cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4211/hs.08c605a1c7244d4f8691154eaa02ecc1
title: Using HydroShare to Enhance Sharing and Reproducibility of Research Results

description: HydroShare is a web-based hydrologic information system operated by the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI). Within HydroShare, users can create and share data and models using a variety of file formats and flexible metadata. HydroShare enables users to formally publish these resources as well as create linkages between published data and model resources and peer reviewed journal publications that describe them. Ability to link published data and models with the papers that describe them is a great step in the direction of scientific reproducibility, but is only a first step. HydroShare supports further transparency in the scientific process by enabling scripting of analytical steps via a RESTful application programming interface (API). Using this API, HydroShare users can develop scripts to read data from HydroShare, perform an analytical step (e.g., data processing or visualization), and then write results back to HydroShare. The script itself can then be shared as part of the published dataset in HydroShare, or it can be shared as a Jupyter Notebook that can be executed within the HydroShare environment. Scripts or Jupyter Notebooks can then be executed by others to reproduce the analysis used by the original authors. In this presentation, we discuss how HydroShare can enable best practices for linking publications with data and models and for promoting reproducibility in environmental analyses through sharing of data, models, and scripts that encode the scientific workflow. The HydroShare system is available at http://www.hydroshare.org. Source code for HydroShare is available at https://github.com/hydroshare.
DOI: 10.4211/hs.8ee5e32d023f4e23b0dff487d680309a
title: Great Salt Lake Water Markets

description: Data collection on water the potential for water markets to address Great Salt Lake water conservation needs. 

To create cost estimates we build on the approach of Edwards et al (2017) to create conservation cost curves estimates for each of the Bear River, Weber River, and Jordan River watersheds. We designate potential conservation measures as occurring in the agricultural or urban sectors. Estimates come from other sources and are then applied to the case at hand. Overall we estimate the conservation potential and cost savings of 15 measures, shown in the table. While the list is not comprehensive, efforts were made to include the measures likely to be implemented.

Conservation measures by category.
Urban	Residential: low-flow toilets
Residential: low-flow showers
Residential: high-efficiency clothes washers
	Residential irrigation: rainwater harvesting
Residential irrigation: watering at night
Residential irrigation: scheduling
Residential irrigation: partial turf conversion
	Institutional irrigation: watering at night
Institutional irrigation: scheduling
	Commercial irrigation: watering at night
Commercial irrigation: scheduling
	Secondary wastewater reuse
Agriculture	Conversion to sprinkler irrigation
Improved irrigation efficiency
Canal piping
	
For each conservation we estimate the quantity of water that could be conserved as well as the cost of conserving that water. We create a low, baseline, and high estimate of costs for each measure. We also create a high, baseline, and low estimate of the amount of water made available by each measure. The low cost estimate is combined with the high water availability estimate to arrive at an upper bound of each water supply curve; similarly the high-cost and low water-availability estimates are combined to create a lower-bound.
DOI: 10.4211/hs.20891fd47c3d4be28d723950ff415671
title: Snow Chemistry upper Provo River watershed, Uinta Mountains, UT, USA

description: Snow chemistry data from the Uinta Mountains in the upper Provo River Watershed. Data set includes sampling location, water isotopes, disolved organic carbon(DOC), flitered major and trace elements, and 87Sr/86Sr ratios.
DOI: 10.4211/hs.1825ac7f0cd94f4d950929600729f36d
title: Upper Provo River Water Chemistry

description: Water chemistry data for the upper Provo River at three aquatic sites, Soapstone, Woodland and Hailstone. Data set includes, water isotopes, DOC, trace elements, major elements, and 87Sr/86Sr ratios.
DOI: 10.4211/hs.4d72b8e0c7414ec5b5b688f4b4faa691
title: Uinta Mountain soil: trace elements, major elements, strontium isotopes

description: Soil chemistry for two locations in the upper Provo River watershed of the Uinta Mountains. Data set includes sequential leaches of soil pits in 10 cm increments for trace elements, major elements and 87Sr/86Sr ratios.
DOI: 10.4211/hs.b5f8b9a80fa44d9b869a4d1604f8df2b
title: Soil water, spring and ephemeral stream chemistry in upper Provo River watershed above Soapstone

description: Water chemistry data for springs, soil water, and ephemeral streams in the upper Provo river within the Uinta Mountains. Data set includes water isotopes, trace elements, major elements, 87Sr/86Sr, DOC, and various other water quality measurements.
DOI: 10.4211/hs.508f0ca823f34cbe9d98f8d2ff3cabe4
title: Derivation of flood hydrographs with Landlab

description: This resource contains a model that enables to obtain the flood hydrographs or the peak discharges for a real basin in Sicily and a set of return times.
DOI: 10.4211/hs.f154c58eef364d7582a081eefc3b1d08
title: ParFlow.CLM model input files of Waterview permeable pavement site, Philadelphia, Pennsylvania, USA

description: A permeable pavement green infrastructure (GI) site, located in Philadelphia, Pennsylvania, USA, was simulated using ParFlow.CLM. We utilized 1-m horizontal gridding, representing a site area of 400 square meters. Vertical discretization was variable ranging from 0.01 to 5m with the terrain-following grid feature of ParFlow.CLM activated. The model domain contains 8,000 finite difference cells. The simulation period was 1 January 2016 to 31 December 2016. 
The zip archive (.zip) contains the inputs required to execute the model run. These include: ParFlow binary files (.pfb) for the geologic unit indicator field and pressure initial condition, CLM text files (.dat and .txt) for input parameters, 1-D NLDAS2 forcing, vegetation matrix and vegetation parameters, and a ParFlow input tcl file to generate model input database (.tcl). CLM restart files (.rst) contain the CLM initial condition.  A Bash shell script (.sh) containing model dimensions is also included.
DOI: 10.4211/hs.4fa250f7954e4cda9021b6c722cce8d6
title: HYMOD2 Hydrological Model Matlab Code

description: HYMOD2 is an improved version of the widely used hydrological model HYMOD. The improvements are made based on simple but realistic evaporation process parameterizations. The file "hymod2.m" is the model code, which is also well commented so that it is easy to follow. 

The input file needs to be in MATLAB data format (.mat).  Rows should include daily sequence and columns are for the following variables: Precipitation (column-1), Potential Evaporation (column-2) and Discharge (column-3).  Check "LoadData.m" function for input information and make changes as necessary.  Parameter values are assigned in "PriorHyModV2.m" function. Results are stored in "Results.mat" file.

Disclaimer:
This program comes "as is" and the authors cannot be held responsible for any issues resulting from the improper functioning of the program. If found, please report the bugs to royt@email.arizona.edu. Prompt action will be taken to fix reported bugs.

HYMOD2 Citation: ​
Roy, T., H. V. Gupta, A. Serrat-Capdevila, and J. B. Valdes (2017), Using Satellite-Based Evapotranspiration Estimates to Improve the Structure of a Simple Conceptual Rainfall-Runoff Model, Hydrology and Earth System Sciences, 21(2), 879–896, doi:10.5194/hess-21-879-2017.

HYMOD Citation:
​Boyle, D. P., H. V Gupta, and S. Sorooshian (2000), Toward improved calibration of hydrologic models: Combining the strengths of manual and automatic methods, Water Resources Research, 36, 3663– 3674, doi:10.1029/2000WR900207.
DOI: 10.4211/hs.f0740db7831d4096967faa84abdd95cf
title: Hurricane Irma 2017 Collection

description: Quick Start
This is a collection of flood datasets to support hydrologic research for Hurricane Irma in Florida-Georgia, August-September 2017. The best way to start exploring this collection is by opening the Hurricane Irma 2017 Story Map [http://arcg.is/PSOKH]. It has separate tabs for the different content categories, and links to the relevant HydroShare resources within this collection. 
For more information on this hurricane archive project, as well as links to Hurricanes Harvey and Maria data archives, see the CUAHSI public page on the Hurricane 2017 Archives. [1]

More Details
This is the root collection resource for management of hydrologic and related data collected during Hurricane Irma, primarily in Florida, Georgia, and neighboring states within the storm's wind swath. This collection holds numerous composite resources comprising streamflow forecasts, inundation polygons and depth grids, flooding impacts, elevation grids, high water marks, and numerous other related information sources. Building outlines (polygons) for the affected states are also provided, to help understand storm impacts. 

The data providers for this collection are the NOAA National Weather Service, NOAA National Hurricane Center, NOAA National Water Center, FEMA, 9-1-1 emergency communications agencies, and many others. 

User-contributed resources from 2017 US Hurricanes may also be shared with The CUAHSI 2017 Hurricane Data Community group [2] to make them accessible to interested researchers, Anyone may join this group.

This collection has been produced by work on a US National Science Foundation RAPID Award "Archiving and Enabling Community Access to Data from Recent US Hurricanes" [4].

References
[1] CUAHSI Projects > Hurricane 2017 Archives [https://www.cuahsi.org/projects/hurricanes-2017-data-archive ]
[2] CUAHSI 2017 Hurricane Data Community group [https://www.hydroshare.org/group/41]
[3] Hurricane Irma 2017 Archive Story Map [http://arcg.is/PSOKH]
[4] NSF RAPID Grant [https://nsf.gov/awardsearch/showAward?AWD_ID=1761673]
DOI: 10.4211/hs.db5883d16e874ee3b7edd666dbad7d03
title: Irma Flood Data Collections

description: This collection is for datasets of flood depths, flood extents, high water marks, streamflow, damages recorded, aerial oblique photos, and related subjects. This includes both forecast and observed data. These were primarily obtained from national agencies such as NOAA (weather related), USGS (surface water related), FEMA (surface water and damage related), the Civil Air Patrol (aerial photos), and ECMWF (European Centre for Medium-Range Weather Forecasting, for flood area grids).
DOI: 10.4211/hs.aa5c9982a4694a19be2fa9299b78e5ca
title: NOAA NHC - Irma Storm Track - Best Track + Advisories

description: The NOAA National Hurricane Center (NHC) publishes advisory bulletins with named storm conditions and expectations, see [1]. We have also downloaded shapefiles for eighty-four 5-day forecasts (published from August 30 to September 11) of track line, predicted points, ensemble forecasts envelope, and affected shoreline where applicable [2]. NOAA also publishes the best track for major storms [3]. The "best track" is a smoothed version of the advisories track. Web services are also provided by NHC for the advisory points and lines [4] [5].  Another user has constructed the Irma track (shapefile) from the NHC advisory bulletins [6].

FEMA also posts windfield data, including peak wind gust and contours [7]. 
See FEMA disaster webpage [8] for map and list of counties receiving disaster declarations (map pdf available for download from this page)

References
[1] NOAA NHC - Irma storm advisories [http://www.nhc.noaa.gov/archive/2017/IRMA.shtml]  
[2] NOAA NHC - Irma 5-day forecasts [https://www.nhc.noaa.gov/gis/archive_forecast_results.php?id=al11&year=2017&name=Hurricane%20IRMA]
[3] NOAA NHC - best tracks for 2017 storms [https://www.nhc.noaa.gov/data/tcr/index.php?season=2017&basin=atl]
[4] NOAA NHC - Irma advisory points web service [https://services.arcgis.com/XSeYKQzfXnEgju9o/ArcGIS/rest/services/The_2017_Atlantic_Hurricane_season_(to_October_16th)/FeatureServer/1]
[5] NOAA NHC - Irma advisory lines web service [https://services.arcgis.com/XSeYKQzfXnEgju9o/ArcGIS/rest/services/The_2017_Atlantic_Hurricane_season_(to_October_16th)/FeatureServer/6]
[6] Irma Advisories Track, compiled by David Tarboton [https://www.hydroshare.org/resource/546fa3feeaf242fc8aabf9fe05ab454c/]
[7] FEMA public download site for Hurricane Irma 2017 [https://data.femadata.com/NationalDisasters/HurricaneIrma/]
[8] FEMA Disaster Declarations and related links [https://www.fema.gov/disaster/4337]
DOI: 10.15468/dl.mxcq96
title: Occurrence Download

description: A dataset containing 259 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is ITA.15_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Asplenium ceterach"
 ]
}

 The dataset includes 259 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049934-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4211/hs.1b63089342354239a48209dfa84554d2
title: USGS - Irma High Water Marks

description: During and after Hurricane Irma, the US Geological Survey recorded high water marks across the affected area, as they do for every major storm [https://www.usgs.gov/special-topic/hurricane-irma]. The files in this dataset provide 506 high water marks for Hurricane Irma flooding, and 202 peak sites. These files were downloaded following the steps below. If you'd like to check the original sources again, or search for HWM for a different storm, you may find these directions helpful.  

The High Water Marks can also be visualized directly from the USGS Flood Event Viewer for Irma [https://stn.wim.usgs.gov/fev/#IrmaSeptember2017]

Finding, Downloading and Filtering USGS High Water Marks (HWM)
1. Visit USGS website: https://water.usgs.gov/floods/history.html, which lets you…
2. Click on Hurricane Irma: https://www.usgs.gov/irma, which lets you… 
3. Click on green button Get Data: https://stn.wim.usgs.gov/fev/#IrmaSeptember2017 
4. In left margin menu of resulting page, click a second Get Data link. This will open up the remaining options below. 
5. Click each data type you want, such as High-Water Mark, Peak Summary, or Sensor Data. It’s only csv or REST (json or xml).

* To understand the fields or columns of this table, see HWM_Peaks_Sensors_Data_Dictionary_20180329.xslx in the contents below.
DOI: 10.15468/dl.4zw74n
title: Occurrence Download

description: A dataset containing 400 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-0.981898 41.327788, -0.982262 41.366366, -1.033304 41.366366, -1.032921 41.327788, -0.981898 41.327788))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2015",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 400 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049935-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4211/hs.f23b2f6f100149ecbde40f4b49ea6fec
title: NOAA NWC - Irma National Water Model Streamflow Forecasts

description: The National Water Model (NWM) is a water forecasting model operated by the NOAA National Weather Service that continually forecasts flows on 2.7 million stream reaches covering 3.2 million miles of streams and rivers in the continental United States [1]. It operates as part of the national weather forecasting system, with inputs from NOAA numerical weather prediction models, and from weather and water conditions observed through the US Geological Survey's National Water Information System. Reference materials for the computational framework behind NWM is published by NCAR [9] [10]. 

The NWC generates NWM streamflow forecasts for the continental US (CONUS) with multiple forecast horizons and time steps. Due to the output file sizes, these are normally not available for download more than a couple days at a time [2]. A 40-day rolling window of these forecasts is maintained by HydroShare at RENCI [3], and a complete retrospective (August 2016 to the present) of the NWM Analysis & Assimilation outputs is maintained as well (contact help@cuahsi.org for access).

An archive of all NWM forecasts for the period Aug 29 to Sept 17, 2017 has been compiled at RENCI [4] [5], available as netCDF (.nc) files totaling 6.8 TB. These can be browsed, subsetted, visualized, and downloaded (see [6] [7] [8]). In addition to these output files, we have uploaded to this HydroShare resource the input parameter files needed to re-run the NWM for the Irma period, or for any time period covered by NWM v1.1 and 1.2 (August 2016 to this publication date in August 2018). These parameter files are also made available at [1].

See README for further details and usage guidance. Please see NOAA contacts listed on [1] for questions about the NWM data contents, structure and formats. Contact help@cuahsi.org if any questions about HydroShare-based tools and data access.

References
[1] Overview of the NWM framework and output files [http://water.noaa.gov/about/nwm] 
[2] Free access to all National Water Model output for the most recent two days [ftp://ftpprd.ncep.noaa.gov/pub/data/nccf/com/nwm]
[3] NWM outputs for rolling 40-day window, maintained by HydroShare [http://thredds.hydroshare.org/thredds/catalog/nwm/catalog.html]
[4] Archived Irma NWM outputs via RENCI THREDDS server [http://thredds.hydroshare.org/thredds/catalog/nwm/irma/catalog.html]
[5] RENCI is an Institute at the University of North Carolina at Chapel Hill 
[6] Live map for National Water Model forecasts [http://water.noaa.gov/map]
[7] NWM Forecast Viewer app [https://hs-apps.hydroshare.org/apps/nwm-forecasts]
[8] CUAHSI JupyterHub example scripts for subsetting NWM output files [https://hydroshare.org/resource/3db192783bcb4599bab36d43fc3413db/]
[9] WRF-Hydro Overview [https://ral.ucar.edu/projects/wrf_hydro/overview]
[10] WRF-Hydro User Guide 2013 [https://ral.ucar.edu/sites/default/files/public/images/project/WRF_Hydro_User_Guide_v3.0.pdf]
DOI: 10.4211/hs.fb519c27b3284fa68ac60a85899df33b
title: CUAHSI Tools and Services for Managing Research Data

description: Scientists are faced with many data-centric challenges in their day-to-day research including, but not limited to, management, collaboration, archival, and publication. This is complicated by the disparate and diverse nature of earth surface data which typically makes a single repository less than ideal for all data used and created for a given study. In recent years, initiatives such as National Science Foundation data management plans and the American Geophysical Union findable, accessible, interoperable, and reusable (FAIR) principals have incentivized researchers to explore solutions for archiving data that will improve future research capabilities. In the area of Hydrologic Data Management, CUAHSI has been developing software tools to help researchers collaborate, share, manage and publish their research data, making it FAIR. This workshop will introduce these tools which include the hydrologic information system (HIS), observations data model version 2 (ODM2), ODM2Admin data management portal, and HydroShare. Attendees will be given an overview of CUAHSI's efforts to support research activities by participating in a series of interactive presentations that progress from (1) simple time series data, to (2) advanced earth observations, and finally to (3) complex data types. We welcome novice and advanced data creators, users, and managers to join us in this workshop.
DOI: 10.4211/hs.7f1c8d5a61a541e388403f5dbde272a8
title: Meteorological data at Lysina

description: This is the meteorological data at Lysina, Czech Republic
DOI: 10.4211/hs.85ddf1b1cce44323986b1efe788040a4
title: PIHM files for hydrologic modeling at Lysina Czech Republic

description: It includes all inputs, outputs and source code of PIHM simulation at Lysina
DOI: 10.4211/hs.c47cf6107dd046e2991a459fa6c72fca
title: Supporting Data for Neilson et al., 2018 Groundwater flow and exchange across the land surface explain carbon export patterns in continuous permafrost watersheds, Geophysical Research Letters

description: Supporting data files for Neilson et al., 2018, Groundwater flow and exchange across the land surface explain carbon export patterns in continuous permafrost watersheds.

Flow and DOC data used in the manuscript can be found online at http://ine.uaf.edu/werc/projects/NorthSlope/imnavait/flume/flume.html and http://arclter.ecosystems.mbl.edu/data-catalog, respectively.

Permeability_Depth_Profile.xlsx
Figure S3a: Vertical permeability profile measured with KSAT or slug test methods and used in the vertically explicit groundwater model.  KSAT done in lab, slug tests done in the field.

Porosity_Depth_Profile.xlsx
Figure S3b: Vertical porosity profile used in the vertically explicit groundwater model.

Fill_DEM_3m1.tif
Figures S1a and S4: Digital Elevation Model at 3 m resolution resampled from 20cm FodarDEM (http://fairbanksfodar.com/fodar-earth) and used in the vertically integrated groundwater model.

ALT_RawData_IncludeSmallGrid.xlsx
Figure S2: Top of casing elevation, ground surface elevation, water depth in well, total well length, and triplicate distance below land surface to frozen surface.

SurfaceTopography.xlsx
Figures 1, 2, S3, and S5: Land surface elevation profile used in the vertically explicit groundwater model.

Hydrozoid_DOC_to_WEB.xlsx
Figure S6: Soil dissolved organic carbon concentrations from Imnavait Creek.
DOI: 10.4211/hs.4369c453d4cc4b9a8397278f10ad40f2
title: Mississippi_River_Basin_Discharge_Series_USGS_Sampled_SWOT

description: Includes daily USGS streamflow measurements for 454 gauges throughout the Mississippi River Basin for the period April 1, 2010 to May 1, 2016, a shapefile of the USGS gauges, and assuming a theoretical launch date of the Surface Water and Ocean Topography (SWOT) Mission being April 16, 2010, sampled SWOT-observed discharges with and without preliminary SWOT discharge uncertainties (based on Hagemann et al. 2017; DOI: 10.1002/2017WR021626) .
DOI: 10.4211/hs.7839bf475a674052b790c0ef847d58ee
title: Irma Basemap - Florida Transportation Data

description: This resource contains statewide networks of roadways, bridges, and railway crossings, for Florida only. These datasets  were obtained from Florida Dept of Transportation (FDOT) in August 2018 via their website [1].  The FDOT GIS data is continually being updated, so if you wish to find the most complete and current data, please visit that site. 

Contained in the zipfile:
- Roadways (28,992 instances) including the following:
      - Interstate Highways (81)
      - US Highways (643)
      - Toll Roads (90)
      - State Highways(1,917)
      - Active on the State Highway System (1,450)
      - Active off the State Highway System (9,452)
      - Florida Roadways (15,359)
- Bridges (9,527)
- Railway Crossings (1,937)
- Numerous other GIS feature layers as well. 
All feature layers in the FDOT geodatabase also have ArcMap (.lyr) files for efficient loading and symbolizing.  

References:
[1] FDOT GIS data [http://www.fdot.gov/statistics/gis/]