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stream-intermittency-visualization-dashboard-GP P1-3
continuous streamflow duration, water temperature, and precipitation data collected for the development of the beta streamflow duration assessment method for the Great Plains. This dataset is associated with the following publication: Kelso, J., W. Saulnier, K. Fritz, T. Nadeau, and B. Topping. The stream intermittency visualization dashboard: A web application for high-frequency logger data and daily flow observations. Hydrological Processes. John Wiley & Sons, Ltd., Indianapolis, IN, USA, 37(2): e14809, (2023).
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stream-intermittency-visualization-dashboard-GP P1-3
공공데이터포털
continuous streamflow duration, water temperature, and precipitation data collected for the development of the beta streamflow duration assessment method for the Great Plains. This dataset is associated with the following publication: Kelso, J., W. Saulnier, K. Fritz, T. Nadeau, and B. Topping. The stream intermittency visualization dashboard: A web application for high-frequency logger data and daily flow observations. Hydrological Processes. John Wiley & Sons, Ltd., Indianapolis, IN, USA, 37(2): e14809, (2023).
Daily streamflow performance benchmark defined by the standard statistical suite (v1.0) for the National Hydrologic Model application of the Precipitation-Runoff Modeling System (v1 byObs Muskingum) at benchmark streamflow locations in the conterminous United States (ver 3.0, March 2023)
공공데이터포털
This data release contains the standard statistical suite (version 1.0) daily streamflow performance benchmark results for the National Hydrologic Model Infrastructure application of the Precipitation-Runoff Modeling System (NHM-PRMS) version 1 "byObs" calibration with Muskingum routing computed at streamflow benchmark locations defined by Foks and others (2022). Model error was determined by evaluating predicted daily mean streamflow versus observed daily mean streamflow using various statistics; the Nash-Sutcliffe efficiency (NSE), the Kling-Gupta efficiency (KGE), the logNSE, the Pearson correlation coefficient, the Spearman correlation coefficient, the ratio of the standard deviation, the percent bias, the percent bias in flow duration curve midsegment slope, the percent bias in the flow duration curve high-segment volume, and the percent bias in flow duration curve low-segment volume. Two climatological KGE benchmarks are included that are calculated using daily mean streamflow observations and interannual daily mean or median flows. Additionally, KGE uncertainty estimates have been added as a separate csv file including the standard error of jackknife, standard error of bootstrap, the 5th, 50th and 95th percentiles of the estimates, the jackknife score, the bias of jackknife, the bias of bootstrap, and the standard error of jackknife after bootstrap.
Streamgage Streamflow with Precipitation and Runoff Indication
공공데이터포털
The datasets herein are the observed instantaneous values of streamflow for the titled U.S. Geological Survey streamgage with precipitation metadata added. Days where streamflow is directly affected by precipitation and the day afterwards is identified with a "B". Two days after a precipitation event is identified with a "C". If the streamflow was affected by snow or ice, the data is identified with a "D". Any data that is not precipitation influenced is identified with an "A". This metadata was applied on the basis of numerous rain gages in the vicinity of the streamgage and radar images obtained from the National Oceanic and Atmospheric Administration website https://www.ncdc.noaa.gov/data-access/radar-data/radar-map-tool (accessed various times throughout the project).
Streamgage Streamflow with Precipitation and Runoff Indication
공공데이터포털
The datasets herein are the observed instantaneous values of streamflow for the titled U.S. Geological Survey streamgage with precipitation metadata added. Days where streamflow is directly affected by precipitation and the day afterwards is identified with a "B". Two days after a precipitation event is identified with a "C". If the streamflow was affected by snow or ice, the data is identified with a "D". Any data that is not precipitation influenced is identified with an "A". This metadata was applied on the basis of numerous rain gages in the vicinity of the streamgage and radar images obtained from the National Oceanic and Atmospheric Administration website https://www.ncdc.noaa.gov/data-access/radar-data/radar-map-tool (accessed various times throughout the project).
FLOwPER Database: StreamFLOw PERmanence field observations, Jan 2022 - Dec 2022
공공데이터포털
IMPORTANT NOTE: This dataset includes spatial locations where streamflow permanence observations (continuous flow, discontinuous flow, and dry) were recorded using the FLOwPER (FLOw PERmanence) field survey available in the Survey 123 mobile data collection application. Additional information to describe the field conditions are included as part of the survey. Field observations in the FLOwPER Database have not been processed for quality control including spatial data accuracy or association with a stream network such as the National Hydrography Dataset. Streamflow permanence observations are collected from several governmental and non-governmental organizations on a continuing basis. This data release is formatted as a shapefile that includes streamflow permanence observations with associated information. Photographs associated with FLOwPER data observations are included. The spatial extent of this dataset is the western United States and includes the following states: Oregon, Washington, Idaho, Nevada, Arizona, Utah, Alabama, and Alaska.
Daily streamflow performance benchmark defined by D-score (v0.1) for the NHM (v1 byObs Muskingum) at benchmark streamflow locations
공공데이터포털
This data release contains the D-score (version 0.1) daily streamflow performance benchmark results for the National Hydrologic Model Infrastructure application of the Precipitation-Runoff Modeling System (NHM-PRMS) version 1 "byObs" calibration with Muskingum routing (Hay and LaFontaine, 2020) computed at streamflow benchmark locations (version 1.0) as defined by Foks and others (2022). Model error was determined by evaluating predicted daily mean streamflow versus observed daily mean streamflow. Using those errors, the D-score performance benchmark computes the mean squared logarithmic error (MSLE), then decomposes the overall MSLE into orthogonal components such as bias, distribution, and sequence (Hodson and others, 2021). For easier interpretation, the MSLE components can be passed through a scoring function as described in Hodson and others (2021).
Streamflow Observation Points in the Upper Missouri River Basin, 1973-2018
공공데이터포털
This produced dataset includes spatially aggregated records of measurements and observations from public and private organizations across the Upper Missouri River Basin. For this dataset the Upper Missouri River Basin is defined as Hydrologic Unit Code 1002-1013, and includes portions of the states of Montana, Wyoming, North Dakota, and South Dakota. Streamflow observations, defined as this dataset as the identification of flowing, dry, or pooled streamflow conditions, are an essential part of understanding the relationship between streamflow permanence and climatic and physical factors. For the purpose of this investigation, all streamflow observations were identified as perennial, non-perennial, or pooled to be used in the PROSPER (PRObability of Streamflow PERmanence) model.
Streamflow Observation Points in the Upper Missouri River Basin, 1973-2018
공공데이터포털
This produced dataset includes spatially aggregated records of measurements and observations from public and private organizations across the Upper Missouri River Basin. For this dataset the Upper Missouri River Basin is defined as Hydrologic Unit Code 1002-1013, and includes portions of the states of Montana, Wyoming, North Dakota, and South Dakota. Streamflow observations, defined as this dataset as the identification of flowing, dry, or pooled streamflow conditions, are an essential part of understanding the relationship between streamflow permanence and climatic and physical factors. For the purpose of this investigation, all streamflow observations were identified as perennial, non-perennial, or pooled to be used in the PROSPER (PRObability of Streamflow PERmanence) model.
FLOwPER Database: StreamFLOw PERmanence field observations, April 2020 - Nov 2020
공공데이터포털
IMPORTANT NOTE: This dataset includes spatial locations where streamflow permanence observations (continuous flow, discontinuous flow, and dry) were recorded using the FLOwPER (FLOw PERmanence) field survey available in the Survey 123 and S1 mobile application. Additional information to describe the field conditions are included as part of the survey. Field observations in the FLOwPER Database have not been processed for quality control including spatial data accuracy or association with a stream network such as the National Hydrography Dataset. Streamflow permanence observations are collected from several governmental and non-governmental organizations on a continuing basis. This data release is formatted as a shapefile that includes streamflow permanence observations with associated information. Photographs associated with FLOwPER data points are included.The spatial extent of this data is the pacific norhtwest of the United States and inlcudes data collected in the following states: Oregon, Washington, and Idaho.
FLOwPER Database: StreamFLOw PERmanence field observations, April 2020 - Nov 2020
공공데이터포털
IMPORTANT NOTE: This dataset includes spatial locations where streamflow permanence observations (continuous flow, discontinuous flow, and dry) were recorded using the FLOwPER (FLOw PERmanence) field survey available in the Survey 123 and S1 mobile application. Additional information to describe the field conditions are included as part of the survey. Field observations in the FLOwPER Database have not been processed for quality control including spatial data accuracy or association with a stream network such as the National Hydrography Dataset. Streamflow permanence observations are collected from several governmental and non-governmental organizations on a continuing basis. This data release is formatted as a shapefile that includes streamflow permanence observations with associated information. Photographs associated with FLOwPER data points are included.The spatial extent of this data is the pacific norhtwest of the United States and inlcudes data collected in the following states: Oregon, Washington, and Idaho.