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Peak-flow frequency analysis is crucial in various water-resources management applications, including floodplain management and critical structure design. Federal guidelines for peak-flow frequency analyses, provided in Bulletin 17C, assume that the statistical properties of the hydrologic processes driving variability in peak flows do not change over time and so the frequency distribution of annual peak flows is stationary. Better understanding of long-term climatic persistence and further consideration of potential climate and land-use changes have caused the assumption of stationarity to be reexamined. This data release contains input data and results of a study investigating hydroclimatic trends in peak streamflow...
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Peak-flow frequency analysis is crucial in various water-resources management applications, including floodplain management and critical structure design. Federal guidelines for peak-flow frequency analyses, provided in Bulletin 17C, assume that the statistical properties of the hydrologic processes driving variability in peak flows do not change over time and so the frequency distribution of annual peak flows is stationary. Better understanding of long-term climatic persistence and further consideration of potential climate and land-use changes have caused the assumption of stationarity to be reexamined. This data release contains input data and results of a study investigating hydroclimatic trends in peak streamflow...
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Peak-flow frequency analysis is crucial in various water-resources management applications, including floodplain management and critical structure design. Federal guidelines for peak-flow frequency analyses, provided in Bulletin 17C, assume that the statistical properties of the hydrologic processes driving variability in peak flows do not change over time and so the frequency distribution of annual peak flows is stationary. Better understanding of long-term climatic persistence and further consideration of potential climate and land-use changes have caused the assumption of stationarity to be reexamined. This data release contains input and results of a study investigating hydroclimatic trends in peak streamflow...
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The U.S. Geological Survey (USGS) works closely with the Mississippi Department of Transportation (MDOT) to provide information to be used by the MDOT for design of highway-drainage structures. MDOT spends millions of dollars annually for highway construction. Streamflow records, hydrologic analyses of basins, and hydraulic analyses of flooding potential at proposed highway crossings help the MDOT to make more informed decisions on the use of highway construction funding. Flood-frequency and hydraulic characteristics at highway crossings are determined from historical flood-elevation data recovered by the USGS, cross-section data, and correlations with data from nearby gaging stations. Additional streamflow data...
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Note: this data release has been deprecated due to errors found in the ARGNXX.wdm file. Please see the detail in new data release at https://doi.org/10.5066/P146RBHK This data release is the update of the U.S. Geological Survey - ScienceBase data release by Bera and Over (2017), with the processed data through September 30, 2017. The primary data for each year is downloaded from the Argonne National Laboratory (ANL) (Argonne National Laboratory, 2017) and is processed following the guidelines documented in Over and others (2010). Daily potential evapotranspiration (PET) in thousandths of an inch is computed from average daily air temperature in degrees Fahrenheit (°F), average daily dewpoint temperature in degrees...
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This data repository documents the input files, output files, and RStudio script files used to generate the Curve Number (CN) regression analysis performed for a U.S Army Corps of Engineers and U.S. Geological Survey study investigating the post-wildfire CN estimates for the Southern Rocky Mountains. For this CN analysis, streamgage data for runoff events within 77 burned watersheds in Colorado Rocky Mountain region were used to quantify CN values and changes in CN values from pre- to post-wildfire conditions. Various watershed characteristics (slope, elevation, northness, and eastness), percent watershed area burned, and land cover type were used to develop predictive models that provide estimates of post-wildfire...
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Note: this data release has been deprecated due to errors found in the ARGNXX.wdm file. Please see the detail in new data release at https://doi.org/10.5066/P146RBHK IMPORTANT NOTE: A more recent version of this data release is available from this link. This data release is the update of the U.S. Geological Survey - ScienceBase data release by Bera and Over (2016), with the processed data through September 30, 2016. The primary data for each year is downloaded from the Argonne National Laboratory (ANL) (http://gonzalo.er.anl.gov/ANLMET/numeric/) and is processed following the guidelines documented in Over and others (2010) and Bera (2014). Daily potential evapotranspiration (PET) in thousandths of an inch is...


    map background search result map search result map Meteorological Database, Argonne National Laboratory, Illinois, January 1, 1948 - September 30, 2016 (Deprecated) Meteorological Database, Argonne National Laboratory, Illinois, January 1, 1948 - September 30, 2017 (Deprecated) Peak Streamflow Data, Climate Data, and Results from Investigating Hydroclimatic Trends and Climate Change Effects on Peak Streamflow in the Central United States, 1921–2020 Peak Streamflow Data, Climate Data, and Results from Investigating Hydroclimatic Trends and Climate Change Effects on Peak Streamflow in the Central United States, 1921–2020 (Peak Streamflow Data) Peak Streamflow Data, Climate Data, and Results from Investigating Hydroclimatic Trends and Climate Change Effects on Peak Streamflow in the Central United States, 1921–2020 (Climate Data) Bridge-Site Study Data for Selected Highway Crossings in Mississippi, 2023 Post-wildfire Curve Number Estimates for the Southern Rocky Mountains Data Bridge-Site Study Data for Selected Highway Crossings in Mississippi, 2023 Post-wildfire Curve Number Estimates for the Southern Rocky Mountains Data Peak Streamflow Data, Climate Data, and Results from Investigating Hydroclimatic Trends and Climate Change Effects on Peak Streamflow in the Central United States, 1921–2020 Peak Streamflow Data, Climate Data, and Results from Investigating Hydroclimatic Trends and Climate Change Effects on Peak Streamflow in the Central United States, 1921–2020 (Peak Streamflow Data) Peak Streamflow Data, Climate Data, and Results from Investigating Hydroclimatic Trends and Climate Change Effects on Peak Streamflow in the Central United States, 1921–2020 (Climate Data)