20241030 13274400 1.0 TRUE 150000000 5000 ItemDescription EDW_ForeststoFaucets_02 Forests Faucets F2F2 September 2023 Update: Water yields (Q_YLD_MM; PER_Q40_45; PER_Q90_45; PER_Q40_85; PER_Q90_85) were updated to tie back to WASSI source data. All Forests to Faucets models and indices were recalculated. HUCs that did not have a corresponding water yield from WASSI were recalculated to the nearest HUC. Forests to Faucets 2.0 builds upon the national Forests to Faucets (2011) by updating base data and adding new threats including wildfire, invasive pests, and future stresses such as climate-induced changes in land use and water quantity. The purpose of this project is to quantify, rank, and illustrate the geographic connection between forests and other natural cover (private and public), surface drinking water supplies, and the populations that depend on them–the ecosystem service of water supply. The project assesses subwatersheds across the US to identify those important to downstream surface drinking water supplies as well as evaluate a subwatersheds natural ability to produce clean water based on its biophysical characteristics: percent natural cover, percent agricultural land, percent impervious, percent riparian natural cover, and mean annual water yield. <div style='text-align:Left;'><div><div><div style='font-size:12pt'><p><span>Forests to Faucets 2.0 builds upon the national Forests to Faucets(2011) by updating base data and adding new threats including wildfire, invasive pests, and future stresses such as climate-induced changes in land use and water quantity. The purpose of this project is to quantify, rank, and illustrate the geographic connection between forests and other natural cover (private and public), surface drinking water supplies, and the populations that depend on them–the ecosystem service of water supply. The project assesses subwatersheds across the US to identify those important to downstream surface drinking water supplies as well as evaluate a subwatersheds natural ability to produce clean water based on its biophysical characteristics: percent natural cover, percent agricultural land, percent impervious, percent riparian natural cover, and mean annual water yield. Using data from a variety of existing sources and maps generated through GIS analyses, the project uses maps and statistics to describe the relative importance of private forests and National Forest System lands to surface drinking water supplies across the United States. The data produced by this assessment provides information needed to identify opportunities for water market approaches or schemes based upon payments for environmental services (PES).September 2023 Update: Water yields (Q_YLD_MM; PER_Q40_45; PER_Q90_45; PER_Q40_85; PER_Q90_85) were updated to tie back to WASSI source data. All Forests to Faucets models and indices were recalculated. HUCs that did not have a corresponding water yield from WASSI were recalculated to the nearest HUC. AttributeDescriptionSourcesAcresHUC 12 AcresCalculated using ArcGISSTATESStatesWBD 2019HUC1212-digit Hydrologic Unit CodeWBD 2019NAME12-digit Hydrologic Unit NameWBD 2019HUTYPEHUC TypeWBD 2019From_HUC 12 From for routingWBD 2019ToHUC 12 To for routingWBD 2019 (edited by USDA FS)LevelHUC levelCalculated HUC level from outlet (1) to headwater (351)NLCDAcres of NLCDNLCDPER_NLCDPercent of HUC with NLCD DataCalculated using ArcGISFOREST_ACAcres of all forestNLCD Forest = 41,42,43, 90NLCDPER_FORPercent ForestCalculated using ArcGISAG_ACAcres of agricultural landNLCD = 81,82NLCDPER_AGPercent agricultural landCalculated using ArcGISIMPV_ACAcres of ImperviousNLCDPER_IMPVPercent ImperviousCalculated using ArcGISNATCOVER_ACAcres of Natural CoverNLCD = 11,12,41,42,43,51,52,71,90,95NLCDPER_NATCOVPercent Natural CoverCalculated using ArcGISRIPNAT_ACAcres of riparian natural coverSinan AboodPER_RIPNATPercent riparian natural coverCalculated using ArcGISQ_YLD_MM Mean Annual Water Yield in mm (Q) based on the historical time period (1961 to 2015). Baseline water yield for 2010.WASSI , Updated September 2023R_NATCOVNatural Cover score for APCWCalculated using ArcGISR_AGAgricultural land score for APCWCalculated using ArcGISR_IMPVImpervious Surface score for APCWCalculated using ArcGISR_RIPRiparian Natural Cover score for APCWCalculated using ArcGISR_QMean Annual Water Yield score for APCWCalculated using ArcGISAPCWAbility to Produce Clean Water (APCW)= (R_NATCOV+R_AG+R_IMPV+R_RIP) * R_QCalculated using ArcGISAPCW_RAPCW Score (0-100 Quantiles)Calculated using RGWNumber of groundwater water intakesSDWISSWNumber of surface water intakes (includes GU, groundwater under the influence of surface water)SDWISGW_POPNumber of groundwater water consumersSDWISSW_POPNumber of surface water consumers (includes GU, groundwater under the influence of surface water)SDWISGL_IntakesNumber of surface water intakes in the Great Lakes*SDWISGL_POPNumber of surface water consumers in the Great Lakes*SDWISSUM_POPP, Total number of Surface water consumers SW_POP+ GL_POPSDWISPRDrinking water protection model PRn = ∑(Wi* Pi)Calculated using RPOP_DSSum of surface drinking water population downstream of HUC 12 ∑(SUM_POPn) ***Cannot be summed across multiple HUC12 due to double counting down stream populations. Only accurate for an individual HUC12.Calculated using RIMPRaw Important Areas for Surface Drinking Water (IMP) Value. As developed in Forests to Faucets (USFS 2011), the Important Areas for Surface Drinking Water (IMP) model can be broken down into two parts: IMPn = (PRn) * (Qn)Calculated using R, Updated September 2023IMP_RIMP, Important Areas for Surface Drinking Water (0-100 Quantiles)Calculated using R, Updated September 2023NON_FORESTAcres of non-forestPADUS and NLCDPRIVATE_FORESTAcres of private forestPADUS and NLCDPROTECTED_FORESTAcres of protected forest (State, Local, NGO, Permanent Easement)PADUS, NCED, and NLCDNFS_FORESTAcres of National Forest System (NFS) forestPADUS and NLCDFEDERAL_FORESTAcres of Other Federal forest (Non-NFS Federal)PADUS and NLCDPER_FORPRIPercent Private ForestCalculated using ArcGISPER_FORNFSPercent NFS ForestCalculated using ArcGISPER_FORPROPercent Protected (Other State, Local, NGO, Permanent Easement, NFS, and Federal) ForestCalculated using ArcGISWFP_HI_ACAcres with High and Very High Wildfire Hazard Potential (WHP)Dillon, 2018PER_WFPPercent of HU 12 with High and Very High Wildfire Hazard Potential (WHP)Dillon, 2018PER_IDRISKPercent of HU 12 that is at risk for mortality - 25% of standing live basal area greater than one inch in diameter will die over a 15- year time frame (2013 to 2027) due to insects and diseases.Krist, et Al,. 2014PERDEV_1040_45% Landuse Change 2010-2040 (low)ICLUSPERDEV_1090_45% Landuse Change 2010-2090 (low)ICLUSPERDEV_1040_85% Landuse Change 2010-2040 (high)ICLUSPERDEV_1090_85% Landuse Change 2010-2090 (high)ICLUSPER_Q40_45% Water Yield Change 2010-2040 (low) WASSI , Updated September 2023PER_Q90_45% Water Yield Change 2010-2090 (low) WASSI , Updated September 2023PER_Q40_85% Water Yield Change 2010-2040 (high) WASSI , Updated September 2023PER_Q90_85% Water Yield Change 2010-2090 (high) WASSI , Updated September 2023WFP(APCW_R * IMP_R * PER_WFP )/ 10,000Wildfire Threat to Important Surface Drinking Water Watersheds Calculated using ArcGIS, Updated September 2023IDRISK(APCW_R * IMP_R * PER_IDRISK )/ 10,000Insect &amp;amp; Disease Threat to Important Surface Drinking Water Watersheds Calculated using ArcGIS, Updated September 2023DEV1040_45(APCW_R * IMP_R * PERDEV_1040_45)/ 10,000 Landuse Change in Important Surface Drinking Water Watersheds 2010-2040 (low emissions) Calculated using ArcGIS, Updated September 2023DEV1090_45(APCW_R * IMP_R * PERDEV_1090_45)/ 10,000 Landuse Change in Important Surface Drinking Water Watersheds 2010-2040 (high emissions) Calculated using ArcGIS, Updated September 2023DEV1040_85(APCW_R * IMP_R * PERDEV_1040_85)/ 10,000 Landuse Change in Important Surface Drinking Water Watersheds 2010-2090 (low emissions) Calculated using ArcGIS, Updated September 2023DEV1090_85(APCW_R * IMP_R * PERDEV_1090_85)/ 10,000 Landuse Change in Important Surface Drinking Water Watersheds 2010-2090 (high emissions) Calculated using ArcGIS, Updated September 2023Q1040_45-1 * (APCW_R * IMP_R * PER_Q40_45)/ 10,000 Water Yield Decrease in Important Surface Drinking Water Watersheds 2010-2040 (low emissions) Calculated using ArcGIS, Updated September 2023Q1090_45-1 * (APCW_R * IMP_R * PER_Q90_45)/ 10,000 Water Yield Decrease in Important Surface Drinking Water Watersheds 2010-2040 (high emissions) Calculated using ArcGIS, Updated September 2023Q1040_85-1 * (APCW_R * IMP_R * PER_Q40_85)/ 10,000 Water Yield Decrease in Important Surface Drinking Water Watersheds 2010-2090 (low emissions) Calculated using ArcGIS, Updated September 2023Q1090_85-1 * (APCW_R * IMP_R * PER_Q90_85)/ 10,000 Water Yield Decrease in Important Surface Drinking Water Watersheds 2010-2090 (high emissions) Calculated using ArcGIS, Updated September 2023WFP_IMP_RWildfire Threat to Important Surface Drinking Water Watersheds (0-100 Quantiles)Calculated using R, Updated September 2023IDRISK_RInsect &amp;amp; Disease Threat to Important Surface Drinking Water Watersheds (0-100 Quantiles)Calculated using R, Updated September 2023DEV40_45_RLanduse Change in Important Surface Drinking Water Watersheds 2010-2040 (low emissions) (0-100 Quantiles)Calculated using R, Updated September 2023DEV40_85_RLanduse Change in Important Surface Drinking Water Watersheds 2010-2040 (high emissions) (0-100 Quantiles)Calculated using R, Updated September 2023DEV90_45_RLanduse Change in Important Surface Drinking Water Watersheds 2010-2090 (low emissions) (0-100 Quantiles)Calculated using R, Updated September 2023DEV90_85_RLanduse Change in Important Surface Drinking Water Watersheds 2010-2090 (high emissions) (0-100 Quantiles)Calculated using R, Updated September 2023Q40_45_RWater Yield Decrease in Important Surface Drinking Water Watersheds 2010-2040 (low emissions) (0-100 Quantiles)Calculated using R, Updated September 2023Q40_85_RWater Yield Decrease in Important Surface Drinking Water Watersheds 2010-2040 (high emissions) (0-100 Quantiles)Calculated using R, Updated September 2023Q90_45_RWater Yield Decrease in Important Surface Drinking Water Watersheds 2010-2090 (low emissions) (0-100 Quantiles)Calculated using R, Updated September 2023Q90_85_RWater Yield Decrease in Important Surface Drinking Water Watersheds 2010-2090 (high emissions) (0-100 Quantiles)Calculated using R, Updated September 2023RegionUS Forest Service Region numberUSFSRegionnameUS Forest Service Region nameUSFSHUC_Num_DiffThis field compares the value in column HUC12(circa 2019 wbd) with the value in HUC_12 (circa 2009 wassi)-1 = No equivalent WASSI HUC. Water yield (Q_YLD_MM) was estimating using the nearest HUC.USFS, Updated September 2023HUC_12_WASSIWASSI HUC numberWASSI, Updated September 2023</span></p></div></div></div></div> USDA Forest Service, 2019. Forests to Faucets 2.0 [Spatial Dataset.] <div style='text-align:Left;'><div><div><div style='font-size:12pt'><p><span>The USDA Forest Service makes no warranty, expressed or implied, including the warranties of merchantability and fitness for a particular purpose, nor assumes any legal liability or responsibility for the accuracy, reliability, completeness or utility of these geospatial data, or for the improper or incorrect use of these geospatial data. These geospatial data and related maps or graphics are not legal documents and are not intended to be used as such. The data and maps may not be used to determine title, ownership, legal descriptions or boundaries, legal jurisdiction, or restrictions that may be in place on either public or private land. Natural hazards may or may not be depicted on the data and maps, and users should exercise due caution. The data are dynamic and may change over time. The user is responsible to verify the limitations of the geospatial data and to use the data accordingly.</span></p></div></div></div></div> 20241031 iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO xAAADsQBlSsOGwAAIABJREFUeJzsvVmPJFl6pvfYObabr7FHRuRaWZW1V1c3m2tzhpyBRIDCEIKg udCNgBF0ozsButGN/oN+gC4kSJgLaQBqIJCiNMIMhzvZzemq7qruWnKPzMhYfbfd7BzhHI+oyi52 N9lD9JI9/gYc7uFubpvbee1b3u87rtZas8IKK6zwAsD9ae/ACiussMLfFSvCWmGFFV4YrAhrhRVW eGGwIqwVVljhhcGKsFZYYYUXBivCWmGFFV4YrAhrhRVWeGGwIqwVVljhhcGKsFZYYYUXBivCWmGF FV4YrAhrhRVWeGGwIqwVVljhhcGKsFZYYYUXBivCWmGFFV4YrAhrhRVWeGGwIqwVVljhhcGKsFZY YYUXBivCWmGFFV4YrAhrhRVWeGGwIqwVVljhhcGKsFZYYYUXBivCWmGFFV4YrAhrhRVWeGGwIqwV VljhhcGKsFZYYYUXBivCWmGFFV4YrAhrhRVWeGGwIqwVVljhhcGKsFZYYYUXBivCWmGFFV4YrAhr hRVWeGGwIqwVVljhhcGKsFZYYYUXBivCWmGFFV4YrAhrhRVWeGGwIqwVVljhhcGKsFZYYYUXBivC WmGFFV4YrAhrhRVWeGHw0yesBmphHora/IODi2d3TNoFMjQ+4mJXWzKEXcqnaV28NkcIAebhgEKD 42D+lqt3L15BpZaLme8b1K0mkQ0aZf9X9q+9eK2Xy9BFa410zH4tv9suF0cKs1xp3xNaIZzLNZvv 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