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The South Florida Water Management District (SFWMD) and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 174 National Oceanic and Atmospheric Administration (NOAA) Atlas 14 stations in central and south Florida. The change factors were computed as the ratio of projected future to historical extreme precipitation depths fitted to extreme precipitation data from various downscaled climate datasets using a constrained maximum likelihood (CML) approach. The change factors correspond to the period 2050-2089 (centered in the year 2070) as compared to the 1966-2005 historical period. An R script (basin_boxplot.R) is provided provided as...
The continental United States (CONUS) was modeled to produce simulations of historical and potential future streamflow using the Precipitation-Runoff Modeling System (PRMS) application of the USGS National Hydrologic Model Infrastructure (NHMI; Regan and others, 2018). This child page specifically contains forcings (daily minimum air temperature, daily maximum air temperature, and daily precipitation accumulation) from each of the global circulation models (GCMs) presented in table1_GCMs_used.csv, using the Representative Concentration Pathway 8.5 for simulating potential future streamflow for the period 2006 - 2100.
This data release contains monthly 270-meter gridded Basin Characterization Model (BCMv8) climate inputs and hydrologic outputs for Los Angeles (LA). Gridded climate inputs include: precipitation (ppt), minimum temperature (tmn), maximum temperature (tmx), and potential evapotranspiration (pet). Gridded hydrologic variables include: actual evapotranspiration (aet), climatic water deficit (cwd), snowpack (pck), recharge (rch), runoff (run), and soil storage (str). The units for temperature variables are degrees Celsius, and all other variables are in millimeters. Monthly historical variables from water years 1896 to 2019 are summarized into water year files and long-term average summaries for water years 1981-2010....
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2020-59 (centered in the year 2040) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates quantiles of change...
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2020-59 (centered in the year 2040) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates change factors derived...
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2020-59 (centered in the year 2040) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates projected future...
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2020-59 (centered in the year 2040) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates projected future...
The U.S. Geological Survey (USGS) computed rasters of pre-solved values for the watersheds draining to the pixel delineation point representing the watershed's mean maximum 30-minute precipitation occurring on average once in 2 years from NOAA Atlas 14. These values will be served in the National StreamStats Fire-Hydrology application to describe delineated watersheds ( https://streamstats.usgs.gov/ ). The StreamStats application provides access to spatial analysis tools that are useful for water-resources planning and management, and for engineering and design purposes. The map-based user interface can be used to delineate drainage areas, to retrieve basin characteristics, to estimate flow statistics, and more.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service,
Raster;
Tags: Alabama,
Arizona,
Arkansas,
California,
Climatology,
This dataset contains the data and results of an analysis estimating wet deposition and streamwater solute fluxes at Panola Mountain Research Watershed (PMRW), Panola Mountain State Park, Stockbridge, Georgia for water years 1986–2016. The PMRW is a small (41 ha), relatively undisturbed, forested headwater catchment in the Piedmont Province of Southeastern United States. This data provides the basis for using a watershed mass-balance approach, in which inputs and outputs of water and solutes are quantified and compared to better understand hydrologic and biogeochemical processes on a watershed scale. The dataset contains 13 datasets consisting of a variety of data series and results, which are summarized herein...
These data were compiled for a study that investigated the effects of drought seasonality and plant community composition on two dominant perennial grasses, Achnatherum hymenoides (C3 photosynthesis), and Pleuraphis jamesii (C4 photosynthesis), in a dryland ecosystem. In 2015 USGS Ecologists recorded vegetation and soil moisture data in 36 experimental plots which manipulated precipitation in two plant community types. The experiment consisted of three precipitation treatments: control (ambient precipitation), cool-season drought (-66% ambient precipitation November-April), and warm-season drought (-66% ambient precipitation May-October), applied in two plant communities (perennial grasses with or without a large...
In cooperation with the Puerto Rico Environmental Quality Board, the U.S. Geological Survey (USGS) calculated over 40 different basin characteristics as part of preparing the Puerto Rico StreamStats application. These data were used to update the peak flow and low flow regression equations for Puerto Rico. These datasets are raster representations of various environmental, geological, and land use attributes within the Puerto Rico StreamStats 2020 study area, and will be served in the Puerto Rico StreamStats 2020 application to describe delineated watersheds. The StreamStats application provides access to spatial analytical tools that are useful for water-resources planning and management, and for engineering and...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Atmosphere,
Hydrology,
Precipitation,
Precipitation Frequency,
Puerto Rico,
The South Florida Water Management District (SFWMD) and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 174 NOAA Atlas 14 stations in central and south Florida. The change factors were computed as the ratio of projected future to historical extreme precipitation depths fitted to extreme precipitation data from various downscaled climate datasets using a constrained maximum likelihood (CML) approach. The change factors correspond to the period 2050-2089 (centered in the year 2070) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates quantiles of change factors derived from various...
Categories: Data;
Tags: Florida,
Florida,
South Florida Water Management District,
Southern Florida,
climatologyMeteorologyAtmosphere,
Note: This data release has been deprecated. Please see new data release here: https://doi.org/10.5066/P935WRTG. This data release consists of Microsoft Excel workbooks, shapefiles, and a figure (png format) related to a cooperative project between the U.S. Geological Survey (USGS) and the South Florida Water Management District (SFWMD) to derive future change factors for precipitation depth-duration-frequency (DDF) curves at 174 National Oceanic and Atmospheric Administration (NOAA) Atlas 14 stations in central and south Florida. The change factors were computed as the ratio of future (2050-2089) to historical (1966-2005) extreme precipitation depths fitted to extreme precipitation data using a constrained maximum...
This dataset consists of several measures of landscape characteristics, each of which is summarized from raster data within spatial polygons. These spatial polygons represent the land area upstream of sampled stream reaches. These stream reaches were sampled by the Maryland Department of Natural Resources for the Maryland Biological Stream Survey program during survey rounds one, two, and four. Landscape characteristics summarized here are either represented by continuous or discrete raster layers which are summarized as the average value of a given characteristic (continuous data) or the area occupied by each class (discrete data). The continuous datasets summarized included percentage of area occupied by tree...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Climatology,
Geochemistry,
Geomorphology,
Hydrology,
Information Sciences,
The continental United States (CONUS) was modeled to produce simulations of historical and potential future streamflow using the Precipitation-Runoff Modeling System (PRMS) application of the USGS National Hydrologic Model Infrastructure (NHMI; Regan and others, 2018). This child page specifically contains the spatial model features (hydrologic response units [HRU_subset.zip] and stream segments [Segments_subset.zip]) on which model inputs and outputs are based. The assembly of model-ready files results in HRU and segment IDs that are different than those in the NHMI database. Two "crosswalk files" (nhm_hru_id_crosswalk.csv, nhm_segment_id_crosswalk.csv) are provided so that the model inputs and outputs can be mapped...
Categories: Data;
Tags: United States,
air temperature,
inlandWaters,
model,
precipitation (atmospheric),
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2020-59 (centered in the year 2040) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates quantiles of change...
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2068-72 (centered in the year 2070) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates projected future...
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2020-59 (centered in the year 2040) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates change factors derived...
The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2020-59 (centered in 2040) or to the period 2050-89 (centered in the year 2070) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is...
This data release contains monthly 270-meter gridded Basin Characterization Model (BCMv8) climate inputs and hydrologic outputs for Smith (SM). Gridded climate inputs include: precipitation (ppt), minimum temperature (tmn), maximum temperature (tmx), and potential evapotranspiration (pet). Gridded hydrologic variables include: actual evapotranspiration (aet), climatic water deficit (cwd), snowpack (pck), recharge (rch), runoff (run), and soil storage (str). The units for temperature variables are degrees Celsius, and all other variables are in millimeters. Monthly historical variables from water years 1896 to 2019 are summarized into water year files and long-term average summaries for water years 1981-2010. Four...
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