers automated updates of vegetative condition at daily, weekly, and biweekly intervals. VegScape delivers interactive vegetation indices that enable quantification of U.S. crop conditions for exploring, visualizing, querying, and disseminating via interactive maps.", "distribution": [ { "@type": "dcat:Distribution", - "downloadURL": "https://doi.org/10.1371/journal.pone.0150055.s001", - "license": "https://creativecommons.org/licenses/by/4.0/", - "mediaType": "text/html", - "title": "https://doi.org/10.1371/journal.pone.0150055.s001" + "accessURL": "https://nassgeodata.gmu.edu/VegScape/", + "format": "HTML", + "license": "https://creativecommons.org/publicdomain/zero/1.0/", + "title": "VegScape" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://nassgeodata.gmu.edu/VegScape/devhelp/help.html", + "format": "API", + "license": "https://creativecommons.org/publicdomain/zero/1.0/", + "title": "VegScape API" } ], - "identifier": "10.1371/journal.pone.0150055", + "identifier": "USDA-NASS-00005", "keyword": [ - "ARS", - "data.gov", - "hive collapse" - ], - "license": "https://creativecommons.org/licenses/by/4.0/", - "modified": "2024-02-13", + "Agriculture", + "Condition", + "NASS", + "NDVI", + "USDA", + "data", + "vegetation", + "vegetation index" + ], + "license": "https://creativecommons.org/publicdomain/zero/1.0/", + "modified": "2015-01-28", "programCode": [ - "005:040" + "005:042" ], "publisher": { "@type": "org:Organization", - "name": "Agricultural Research Service" - }, - "title": "Data from: How Hives Collapse: Allee Effects, Ecological Resilience, and the Honey Bee" - }, - "description": "<p>A mathematical model is constructed to quantify the loss of resilience in collapsing honey bee colonies due to the presence of a strong Allee effect. In the model, recruitment and mortality of adult bees have substantial social components, with recruitment enhanced and mortality reduced by additional adult bee numbers. The result is an Allee effect, a net per-individual rate of hive increase that increases as a function of adult bee numbers. The Allee effect creates a critical minimum size in adult bee numbers, below which mortality is greater than recruitment, with ensuing loss of viability of the hive. Under ordinary and favorable environmental circumstances, the critical size is low, and hives remain large, sending off viably-sized swarms (naturally or through beekeeping management) when hive numbers approach an upper stable equilibrium size (carrying capacity). However, both the lower critical size and the upper stable size depend on many parameters related to demographic rates and their enhancement by bee sociality. Any environmental factors that increase mortality, decrease recruitment, or interfere with the social moderation of these rates has the effect of exacerbating the Allee effect by increasing the lower critical size and substantially decreasing the upper stable size. As well, the basin of attraction to the upper stable size, defined by the model potential function, becomes narrower and shallower, indicating the loss of resilience as the hive becomes subjected to increased risk of falling below the critical size. Environmental effects of greater severity can cause the two equilibria to merge and the basin of attraction to the upper stable size to disappear, resulting in collapse of the hive from any initial size. The model suggests that multiple proximate causes, among them pesticides, mites, pathogens, and climate change, working singly or in combinations, could trigger hive collapse. 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By testing and comparing different options with the model, those offering the greatest economic benefit with acceptable environmental impact can be found.</p>\n<p>Input information is supplied to the program through three parameter files. The farm parameter file contains data describing the farm such as crop areas, soil type, equipment and structures used, numbers of animals at various ages, harvest, tillage, and manure handling strategies, and prices for various farm inputs and outputs. The machinery file includes parameters for each machine available for use on a simulated farm.</p>\n<p>Simulation output is available in four files, which contain summary tables, report tables, optional tables, and parameter tables. The summary tables provide average performance, environmental impact, costs, and returns for the years simulated. These values consist of crop yields, feeds produced, feeds bought and sold, manure produced, nutrient losses to the environment, production costs, income from products sold, and the net return or profitability of the farm. Values are provided for the average and standard deviation of each over all simulated years. The report tables provide extensive output information including all the data given in the summary tables. In these tables, values are given for each simulated year of weather as well as the mean and variance over all simulated years. Optional tables are available for a closer inspection of how the components of the full simulation are functioning. These tables include very detailed data, often on a daily basis. Parameter tables summarize the input parameters specified for a given simulation. These tables provide a convenient method of documenting the parameter settings used for a simulation.</p>\n<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Projected Climate Data for IFSM.</p> <p>File Name: Web Page, url: <a href=\"https://www.ars.usda.gov/research/software/download/?softwareid=497&modecode=80-70-05-00\" target=\"_blank\">https://www.ars.usda.gov/research/software/download/?softwareid=497&modecode=80-70-05-00</a> </p><p>Downscaled climate data (1950 to 2100) are available for 78 locations across the United States formatted for use in IFSM. Each location includes 18 climate files created using 9 general circulation models (GCM) and 2 projected emission scenarios. Emission scenarios include Representative Concentration Pathways (RCP) 4.5 and 8.5 where RCP 4.5 represents a somewhat optimistic outlook for reducing greenhouse gas emissions and 8.5 represents continuing the current trend for emissions. </p></li></ul>", + "@type": "vcard:Contact", + "fn": "ASB Secretary", + "hasEmail": "mailto:nass@nass.usda.gov" + }, + "dataQuality": true, + "describedBy": { + "accessURL": "http://www.agcensus.usda.gov/Publications/2007/Full_Report/Volume_1,_Chapter_1_US/usappxb.pdf", + "mediaType": "application/pdf" + }, + "description": "Quick Stats API is the programmatic interface to the National Agricultural Statistics Service's (NASS) online database containing results from the 1997, 2002, 2007, and 2012 Censuses of Agriculture as well as the best source of NASS survey published estimates. The census collects data on all commodities produced on U.S. farms and ranches, as well as detailed information on expenses, income, and operator characteristics. The surveys that NASS conducts collect information on virtually every facet of U.S. agricultural production.", "distribution": [ { "@type": "dcat:Distribution", - "downloadURL": "https://www.ars.usda.gov/research/software/download/?softwareid=497&modecode=80-70-05-00", - "license": "https://www.usa.gov/publicdomain/label/1.0/", - "mediaType": "text/html", - "title": "https://www.ars.usda.gov/research/software/download/?softwareid=497&modecode=80-70-05-00" + "accessURL": "http://quickstats.nass.usda.gov/api", + "license": "http://creativecommons.org/publicdomain/zero/1.0/", + "title": "Quick Stats API" } ], - "identifier": "10113/AA7768", + "identifier": "USDA-NASS-00003", + "issued": "2014-05-02", "keyword": [ - "ARS", - "IFSM", - "Integrated Farm System Model", - "data.gov" - ], - "license": "https://www.usa.gov/publicdomain/label/1.0/", - "modified": "2024-02-09", + "African American operators", + "Agriculture", + "American Indian Reservation farms", + "Asian operators", + "Brussels sprouts", + "CCC", + "CRP", + "Chinese cabbage", + "Christmas trees", + "Commodity Credit Corporation loans", + "Conservation Reserve", + "Data", + "English walnuts", + "Farmable Wetlands", + "Hispanic operators", + "Latino operators", + "NAICS", + "NASS", + "North American Industry Classification System", + "Pacific Island operators", + "Spanish operators", + "Temples", + "USDA", + "Valencia oranges", + "Wetlands Reserve", + "abandoned", + "acres", + "ag land", + "ag services", + "age", + "agri-tourism", + "agriculture", + "alfalfa", + "alfalfa seed", + "almonds", + "alpacas", + "angora goats", + "apples", + "apricots", + "aquaculture", + "aquatic plants", + "artichokes", + "asparagus", + "avocados", + "bales", + "bananas", + "barley", + "bedding plants", + "bee colonies", + "beef cow", + "bees", + "beets", + "bell peppers", + "berries", + "bison", + "black operators", + "blackberries", + "blackeyed peas", + "blueberries", + "boysenberries", + "broccoli", + "broilers", + "bulbs", + "bull", + "burros", + "bushels", + "cabbage", + "calves", + "cantaloupes", + "carrots", + "cash rents", + "cattle", + "cauliflower", + "celery", + "chemicals", + "cherries", + "chestnuts", + "chickens", + "chicory", + "chile", + "citrus", + "coffee", + "collards", + "combines", + "conservation practices", + "contract labor", + "corms", + "corn", + "cotton", + "cotton pickers", + "cowpeas", + "cranberries", + "crop insurance", + "cropland", + "cucumbers", + "currants", + "custom hauling", + "customwork", + "cut flowers", + "cuttings", + "cwt", + "daikon", + "dairy products", + "dates", + "deer", + "dewberries", + "donkeys", + "dry edible beans", + "dry edible peas", + "ducks", + "durum wheat", + "eggplant", + "eggs", + "elk", + "emus", + "endive", + "equipment", + "escarole", + "ewe", + "experimental farms", + "farm demographics", + "farm economics", + "farm income", + "farm operations", + "farms", + "feed purchased", + "fertilizer", + "fescue seed", + "field crops", + "figs", + 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"woodland", + "woody crops", + "wool" + ], + "landingPage": { + "@type": "Document", + "accessURL": "http://www.nass.usda.gov/Quick_Stats/", + "title": "Quick Stats Agricultural Database API" + }, + "license": "http://creativecommons.org/publicdomain/zero/1.0/", + "modified": "2015-01-01", "programCode": [ - "005:040" + "005:042" ], "publisher": { "@type": "org:Organization", - "name": "Agricultural Research Service" - }, - "title": "Integrated Farm System Model (IFSM)" - }, - "description": "<p>The need for a research tool that integrates the many physical and biological processes on a farm has led to the development of the Integrated Farm System Model (IFSM). The model has been used to evaluate a wide variety of technologies and management strategies, and these analyses have been reported in the scientific and farm-trade literature. Systems research in dairy and beef production remains as the primary purpose of this tool, but the model also provides an effective teaching aid. With the model, students gain a better appreciation for the complexity of livestock forage systems. The learn how small changes affect many parts of the system, causing unanticipated results. They may also use the model to develop a more optimum food production system. When used in extension type teaching, producers can learn more about their farms and obtain information useful in strategic planning. By testing and comparing different options with the model, those offering the greatest economic benefit with acceptable environmental impact can be found.</p>\n<p>Input information is supplied to the program through three parameter files. The farm parameter file contains data describing the farm such as crop areas, soil type, equipment and structures used, numbers of animals at various ages, harvest, tillage, and manure handling strategies, and prices for various farm inputs and outputs. The machinery file includes parameters for each machine available for use on a simulated farm.</p>\n<p>Simulation output is available in four files, which contain summary tables, report tables, optional tables, and parameter tables. The summary tables provide average performance, environmental impact, costs, and returns for the years simulated. These values consist of crop yields, feeds produced, feeds bought and sold, manure produced, nutrient losses to the environment, production costs, income from products sold, and the net return or profitability of the farm. Values are provided for the average and standard deviation of each over all simulated years. 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operators", + "Agriculture", + "American Indian Reservation farms", + "Asian operators", + "Brussels sprouts", + "CCC", + "CRP", + "Chinese cabbage", + "Christmas trees", + "Commodity Credit Corporation loans", + "Conservation Reserve", + "Data", + "English walnuts", + "Farmable Wetlands", + "Hispanic operators", + "Latino operators", + "NAICS", + "NASS", + "North American Industry Classification System", + "Pacific Island operators", + "Spanish operators", + "Temples", + "USDA", + "Valencia oranges", + "Wetlands Reserve", + "abandoned", + "acres", + "ag land", + "ag services", + "age", + "agri-tourism", + "agriculture", + "alfalfa", + "alfalfa seed", + "almonds", + "alpacas", + "angora goats", + "apples", + "apricots", + "aquaculture", + "aquatic plants", + "artichokes", + "asparagus", + "avocados", + "bales", + "bananas", + "barley", + "bedding plants", + "bee colonies", + "beef cow", + "bees", + "beets", + "bell peppers", + "berries", + "bison", + "black operators", + 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] + ] + ], + "type": "MultiPolygon" + }, + "theme": [ + "Agriculture", + "Climate", + "Research", + "Weather" + ], + "title": "Quick Stats Agricultural Database API", "type": "dataset" }, { - "_score": 11.436691, + "_score": 25.386974, "_sort": [ - 1791499460537, - 11.436691, - 3, - "41c01bb6-e9a7-4a96-80d8-5bcabf4d2c97" + 1791563999766, + 25.386974, + 2, + "2736c18f-5ec6-4542-b88e-b073b68e7236" ], "access_level": "public", "dcat": { @@ -1084,54 +2224,81 @@ "accessLevel": "public", "accessRights": "public", "bureauCode": [ - "005:18" + "005:13" ], "contactPoint": { - "fn": "Rotz, C. 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Primary sources occur during the farm production process and secondary sources are those occurring during the production of resources used including machinery, fuel, electricity, fertilizer, pesticides, and plastic. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Dairy Gas Emissions Model - home.</p> <p>File Name: Web Page, url: <a href=\"https://www.ars.usda.gov/northeast-area/up-pa/pswmru/docs/dairy-gas-emissions-model/\">https://www.ars.usda.gov/northeast-area/up-pa/pswmru/docs/dairy-gas-emissions-model/</a> </p><p>Provides description of the DairyGEM model with links to reference manual, download instructions, and training video module.</p></li></ul><p></p>", + "@type": "vcard:Contact", + "fn": "David McGranahan", + "hasEmail": "mailto:dmcg@ers.usda.gov" + }, + "describedBy": { + "accessURL": "http://www.ers.usda.gov/data-products/natural-amenities-scale/documentation.aspx" + }, + "description": "The natural amenities scale is a measure of the physical characteristics of a county area that enhance the location as a place to live. The scale was constructed by combining six measures of climate, topography, and water area that reflect environmental qualities most people prefer. These measures are warm winter, winter sun, temperate summer, low summer humidity, topographic variation, and water area. The data are available for counties in the lower 48 States. The file contains the original measures and standardized scores for each county as well as the amenities scale.", "distribution": [ { "@type": "dcat:Distribution", - "downloadURL": "https://www.ars.usda.gov/northeast-area/up-pa/pswmru/docs/dairy-gas-emissions-model/", - "license": "https://www.usa.gov/publicdomain/label/1.0/", - "mediaType": "text/html", - "title": "https://www.ars.usda.gov/northeast-area/up-pa/pswmru/docs/dairy-gas-emissions-model/" + "downloadURL": "https://www.ers.usda.gov/data-products/natural-amenities-scale.aspx", + "license": "https://creativecommons.org/publicdomain/zero/1.0/", + "mediaType": "application/vnd.ms-excel", + "title": "Data file" } ], - "identifier": "10113/AA7203", + "identifier": "USDA-ERS-29161", + "issued": "2019-08-20", "keyword": [ - "ARS", - "DairyGEM", - "data.gov" - ], - "license": "https://www.usa.gov/publicdomain/label/1.0/", - "modified": "2023-11-30", + "climate", + "county", + "data", + "low summer humidity", + "map", + "natural amenities", + "temperate summer", + "topographic variation", + "warm winter", + "water area", + "winter sun" + ], + "landingPage": { + "@type": "Document", + "accessURL": "http://www.ers.usda.gov/data-products/natural-amenities-scale.aspx", + "title": "Natural Amenities Scale" + }, + "license": "https://creativecommons.org/publicdomain/zero/1.0/", + "modified": "2019-08-20", "programCode": [ - "005:040" + "005:041" ], "publisher": { "@type": "org:Organization", - "name": "Agricultural Research Service" - }, - "title": "Dairy Gas Emissions Model (DairyGEM)" - }, - "description": "<p>The Dairy Gas Emissions Model (DairyGEM) uses process level simulation and process related emission factors to predict ammonia, hydrogen sulfide, VOC and greenhouse gas emissions along with the carbon, energy and water footprints of dairy production systems. A process-based simulation is used to predict ammonia, hydrogen sulfide, and VOC emissions as influenced by climate and farm management. Net carbon dioxide, methane, and nitrous oxide emissions are also estimated using process simulation or process related emission factors. Environmental footprints are determined that include both primary and secondary sources. Primary sources occur during the farm production process and secondary sources are those occurring during the production of resources used including machinery, fuel, electricity, fertilizer, pesticides, and plastic. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Dairy Gas Emissions Model - home.</p> <p>File Name: Web Page, url: <a href=\"https://www.ars.usda.gov/northeast-area/up-pa/pswmru/docs/dairy-gas-emissions-model/\">https://www.ars.usda.gov/northeast-area/up-pa/pswmru/docs/dairy-gas-emissions-model/</a> </p><p>Provides description of the DairyGEM model with links to reference manual, download instructions, and training video module.</p></li></ul><p></p>", + "name": "Economic Research Service, Department of Agriculture" + }, + "spatial": "[{\"@type\": \"Location\", \"prefLabel\": \"United States\"}]", + "title": "Natural Amenities Scale" + }, + "description": "The natural amenities scale is a measure of the physical characteristics of a county area that enhance the location as a place to live. The scale was constructed by combining six measures of climate, topography, and water area that reflect environmental qualities most people prefer. These measures are warm winter, winter sun, temperate summer, low summer humidity, topographic variation, and water area. The data are available for counties in the lower 48 States. The file contains the original measures and standardized scores for each county as well as the amenities scale.", "distribution_titles": [ - "https://www.ars.usda.gov/northeast-area/up-pa/pswmru/docs/dairy-gas-emissions-model/" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/f16d82c1-32d6-47da-8710-9396d1090846", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/f16d82c1-32d6-47da-8710-9396d1090846/raw", + "Data file" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/f01c3cfd-24ad-4a9c-bd8f-a9d49275f030", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/f01c3cfd-24ad-4a9c-bd8f-a9d49275f030/raw", "has_download": true, - "has_spatial": false, - "identifier": "10113/AA7203", + "has_spatial": true, + "identifier": "USDA-ERS-29161", "keyword": [ - "ARS", - "DairyGEM", - "data.gov" - ], - "last_harvested_date": "2026-10-08T22:44:20.537789", + "climate", + "county", + "data", + "low summer humidity", + "map", + "natural amenities", + "temperate summer", + "topographic variation", + "warm winter", + "water area", + "winter sun" + ], + "last_harvested_date": "2026-10-09T16:39:59.766498", "organization": { "aliases": [ "dept" @@ -1146,22 +2313,53 @@ "slug": "usda" }, "parent_identifier": null, - "popularity": 3, - "publisher": "Agricultural Research Service", - "slug": "dairy-gas-emissions-model-dairygem", - "spatial_centroid": null, - "spatial_shape": null, + "popularity": 2, + "publisher": "Economic Research Service, Department of Agriculture", + "slug": "natural-amenities-scale", + "spatial_centroid": { + "lat": 34.4819914, + "lon": -101.6218762 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + [ + -124.733253, + 24.544245 + ], + [ + -124.733253, + 49.388611 + ], + [ + -66.954811, + 49.388611 + ], + [ + -66.954811, + 24.544245 + ], + [ + -124.733253, + 24.544245 + ] + ] + ] + ], + "type": "MultiPolygon" + }, "theme": [], - "title": "Dairy Gas Emissions Model (DairyGEM)", + "title": "Natural Amenities Scale", "type": "dataset" }, { - "_score": 16.121773, + "_score": 13.705908, "_sort": [ - 1791499458326, - 16.121773, - 10, - "1535ec97-a3df-4233-aaf8-89797ef9e884" + 1791563970875, + 13.705908, + 5, + "19a57778-14bb-4991-8ec3-88b534d5028a" ], "access_level": "public", "dcat": { @@ -1169,118 +2367,89 @@ "accessLevel": "public", "accessRights": "public", "bureauCode": [ - "005:18" + "005:96" ], "contactPoint": { - "fn": "Frankenberger, Jim", - "hasEmail": "mailto:jim.frankenberger@ars.usda.gov" - }, - "description": "<p>Cligen is a stochastic weather generator which produces daily estimates of precipitation, temperature, dewpoint, wind, and solar radiation for a single geographic point, using monthly parameters (means, SD's, skewness, etc.) derived from the historic measurements. Unlike other climate generators, it produces individual storm parameter estimates, including time to peak, peak intensity, and storm duration, which are required to run the WEPP and the WEPS soil erosion models. Station parameter files to run Cligen for several thousand U. S. sites are available for download from this website: also data and software to build station files for international sites. With the exception of Tmin, Tmax, and Tdew temperatures (changed in January 2004), daily estimates for each parameter are generated independently of the others. With the current random number generator, subsequent runs on the same machine made with identical inputs will produce identical results.</p>\n<p>Users of daily simulation models should consider the impacts of Cligen's characteristics on their application. Individual parameter distributions may be expected to reproduce monthly historic distributions quite well. However, if the model in question is sensitive to the daily interactions of two or more of the parameters Cligen produces, Cligen may not be the most appropriate weather generator to use. This is because for a given day, it generates solar radiation, and maximum and minimum temperatures completely independently from precipitation. Experience and common sense tell us that these parameters are NOT independent. In practice this may not be a huge issue, since it is not uncommon for models to be sensitive to one weather parameter on a daily basis, and relatively insensitive to the others, as long as their monthly trends are preserved. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Cligen.</p> <p>File Name: Web Page, url: <a href=\"https://www.ars.usda.gov/midwest-area/west-lafayette-in/national-soil-erosion-research/docs/wepp/cligen/\">https://www.ars.usda.gov/midwest-area/west-lafayette-in/national-soil-erosion-research/docs/wepp/cligen/</a> </p><p>Overview, source code downloads, data files, and publications.</p></li></ul><p></p>", + "@type": "vcard:Contact", + "fn": "USFSEnterpriseContent", + "hasEmail": "mailto:SM.FS.data@usda.gov" + }, + "description": "Healthy forests not only provide a beautiful setting for our outdoor activities, they are at lower risk for catastrophic wild fires, and are more resilient to changes in climate and insect and disease attack.<div><br /></div><div>Many forest pests are part of the natural environment. However, as our nation's forests grow older and more dense, they are at greater risk of attack and new invasive pests can become established. Fortunately, we have projections which can identify tree species at risk of attack well ahead of time. Armed with this and other local information we can be proactive about protecting and restoring our forests to a healthy state. By planting new trees, removing unhealthy trees, and limiting the spread of invasive forest pests, we can ensure our nation's forests remain healthy for future generations.</div>", "distribution": [ { "@type": "dcat:Distribution", - "downloadURL": "https://www.ars.usda.gov/midwest-area/west-lafayette-in/national-soil-erosion-research/docs/wepp/cligen/", - "license": "https://www.usa.gov/publicdomain/label/1.0/", + "accessURL": "https://apps.fs.usda.gov/fhas", + "format": "ArcGIS GeoServices REST API", + "license": "https://creativecommons.org/licenses/by/4.0/", + "mediaType": "application/json", + "title": "ArcGIS GeoService" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data-usfs.hub.arcgis.com/documents/usfs::forest-health-advisory-system", + "format": "Web Page", + "license": "https://creativecommons.org/licenses/by/4.0/", "mediaType": "text/html", - "title": "https://www.ars.usda.gov/midwest-area/west-lafayette-in/national-soil-erosion-research/docs/wepp/cligen/" + "title": "ArcGIS Hub Dataset" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://www.arcgis.com/sharing/rest/content/items/98f6c0c731a04b308bd96fedbfa84604/info/metadata/metadata.xml?format=iso19139", + "conformsTo": "[{\"@type\": \"Standard\", \"identifier\": \"https://www.isotc211.org/2005/gmi\"}]", + "license": "https://creativecommons.org/licenses/by/4.0/", + "mediaType": "text/xml", + "title": "ISO-19139 metadata" } ], - "identifier": "10113/AA22467", + "identifier": "https://www.arcgis.com/home/item.html?id=98f6c0c731a04b308bd96fedbfa84604", + "issued": "2017-09-29", "keyword": [ - "Agricultural Research Service", - "Australia", - "Idaho", - "Indiana", - "Oklahoma", - "USDA Forest Service", - "United States", - "Water Erosion Prediction Project", - "autumn", - "cleaning", - "climate models", - "computer software", - "computers", - "death", - "dewpoint", - "engineering", - "ganders", - "genes", - "meteorological data", - "meteorology", - "models", - "people", - "prediction", - "quality control", - "rain intensity", - "runoff", - "simulation models", - "soil erosion", - "solar radiation", - "statistical analysis", - "stochastic processes", - "storms", - "streams", - "temperature", - "wind" - ], - "license": "https://www.usa.gov/publicdomain/label/1.0/", - "modified": "2024-02-15", + "Advisory", + "FHAS", + "FHP", + "Forest Health", + "Open Data" + ], + "landingPage": { + "@type": "Document", + "accessURL": "https://data-usfs.hub.arcgis.com/documents/usfs::forest-health-advisory-system", + "title": "Forest Health Advisory System" + }, + "license": "https://creativecommons.org/licenses/by/4.0/", + "modified": "2022-08-29", "programCode": [ - "005:040" - ], + "005:059" + ], + "progressCode": "onGoing", "publisher": { - "@type": "org:Organization", - "name": "Agricultural Research Service" - }, - "title": "Cligen" - }, - "description": "<p>Cligen is a stochastic weather generator which produces daily estimates of precipitation, temperature, dewpoint, wind, and solar radiation for a single geographic point, using monthly parameters (means, SD's, skewness, etc.) derived from the historic measurements. Unlike other climate generators, it produces individual storm parameter estimates, including time to peak, peak intensity, and storm duration, which are required to run the WEPP and the WEPS soil erosion models. Station parameter files to run Cligen for several thousand U. S. sites are available for download from this website: also data and software to build station files for international sites. With the exception of Tmin, Tmax, and Tdew temperatures (changed in January 2004), daily estimates for each parameter are generated independently of the others. With the current random number generator, subsequent runs on the same machine made with identical inputs will produce identical results.</p>\n<p>Users of daily simulation models should consider the impacts of Cligen's characteristics on their application. Individual parameter distributions may be expected to reproduce monthly historic distributions quite well. However, if the model in question is sensitive to the daily interactions of two or more of the parameters Cligen produces, Cligen may not be the most appropriate weather generator to use. This is because for a given day, it generates solar radiation, and maximum and minimum temperatures completely independently from precipitation. Experience and common sense tell us that these parameters are NOT independent. In practice this may not be a huge issue, since it is not uncommon for models to be sensitive to one weather parameter on a daily basis, and relatively insensitive to the others, as long as their monthly trends are preserved. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Cligen.</p> <p>File Name: Web Page, url: <a href=\"https://www.ars.usda.gov/midwest-area/west-lafayette-in/national-soil-erosion-research/docs/wepp/cligen/\">https://www.ars.usda.gov/midwest-area/west-lafayette-in/national-soil-erosion-research/docs/wepp/cligen/</a> </p><p>Overview, source code downloads, data files, and publications.</p></li></ul><p></p>", + "name": "U.S. Forest Service", + "source": "U.S. Forest Service" + }, + "spatial": "[{\"@type\": \"Location\", \"bbox\": \"POLYGON((-131.362 6.898, -65.638 6.898, -65.638 72.622, -131.362 72.622, -131.362 6.898))\"}]", + "theme": [ + "geospatial" + ], + "title": "Forest Health Advisory System" + }, + "description": "Healthy forests not only provide a beautiful setting for our outdoor activities, they are at lower risk for catastrophic wild fires, and are more resilient to changes in climate and insect and disease attack.<div><br /></div><div>Many forest pests are part of the natural environment. However, as our nation's forests grow older and more dense, they are at greater risk of attack and new invasive pests can become established. Fortunately, we have projections which can identify tree species at risk of attack well ahead of time. Armed with this and other local information we can be proactive about protecting and restoring our forests to a healthy state. By planting new trees, removing unhealthy trees, and limiting the spread of invasive forest pests, we can ensure our nation's forests remain healthy for future generations.</div>", "distribution_titles": [ - "https://www.ars.usda.gov/midwest-area/west-lafayette-in/national-soil-erosion-research/docs/wepp/cligen/" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/17034f76-a283-43ad-a1dd-27e0957d237d", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/17034f76-a283-43ad-a1dd-27e0957d237d/raw", - "has_download": true, - "has_spatial": false, - "identifier": "10113/AA22467", + "ArcGIS GeoService", + "ArcGIS Hub Dataset", + "ISO-19139 metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/1373123e-34ed-4da2-b849-b88b6834be2b", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/1373123e-34ed-4da2-b849-b88b6834be2b/raw", + "has_download": false, + "has_spatial": true, + "identifier": "https://www.arcgis.com/home/item.html?id=98f6c0c731a04b308bd96fedbfa84604", "keyword": [ - "Agricultural Research Service", - "Australia", - "Idaho", - "Indiana", - "Oklahoma", - "USDA Forest Service", - "United States", - "Water Erosion Prediction Project", - "autumn", - "cleaning", - "climate models", - "computer software", - "computers", - "death", - "dewpoint", - "engineering", - "ganders", - "genes", - "meteorological data", - "meteorology", - "models", - "people", - "prediction", - "quality control", - "rain intensity", - "runoff", - "simulation models", - "soil erosion", - "solar radiation", - "statistical analysis", - "stochastic processes", - "storms", - "streams", - "temperature", - "wind" - ], - "last_harvested_date": "2026-10-08T22:44:18.326680", + "Advisory", + "FHAS", + "FHP", + "Forest Health", + "Open Data" + ], + "last_harvested_date": "2026-10-09T16:39:30.875556", "organization": { "aliases": [ "dept" @@ -1295,22 +2464,53 @@ "slug": "usda" }, "parent_identifier": null, - "popularity": 10, - "publisher": "Agricultural Research Service", - "slug": "cligen", - "spatial_centroid": null, - "spatial_shape": null, - "theme": [], - "title": "Cligen", + "popularity": 5, + "publisher": "U.S. Forest Service", + "slug": "forest-health-advisory-system", + "spatial_centroid": { + "lat": 33.187599999999996, + "lon": -105.07239999999999 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -131.362, + 6.898 + ], + [ + -65.638, + 6.898 + ], + [ + -65.638, + 72.622 + ], + [ + -131.362, + 72.622 + ], + [ + -131.362, + 6.898 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "Forest Health Advisory System", "type": "dataset" }, { - "_score": 61.599426, + "_score": 60.248497, "_sort": [ - 1791499457534, - 61.599426, - 1, - "3bdc31ee-ec25-49bf-ab74-b2ce189b5811" + 1791563970284, + 60.248497, + 2, + "18b165e1-14fa-48f3-a6b3-59ea341b1807" ], "access_level": "public", "dcat": { @@ -1318,62 +2518,153 @@ "accessLevel": "public", "accessRights": "public", "bureauCode": [ - "005:18" + "005:96" ], "contactPoint": { - "fn": "Blackland Research and Extension Center", - "hasEmail": "mailto:epicapex@brc.tamus.edu" - }, - "description": "<p>Environmental Policy Integrated Climate (EPIC) model is a cropping systems model that was developed to estimate soil productivity as affected by erosion as part of the Soil and Water Resources Conservation Act analysis for 1980, which revealed a significant need for improving technology for evaluating the impacts of soil erosion on soil productivity. EPIC simulates approximately eighty crops with one crop growth model using unique parameter values for each crop. It can be configured for a wide range of crop rotations and other vegetative systems, tillage systems, and other management strategies. It predicts effects of management decisions on soil, water, nutrient and pesticide movements, and their combined impact on soil loss, water quality, and crop yields for areas with homogeneous soils and management. </p>\n<p>EPIC functions on a daily time step and can simulate hundreds of years. Since the initial development, EPIC has been continually improving through the additions of algorithms to simulate water quality, nitrogen and carbon cycling, climate change, and the effects of atmospheric carbon dioxide. The processes simulated include leaf interception of solar radiation; conversion to biomass; division of biomass into roots, above ground mass, and economic yield; root growth; water use; and nutrient uptake. It can be configured for a wide range of crop rotations and other vegetative systems, tillage systems, and other management practices. The model can also assess the cost of erosion for determining optimal management strategies. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Environmental Policy Integrated Climate (EPIC) Model.</p> <p>File Name: Web Page, url: <a href=\"https://epicapex.tamu.edu/epic/\">https://epicapex.tamu.edu/epic/</a> </p><p>Web site for the EPIC model: describes capabilities, examples of applications, and download links for executables, source code, and supporting tools.</p></li></ul><p></p>", + "@type": "vcard:Contact", + "fn": "USFSEnterpriseContent", + "hasEmail": "mailto:SM.FS.data@usda.gov" + }, + "description": "This feature class represents the historical (1970-1999) scenario for bull trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change and brook trout invasions. These datasets indicate all potential cold-water habitats less than 11 degrees Celsius. The attribute fields BT_0BRK - BT_100BRK indicate the probabilities of bull trout occurrence within a cold-water habitat based on the prevalence of brook trout at 0%, 25%, 50%, 75%, or 100% of the sites within a habitat. The probabilities were predicted using the Climate Shield native trout models developed from known species occurrence in greater than 500 cold-water streams. 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EPIC simulates approximately eighty crops with one crop growth model using unique parameter values for each crop. It can be configured for a wide range of crop rotations and other vegetative systems, tillage systems, and other management strategies. It predicts effects of management decisions on soil, water, nutrient and pesticide movements, and their combined impact on soil loss, water quality, and crop yields for areas with homogeneous soils and management. </p>\n<p>EPIC functions on a daily time step and can simulate hundreds of years. Since the initial development, EPIC has been continually improving through the additions of algorithms to simulate water quality, nitrogen and carbon cycling, climate change, and the effects of atmospheric carbon dioxide. The processes simulated include leaf interception of solar radiation; conversion to biomass; division of biomass into roots, above ground mass, and economic yield; root growth; water use; and nutrient uptake. It can be configured for a wide range of crop rotations and other vegetative systems, tillage systems, and other management practices. The model can also assess the cost of erosion for determining optimal management strategies. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Environmental Policy Integrated Climate (EPIC) Model.</p> <p>File Name: Web Page, url: <a href=\"https://epicapex.tamu.edu/epic/\">https://epicapex.tamu.edu/epic/</a> </p><p>Web site for the EPIC model: describes capabilities, examples of applications, and download links for executables, source code, and supporting tools.</p></li></ul><p></p>", + "name": "U.S. Forest Service", + "source": "U.S. Forest Service" + }, + "spatial": "[{\"@type\": \"Location\", \"bbox\": \"POLYGON((-124.2143 41.494, -112.3001 41.494, -112.3001 49.0, -124.2143 49.0, -124.2143 41.494))\"}]", + "theme": [ + "geospatial" + ], + "title": "Climate Shield Bull Trout (0% Brook Trout), 1980 (Feature Layer)" + }, + "description": "This feature class represents the historical (1970-1999) scenario for bull trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change and brook trout invasions. These datasets indicate all potential cold-water habitats less than 11 degrees Celsius. The attribute fields BT_0BRK - BT_100BRK indicate the probabilities of bull trout occurrence within a cold-water habitat based on the prevalence of brook trout at 0%, 25%, 50%, 75%, or 100% of the sites within a habitat. The probabilities were predicted using the Climate Shield native trout models developed from known species occurrence in greater than 500 cold-water streams. 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SPUR2 simulates grassland hydrology, nitrogen cycling, and soil organic matter on grazed ecosystems as well as rangeland production under different climatic regimes, environmental conditions, and management alternatives. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: SPUR2 download page.</p> <p>File Name: Web Page, url: <a href=\"https://www.ars.usda.gov/research/software/download/?softwareid=241&modecode=30-12-30-25\">https://www.ars.usda.gov/research/software/download/?softwareid=241&modecode=30-12-30-25</a> </p></li></ul><p></p>", + "@type": "vcard:Contact", + "fn": "USFSEnterpriseContent", + "hasEmail": "mailto:SM.FS.data@usda.gov" + }, + "description": "<div>Available water supply varies greatly across the United States depending on topography, climate, elevation and geology. Forested and mountainous locations, such as national forests, tend to receive more precipitation than adjacent non-forested or low-lying areas. However, contributions of national forest lands to regional streamflow volumes is largely unknown. Using outputs from the Variable Infiltration Capacity hydrologic model, we calculated mean annual and mean summer (July and August) streamflow metrics based on total flow and flow from national forest lands for each 1:100,000 scale National Hydrography Dataset stream reach in the contiguous United States. Specifically, this data publication contains twenty-one comma-delimited ASCII text files (for different drainage areas and processing units across the United States) containing 1915-2011 mean annual flow and mean summer flow.</div><div><br /></div><div>Data can be downloaded here: <a href='https://data.fs.usda.gov/geodata/edw/edw_resources/fc/S_USA.Hydro_Pct_StreamFlow_NFS.gdb.zip' target='_blank' rel='nofollow ugc noopener noreferrer'>Geodatabase</a> or <a href='https://data.fs.usda.gov/geodata/edw/edw_resources/shp/S_USA.Hydro_Pct_StreamFlow_NFS.zip' target='_blank' rel='nofollow ugc noopener noreferrer'>Shapefile</a><br /></div><div><br /></div><div>These files also contain the mean annual and mean summer flows from National Forest System (NFS) lands as well as the portion of total mean annual and summer flow contributed by flow from NFS lands.</div><div><br /></div><div>These data provide insight into 1915-2011 hydrologic regimes and national forest contributions to total water yield. These non-spatial files were then merged and joined to the September 2012 snapshot of the National Hydrography Dataset (NHD), version 2.</div><div><br /></div><div>Note: 'Forest Service lands' are here defined as those lands within the Forest Service administrative boundaries; these include some inholdings and other non-USFS lands enclosed within these boundaries.<br /></div>", "distribution": [ { "@type": "dcat:Distribution", - "downloadURL": "https://www.ars.usda.gov/research/software/download/?softwareid=241&modecode=30-12-30-25", - "license": "https://creativecommons.org/publicdomain/zero/1.0/", + "accessURL": "https://data-usfs.hub.arcgis.com/documents/usfs::mean-fraction-of-summer-runoff-from-forest-service-lands-map-service", + "format": "Web Page", + "license": "https://creativecommons.org/licenses/by/4.0/", "mediaType": "text/html", - "title": "https://www.ars.usda.gov/research/software/download/?softwareid=241&modecode=30-12-30-25" + "title": "ArcGIS Hub Dataset" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://usfs.maps.arcgis.com/home/item.html?id=53c89c7800b748069c90691dbb033599", + "format": "ArcGIS GeoServices REST API", + "license": "https://creativecommons.org/licenses/by/4.0/", + "mediaType": "application/json", + "title": "ArcGIS GeoService" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://www.arcgis.com/sharing/rest/content/items/8e1c2c466dfe4aa887c7068b4e218a83/info/metadata/metadata.xml?format=iso19139", + "conformsTo": "[{\"@type\": \"Standard\", \"identifier\": \"https://www.isotc211.org/2005/gmi\"}]", + "license": "https://creativecommons.org/licenses/by/4.0/", + "mediaType": "text/xml", + "title": "ISO-19139 metadata" } ], - "identifier": "10113/AA22587", + "identifier": "https://www.arcgis.com/home/item.html?id=8e1c2c466dfe4aa887c7068b4e218a83", + "issued": "2019-11-22", "keyword": [ - "Agricultural Research Service", - "Great Plains region", - "Soil and Water Assessment Tool model", - "animals", - "beef cattle", - "biomass", - "climate", - "computer software", - "databases", - "ecosystems", - "environmental factors", - "equations", - "evapotranspiration", - "forage", - "geographic information systems", - "grasslands", - "grazing", - "models", - "nitrogen cycle", - "plant communities", - "prediction", - "rainfall simulation", - "rangelands", - "runoff", - "sediments", - "simulation models", - "soil", - "soil organic matter", - "soil water", - "storms", - "vegetation", - "watersheds" - ], - "license": "https://creativecommons.org/publicdomain/zero/1.0/", - "modified": "2024-02-13", + "EDW", + "Fraction of Runoff", + "Hydro", + "NHD", + "Open Data", + "Streams", + "USFS" + ], + "landingPage": { + "@type": "Document", + "accessURL": "https://data-usfs.hub.arcgis.com/documents/usfs::mean-fraction-of-summer-runoff-from-forest-service-lands-map-service", + "title": "Mean Fraction of Summer Runoff from Forest Service Lands (Map Service)" + }, + "license": "https://creativecommons.org/licenses/by/4.0/", + "modified": "2022-08-29", "programCode": [ - "005:040" - ], + "005:059" + ], + "progressCode": "onGoing", "publisher": { - "@type": "org:Organization", - "name": "Agricultural Research Service" - }, - "title": "SPUR2" - }, - "description": "<p><strong><em> Please note: This software is no longer being updated or maintained, and is out of date. </em></strong></p>\n<p>SPUR2 DOS ver. 2.2 is a general grassland ecosystem simulation model designed to determine beef cattle performance and production by simultaneously simulating production of up to 15 plant species on 36 heterogeneous grassland sites. SPUR2 simulates grassland hydrology, nitrogen cycling, and soil organic matter on grazed ecosystems as well as rangeland production under different climatic regimes, environmental conditions, and management alternatives. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: SPUR2 download page.</p> <p>File Name: Web Page, url: <a href=\"https://www.ars.usda.gov/research/software/download/?softwareid=241&modecode=30-12-30-25\">https://www.ars.usda.gov/research/software/download/?softwareid=241&modecode=30-12-30-25</a> </p></li></ul><p></p>", + "name": "U.S. Forest Service", + "source": "U.S. Forest Service" + }, + "spatial": "[{\"@type\": \"Location\", \"bbox\": \"POLYGON((-131.362 6.898, -65.638 6.898, -65.638 72.622, -131.362 72.622, -131.362 6.898))\"}]", + "theme": [ + "geospatial" + ], + "title": "Mean Fraction of Summer Runoff from Forest Service Lands (Map Service)" + }, + "description": "<div>Available water supply varies greatly across the United States depending on topography, climate, elevation and geology. Forested and mountainous locations, such as national forests, tend to receive more precipitation than adjacent non-forested or low-lying areas. However, contributions of national forest lands to regional streamflow volumes is largely unknown. Using outputs from the Variable Infiltration Capacity hydrologic model, we calculated mean annual and mean summer (July and August) streamflow metrics based on total flow and flow from national forest lands for each 1:100,000 scale National Hydrography Dataset stream reach in the contiguous United States. Specifically, this data publication contains twenty-one comma-delimited ASCII text files (for different drainage areas and processing units across the United States) containing 1915-2011 mean annual flow and mean summer flow.</div><div><br /></div><div>Data can be downloaded here: <a href='https://data.fs.usda.gov/geodata/edw/edw_resources/fc/S_USA.Hydro_Pct_StreamFlow_NFS.gdb.zip' target='_blank' rel='nofollow ugc noopener noreferrer'>Geodatabase</a> or <a href='https://data.fs.usda.gov/geodata/edw/edw_resources/shp/S_USA.Hydro_Pct_StreamFlow_NFS.zip' target='_blank' rel='nofollow ugc noopener noreferrer'>Shapefile</a><br /></div><div><br /></div><div>These files also contain the mean annual and mean summer flows from National Forest System (NFS) lands as well as the portion of total mean annual and summer flow contributed by flow from NFS lands.</div><div><br /></div><div>These data provide insight into 1915-2011 hydrologic regimes and national forest contributions to total water yield. These non-spatial files were then merged and joined to the September 2012 snapshot of the National Hydrography Dataset (NHD), version 2.</div><div><br /></div><div>Note: 'Forest Service lands' are here defined as those lands within the Forest Service administrative boundaries; these include some inholdings and other non-USFS lands enclosed within these boundaries.<br /></div>", "distribution_titles": [ - "https://www.ars.usda.gov/research/software/download/?softwareid=241&modecode=30-12-30-25" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/ea0c6257-32ed-4fb9-a623-32b0be066fc6", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/ea0c6257-32ed-4fb9-a623-32b0be066fc6/raw", - "has_download": true, - "has_spatial": false, - "identifier": "10113/AA22587", + "ArcGIS Hub Dataset", + "ArcGIS GeoService", + "ISO-19139 metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/003a7f97-e4eb-46f6-b663-5d29b84cd4d1", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/003a7f97-e4eb-46f6-b663-5d29b84cd4d1/raw", + "has_download": false, + "has_spatial": true, + "identifier": "https://www.arcgis.com/home/item.html?id=8e1c2c466dfe4aa887c7068b4e218a83", "keyword": [ - "Agricultural Research Service", - "Great Plains region", - "Soil and Water Assessment Tool model", - "animals", - "beef cattle", - "biomass", - "climate", - "computer software", - "databases", - "ecosystems", - "environmental factors", - "equations", - "evapotranspiration", - "forage", - "geographic information systems", - "grasslands", - "grazing", - "models", - "nitrogen cycle", - "plant communities", - "prediction", - "rainfall simulation", - "rangelands", - "runoff", - "sediments", - "simulation models", - "soil", - "soil organic matter", - "soil water", - "storms", - "vegetation", - "watersheds" - ], - "last_harvested_date": "2026-10-08T22:44:12.472185", + "EDW", + "Fraction of Runoff", + "Hydro", + "NHD", + "Open Data", + "Streams", + "USFS" + ], + "last_harvested_date": "2026-10-09T16:39:28.623748", "organization": { "aliases": [ "dept" @@ -1532,21 +2835,52 @@ }, "parent_identifier": null, "popularity": 1, - "publisher": "Agricultural Research Service", - "slug": "spur2", - "spatial_centroid": null, - "spatial_shape": null, - "theme": [], - "title": "SPUR2", + "publisher": "U.S. Forest Service", + "slug": "mean-fraction-of-summer-runoff-from-forest-service-lands-map-service", + "spatial_centroid": { + "lat": 33.187599999999996, + "lon": -105.07239999999999 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -131.362, + 6.898 + ], + [ + -65.638, + 6.898 + ], + [ + -65.638, + 72.622 + ], + [ + -131.362, + 72.622 + ], + [ + -131.362, + 6.898 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "Mean Fraction of Summer Runoff from Forest Service Lands (Map Service)", "type": "dataset" }, { - "_score": 15.221466, + "_score": 8.875279, "_sort": [ - 1791499440160, - 15.221466, - 3, - "1fa21924-5532-4432-a45d-b453082170f1" + 1791563968478, + 8.875279, + 2, + "584d7939-26d7-4415-a508-b2602d6d14c8" ], "access_level": "public", "dcat": { @@ -1554,54 +2888,107 @@ "accessLevel": "public", "accessRights": "public", "bureauCode": [ - "005:18" + "005:96" ], "contactPoint": { - "fn": "Marks, Danny", - "hasEmail": "mailto:ars.danny@gmail.com" - }, - "description": "<p>iSnobal is a physically-based distributed snowmelt model. Snowmelt is the principal source for soil moisture, ground-water re-charge, and stream-flow in mountainous regions of the western US, Canada, and other similar regions of the world. Information on the timing, magnitude, and contributing area of melt under variable or changing climate conditions is required for successful water and resource management. A coupled energy and mass-balance model iSnobal is used to simulate the development and melting of the seasonal snowcover in several mountain basins in California, Idaho, and Utah. Simulations are done over basins varying from 1 to 2500 km2 , with simulation periods varying from a few days for the smallest basin, Emerald Lake watershed in California, to multiple snow seasons for the Park City area in Utah. The model is driven by topographically corrected estimates of radiation, temperature, humidity, wind, and precipitation. Simulation results in all basins closely match independently measured snow water equivalent, snow depth, or runoff during both the development and depletion of the snowcover. Spatially distributed estimates of snow deposition and melt allow us to better understand the interaction between topographic structure, climate, and moisture availability in mountain basins of the western US. Application of topographically distributed models such as this will lead to improved water resource and watershed management. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Image Processing Workbench (IPW).</p> <p>File Name: Web Page, url: <a href=\"https://gitlab.com/ars-snow/ipw\">https://gitlab.com/ars-snow/ipw</a> </p><p>GitHub repository where the model can be accessed and downloaded.</p></li></ul><p></p>", + "@type": "vcard:Contact", + "fn": "USFSEnterpriseContent", + "hasEmail": "mailto:SM.FS.data@usda.gov" + }, + "description": "This map service represents modeled streamflow metrics from the mid-century time period (2030-2059) in the United States. In addition to standard NHD attributes, the streamflow datasets include metrics on mean daily flow (annual and seasonal), flood levels associated with 1.5-year, 10-year, and 25-year floods; annual and decadal minimum weekly flows and date of minimum weekly flow, center of flow mass date; baseflow index, and average number of winter floods. These files and additional information are available on the project website, <a href='https://www.fs.usda.gov/rm/boise/AWAE/projects/modeled_stream_flow_metrics.shtml' target='_blank' rel='nofollow ugc noopener noreferrer'>https://www.fs.usda.gov/rm/boise/AWAE/projects/modeled_stream_flow_metrics.shtml.</a> Streams without flow metrics (null values) were removed from this dataset to improve display speed; to see all stream lines, use an NHD flowline dataset.<div><br /></div><div>Hydro flow metrics data can be downloaded from <a href='https://data.fs.usda.gov/geodata/edw/datasets.php?xmlKeyword=hydro+flow+metrics' target='_blank' rel='nofollow ugc noopener noreferrer'>here</a>.<br /></div>", "distribution": [ { "@type": "dcat:Distribution", - "downloadURL": "https://gitlab.com/ars-snow/ipw", - "license": "https://www.usa.gov/publicdomain/label/1.0/", + "accessURL": "https://data-usfs.hub.arcgis.com/documents/usfs::hydro-flow-metrics-2040-map-service", + "format": "Web Page", + "license": "https://creativecommons.org/licenses/by/4.0/", "mediaType": "text/html", - "title": "https://gitlab.com/ars-snow/ipw" + "title": "ArcGIS Hub Dataset" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://usfs.maps.arcgis.com/home/item.html?id=2cd299886734450d8f5645f5e66befa6", + "format": "ArcGIS GeoServices REST API", + "license": "https://creativecommons.org/licenses/by/4.0/", + "mediaType": "application/json", + "title": "ArcGIS GeoService" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://www.arcgis.com/sharing/rest/content/items/f47db9337f054e258ef73df641aa8541/info/metadata/metadata.xml?format=iso19139", + "conformsTo": "[{\"@type\": \"Standard\", \"identifier\": \"https://www.isotc211.org/2005/gmi\"}]", + "license": "https://creativecommons.org/licenses/by/4.0/", + "mediaType": "text/xml", + "title": "ISO-19139 metadata" } ], - "identifier": "10.5281/zenodo.1301290", + "identifier": "https://www.arcgis.com/home/item.html?id=f47db9337f054e258ef73df641aa8541", + "issued": "2019-11-21", "keyword": [ - "ARS", - "NP211", - "data.gov" - ], - "license": "https://www.usa.gov/publicdomain/label/1.0/", - "modified": "2024-02-09", + "EDW", + "Hydro", + "NHD", + "OSC", + "Office of Sustainability and Climate", + "Open Data", + "USDA Forest Service", + "USFS", + "VIC", + "hydrology", + "national hydrography dataset", + "stream flow", + "streams", + "variable infiltration capacity" + ], + "landingPage": { + "@type": "Document", + "accessURL": "https://data-usfs.hub.arcgis.com/documents/usfs::hydro-flow-metrics-2040-map-service", + "title": "Hydro Flow Metrics 2040 (Map Service)" + }, + "license": "https://creativecommons.org/licenses/by/4.0/", + "modified": "2022-08-29", "programCode": [ - "005:040" - ], + "005:059" + ], + "progressCode": "onGoing", "publisher": { - "@type": "org:Organization", - "name": "Agricultural Research Service" - }, - "title": "iSnobal" - }, - "description": "<p>iSnobal is a physically-based distributed snowmelt model. Snowmelt is the principal source for soil moisture, ground-water re-charge, and stream-flow in mountainous regions of the western US, Canada, and other similar regions of the world. Information on the timing, magnitude, and contributing area of melt under variable or changing climate conditions is required for successful water and resource management. A coupled energy and mass-balance model iSnobal is used to simulate the development and melting of the seasonal snowcover in several mountain basins in California, Idaho, and Utah. Simulations are done over basins varying from 1 to 2500 km2 , with simulation periods varying from a few days for the smallest basin, Emerald Lake watershed in California, to multiple snow seasons for the Park City area in Utah. The model is driven by topographically corrected estimates of radiation, temperature, humidity, wind, and precipitation. Simulation results in all basins closely match independently measured snow water equivalent, snow depth, or runoff during both the development and depletion of the snowcover. Spatially distributed estimates of snow deposition and melt allow us to better understand the interaction between topographic structure, climate, and moisture availability in mountain basins of the western US. Application of topographically distributed models such as this will lead to improved water resource and watershed management. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Image Processing Workbench (IPW).</p> <p>File Name: Web Page, url: <a href=\"https://gitlab.com/ars-snow/ipw\">https://gitlab.com/ars-snow/ipw</a> </p><p>GitHub repository where the model can be accessed and downloaded.</p></li></ul><p></p>", + "name": "U.S. Forest Service", + "source": "U.S. Forest Service" + }, + "spatial": "[{\"@type\": \"Location\", \"bbox\": \"POLYGON((-131.362 6.898, -65.638 6.898, -65.638 72.622, -131.362 72.622, -131.362 6.898))\"}]", + "theme": [ + "geospatial" + ], + "title": "Hydro Flow Metrics 2040 (Map Service)" + }, + "description": "This map service represents modeled streamflow metrics from the mid-century time period (2030-2059) in the United States. In addition to standard NHD attributes, the streamflow datasets include metrics on mean daily flow (annual and seasonal), flood levels associated with 1.5-year, 10-year, and 25-year floods; annual and decadal minimum weekly flows and date of minimum weekly flow, center of flow mass date; baseflow index, and average number of winter floods. These files and additional information are available on the project website, <a href='https://www.fs.usda.gov/rm/boise/AWAE/projects/modeled_stream_flow_metrics.shtml' target='_blank' rel='nofollow ugc noopener noreferrer'>https://www.fs.usda.gov/rm/boise/AWAE/projects/modeled_stream_flow_metrics.shtml.</a> Streams without flow metrics (null values) were removed from this dataset to improve display speed; to see all stream lines, use an NHD flowline dataset.<div><br /></div><div>Hydro flow metrics data can be downloaded from <a href='https://data.fs.usda.gov/geodata/edw/datasets.php?xmlKeyword=hydro+flow+metrics' target='_blank' rel='nofollow ugc noopener noreferrer'>here</a>.<br /></div>", "distribution_titles": [ - "https://gitlab.com/ars-snow/ipw" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/b1e969e4-5fe5-4e66-9b52-f5c6ad971da2", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/b1e969e4-5fe5-4e66-9b52-f5c6ad971da2/raw", - "has_download": true, - "has_spatial": false, - "identifier": "10.5281/zenodo.1301290", + "ArcGIS Hub Dataset", + "ArcGIS GeoService", + "ISO-19139 metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/8895a62f-f02e-4c49-b2b1-d29b4367bedd", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/8895a62f-f02e-4c49-b2b1-d29b4367bedd/raw", + "has_download": false, + "has_spatial": true, + "identifier": "https://www.arcgis.com/home/item.html?id=f47db9337f054e258ef73df641aa8541", "keyword": [ - "ARS", - "NP211", - "data.gov" - ], - "last_harvested_date": "2026-10-08T22:44:00.160775", + "EDW", + "Hydro", + "NHD", + "OSC", + "Office of Sustainability and Climate", + "Open Data", + "USDA Forest Service", + "USFS", + "VIC", + "hydrology", + "national hydrography dataset", + "stream flow", + "streams", + "variable infiltration capacity" + ], + "last_harvested_date": "2026-10-09T16:39:28.478322", "organization": { "aliases": [ "dept" @@ -1616,22 +3003,53 @@ "slug": "usda" }, "parent_identifier": null, - "popularity": 3, - "publisher": "Agricultural Research Service", - "slug": "isnobal", - "spatial_centroid": null, - "spatial_shape": null, - "theme": [], - "title": "iSnobal", + "popularity": 2, + "publisher": "U.S. Forest Service", + "slug": "hydro-flow-metrics-2040-map-service", + "spatial_centroid": { + "lat": 33.187599999999996, + "lon": -105.07239999999999 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -131.362, + 6.898 + ], + [ + -65.638, + 6.898 + ], + [ + -65.638, + 72.622 + ], + [ + -131.362, + 72.622 + ], + [ + -131.362, + 6.898 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "Hydro Flow Metrics 2040 (Map Service)", "type": "dataset" }, { - "_score": 8.905354, + "_score": 9.170895, "_sort": [ - 1791499438506, - 8.905354, - 4, - "d608d3bf-32f7-4eb4-a69d-a0d46f318a02" + 1791563968324, + 9.170895, + 2, + "fb0495af-a17a-4be8-9943-30322cc253c6" ], "access_level": "public", "dcat": { @@ -1639,92 +3057,95 @@ "accessLevel": "public", "accessRights": "public", "bureauCode": [ - "005:18" + "005:96" ], "contactPoint": { - "fn": "Bjorneberg, David", - "hasEmail": "mailto:DAVE.BJORNEBERG@USDA.GOV" - }, - "description": "<p>Effectively managing salt affected irrigated lands and judicially using irrigation water of marginal salinity quality requires understanding the interactions among many inputs. They include soil salinity, crop salt tolerances, soil physical properties, irrigation water quality, irrigation management, water table depth and quality, climatic factors and crop yield. Visualizing the simultaneous interactions among this many factors over a cropping season extends beyond the capacity of the human mind.</p>\n<p>An interactive computer program was developed to simulate the interactions among the above factors. It shows how changing one factor impacts the outcome of the other factors for a single growing season. The user selects a climate, a crop, and soil characteristics from menu lists, and then sets the water table depth and quality, irrigation (river or well) water quality and then develops an irrigation schedule. On execution, the relative yield reductions due to over irrigation, under irrigation, and salinity, water table rise or fall and surface runoff are shown numerically for the growing season. Soil water content, soil salinity, water table depth changes and rain and irrigation events during the season are also shown graphically.</p>\n<p>This is an educational tool designed to teach the concepts of salinity and irrigation management and IS NOT an irrigation scheduling program nor a management tool. Two versions have been developed, one using metric units, southern hemisphere growing seasons and Australian terminology, and a second using northern hemisphere growing seasons, with units and terminology currently used in US irrigated agriculture. An option in the US version also allows use of metric units.</p>\n<p>The SWAGMAN acronym and the SWAGMAN-Whatif program copyrights are owned by Commonwealth Scientific and Industrial Research Organization (CSIRO) of Australia. The SWAGMAN acronym is not to be used for other programs.</p>\n<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: SWAGMAN.</p> <p>File Name: Web Page, url: <a href=\"https://www.ars.usda.gov/research/software/download/?softwareid=207\" target=\"_blank\">https://www.ars.usda.gov/research/software/download/?softwareid=207</a> </p><p>download page</p></li></ul>", + "@type": "vcard:Contact", + "fn": "USFSEnterpriseContent", + "hasEmail": "mailto:SM.FS.data@usda.gov" + }, + "description": "Available water supply varies greatly across the United States depending on topography, climate, elevation and geology. Forested and mountainous locations, such as national forests, tend to receive more precipitation than adjacent non-forested or low-lying areas. However, contributions of national forest lands to regional streamflow volumes is largely unknown. Using outputs from the Variable Infiltration Capacity hydrologic model, we calculated mean annual and mean summer (July and August) streamflow metrics based on total flow and flow from national forest lands for each 1:100,000 scale National Hydrography Dataset stream reach in the contiguous United States. Specifically, this data publication contains twenty-one comma-delimited ASCII text files (for different drainage areas and processing units across the United States) containing 1915-2011 mean annual flow and mean summer flow.<div><br /></div><div>Data can be downloaded here: <a href='https://data.fs.usda.gov/geodata/edw/edw_resources/fc/S_USA.Hydro_Pct_StreamFlow_NFS.gdb.zip' target='_blank' rel='nofollow ugc noopener noreferrer'>Geodatabase</a> or <a href='https://data.fs.usda.gov/geodata/edw/edw_resources/shp/S_USA.Hydro_Pct_StreamFlow_NFS.zip' target='_blank' rel='nofollow ugc noopener noreferrer'>Shapefile</a><div><br /></div><div>These files also contain the mean annual and mean summer flows from National Forest System (NFS) lands as well as the portion of total mean annual and summer flow contributed by flow from NFS lands.</div><div><br /><div>These data provide insight into 1915-2011 hydrologic regimes and national forest contributions to total water yield. These non-spatial files were then merged and joined to the September 2012 snapshot of the National Hydrography Dataset (NHD), version 2.<div><br /></div><div>Note: 'Forest Service lands' are here defined as those lands within the Forest Service administrative boundaries; these include some inholdings and other non-USFS lands enclosed within these boundaries.</div></div></div></div>", "distribution": [ { "@type": "dcat:Distribution", - "downloadURL": "https://www.ars.usda.gov/research/software/download/?softwareid=207", - "license": "https://creativecommons.org/publicdomain/zero/1.0/", + "accessURL": "https://data-usfs.hub.arcgis.com/documents/usfs::mean-fraction-of-annual-runoff-from-forest-service-lands-map-service", + "format": "Web Page", + "license": "https://creativecommons.org/licenses/by/4.0/", "mediaType": "text/html", - "title": "https://www.ars.usda.gov/research/software/download/?softwareid=207" + "title": "ArcGIS Hub Dataset" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://usfs.maps.arcgis.com/home/item.html?id=5d691af02ab84ed792b18e56f2672d55", + "format": "ArcGIS GeoServices REST API", + "license": "https://creativecommons.org/licenses/by/4.0/", + "mediaType": "application/json", + "title": "ArcGIS GeoService" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://www.arcgis.com/sharing/rest/content/items/de6ff66580a2449b9dfda15efdabd3bf/info/metadata/metadata.xml?format=iso19139", + "conformsTo": "[{\"@type\": \"Standard\", \"identifier\": \"https://www.isotc211.org/2005/gmi\"}]", + "license": "https://creativecommons.org/licenses/by/4.0/", + "mediaType": "text/xml", + "title": "ISO-19139 metadata" } ], - "identifier": "10113/AA22541", + "identifier": "https://www.arcgis.com/home/item.html?id=de6ff66580a2449b9dfda15efdabd3bf", + "issued": "2019-11-22", "keyword": [ - "Australia", - "United States", - "climatic factors", - "computer software", - "crop yield", - "educational materials", - "growing season", - "humans", - "irrigation scheduling", - "irrigation water", - "models", - "rain", - "rivers", - "runoff", - "salinity", - "soil physical properties", - "soil salinity", - "soil water", - "soil water content", - "terminology", - "water quality", - "water table" - ], - "license": "https://creativecommons.org/publicdomain/zero/1.0/", - "modified": "2023-11-30", + "Flow", + "Forest Service Lands", + "Fraction of Runoff", + "Hydro", + "NHD", + "Open Data", + "Streams", + "Summer" + ], + "landingPage": { + "@type": "Document", + "accessURL": "https://data-usfs.hub.arcgis.com/documents/usfs::mean-fraction-of-annual-runoff-from-forest-service-lands-map-service", + "title": "Mean Fraction of Annual Runoff from Forest Service Lands (Map Service)" + }, + "license": "https://creativecommons.org/licenses/by/4.0/", + "modified": "2022-08-29", "programCode": [ - "005:040" - ], + "005:059" + ], + "progressCode": "onGoing", "publisher": { - "@type": "org:Organization", - "name": "Agricultural Research Service" - }, - "title": "SWAGMAN-Whatif" - }, - "description": "<p>Effectively managing salt affected irrigated lands and judicially using irrigation water of marginal salinity quality requires understanding the interactions among many inputs. They include soil salinity, crop salt tolerances, soil physical properties, irrigation water quality, irrigation management, water table depth and quality, climatic factors and crop yield. Visualizing the simultaneous interactions among this many factors over a cropping season extends beyond the capacity of the human mind.</p>\n<p>An interactive computer program was developed to simulate the interactions among the above factors. It shows how changing one factor impacts the outcome of the other factors for a single growing season. The user selects a climate, a crop, and soil characteristics from menu lists, and then sets the water table depth and quality, irrigation (river or well) water quality and then develops an irrigation schedule. On execution, the relative yield reductions due to over irrigation, under irrigation, and salinity, water table rise or fall and surface runoff are shown numerically for the growing season. Soil water content, soil salinity, water table depth changes and rain and irrigation events during the season are also shown graphically.</p>\n<p>This is an educational tool designed to teach the concepts of salinity and irrigation management and IS NOT an irrigation scheduling program nor a management tool. Two versions have been developed, one using metric units, southern hemisphere growing seasons and Australian terminology, and a second using northern hemisphere growing seasons, with units and terminology currently used in US irrigated agriculture. An option in the US version also allows use of metric units.</p>\n<p>The SWAGMAN acronym and the SWAGMAN-Whatif program copyrights are owned by Commonwealth Scientific and Industrial Research Organization (CSIRO) of Australia. The SWAGMAN acronym is not to be used for other programs.</p>\n<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: SWAGMAN.</p> <p>File Name: Web Page, url: <a href=\"https://www.ars.usda.gov/research/software/download/?softwareid=207\" target=\"_blank\">https://www.ars.usda.gov/research/software/download/?softwareid=207</a> </p><p>download page</p></li></ul>", + "name": "U.S. Forest Service", + "source": "U.S. Forest Service" + }, + "spatial": "[{\"@type\": \"Location\", \"bbox\": \"POLYGON((-131.362 6.898, -65.638 6.898, -65.638 72.622, -131.362 72.622, -131.362 6.898))\"}]", + "theme": [ + "geospatial" + ], + "title": "Mean Fraction of Annual Runoff from Forest Service Lands (Map Service)" + }, + "description": "Available water supply varies greatly across the United States depending on topography, climate, elevation and geology. Forested and mountainous locations, such as national forests, tend to receive more precipitation than adjacent non-forested or low-lying areas. However, contributions of national forest lands to regional streamflow volumes is largely unknown. Using outputs from the Variable Infiltration Capacity hydrologic model, we calculated mean annual and mean summer (July and August) streamflow metrics based on total flow and flow from national forest lands for each 1:100,000 scale National Hydrography Dataset stream reach in the contiguous United States. Specifically, this data publication contains twenty-one comma-delimited ASCII text files (for different drainage areas and processing units across the United States) containing 1915-2011 mean annual flow and mean summer flow.<div><br /></div><div>Data can be downloaded here: <a href='https://data.fs.usda.gov/geodata/edw/edw_resources/fc/S_USA.Hydro_Pct_StreamFlow_NFS.gdb.zip' target='_blank' rel='nofollow ugc noopener noreferrer'>Geodatabase</a> or <a href='https://data.fs.usda.gov/geodata/edw/edw_resources/shp/S_USA.Hydro_Pct_StreamFlow_NFS.zip' target='_blank' rel='nofollow ugc noopener noreferrer'>Shapefile</a><div><br /></div><div>These files also contain the mean annual and mean summer flows from National Forest System (NFS) lands as well as the portion of total mean annual and summer flow contributed by flow from NFS lands.</div><div><br /><div>These data provide insight into 1915-2011 hydrologic regimes and national forest contributions to total water yield. These non-spatial files were then merged and joined to the September 2012 snapshot of the National Hydrography Dataset (NHD), version 2.<div><br /></div><div>Note: 'Forest Service lands' are here defined as those lands within the Forest Service administrative boundaries; these include some inholdings and other non-USFS lands enclosed within these boundaries.</div></div></div></div>", "distribution_titles": [ - "https://www.ars.usda.gov/research/software/download/?softwareid=207" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/47eea2fc-f424-4283-9922-c1cd8b64a943", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/47eea2fc-f424-4283-9922-c1cd8b64a943/raw", - "has_download": true, - "has_spatial": false, - "identifier": "10113/AA22541", + "ArcGIS Hub Dataset", + "ArcGIS GeoService", + "ISO-19139 metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/4fb4684e-fd1a-46ec-a6d9-bf8527e32e1e", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/4fb4684e-fd1a-46ec-a6d9-bf8527e32e1e/raw", + "has_download": false, + "has_spatial": true, + "identifier": "https://www.arcgis.com/home/item.html?id=de6ff66580a2449b9dfda15efdabd3bf", "keyword": [ - "Australia", - "United States", - "climatic factors", - "computer software", - "crop yield", - "educational materials", - "growing season", - "humans", - "irrigation scheduling", - "irrigation water", - "models", - "rain", - "rivers", - "runoff", - "salinity", - "soil physical properties", - "soil salinity", - "soil water", - "soil water content", - "terminology", - "water quality", - "water table" - ], - "last_harvested_date": "2026-10-08T22:43:58.506721", + "Flow", + "Forest Service Lands", + "Fraction of Runoff", + "Hydro", + "NHD", + "Open Data", + "Streams", + "Summer" + ], + "last_harvested_date": "2026-10-09T16:39:28.324908", "organization": { "aliases": [ "dept" @@ -1739,22 +3160,53 @@ "slug": "usda" }, "parent_identifier": null, - "popularity": 4, - "publisher": "Agricultural Research Service", - "slug": "swagman-whatif", - "spatial_centroid": null, - "spatial_shape": null, - "theme": [], - "title": "SWAGMAN-Whatif", + "popularity": 2, + "publisher": "U.S. Forest Service", + "slug": "mean-fraction-of-annual-runoff-from-forest-service-lands-map-service", + "spatial_centroid": { + "lat": 33.187599999999996, + "lon": -105.07239999999999 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -131.362, + 6.898 + ], + [ + -65.638, + 6.898 + ], + [ + -65.638, + 72.622 + ], + [ + -131.362, + 72.622 + ], + [ + -131.362, + 6.898 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "Mean Fraction of Annual Runoff from Forest Service Lands (Map Service)", "type": "dataset" }, { - "_score": 17.50407, + "_score": 8.875279, "_sort": [ - 1791499428006, - 17.50407, + 1791563968026, + 8.875279, 1, - "4516b590-d5d0-486b-b68f-ab8152f0a3b7" + "fa3c3fdf-9545-448e-b919-3ae8028d3d76" ], "access_level": "public", "dcat": { @@ -1762,90 +3214,107 @@ "accessLevel": "public", "accessRights": "public", "bureauCode": [ - "005:18" + "005:96" ], "contactPoint": { - "fn": "Nearing, Mark", - "hasEmail": "mailto:mark.nearing@ars.usda.gov" - }, - "description": "<p>Global warming is expected to lead to a more vigorous hydrological cycle, including more total rainfall and more frequent high intensity rainfall events. Rainfall amounts and intensities increased on average in the United States during the 20th century and, according to climate change models, they are expected to continue to increase during the 21st century. These rainfall changes, along with expected changes in temperature, solar radiation, and atmospheric CO2 concentrations, will have significant impacts on soil erosion rates. The processes involved in the impact of climate change on soil erosion by water are complex, involving changes in rainfall amounts and intensities, number of days of precipitation, ratio of rain to snow, plant biomass production, plant residue decomposition rates, soil microbial activity, evapo-transpiration rates, and shifts in land use necessary to accommodate a new climatic regime. WEPPCAT is a web-based erosion simulation tool that allows for the assessment of changes in erosion rates as a consequence of user-defined climate change scenarios. This tool is based on the USDA-ARS Water Erosion Prediction Project (WEPP) erosion model. It has the capability of taking into account all of the erosion-affecting processes listed above.</p>\n<p>This applications has been packaged into a virtual machine. Please fill out the form below to download the application. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: WEPPCAT.</p> <p>File Name: Web Page, url: <a href=\"https://www.ars.usda.gov/research/software/download/?softwareid=WEPPCAT&modecode=20-22-10-00\">https://www.ars.usda.gov/research/software/download/?softwareid=WEPPCAT&modecode=20-22-10-00</a> </p><p>This applications has been packaged into a virtual machine. Please fill out the form below to download the application.</p></li></ul><p></p>", + "@type": "vcard:Contact", + "fn": "USFSEnterpriseContent", + "hasEmail": "mailto:SM.FS.data@usda.gov" + }, + "description": "This map service represents modeled streamflow metrics from the end-of-century time period (2070-2099) in the United States. In addition to standard NHD attributes, the streamflow datasets include \\nmetrics on mean daily flow (annual and seasonal), flood levels \\nassociated with 1.5-year, 10-year, and 25-year floods; annual and \\ndecadal minimum weekly flows and date of minimum weekly flow, center of \\nflow mass date; baseflow index, and average number of winter floods. These files and additional information are available on the project website, <a href='https://www.fs.usda.gov/rm/boise/AWAE/projects/modeled_stream_flow_metrics.shtml' target='_blank' rel='nofollow ugc noopener noreferrer'>https://www.fs.usda.gov/rm/boise/AWAE/projects/modeled_stream_flow_metrics.shtml</a>. Streams without flow metrics (null values) were removed from this dataset to improve display speed; to see all stream lines, use an NHD flowline dataset.<div><br /></div><div>Hydro flow metrics data can be downloaded from <a href='https://data.fs.usda.gov/geodata/edw/datasets.php?xmlKeyword=hydro+flow+metrics' target='_blank' rel='nofollow ugc noopener noreferrer'>here</a>.<br /></div>", "distribution": [ { "@type": "dcat:Distribution", - "downloadURL": "https://www.ars.usda.gov/research/software/download/?softwareid=WEPPCAT&modecode=20-22-10-00", - "license": "https://www.usa.gov/publicdomain/label/1.0/", + "accessURL": "https://data-usfs.hub.arcgis.com/documents/usfs::hydro-flow-metrics-2080-map-service", + "format": "Web Page", + "license": "https://creativecommons.org/licenses/by/4.0/", "mediaType": "text/html", - "title": "https://www.ars.usda.gov/research/software/download/?softwareid=WEPPCAT&modecode=20-22-10-00" + "title": "ArcGIS Hub Dataset" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://usfs.maps.arcgis.com/home/item.html?id=d60a1e84f17f4111893d1688a6e22a7e", + "format": "ArcGIS GeoServices REST API", + "license": "https://creativecommons.org/licenses/by/4.0/", + "mediaType": "application/json", + "title": "ArcGIS GeoService" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://www.arcgis.com/sharing/rest/content/items/3b914c25586243808499383eda808f1b/info/metadata/metadata.xml?format=iso19139", + "conformsTo": "[{\"@type\": \"Standard\", \"identifier\": \"https://www.isotc211.org/2005/gmi\"}]", + "license": "https://creativecommons.org/licenses/by/4.0/", + "mediaType": "text/xml", + "title": "ISO-19139 metadata" } ], - "identifier": "10113/AA22465", + "identifier": "https://www.arcgis.com/home/item.html?id=3b914c25586243808499383eda808f1b", + "issued": "2019-11-21", "keyword": [ - "Agricultural Research Service", - "Internet", - "United States", - "Water Erosion Prediction Project", - "biomass production", - "carbon dioxide", - "computer software", - "evapotranspiration", - "global warming", - "hydrologic cycle", - "land use", - "microbial activity", - "models", - "phytomass", - "plant residues", - "rain", - "snow", - "soil", - "soil erosion", - "solar radiation", - "temperature" - ], - "license": "https://www.usa.gov/publicdomain/label/1.0/", - "modified": "2023-11-30", + "EDW", + "Hydro", + "NHD", + "OSC", + "Office of Sustainability and Climate", + "Open Data", + "USDA Forest Service", + "USFS", + "VIC", + "hydrology", + "national hydrography dataset", + "stream flow", + "streams", + "variable infiltration capacity" + ], + "landingPage": { + "@type": "Document", + "accessURL": "https://data-usfs.hub.arcgis.com/documents/usfs::hydro-flow-metrics-2080-map-service", + "title": "Hydro Flow Metrics 2080 (Map Service)" + }, + "license": "https://creativecommons.org/licenses/by/4.0/", + "modified": "2022-08-29", "programCode": [ - "005:040" - ], + "005:059" + ], + "progressCode": "onGoing", "publisher": { - "@type": "org:Organization", - "name": "Agricultural Research Service" - }, - "title": "WEPPCAT" - }, - "description": "<p>Global warming is expected to lead to a more vigorous hydrological cycle, including more total rainfall and more frequent high intensity rainfall events. Rainfall amounts and intensities increased on average in the United States during the 20th century and, according to climate change models, they are expected to continue to increase during the 21st century. These rainfall changes, along with expected changes in temperature, solar radiation, and atmospheric CO2 concentrations, will have significant impacts on soil erosion rates. The processes involved in the impact of climate change on soil erosion by water are complex, involving changes in rainfall amounts and intensities, number of days of precipitation, ratio of rain to snow, plant biomass production, plant residue decomposition rates, soil microbial activity, evapo-transpiration rates, and shifts in land use necessary to accommodate a new climatic regime. WEPPCAT is a web-based erosion simulation tool that allows for the assessment of changes in erosion rates as a consequence of user-defined climate change scenarios. This tool is based on the USDA-ARS Water Erosion Prediction Project (WEPP) erosion model. It has the capability of taking into account all of the erosion-affecting processes listed above.</p>\n<p>This applications has been packaged into a virtual machine. Please fill out the form below to download the application. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: WEPPCAT.</p> <p>File Name: Web Page, url: <a href=\"https://www.ars.usda.gov/research/software/download/?softwareid=WEPPCAT&modecode=20-22-10-00\">https://www.ars.usda.gov/research/software/download/?softwareid=WEPPCAT&modecode=20-22-10-00</a> </p><p>This applications has been packaged into a virtual machine. Please fill out the form below to download the application.</p></li></ul><p></p>", + "name": "U.S. Forest Service", + "source": "U.S. Forest Service" + }, + "spatial": "[{\"@type\": \"Location\", \"bbox\": \"POLYGON((-131.362 6.898, -65.638 6.898, -65.638 72.622, -131.362 72.622, -131.362 6.898))\"}]", + "theme": [ + "geospatial" + ], + "title": "Hydro Flow Metrics 2080 (Map Service)" + }, + "description": "This map service represents modeled streamflow metrics from the end-of-century time period (2070-2099) in the United States. In addition to standard NHD attributes, the streamflow datasets include \\nmetrics on mean daily flow (annual and seasonal), flood levels \\nassociated with 1.5-year, 10-year, and 25-year floods; annual and \\ndecadal minimum weekly flows and date of minimum weekly flow, center of \\nflow mass date; baseflow index, and average number of winter floods. These files and additional information are available on the project website, <a href='https://www.fs.usda.gov/rm/boise/AWAE/projects/modeled_stream_flow_metrics.shtml' target='_blank' rel='nofollow ugc noopener noreferrer'>https://www.fs.usda.gov/rm/boise/AWAE/projects/modeled_stream_flow_metrics.shtml</a>. Streams without flow metrics (null values) were removed from this dataset to improve display speed; to see all stream lines, use an NHD flowline dataset.<div><br /></div><div>Hydro flow metrics data can be downloaded from <a href='https://data.fs.usda.gov/geodata/edw/datasets.php?xmlKeyword=hydro+flow+metrics' target='_blank' rel='nofollow ugc noopener noreferrer'>here</a>.<br /></div>", "distribution_titles": [ - "https://www.ars.usda.gov/research/software/download/?softwareid=WEPPCAT&modecode=20-22-10-00" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/c9ab5eeb-d5f4-4438-9ac9-8afa6d3cf946", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/c9ab5eeb-d5f4-4438-9ac9-8afa6d3cf946/raw", - "has_download": true, - "has_spatial": false, - "identifier": "10113/AA22465", + "ArcGIS Hub Dataset", + "ArcGIS GeoService", + "ISO-19139 metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/1b91a25c-004f-4c88-83c0-36c8d3b558b1", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/1b91a25c-004f-4c88-83c0-36c8d3b558b1/raw", + "has_download": false, + "has_spatial": true, + "identifier": "https://www.arcgis.com/home/item.html?id=3b914c25586243808499383eda808f1b", "keyword": [ - "Agricultural Research Service", - "Internet", - "United States", - "Water Erosion Prediction Project", - "biomass production", - "carbon dioxide", - "computer software", - "evapotranspiration", - "global warming", - "hydrologic cycle", - "land use", - "microbial activity", - "models", - "phytomass", - "plant residues", - "rain", - "snow", - "soil", - "soil erosion", - "solar radiation", - "temperature" - ], - "last_harvested_date": "2026-10-08T22:43:48.006684", + "EDW", + "Hydro", + "NHD", + "OSC", + "Office of Sustainability and Climate", + "Open Data", + "USDA Forest Service", + "USFS", + "VIC", + "hydrology", + "national hydrography dataset", + "stream flow", + "streams", + "variable infiltration capacity" + ], + "last_harvested_date": "2026-10-09T16:39:28.026661", "organization": { "aliases": [ "dept" @@ -1861,21 +3330,52 @@ }, "parent_identifier": null, "popularity": 1, - "publisher": "Agricultural Research Service", - "slug": "weppcat", - "spatial_centroid": null, - "spatial_shape": null, - "theme": [], - "title": "WEPPCAT", + "publisher": "U.S. Forest Service", + "slug": "hydro-flow-metrics-2080-map-service", + "spatial_centroid": { + "lat": 33.187599999999996, + "lon": -105.07239999999999 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -131.362, + 6.898 + ], + [ + -65.638, + 6.898 + ], + [ + -65.638, + 72.622 + ], + [ + -131.362, + 72.622 + ], + [ + -131.362, + 6.898 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "Hydro Flow Metrics 2080 (Map Service)", "type": "dataset" }, { - "_score": 56.78442, + "_score": 13.263279, "_sort": [ - 1791499427863, - 56.78442, - 3, - "3c9cecb5-5c85-41ed-bde1-dd886dec8c01" + 1791563967872, + 13.263279, + 1, + "508e830b-a69f-4e27-aa0f-4143db684a39" ], "access_level": "public", "dcat": { @@ -1883,80 +3383,137 @@ "accessLevel": "public", "accessRights": "public", "bureauCode": [ - "005:18" + "005:96" ], "contactPoint": { - "fn": "Mauget, Steve", - "hasEmail": "mailto:Steven.Mauget@ars.usda.gov" - }, - "description": "<p>West Texas Mesonet Agro-Climate Monitor shows the precipitation, temperature, weather forecast for mesonet stations in West Texas. Although dependent on rainfall and other climate factors to produce crops, West Texas crop consultants, extension agents, and agricultural producers have few tools that allow them to track the current growing season’s climate conditions and determine how current conditions compare with those of past years. The West Texas Mesonet Agro-Climate Monitor (ACM), a JavaScript web application based on daily data from Texas Tech University’s mesonet weather station network, was designed to meet this need. By displaying continuously updated information on variables such as soil temperature, cumulative growing degree days (GDD), cumulative precipitation, and first freeze dates, the ACM allows producers to monitor planting conditions, track crop development, and compare current conditions with those during the previous 10 yr’s growing seasons. In illustrating how mesonet data might be used as an operational climate data resource, the ACM might also serve as a conceptual model for other high resolution climate tools that estimate measures of current climate using continuously updated daily data sets. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: West Texas Mesonet Agro-Climate Monitor.</p> <p>File Name: Web Page, url: <a href=\"https://www.ars.usda.gov/research/software/download/?softwareid=484&modecode=30-96-05-00\">https://www.ars.usda.gov/research/software/download/?softwareid=484&modecode=30-96-05-00</a> </p><p>download page</p></li></ul><p></p>", + "@type": "vcard:Contact", + "fn": "USFSEnterpriseContent", + "hasEmail": "mailto:SM.FS.data@usda.gov" + }, + "description": "An area depicting designated land boundaries, excluding boundaries designated by proclamation. This data is intended for read-only use. The PAD-US feature classes were developed by the Forest Service for submission to the Protected Areas Database of the United States (PAD-US). It is the official inventory of public parks and other protected open space. With more than 3 billion acres in 150,000 holdings, the spatial data in PAD-US represents public lands held in trust by thousands of national, State and regional/local governments, as well as non-profit conservation organizations. PAD-US is published by the U.S. Geological Survey Gap Analysis Program (GAP). GAP produces data and tools that help meet critical national challenges such as biodiversity, conservation, recreation, public health, climate change adaptation, and infrastructure investment. <a href='https://data.fs.usda.gov/geodata/edw/edw_resources/meta/S_USA.PADUS_Designation.xml' target='_blank' rel='nofollow ugc noopener noreferrer'>Metadata</a>", "distribution": [ { "@type": "dcat:Distribution", - "downloadURL": "https://www.ars.usda.gov/research/software/download/?softwareid=484&modecode=30-96-05-00", - "license": "https://creativecommons.org/publicdomain/zero/1.0/", + "accessURL": "https://apps.fs.usda.gov/arcx/rest/services/EDW/EDW_PADUS_01/MapServer/1", + "format": "ArcGIS GeoServices REST API", + "license": "https://creativecommons.org/licenses/by/4.0/", + "mediaType": "application/json", + "title": "ArcGIS GeoService" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data-usfs.hub.arcgis.com/api/download/v1/items/28b6119a1b664d88a9fad12e005eec82/csv?layers=1", + "format": "CSV", + "license": "https://creativecommons.org/licenses/by/4.0/", + "mediaType": "text/csv", + "title": "CSV" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data-usfs.hub.arcgis.com/api/download/v1/items/28b6119a1b664d88a9fad12e005eec82/geojson?layers=1", + "format": "GeoJSON", + "license": "https://creativecommons.org/licenses/by/4.0/", + "mediaType": "application/vnd.geo+json", + "title": "GeoJSON" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data-usfs.hub.arcgis.com/api/download/v1/items/28b6119a1b664d88a9fad12e005eec82/kml?layers=1", + "format": "KML", + "license": "https://creativecommons.org/licenses/by/4.0/", + "mediaType": "application/vnd.google-earth.kml+xml", + "title": "KML" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data-usfs.hub.arcgis.com/api/download/v1/items/28b6119a1b664d88a9fad12e005eec82/shapefile?layers=1", + "format": "ZIP", + "license": "https://creativecommons.org/licenses/by/4.0/", + "mediaType": "application/zip", + "title": "Shapefile" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data-usfs.hub.arcgis.com/datasets/usfs::padus-fs-national-designated-areas-feature-layer", + "format": "Web Page", + "license": "https://creativecommons.org/licenses/by/4.0/", "mediaType": "text/html", - "title": "https://www.ars.usda.gov/research/software/download/?softwareid=484&modecode=30-96-05-00" + "title": "ArcGIS Hub Dataset" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://www.arcgis.com/sharing/rest/content/items/28b6119a1b664d88a9fad12e005eec82/info/metadata/metadata.xml?format=iso19139", + "conformsTo": "[{\"@type\": \"Standard\", \"identifier\": \"https://www.isotc211.org/2005/gmi\"}]", + "license": "https://creativecommons.org/licenses/by/4.0/", + "mediaType": "text/xml", + "title": "ISO-19139 metadata" } ], - "identifier": "10113/AA22624", + "identifier": "https://www.arcgis.com/home/item.html?id=28b6119a1b664d88a9fad12e005eec82&sublayer=1", + "issued": "2017-04-28", "keyword": [ - "Internet", - "Texas", - "climatic factors", - "computer software", - "consultants", - "crops", - "data collection", - "extension agents", - "growing season", - "heat sums", - "meteorological data", - "models", - "planting", - "rain", - "soil temperature", - "weather forecasting" - ], - "license": "https://creativecommons.org/publicdomain/zero/1.0/", - "modified": "2024-02-13", + "ALP Land Dataset", + "Designation", + "Easement", + "Fee", + "Land Status", + "NFS Lands", + "Open Data", + "PADUS", + "Proclamation", + "Protected Areas Database", + "USDA Forest Service" + ], + "landingPage": { + "@type": "Document", + "accessURL": "https://data-usfs.hub.arcgis.com/datasets/usfs::padus-fs-national-designated-areas-feature-layer", + "title": "PADUS FS National Designated Areas (Feature Layer)" + }, + "license": "https://creativecommons.org/licenses/by/4.0/", + "modified": "2022-08-29", "programCode": [ - "005:040" - ], + "005:059" + ], + "progressCode": "onGoing", "publisher": { - "@type": "org:Organization", - "name": "Agricultural Research Service" - }, - "title": "West Texas Mesonet Agro-Climate Monitor" - }, - "description": "<p>West Texas Mesonet Agro-Climate Monitor shows the precipitation, temperature, weather forecast for mesonet stations in West Texas. Although dependent on rainfall and other climate factors to produce crops, West Texas crop consultants, extension agents, and agricultural producers have few tools that allow them to track the current growing season’s climate conditions and determine how current conditions compare with those of past years. The West Texas Mesonet Agro-Climate Monitor (ACM), a JavaScript web application based on daily data from Texas Tech University’s mesonet weather station network, was designed to meet this need. By displaying continuously updated information on variables such as soil temperature, cumulative growing degree days (GDD), cumulative precipitation, and first freeze dates, the ACM allows producers to monitor planting conditions, track crop development, and compare current conditions with those during the previous 10 yr’s growing seasons. In illustrating how mesonet data might be used as an operational climate data resource, the ACM might also serve as a conceptual model for other high resolution climate tools that estimate measures of current climate using continuously updated daily data sets. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: West Texas Mesonet Agro-Climate Monitor.</p> <p>File Name: Web Page, url: <a href=\"https://www.ars.usda.gov/research/software/download/?softwareid=484&modecode=30-96-05-00\">https://www.ars.usda.gov/research/software/download/?softwareid=484&modecode=30-96-05-00</a> </p><p>download page</p></li></ul><p></p>", + "name": "U.S. Forest Service", + "source": "U.S. Forest Service" + }, + "spatial": "[{\"@type\": \"Location\", \"bbox\": \"POLYGON((-155.9513 17.739, -64.7343 17.739, -64.7343 61.519, -155.9513 61.519, -155.9513 17.739))\"}]", + "theme": [ + "geospatial" + ], + "title": "PADUS FS National Designated Areas (Feature Layer)" + }, + "description": "An area depicting designated land boundaries, excluding boundaries designated by proclamation. This data is intended for read-only use. The PAD-US feature classes were developed by the Forest Service for submission to the Protected Areas Database of the United States (PAD-US). It is the official inventory of public parks and other protected open space. With more than 3 billion acres in 150,000 holdings, the spatial data in PAD-US represents public lands held in trust by thousands of national, State and regional/local governments, as well as non-profit conservation organizations. PAD-US is published by the U.S. Geological Survey Gap Analysis Program (GAP). GAP produces data and tools that help meet critical national challenges such as biodiversity, conservation, recreation, public health, climate change adaptation, and infrastructure investment. <a href='https://data.fs.usda.gov/geodata/edw/edw_resources/meta/S_USA.PADUS_Designation.xml' target='_blank' rel='nofollow ugc noopener noreferrer'>Metadata</a>", "distribution_titles": [ - "https://www.ars.usda.gov/research/software/download/?softwareid=484&modecode=30-96-05-00" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/c6d57606-c634-4de7-a8db-3aed58c094cd", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/c6d57606-c634-4de7-a8db-3aed58c094cd/raw", - "has_download": true, - "has_spatial": false, - "identifier": "10113/AA22624", + "ArcGIS GeoService", + "CSV", + "GeoJSON", + "KML", + "Shapefile", + "ArcGIS Hub Dataset", + "ISO-19139 metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/30fa0802-9c43-4b94-b433-f68452d3aa9a", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/30fa0802-9c43-4b94-b433-f68452d3aa9a/raw", + "has_download": false, + "has_spatial": true, + "identifier": "https://www.arcgis.com/home/item.html?id=28b6119a1b664d88a9fad12e005eec82&sublayer=1", "keyword": [ - "Internet", - "Texas", - "climatic factors", - "computer software", - "consultants", - "crops", - "data collection", - "extension agents", - "growing season", - "heat sums", - "meteorological data", - "models", - "planting", - "rain", - "soil temperature", - "weather forecasting" - ], - "last_harvested_date": "2026-10-08T22:43:47.863881", + "ALP Land Dataset", + "Designation", + "Easement", + "Fee", + "Land Status", + "NFS Lands", + "Open Data", + "PADUS", + "Proclamation", + "Protected Areas Database", + "USDA Forest Service" + ], + "last_harvested_date": "2026-10-09T16:39:27.872015", "organization": { "aliases": [ "dept" @@ -1971,22 +3528,53 @@ "slug": "usda" }, "parent_identifier": null, - "popularity": 3, - "publisher": "Agricultural Research Service", - "slug": "west-texas-mesonet-agro-climate-monitor", - "spatial_centroid": null, - "spatial_shape": null, - "theme": [], - "title": "West Texas Mesonet Agro-Climate Monitor", + "popularity": 1, + "publisher": "U.S. Forest Service", + "slug": "padus-fs-national-designated-areas-feature-layer", + "spatial_centroid": { + "lat": 35.251, + "lon": -119.4645 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -155.9513, + 17.739 + ], + [ + -64.7343, + 17.739 + ], + [ + -64.7343, + 61.519 + ], + [ + -155.9513, + 61.519 + ], + [ + -155.9513, + 17.739 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "PADUS FS National Designated Areas (Feature Layer)", "type": "dataset" }, { - "_score": 9.249456, + "_score": 13.396957, "_sort": [ - 1791499423469, - 9.249456, - 8, - "c9bb6cf9-a45d-4d78-81c7-05f6d4a1fd96" + 1791563967712, + 13.396957, + 2, + "83fccc99-fdab-4f10-9476-5e2d94508e70" ], "access_level": "public", "dcat": { @@ -1994,76 +3582,137 @@ "accessLevel": "public", "accessRights": "public", "bureauCode": [ - "005:18" + "005:96" ], "contactPoint": { - "fn": "Rango, Al", - "hasEmail": "mailto:al.rango@ars.usda.gov" - }, - "description": "<p>The Snowmelt-Runoff Model (WinSRM) is designed to simulate and forecast daily streamflow in mountain basins where snowmelt is a major runoff factor. The Snowmelt Runoff Model (SRM) is a simple degree-day model that requires remote sensing input in the form of basin or zonal snow cover extent. The model has been tested successfully on over 60 basins worldwide in the simulation and forecast modes. Model variables are derived from actual observations of temperature, precipitation, and snow covered area. Model parameters can either be derived from measurements or estimated by hydrological judgement taking into account the basin characteristics, physical laws, and theoretical or empirical relationships. To facilitate use of SRM, a microcomputer version of the program has been developed for IBM compatible personal computers. The program itself features user-oriented input and multiple self-help screens which allow the user to select the kind of data input employed and the output products desired. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Snowmelt Runoff Model for Windows (WinSRM).</p> <p>File Name: Web Page, url: <a href=\"https://www.ars.usda.gov/research/software/download/?softwareid=7&modecode=80-42-05-10\">https://www.ars.usda.gov/research/software/download/?softwareid=7&modecode=80-42-05-10</a> </p><p>download page</p></li></ul><p></p>", + "@type": "vcard:Contact", + "fn": "USFSEnterpriseContent", + "hasEmail": "mailto:SM.FS.data@usda.gov" + }, + "description": "An area depicting designated land boundaries which are designated by proclamation. This data is intended for read-only use. The PAD-US feature classes were developed by the Forest Service for submission to the Protected Areas Database of the United States (PAD-US). It is the official inventory of public parks and other protected open space. With more than 3 billion acres in 150,000 holdings, the spatial data in PAD-US represents public lands held in trust by thousands of national, State and regional/local governments, as well as non-profit conservation organizations. PAD-US is published by the U.S. Geological Survey Gap Analysis Program (GAP). 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Anyone interested in delineating the mountain ranges and watersheds within the Great Basin or quantifying the characteristics of the watersheds will be interested in this report. 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Anyone interested in delineating the mountain ranges and watersheds within the Great Basin or quantifying the characteristics of the watersheds will be interested in this report. 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Anyone interested in delineating the mountain ranges and watersheds within the Great Basin or quantifying the characteristics of the watersheds will be interested in this report. 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The approach builds on long-term work by the partners on the responses of these systems to disturbances and management actions. At the core of the assessments is information on past and present watershed and stream channel characteristics, geomorphic and hydrologic processes, and riparian and meadow vegetation. In this report, we describe the approach used to delineate Great Basin mountain ranges and the watersheds within them, and the data that are available for the individual watersheds. We also describe the resulting database and the data sources. Furthermore, we summarize information on the characteristics of the regions and watersheds within the regions and the implications of the assessments for geomorphic sensitivity and ecological resilience. The target audience for this multiscale approach is managers and stakeholders interested in assessing and adaptively managing Great Basin stream systems and riparian and meadow ecosystems. Anyone interested in delineating the mountain ranges and watersheds within the Great Basin or quantifying the characteristics of the watersheds will be interested in this report. 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