These data are daily climate, water balance, and soil moisture data for 270 plots in the National Park Service (NPS) Southern Colorado Plateau Network (SCPN) Inventory & Monitoring (I&M) network. Climate data was collected from a gridded, daily climate dataset, Daymet (https://daymet.ornl.gov/). Climate, alongside field-collected soils (SoilDepthsByPlot.csv) and vegetation information, were then used to drive a point based, daily, multi soil-layer, ecosystem water-balance model, SOILWAT2 (https://github.com/DrylandEcology/SOILWAT2). SCPN plots were established to capture the range of ecosystem conditions present in this network. Plant communities of the SCPN are a vital sign for this region, enhancing habitat, stabilizing soils, and moderating hydrology. However, these ecosystems are water-limited, and many plant and ecosystem processes are driven by the amount of water available in the soil profile (i.e. soil moisture). These data provide daily observations of gridded climate and predicted measures of water-balance (ie. transpiration, evaporation, etc.) and soil moisture availability for the last 38 years for 270 NPS plots and can be used to provide insight into plant and ecosystem processes.

These data are daily climate, water balance, and soil moisture data for 270 plots in the National Park Service (NPS) Southern Colorado Plateau Network (SCPN) Inventory & Monitoring (I&M) network. Climate data was collected from a gridded, daily climate dataset, Daymet (https://daymet.ornl.gov/). Climate, alongside field-collected soils (SoilDepthsByPlot.csv) and vegetation information, were then used to drive a point based, daily, multi soil-layer, ecosystem water-balance model, SOILWAT2 (https://github.com/DrylandEcology/SOILWAT2). SCPN plots were established to capture the range of ecosystem conditions present in this network. Plant communities of the SCPN are a vital sign for this region, enhancing habitat, stabilizing soils, and moderating hydrology. However, these ecosystems are water-limited, and many plant and ecosystem processes are driven by the amount of water available in the soil profile (i.e. soil moisture). These data provide daily observations of gridded climate and predicted measures of water-balance (ie. transpiration, evaporation, etc.) and soil moisture availability for the last 38 years for 270 NPS plots and can be used to provide insight into plant and ecosystem processes.

These data are records collected from six automated weather stations in operation between January 1, 2014 and December 31, 2015 within the Colorado River Corridor of Grand Canyon National Park and Glen Canyon National Recreation Area. Data collection locations, equipment configurations and methods follow those of the original report (OFR 2014-1247). These files are 4-minute interval data for each of the automated weather stations, tab separated by parameter (wind direction, wind speed, wind gusts, air temperature, relative humidity, barometric pressure, and rainfall). Climatic conditions during the reporting period were warm and dry early in 2014 and transitioned to average to slightly above precipitation from mid-2014 to the end of 2015. The El Niño/Southern Oscillation was in a neutral to weak El Niño state during most of the reporting period but transitioned to a strong El Niño state by October 2015.

These data are records collected from six automated weather stations in operation between January 1, 2014 and December 31, 2015 within the Colorado River Corridor of Grand Canyon National Park and Glen Canyon National Recreation Area. Data collection locations, equipment configurations and methods follow those of the original report (OFR 2014-1247). These files are 4-minute interval data for each of the automated weather stations, tab separated by parameter (wind direction, wind speed, wind gusts, air temperature, relative humidity, barometric pressure, and rainfall). Climatic conditions during the reporting period were warm and dry early in 2014 and transitioned to average to slightly above precipitation from mid-2014 to the end of 2015. The El Niño/Southern Oscillation was in a neutral to weak El Niño state during most of the reporting period but transitioned to a strong El Niño state by October 2015.

These CLIM-MET stations are meteorological/geological stations that is designed to function in remote areas for long periods of time without human intervention. These stations measure meteorological and wind-erosion parameters under varying climatic and land-use conditions to detect and describe ongoing landscape changes. These data represent multiple years of local detailed landscape and environmental change observations. These data were collected in and close to Canyonlands National Park, Utah from 1 August 2016 to 31 December 2022. These data were collected by U.S. Geological Survey researchers utilizing site visits and automated data collection data loggers. These data can be used to inform studies of local and regional landscape change as well as to provide input into regional climatic models.

These CLIM-MET stations are meteorological/geological stations that is designed to function in remote areas for long periods of time without human intervention. These stations measure meteorological and wind-erosion parameters under varying climatic and land-use conditions to detect and describe ongoing landscape changes. These data represent multiple years of local detailed landscape and environmental change observations. These data were collected in and close to Canyonlands National Park, Utah from 1 August 2016 to 31 December 2022. These data were collected by U.S. Geological Survey researchers utilizing site visits and automated data collection data loggers. These data can be used to inform studies of local and regional landscape change as well as to provide input into regional climatic models.

These data were compiled for monitoring riparian vegetation change along the Colorado River. This file contains data recorded at 42 sandbars between Lees Ferry and Diamond Creek, AZ, which are sampled for both geomorphic and vegetation change annually. Field data contained here were collected from 2012 to 2016 in September and October of each year. Plant species cover values in 5441 1m^2 quadrat frames, locations and elevations of those sampling frames, slope and aspect, sample dates, temperature and precipitation data, and flood frequency parameters were either recorded in the field or calculated. Annual and seasonal climate variables were estimated from eight weather stations distributed along the river corridor from data aquired from Caster et al. 2014. Data collected between 1 February 2008 and 31 January 2011 were used, as the greatest number of weather stations were recording data with the fewest data gaps during this time. Data were linearly interpolated to sandbars lacking weather data based on distance from adjacent weather stations. Available climate variables included minimum and maximum annual temperature; mean annual, winter (November - April) and monsoon (May - October) precipitation; and mean annual humidity. Inundation and depth to water table were estimated for each plot using plot elevation (acquired from Kaplinski et al. 2014), the 15-minute hydrograph from Glen Canyon Dam (https://www.gcmrc.gov/discharge_qw_sediment/?), and the stage calculator developed for sandbars by Hazel et al. (2006). Discharge data from the 365 days preceding the vegetation surveys were used to calculate the proportion of that year, and the maximum number of contiguous days in which a plot was inundated; minimum, mean and maximum inundation depth; and elevation above river stage at 566m3s-1 (average daily peak flow).

These data were compiled for monitoring riparian vegetation change along the Colorado River. This file contains data recorded at 42 sandbars between Lees Ferry and Diamond Creek, AZ, which are sampled for both geomorphic and vegetation change annually. Field data contained here were collected from 2012 to 2016 in September and October of each year. Plant species cover values in 5441 1m^2 quadrat frames, locations and elevations of those sampling frames, slope and aspect, sample dates, temperature and precipitation data, and flood frequency parameters were either recorded in the field or calculated. Annual and seasonal climate variables were estimated from eight weather stations distributed along the river corridor from data aquired from Caster et al. 2014. Data collected between 1 February 2008 and 31 January 2011 were used, as the greatest number of weather stations were recording data with the fewest data gaps during this time. Data were linearly interpolated to sandbars lacking weather data based on distance from adjacent weather stations. Available climate variables included minimum and maximum annual temperature; mean annual, winter (November - April) and monsoon (May - October) precipitation; and mean annual humidity. Inundation and depth to water table were estimated for each plot using plot elevation (acquired from Kaplinski et al. 2014), the 15-minute hydrograph from Glen Canyon Dam (https://www.gcmrc.gov/discharge_qw_sediment/?), and the stage calculator developed for sandbars by Hazel et al. (2006). Discharge data from the 365 days preceding the vegetation surveys were used to calculate the proportion of that year, and the maximum number of contiguous days in which a plot was inundated; minimum, mean and maximum inundation depth; and elevation above river stage at 566m3s-1 (average daily peak flow).

These data represent simulated soil temperature and moisture conditions for current climate, and for future climate represented by all available climate models at two time periods during the 21st century. These data were used to: 1) quantify the direction and magnitude of expected changes in several measures of soil temperature and soil moisture, including the key variables used to distinguish the regimes used in the R and R categories; 2) assess how these changes will impact the geographic distribution of soil temperature and moisture regimes; and 3) explore the implications for using R and R categories for estimating future ecosystem resilience and resistance.