This dataset consists of time series and evaluation metrics (in comma-separated value format [.csv]) which are described in the Bock and others (2018) Advances in Water Resources research article “Quantifying uncertainty in simulated streamflow and runoff from a continental-scale monthly water balance model.” In this paper, uncertainty was quantified in simulated monthly runoff produced by a monthly water balance model for gaged and ungaged locations across the conterminous United States. The compressed folder UI_byGage.zip contains two files. The file UI_byGage.csv contains the monthly time-step uncertainty intervals and measured and simulated time series of streamflow developed at 1,575 streamgages across the conterminous United States (CONUS). The period of record varies by streamgage. The file Met_byGage.csv contains three metrics (coverage ratio, average width index, and interval skill score), which are evaluations of the uncertainty interval at each of the streamgages. The compressed folder RUN_byHRU.zip contains simulated runoff for 109,951 hydrologic response units (HRUs) across the CONUS. Files are organized by ninteen hydrologic regions (NHDPlus, 2010) and available at a monthly time-step from January 1949 through December 2010. The compressed folder UI_byHRU.zip contains uncertainty intervals (rXX_High.csv and rXX_Low.csv) bounding the simulated runoff at the HRUs. The files have naming conventions and formats identical to the files in the RUN_byHRU.zip folder. The file AWI_byHRU.csv is the average width index calculated for each HRU. See Bock and others (2018) for a full description of the data and metrics.

This data set archives all inputs, outputs and scripts needed to reproduce the findings of W.H. Farmer and S. Levin in the 2017 Journal of the American Water Resources Association article entitled “Characterizing Uncertainty in Daily Streamflow Estimates at Ungauged Locations in Support of the Massachusetts Sustainable Yield Estimator”. Input data includes observed streamflow values, in cubic feet per second, for 66 streamgages in and around Massachusetts from 01 October 1960 through 30 September 2004. Cross-validated streamflows, in cubic feet per second, and estimated correlations are included for all basin pairs as archived by Archfield et al. (2010; USGS SIR 2009–5227). Comma-separated-values files contain output data, including all estimated daily confidence intervals, performance thereof (coverage ratio, average width indices and interval skill scores), and multi-day aggregated performance metrics. ESRI ArcGIS shapefiles are available for all maps produced in the original publication. This archive also includes an R script capable of reading the input files and producing output files and figures. See the README.txt file for a full description of model application. The larger publication can be found at https://doi.org/10.1111/1752-1688.12603.

This data set archives all inputs, outputs and scripts needed to reproduce the findings of W.H. Farmer and S. Levin in the 2017 Journal of the American Water Resources Association article entitled “Characterizing Uncertainty in Daily Streamflow Estimates at Ungauged Locations in Support of the Massachusetts Sustainable Yield Estimator”. Input data includes observed streamflow values, in cubic feet per second, for 66 streamgages in and around Massachusetts from 01 October 1960 through 30 September 2004. Cross-validated streamflows, in cubic feet per second, and estimated correlations are included for all basin pairs as archived by Archfield et al. (2010; USGS SIR 2009–5227). Comma-separated-values files contain output data, including all estimated daily confidence intervals, performance thereof (coverage ratio, average width indices and interval skill scores), and multi-day aggregated performance metrics. ESRI ArcGIS shapefiles are available for all maps produced in the original publication. This archive also includes an R script capable of reading the input files and producing output files and figures. See the README.txt file for a full description of model application. The larger publication can be found at https://doi.org/10.1111/1752-1688.12603.

This data release contains the models and their inputs and outputs needed to reproduce the findings for the publication by Soong and Over (2022), "Effect of Uncertainty of Discharge Data on Uncertainty of Discharge Simulation for the Lake Michigan Diversion, Northeastern Illinois and Northwestern Indiana." These data were developed in cooperation with the U.S. Army Corps of Engineers, Chicago District, for the Lake Michigan Diversion Accounting program. Data are provided in four zip files and one MS Word file. The MS Word file 4.ReadMe.HSPF_Recalibrations_with_17TimeSeriesPairs.docx documents the recalibration of the Hydrological Simulation Program - FORTRAN (HSPF) model with discharge time series pairs that characterize the uncertainty of the published daily discharge at the two U.S. Geological Survey (USGS) streamgages, analyzed in 2.PubQUncertaintyEst.zip. It also points to data included in four zip files. The zip files provide the inputs, scripts and other executables, and sample outputs from the model archive for the publication. In addition, the zip files document the executables (1.Executables.zip) and the following modeling tasks: 2.PubQUncertaintyEst.zip - Estimation of the uncertainty of published daily discharge at two USGS streamgages; 3.BaseModel-ParameterUncertainty.zip - Estimation of the parameters of the base HSPF model; and 5.HSPFsimulations.zip - Simulations of discharge with HSPF for the nine study watersheds.

This data release contains the models and their inputs and outputs needed to reproduce the findings for the publication by Soong and Over (2022), "Effect of Uncertainty of Discharge Data on Uncertainty of Discharge Simulation for the Lake Michigan Diversion, Northeastern Illinois and Northwestern Indiana." These data were developed in cooperation with the U.S. Army Corps of Engineers, Chicago District, for the Lake Michigan Diversion Accounting program. Data are provided in four zip files and one MS Word file. The MS Word file 4.ReadMe.HSPF_Recalibrations_with_17TimeSeriesPairs.docx documents the recalibration of the Hydrological Simulation Program - FORTRAN (HSPF) model with discharge time series pairs that characterize the uncertainty of the published daily discharge at the two U.S. Geological Survey (USGS) streamgages, analyzed in 2.PubQUncertaintyEst.zip. It also points to data included in four zip files. The zip files provide the inputs, scripts and other executables, and sample outputs from the model archive for the publication. In addition, the zip files document the executables (1.Executables.zip) and the following modeling tasks: 2.PubQUncertaintyEst.zip - Estimation of the uncertainty of published daily discharge at two USGS streamgages; 3.BaseModel-ParameterUncertainty.zip - Estimation of the parameters of the base HSPF model; and 5.HSPFsimulations.zip - Simulations of discharge with HSPF for the nine study watersheds.

The basis for these features is U.S. Geological Survey Scientific Investigation Report 2017-5024 Flood Inundation Mapping Data for Johnson Creek near Sycamore, Oregon. The domain of the HEC-RAS hydraulic model is a 12.9 mile reach of Johnson Creek from just upstream of SE 174th Avenue in Portland, Oregon to its confluence with the Willamette River. Some of the hydraulics used in the model were taken from Federal Emergency Management Agency, 2010, Flood Insurance Study, City of Portland, Oregon, Multnomah, Clackamas and Washington Counties, Volume 1 of 3, November 26, 2010. The Digital Elevation Model (DEM) utilized for the project was developed from LiDAR data flown in 2015 and provided by the Oregon Department of Geology and Mineral Industries. Bridge decks are generally removed from DEMs as standard practice. Therefore, these features may be shown as inundated when they are not. Judgement should be used when estimating the usefulness of a bridge during flood flow. Comparing the bridge to the surrounding ground can be more informative in this respect than simply looking at the bridge itself. Two model plans were used in the creation of the flood layers. The first is a stable model plan using unsteady flow in which the maximum streamflow is held in place for a long period of time (a number of days) in order to replicate a steady model using an unsteady plan. The stable model plan produced the areas of uncertainty contained in the sycor_breach.shp shapefile. The second is an unstable model plan that uses unsteady flow in which the full hydrograph (rising and falling limb) is represented based on the hydrograph shape of the December 2015 peak annual flood. The unstable model plan produced the flood extent polygons contained in the sycor.shp shapefile and the depth rasters and represents the best estimate of flood inundation for the given streamflow at U.S. Geological Survey streamgage 14211500.

This data set serves to archive the data, analysis and models of the associated publication entitled “Calibration of the USGS National Hydrologic Model in Ungauged Basins Using Statistical At-Site Streamflow Simulations” as published in the Journal of Hydrologic Engineering. The input data files included here as comma-separated values contain measured streamflow, streamflow simulated by the Precipitation-Runoff Modeling System calibrated to measured streamflow, streamflow simulated by the Precipitation-Runoff Modeling System calibrated to streamflow simulated by pooled ordinary kriging, and streamflow simulated by pooled ordinary kriging at 1,410 streamgage locations across the United States. These data sets, built on previously published models, are assessed in the included analysis script (R programming language) to reproduce the findings of the associated manuscript. The manuscript argues that statistically generated daily streamflow can be used to support the ability of physical models to represent hydrologic processes at ungauged locations. The objective of this study was to determine the feasibility of using simulations in place of measured streamflow to calibrate physical models in ungauged basins. Calibrating with statistically simulated streamflow produced performances within 23% of applications with knowledge of at-site measurements. Furthermore, statistically generated streamflows produced accurate timing information, which, when combined with alternative data sets (e.g., evapotranspiration, recharge, etc.), can be used to improve representation of hydrologic processes at ungauged locations.

This data set serves to archive the data, analysis and models of the associated publication entitled “Calibration of the USGS National Hydrologic Model in Ungauged Basins Using Statistical At-Site Streamflow Simulations” as published in the Journal of Hydrologic Engineering. The input data files included here as comma-separated values contain measured streamflow, streamflow simulated by the Precipitation-Runoff Modeling System calibrated to measured streamflow, streamflow simulated by the Precipitation-Runoff Modeling System calibrated to streamflow simulated by pooled ordinary kriging, and streamflow simulated by pooled ordinary kriging at 1,410 streamgage locations across the United States. These data sets, built on previously published models, are assessed in the included analysis script (R programming language) to reproduce the findings of the associated manuscript. The manuscript argues that statistically generated daily streamflow can be used to support the ability of physical models to represent hydrologic processes at ungauged locations. The objective of this study was to determine the feasibility of using simulations in place of measured streamflow to calibrate physical models in ungauged basins. Calibrating with statistically simulated streamflow produced performances within 23% of applications with knowledge of at-site measurements. Furthermore, statistically generated streamflows produced accurate timing information, which, when combined with alternative data sets (e.g., evapotranspiration, recharge, etc.), can be used to improve representation of hydrologic processes at ungauged locations.

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 (NHM; Regan and others, 2018). This child page specifically contains a suite of 52 streamflow metrics. These metrics were computed using daily outputs of runoff from HRUs (PRMS variable hru_outflow) and streamflow from the model stream segments (PRMS variable seg_outflow) for all historical and future simulations (table1_GCMs_used.csv) with both static and dynamic land cover parameters. These streamflow statistics describe the duration, frequency, magnitude, rate of change, and timing of streamflow computed for historical and future simulation periods (streamflow_statistics_description_table.csv).

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 (NHM; Regan and others, 2018). This child page specifically contains a suite of 52 streamflow metrics. These metrics were computed using daily outputs of runoff from HRUs (PRMS variable hru_outflow) and streamflow from the model stream segments (PRMS variable seg_outflow) for all historical and future simulations (table1_GCMs_used.csv) with both static and dynamic land cover parameters. These streamflow statistics describe the duration, frequency, magnitude, rate of change, and timing of streamflow computed for historical and future simulation periods (streamflow_statistics_description_table.csv).