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This landcover raster was generated through a Random Forest predictive model developed in R using a combination of image-derived and ancillary variables, and field-derived training points grouped into 18 classes. Overall accuracy, generated internally through bootstrapping, was 75.5%. A series of post-modeling steps brought the final number of land cover classes to 28.
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Training points collected in the field between 2012 and 2013 were grouped into 18 classes: Forested Burn (66), Foothill Woodland Steppe Transition (73), Greasewood Flat (73), Greasewood Steppe (239), Greasewood Sage Steppe (277), Great Plains Badlands (166), Great Plains Riparian (255), Low Density Sage Steppe (776), Medium Density Sage Steppe (783), Mixed Grass Prairie (555), Mixed Grass Prairie Burned (278), Ponderosa Pine Woodland and Shrubland (512), Riparian Floodplain (223), Semi-Desert Grassland (103), Sparsely Vegetated Mixed Shrub (252), Silver Sage Flat (70) , Silver Sage Steppe (64), and Water (246). When insufficient field data were available for a class, we augmented it through photointerpretation of...
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UW_Olallie_photo_metadata & image files: These are the raw timelapse photographs. The date/time stamp is inaccurate for the camera deployed in the open (at the SNOTEL) due to a programming error. This timestamp is one day early (i.e., subtract 1 day from the timestamp when using these data). Also available is metadata for two timelapse cameras and their associated snow depth poles (two visible in each camera's field of view) deployed at Olallie Meadows SNOTEL during water year 2015. One camera was deployed in the open area that is the Olallie Meadows SNOTEL station (the snow pillow is in the field of view). The other camera was deployed in the adjacent forest, approximately 60 m to the southeast of the SNOTEL....
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UI_Mica_Location: Location metadata and meteorological and snow depth observations from met towers in the Mica Creek Experimental Forest. Data were collected at 7 different station sites at approximately half-hour intervals for water years 2003-2006, with discontinuous records due to equipment malfunction or damage. Stations were located within different forest harvest treatment sections, applied to the watershed in approximately 2001, including clear-cut harvest, partial harvest, and control sections (both second growth and old growth control forests). Site Data Citation for full description of the field campaign and sites. UI_Mica_met: Metadata and associated snow depth and SWE observations from 14 manual...
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Create an inventory of water-related models that have been developed for the Rio Grande/Bravo basin. The summary includes a description of model river extent, spatial and temporal resolution, time period, model type, and their possible application for testing environmental flows or climate change future alternatives.
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Stream flows are essential for maintaining healthy aquatic ecosystems and for supporting human water supply needs. Integrated modeling approaches assessing the impact of changes in climate, land use, and water withdrawals on stream flows and the subsequent impact of changes in flow regime on aquatic biota at multiple spatial scales are necessary to insure an adequate supply of water for humans and healthy river ecosystems. We compared streamflow predictions from a regional-scale hydrological model to those of several fine-scale SW models under a range of hypothetical climate change scenarios to determine the range of predicted streamflow responses to fixed climate perturbations.This spreadsheet contains the results...
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Stream flows are essential for maintaining healthy aquatic ecosystems and for supporting human water supply needs. Integrated modeling approaches assessing the impact of changes in climate, land use, and water withdrawals on stream flows and the subsequent impact of changes in flow regime on aquatic biota at multiple spatial scales are necessary to insure an adequate supply of water for humans and healthy river ecosystems. This spreadsheet contains an inventory of existing hydrologic models in the Southeast region and Puerto Rico. Data were compiled by contacting federal and state agencies, members of academia, and environmental consultants.
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The South Central U.S. is one of the main agricultural regions in North America: annual agricultural production is valued at more than $44 billion dollars. However, as climate conditions change, the region is experiencing more frequent and severe droughts, with significant impacts on agriculture and broader consequences for land management. For example, in 2011 drought caused an estimated $7.6 billion in agricultural losses in Texas and an additional $1.6 billion in Oklahoma. Although there are many drought monitoring tools available, most of these tools were developed without input from the stakeholders, such as farmers and ranchers, who are intended to use them. The goal of this project is to assess the information...
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Daily snow depth values from the UW Snoqualmie Pass site. A timelapse camera and 3 snow depth poles were deployed at the forest plot during water year 2015. Manual snow stake observations were taken in the open plot. This comparison of snow depth between the open and forest uses the daily snow depth data observed with the snow stake, rounded to 5cm, compared to the average of all visible pole values in the forest (read by eye from photos), also rounded to 5 cm. These data have been processed, aggregated and rounded. Raw photographs of the forest poles are also available. UW_Snoqualmie_snow_camera Attributes: Site - Snoqualmie, Cover - Forest or open, WY - water year 2015, Date - yyyy-mm-dd, Method - snow...
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Snow and meteorological observations were collected over a range of water years (WY) by three research institutions and by citizen scientists to characterize forest effects on snow processes across the Pacific Northwest, USA. Fourteen total study sites cover the western slopes and crest of the Cascade Range in WA and OR, and central and northern ID. Each study location includes one or more paired forest and open area in which to compare snow observations. A range of forest canopy densities and data collection strategies are represented, including paired manual snow courses, snow pits, automated sensors, and time-lapse images of snow measurement poles. Analysis and synthesis of all of these sites are presented in...
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Stream flows are essential for maintaining healthy aquatic ecosystems and for supporting human water supply needs. Integrated modeling approaches assessing the impact of changes in climate, land use, and water withdrawals on stream flows and the subsequent impact of changes in flow regime on aquatic biota at multiple spatial scales are necessary to insure an adequate supply of water for humans and healthy river ecosystems. This report inventories and then directly examines and compares a subset of hydrological models implemented in the Southeastern US that were used to estimate streamflow at a number of gaged basins across the region. This effort was designed to evaluate, quantify and compare the magnitude, and...
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This landcover raster was generated through a Random Forest predictive model developed in R using a combination of image-derived and ancillary variables, and field-derived training points grouped into 18 classes. Overall accuracy, generated internally through bootstrapping, was 72.7%. A series of post-modeling steps brought the final number of land cover classes to 28.
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OSU_SnowCourse Summary: Manual snow course observations were collected over WY 2012-2014 from four paired forest-open sites chosen to span a broad elevation range. Study sites were located in the upper McKenzie (McK) River watershed, approximately 100 km east of Corvallis, Oregon, on the western slope of the Cascade Range and in the Middle Fork Willamette (MFW) watershed, located to the south of the McKenzie. The sites were designated based on elevation, with a range of 1110-1480 m. Distributed snow depth and snow water equivalent (SWE) observations were collected via monthly manual snow courses from 1 November through 1 April and bi-weekly thereafter. Snow courses spanned 500 m of forested terrain and 500 m...
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This is one of five general categories that contains the water management elements on the Rio Grande/Bravo basin. This category includes the dams, water districts, and water related models on the United States and Mexico that overlap the basin boundary.
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This is one of five general categories that contain the water related elements of the Rio Grande/Bravo basin. This category includes the land use and cover of the United States and Mexico that are located within the basin boundary. Under this category a digital elevation model for the basin is also included as well as the major soils within the basin.
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Results of a citizen science effort in which students and instructors at the McCall Outdoor Science School (MOSS) collected snow observations every 1-4 weeks at their field site within Ponderosa State Park (elevation 1540 m), adjacent to Payette Lake, ID. Students documented snow cover within forested versus open areas at each site via photographs and estimates of the continuity of snow cover. Additionally, snow depth and density were measured via snow pits in the forest and the open. Data were entered via a Google Form, and the results recorded in this table. Site Data Citation for full description of the field campaign and sites. Field photographs are archived along with these data, sorted by site name, with timestamp...
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This data release includes data processing scripts, data products, and associated metadata for a novel remote-sensing based approach to assess resilience of spring-dependent ecosystems to inter-annual changes in water availability. This approach uses remotely-sensed Normalized Difference Vegetation Index (NDVI) to (1) delineate surface moisture zones (SMZs) in the vicinity of mapped springs in a semi-arid sage-steppe landscape, (2) derive quantitative indicators of the relative resilience of these SMZs to inter-annual changes in water availability, and (3) synthesize these indicators into an overall resilience score for each cluster of springs. Specifically, for 39 spring clusters mapped in the National Hydrography...
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This is one of five general categories that contain the water related elements of the Rio Grande/Bravo basin. This category includes boundaries of the United States and Mexico as well as the States, Counties, and Municipalities that overlap with the basin boundary. This category includes also the extent and location of the cities within the basin and the current and historic population of such cities.
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Human impacts occurring throughout the Northeast and Midwest United States, including urbanization, agriculture, and dams, have multiple effects on the region’s streams which support economically valuable stream fishes. Changes in climate are expected to lead to additional impacts in stream habitats and fish assemblages in multiple ways, including changing stream water temperatures. To manage streams for current impacts and future changes, managers need region-wide information for decision-making and developing proactive management strategies. Our project met that need by integrating results of a current condition assessment of stream habitats based on fish response to human land use, water quality impairment,...


map background search result map search result map Observations of snow depth and meteorological variables in forests and nearby open areas at field sites in Washington, Oregon, and Idaho, USA Large-scale and fine-scale model outputs for model comparison workshop Citizen science snow observations at the McCall Outdoor Science School, McCall, ID Manual snow course observations, raw met data, raw snow depth observations, locations, and associated metadata for Oregon sites Long format snow course observations, meteorological sensor observations,locations, and associated metadata for Mica Creek, Idaho Timelapse photos at SNOTEL station, locations, and associated metadata, Ollalie Meadows, Wash., 2015 Timelapse photos, locations, and associated metadata for Snoqualmie Pass, WA Charles M. Russell National Wildlife Refuge Spot Landcover Classification in Relation to Greater Sage Grouse Charles M. Russell National Wildlife Refuge Landsat 8 Landcover Classification in Relation to Greater Sage Grouse Regional to local coarse to fine scale global change impact study on flow Training Points Southeast modeling efforts for flow and ecology Water Balance and Habitat Suitability Data for Pinus Albicaulis in Greater Yellowstone Ecosystem Delineation and characterization of remotely sensed vegetation conditions in spring-dependent ecosystems, Harney County, Oregon River extent of water related models in the Rio Grande/Bravo basin FishTail, Indices and Supporting Data Characterizing the Current and Future Risk to Fish Habitat Degradation in the Northeast Climate Science Center Region Boundaries and populated places of the Rio Grande/Bravo basin Land use and cover on the Rio Grande/Bravo basin Water management elements on the Rio Grande/Bravo basin Drought Indicators of the South Central Plains (1981-2014) Timelapse photos at SNOTEL station, locations, and associated metadata, Ollalie Meadows, Wash., 2015 Timelapse photos, locations, and associated metadata for Snoqualmie Pass, WA Citizen science snow observations at the McCall Outdoor Science School, McCall, ID Long format snow course observations, meteorological sensor observations,locations, and associated metadata for Mica Creek, Idaho Delineation and characterization of remotely sensed vegetation conditions in spring-dependent ecosystems, Harney County, Oregon Manual snow course observations, raw met data, raw snow depth observations, locations, and associated metadata for Oregon sites Training Points Charles M. Russell National Wildlife Refuge Landsat 8 Landcover Classification in Relation to Greater Sage Grouse Charles M. Russell National Wildlife Refuge Spot Landcover Classification in Relation to Greater Sage Grouse Water Balance and Habitat Suitability Data for Pinus Albicaulis in Greater Yellowstone Ecosystem Observations of snow depth and meteorological variables in forests and nearby open areas at field sites in Washington, Oregon, and Idaho, USA Land use and cover on the Rio Grande/Bravo basin Water management elements on the Rio Grande/Bravo basin River extent of water related models in the Rio Grande/Bravo basin Boundaries and populated places of the Rio Grande/Bravo basin Drought Indicators of the South Central Plains (1981-2014) FishTail, Indices and Supporting Data Characterizing the Current and Future Risk to Fish Habitat Degradation in the Northeast Climate Science Center Region Large-scale and fine-scale model outputs for model comparison workshop Regional to local coarse to fine scale global change impact study on flow Southeast modeling efforts for flow and ecology