Filters: Tags: Forecasting (X) > partyWithName: U.S. Geological Survey - ScienceBase (X)
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The U.S. Geological Survey (USGS) developed a systematic, quantitative approach to prioritize candidate basins that can support the assessment and forecasting objectives of the major USGS water science programs. Candidate basins were the level-4 hydrologic units (HUC4) with some of the smaller HUC4s being combined (hereafter referred to as modified HUC4 basins). Candidate basins for the contiguous United States (CONUS) were grouped into 18 hydrologic regions. Thirty-three geospatial variables representing land use, climate change, water use, water-balance components, streamflow alteration, fire risk, and ecosystem sensitivity were initially considered to assist in ranking candidate basins for study. The two highest...
Categories: Data;
Tags: Climatology,
Ecology,
Hydrology,
Integrated Water Science Basins,
Land Use Change,
This data release is the update of the U.S. Geological Survey (USGS) - ScienceBase data release Bera (2021b), with the processed data for the period October 1, 2019, through September 30, 2020. This data release describes the watershed data management (WDM) database file WBDR20.WDM. The WDM database file WBDR19.WDM (Bera, 2020b) is updated with the quality-assured and quality-controlled meteorological and hydrologic data for the period October 1, 2019, through September 30, 2020, following the guidelines documented in Bera (2017) and is renamed as WBDR20.WDM. Meteorological data other than precipitation (wind speed, solar radiation, air temperature, dew point temperature, and potential evapotranspiration) are copied...
This data release contains the forcings and outputs of 7-day ahead maximum water temperature forecasting models that made real-time predictions in the Delaware River Basin during 2021. The model is driven by weather forecasts and observed reservoir releases and produces maximum water temperature forecasts for the issue day (day 0) and 7 days into the future (days 1-7) at five sites. This data release captures the entire forecasting period that is reported in Zwart et al. 2022, and is an extension of a previous data release that contains all data needed to build these models but only extends to July 16, 2021 (Oliver et al. 2021). Additionally, this release contains a tidy version of the model predictions with paired...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Hydrology,
NY,
New York,
US,
USGS Science Data Catalog (SDC),
The text file "Wind speed.txt" contains hourly data and associated codes from January 1, 1948, to September 30, 2014. The primary source of the data is the Argonne National Laboratory, Illinois. The codes consist of a three-digit sequence in the form "xyz" that describe the origin and transformations of the data values. They indicate if the data are original or missing, the method that was used to fill the missing periods, and any other transformations of the data. The user of the data should consult Over and others (2010) for the detailed documentation of the data codes. Reference Cited: Over, T.M., Price, T.H., and Ishii, A.L., 2010, Development and analysis of a meteorological database, Argonne National...
The text file "Air Temperature.txt" contains hourly data and associated codes from January 1, 1948, to September 30, 2014. The primary source of the data is the Argonne National Laboratory, Illinois. The codes consist of a three-digit sequence in the form "xyz" that describe the origin and transformations of the data values. They indicate if the data are original or missing, the method that was used to fill the missing periods, and any other transformations of the data. The user of the data should consult Over and others (2010) for the detailed documentation of the data codes. Reference Cited: Over, T.M., Price, T.H., and Ishii, A.L., 2010, Development and analysis of a meteorological database, Argonne National...
Tables are presented listing parameters and fit statistics for 25,453 maximum likelihood logistic regression (MLLR) models describing hydrological drought probabilities at 324 gaged locations on rivers and streams in the Delaware River Basin (DRB). Data from previous months are used to estimate chance of hydrological drought during future summer months. Models containing 1 explanatory variable use monthly mean daily streamflow data (DV) to provide hydrological drought streamflow probabilities for July, August, and September as functions of monthly mean DV from the previous 11 months. Outcomes are estimated 1 to 12 months ahead of their occurrence. Models containing 2 explanatory variables use monthly mean daily...
This data release is the update of the U.S. Geological Survey - ScienceBase data release Bera (2021b), with the processed data for the period October 1, 2019, through September 30, 2020. This data release describes the watershed data management (WDM) database SC20.WDM. The precipitation data are collected from a tipping-bucket rain-gage network and the hydrologic data (stage and discharge) are collected at USGS streamflow-gaging stations in and around DuPage County, Illinois. Hourly precipitation and hydrologic data for the period October 1, 2019, through September 30, 2020, are processed following the guidelines described in Bera (2014) and Murphy and Ishii (2006) and appended to SC19.WDM and renamed as SC20.WDM....
These data were compiled to allow examination of northern spotted owl territorial occupancy dynamics, especially with regards to the roles played by habitat and competition with barred owl in past and future dynamics. Data are estimates of parameters derived from previous modelling of northern spotted owl territorial occupancy dynamics. These data were collected as part of monitoring of northern spotted owl demography. Associated code allows analysis of these estimates to understand the roles of competition and habitat in recent northern spotted owl declines and to predict the future of northern spotted owl under various management scenarios.
FGDC Metadata templates for 5 product areas during 2019 have been created to programmatically generate metadata for the products that are produced daily or weekly on the FireDanger production system. Fire Danger products are broken into 5 product areas (Fire Potential Index, Large Fire Probability, Predictive Service Area (provisional), Relative Greenness (weekly), and NDVI Greenness (weekly)). Metadata files are provided for each raster in the 2019 product areas. A folder is also available containing the 5 metadata templates that were used to generate content for each product area. For more details on the FireDanger production system see https://www.usgs.gov/land-resources/lcsp/fire-danger-forecast.
This text file "Solar radiation.txt" contains hourly solar radiation data in Langleys and associated codes from January 1, 1948, to September 30, 2014. The primary source of the data is the Argonne National Laboratory, Illinois. The codes consist of a three-digit sequence in the form "xyz" that describe the origin and transformations of the data values. They indicate if the data are original or missing, the method that was used to fill the missing periods, and any other transformations of the data. Bera (2014) describes in detail an addition of a new code based on the regression analysis of the backup data series at St. Charles (STC) for water years (WY) 2008-10. The user of the data should consult Over and others...
This data release is the update of the U.S. Geological Survey - ScienceBase data release Bera (2022b), with the processed data for the period October 1, 2020, through September 30, 2021. This data release describes the watershed data management (WDM) database SC21.WDM. The precipitation data are collected from a tipping-bucket rain-gage network and the hydrologic data (stage and discharge) are collected at USGS streamflow-gaging stations in and around DuPage County, Illinois. Hourly precipitation and hydrologic data for the period October 1, 2020, through September 30, 2021, are processed following the guidelines described in Bera (2014) and Murphy and Ishii (2006) and appended to SC20.WDM and renamed as SC21.WDM....
Tables are presented listing parameters used in logistic regression equations describing drought streamflow probabilities in the Northeastern United States. Streamflow daily data, streamflow monthly mean data, maximum likelihood logistic regression (MLLR) equation explanatory parameters, equation goodness of fit parameters, and Receiver Operating Characteristic (ROC) AUC values identifying the utility of each relation, describe each model of the probability (chance) of a particular streamflow daily value exceeding or not exceeding an identified drought streamflow threshold.
Meteorological Database, Argonne National Laboratory, Illinois, January 1, 1948 - September 30, 2014
IMPORTANT NOTE: On September 27, 2016, a formatting error in these data was discovered. This error involves extra spaces in certain lines of the .txt data files, which may cause an error in the interpretation of the data values or data-source flags when read by other software. This error has been corrected in the WY 2015 data which can be accessed from this link. The U.S. Geological Survey (USGS), in cooperation with DuPage County, Illinois, maintains a Watershed Data Management (WDM) database consisting of hourly dewpoint temperature, air temperature, solar radiation, wind speed data based on the data collected at the Argonne National Laboratory (ANL) and hourly potential evapotranspiration computed from them...
The text file "Dewpoint temperature.txt" contains hourly data and associated codes from January 1, 1948, to September 30, 2014. The primary source of the data is the Argonne National Laboratory, Illinois. The codes consist of a three-digit sequence in the form "xyz" that describe the origin and transformations of the data values. They indicate if the data are original or missing, the method that was used to fill the missing periods, and any other transformations of the data. The user of the data should consult Over and others (2010) for the detailed documentation of the data codes. Reference Cited: Over, T.M., Price, T.H., and Ishii, A.L., 2010, Development and analysis of a meteorological database, Argonne...
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