A biophysical approach to modeling overland flow in the Everglades can help predict future outcomes for ecological habitat, water storage during droughts, and water conveyance during floods. The data provided include measurements of vegetation stem architecture, microtopography, and landscape pattern metrics. Stem architecture measurements present the opportunity to estimate flow roughness of distinct vegetation communities based on hydraulic principles. At a larger scale, the microtopography and the connectivity of the sloughs between ridges offer a way to quantify the effects of flow blockage and tortuous flow paths on overland flow. Combined with theory, these data provide the capacity to simulate overland flow in both the historic, pre-drainage Everglades as well as in the present-day managed Everglades. Also provided are the hydrologic data, e.g., water slopes, water depths and overland flow velocities, that can be used to verify a biophysical model. Ultimately, the purpose is to anticipate how changing flow and water depth will interact with evolving vegetation and landscape conditions to influence future water availability for society and for the ecosystem, both in the Everglades and in other low-gradient floodplains.

Soil porewater (30cm and 60cm depth) was sampled for specific conductance, salinity and temperature in the southwest coastal Everglades, Everglades National Park from 1997-2012 at four sampling locations. Principal sampling location (HR) was located adjacent the Harney River and had five sampling sites (~ 60m apart) along a 300m N-S transect in a coastal mangrove fringe forest sampled from 1997-2011. Porewater was sampled from 2002-2012 at three secondary locations: Tarpon Bay (TB), Shark River (SR) and Shark Slough (SS). At each of these sampling locations, there were at least three 30cm and three 60cm porewater sampling pipes.

The southeastern United States was modeled to produce 59 simulations of historical and potential future streamflow using the Precipitation Runoff Modeling System (PRMS) as part of the study documented in LaFontaine and others (2019). One simulation used historical observations of climate, 13 used historical climate simulations using statistically downscaled general circulation model (GCM) output from the Coupled Model Intercomparison Project (CMIP5), and 45 used potential future climate simulations using statistically downscaled CMIP5 GCMs for four representative concentration pathways. Historical simulations with observations are for the period 1952-2010, historical simulations with the GCMs are for the period 1952-2005, and potential future simulations are for the period 2007-2099. These data document the PRMS climate input data files for these simulations. Input files for the simulations include the PRMS base parameter file and five dynamic parameter files that update model parameters on an annual time step for impervious area, dominant land cover type, and canopy interception. LaFontaine, J.H., Hart, R.M., Hay, L.E., Farmer, W.H., Bock, A.R., Viger, R.J., Markstrom, S.L., Regan, R.S., and Driscoll, J.M., 2019, Simulation of Water Availability in the Southeastern United States for Historical and Potential Future Climate and Land-Cover Conditions: U.S. Geological Survey Scientific Investigations Report, 2019-5039, 83 p., https://doi.org/10.3133/sir20195039.

The southeastern United States was modeled to produce historical and potential future simulations of streamflow statistics using the Precipitation Runoff Modeling System (PRMS) as part of the study documented in LaFontaine and others (2019). Hydrologic simulations using one observation-based historical climate dataset (Maurer and others, 2002), 13 used historical climate simulations using statistically downscaled general circulation model (GCM) output from the Coupled Model Intercomparison Project (CMIP5), and 45 used potential future climate simulations using statistically downscaled CMIP5 GCMs for four representative concentration pathways were used for the computation of 52 hydrologic statistics of streamflow using output data files from each simulation. Output files for the simulations include: 1) historical annual values of each statistic for each HRU and stream segment for the period 1952-2010 for the observation-based simulation, 1952-2005 for the 13 GCM-based historical simulations, and 2045-2075 for the 45 GCM-based future simulations, 2) PRMS summary output files with daily time step basin-averaged output variables for the period 1950-2010 for the observation-based simulation, 1950-2005 for the 13 GCM-based historical simulations, and 2006-2099 for the 45 GCM-based future simulations. The first year of the PRMS summary output files should be ignored due to model initiation. LaFontaine, J.H., Hart, R.M., Hay, L.E., Farmer, W.H., Bock, A.R., Viger, R.J., Markstrom, S.L., Regan, R.S., and Driscoll, J.M., 2019, Simulation of Water Availability in the Southeastern United States for Historical and Potential Future Climate and Land-Cover Conditions: U.S. Geological Survey Scientific Investigations Report, 2019-5039, 83 p., https://doi.org/10.3133/sir20195039. Maurer, E.P., Wood, A.W., Adam, J.C., Lettenmaier, D.P., and Nijssen, B., 2002, A long-term hydrologically based dataset of land surface fluxes and states for the conterminous United States: Journal of Climate, v. 15, no. 22, p. 3237–3251, accessed September 24, 2017, at https://doi.org/10.1175/1520-0442(2002)015<3237:ALTHBD>2.0.CO;2.

This data release contains inputs for and outputs from hydrologic simulations of the southeastern U.S. using the Monthly Water Balance Model, the Precipitation Runoff Modeling System (PRMS), and statistically-based methods. These simulations were developed to provide estimates of water availability and statistics of streamflow for historical and potential future conditions for an area of approximately 1.16 million square miles. These model input and output data are intended to accompany a U.S. Geological Survey Scientific Investigations Report (LaFontaine and others, 2019); they include four types of data: 1) model input parameters, 2) model output statistics, 3) GIS files of the model hydrologic response units and stream segments, and 4) statistically-based streamflow estimates for headwater watersheds. LaFontaine, J.H., Hart, R.M., Hay, L.E., Farmer, W.H., Bock, A.R., Viger, R.J., Markstrom, S.L., Regan, R.S., and Driscoll, J.M., 2019, Simulation of Water Availability in the Southeastern United States for Historical and Potential Future Climate and Land-Cover Conditions: U.S. Geological Survey Scientific Investigations Report, 2019-5039, 83 p., https://doi.org/10.3133/sir20195039.

This data release presents truth data and benchmark results describing simulation of hydrologic drought events in the conterminous United States. This data release supports a publication (Simeone and others, 2024) which documents drought benchmarking methods and their application to the results of the National Water Model (NWM) version 2.1. Truth data used were observations at U.S. Geological Survey streamgages across the conterminous United States. These data include 4662 U.S. Geological Survey streamgages with a historical period from 1984-2016. The following files are included in this data release: 1) kappa_long_nwm.csv: Benchmark results for the Cohen's kappa evaluation metrics in long table format. 2) spear_bias_dist_long_nwm.csv: Benchmark results for the Spearman's, bias, and distributional evaluation metrics in long table format. 3) ann_eval_long_nwm.csv: Benchmark results for the annual drought evaluation metrics in long table format. 4) streamflow_percentiles_nwm.zip: A zip file containing individual streamflow percentile data files used in this analysis as truth data. 5) input_data_nwm.zip: A zip file with input data for individual streamgages used for our data analysis pipeline as truth data. 6) streamflow_gages_in_study.csv: Metadata information for the 4662 U.S. Geological Survey streamgages contained in the above datasets.

This data release presents truth data and benchmark results describing simulation of hydrologic drought events in the conterminous United States. This data release supports a publication (Simeone and others, 2024) which documents drought benchmarking methods and their application to the results of the National Hydrologic Model Precipitation-Runoff Modeling System v1.0 (NHM-PRMS). Truth data used were observations at U.S. Geological Survey streamgages across the conterminous United States. These data include 4662 U.S. Geological Survey streamgages with a historical period from 1984-2016. The following files are included in this data release: 1) kappa_long_nhm.csv: Benchmark results for the Cohen's kappa evaluation metrics in long table format. 2) spear_bias_dist_long_nhm.csv: Benchmark results for the Spearman's, bias, and distributional evaluation metrics in long table format. 3) ann_eval_long_nhm.csv: Benchmark results for the annual drought evaluation metrics in long table format. 4) streamflow_percentiles_nhm.zip: A zip file containing individual streamflow percentile data files used in this analysis as truth data. 5) input_data_nhm.zip: A zip file with input data for individual streamgages used for our data analysis pipeline as truth data. 6) streamflow_gages_in_study.csv: Metadata information for the 4662 U.S. Geological Survey streamgages contained in the above datasets.

To provide daily mean streamflow values at ungaged (partial-record) sites within the Yankee Fork Salmon River watershed, the U.S. Geological Survey (USGS), in cooperation with U.S. Bureau of Reclamation, used discharge measurements at three partial-record sites and related those measurements to a nearby USGS real-time streamgage (index site). Daily mean streamflow was estimated by developing a regression relationship between each partial-record site and the index site for water years 2012-2019. These data are intended to provide daily mean streamflow estimates at partial-record sites as part of a larger study (Clark and others, 2021) to estimate sediment loading for each site.

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).