cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4211/hs.8da8bb7cb66d475ea03af1a79b38a446
title: Surface Water Hydrology and Flood Recurrence in the Flagstaff, Arizona Area, 2008-2019

description: Flagstaff, Arizona has unique surface water hydrology due to climate, geology, and vegetation. The area experiences extremely low rainfall-runoff in natural undisturbed areas. This “complacent” watershed condition leads to dramatic shifts in flow and flooding when disturbances such as urbanization, wildfire, or even forest thinning are introduced to the landscape. Using 57 stream and rain gauges this report provides preliminary data to inform managers, engineers, and scientists on both the complacent and “violent” watershed characteristics of the Flagstaff area. This is the first regional surface water hydrology report since the 1988 US Geological Survey report on flood frequency in the Flagstaff area. Preliminary results indicate that previous flood frequency analyses provide a much higher predicted flood flow than empirical gauge results have observed. In some sites the over-prediction of regional regressions is over twice observed values. The hope is that this preliminary report will provide a “stepping stone” towards a greater understanding of the hydrologic drivers and stream character of the area. More data, over a longer time period, is required for making defensible predictions of rainfall-runoff, flood frequency, and flood mitigation design in the Flagstaff area.
DOI: 10.4211/hs.3b80707ee9fe4b329d5c5b2abd20c9d8
title: Delayed Impact Calculator Update 2025

description: This calculator is an Excel workbook programmed with Visual Basic for Applications macro code to perform finite-difference computations for assessment of attenuation and delay dynamics of stream-aquifer system response to groundwater impulse time series input.  The spreadsheet estimates impact accrual schedules for well-induced stream depletion and for groundwater return flow scenarios. Single impulse, uniform series, variable series, and annual pattern impulse type options facilitate streamlined input and analysis of a diverse range of occurrence and use patterns, including intermittent pumping.  Segregation of response output by stream reach gives location-specific insight useful to surface water administration.  Tidy secondary output options include cumulative ratio, response ratio, and period ratio of response to impulse.  The workbook (.xlsm) is accompanied by an instruction manual (.pdf) and supplemental materials, primarily consisting of copies configured to match published scenarios.  There is also a version in Spanish residing as a separate resource named Calculadora de Impactos Demorados.
DOI: 10.4211/hs.fcf736ca06d34322bca3b9895ab0864d
title: Prior Appropriations Water Rights Lab (Water in the West)

description: This Excel-based educational resource is designed as a week-long module targeting sophomore-level students in Boise State University's Water in the West course (GEOS 212). At the end of this module, students should be able to accomplish the following: (1) list some consumptive uses of water, (2) articulate the principle of Prior Appropriation, (3) in the context of water rights, describe what curtailment is, (4) translate water rights information into a schedule of diversions, (5) simulate the effect of water withdrawals on a streamflow hydrograph, and (6) develop a report as a member of a team.The lab requires the students to adopt the perspective of a water manager who is tasked with implementing a set water withdrawals from a notional river in the Western US in accordance with a Prior Appropriation approach. They are provided water rights information for five water users that include: (1) a priority date, (2) a date of first use, (3) a date of final use, and (4) an authorized diversion rate. They then have to manage withdrawals (i.e., the timing of curtailment) from the river in accordance with these water rights under three scenarios. The first scenario considers a historical era in which seasonal snowpacks maintained water well into the growing season. The second scenario requires them to undertake curtailments in accordance with priority date to maintain flow in the river due to earlier and more rapid snowmelt associated with climate change. The final scenario provides them a simple storage reservoir to which they can divert water and from which they can withdraw water to sustain late season water use.
DOI: 10.4211/hs.96794cc564894ffa9f8fb4e419a8720f
title: (HS 5) Large Extent Spatial Datasets in Virginia

description: This HydroShare resource was created to share large extent spatial (LES) datasets in Virginia on GeoServer (https://geoserver.hydroshare.org/geoserver/web/wicket/bookmarkable/org.geoserver.web.demo.MapPreviewPage) and THREDDS (https://thredds.hydroshare.org/thredds/catalog/hydroshare/resources/catalog.html).

Users can access the uploaded LES datasets on HydroShare-GeoServer and THREDDS using this HS resource id. This resource was created using HS 2.

Then, through the RHESSys workflows, users can subset LES datasets using OWSLib and xarray.
DOI: 10.4211/hs.7bd3a773639f40458c22c5ec43ae3bc6
title: (HS 3) Large Extent Spatial Datasets in North Carolina

description: This HydroShare resource was created to share large extent spatial (LES) datasets in North Carolina on GeoServer (https://geoserver.hydroshare.org/geoserver/web/wicket/bookmarkable/org.geoserver.web.demo.MapPreviewPage) and THREDDS (https://thredds.hydroshare.org/thredds/catalog/hydroshare/resources/catalog.html).

Users can access the uploaded LES datasets on HydroShare-GeoServer and THREDDS using this HS resource id. This resource was created using HS 2.

Then, through the RHESSys workflows, users can subset LES datasets using OWSLib and xarray.
DOI: 10.25430/researchdata.cab.unipd.it.00001705
title: Functional hyperprolactinemia and primary hypothyroidism: myth or reality in clinical practice?

description: Background: Hyperprolactinemia is a frequent clinical condition with different etiologies. Although primary hypothyroidism is often considered a leading cause of mild hyperprolactinemia, the supporting evidence is limited and often based on small studies with single prolactin (PRL) measurements, especially in cases of subclinical hypothyroidism. This study aims to evaluate the prevalence of thyroid dysfunction in patients assessed for hyperprolactinemia.
Patients and methods: This retrospective study included patients undergoing cannulated PRL sampling (three serial measurements) and TSH assessment on the first sample, between January 2013 and May 2024, at Padova University Hospital. Patients were stratified by the degree of PRL elevation and TSH levels. PRL-secreting pituitary adenoma, functional hyperprolactinemia and normal pituitary function were assessed through review of medical history.
Results: Of 292 patients with available data, 233 fulfilled the inclusion criteria. Hyperprolactinemia was confirmed in 91/233 patients (39%). Among these, 27% had increased TSH compared to 18% in the normoprolactinemic group (p=0.073). No significant differences in TSH levels were observed when comparing subgroups of patients with varying degrees of PRL excess (p=0.474). PRL levels from cannulated samples and their mean values were not significantly higher in patients with hypothyroidism. Bivariate correlation analysis revealed no significant association between TSH and PRL levels. 
Conclusion: Our findings suggest a low probability of hypothyroidism as a primary cause of hyperprolactinemia: TSH increase should not delay the diagnostic evaluation for hyperprolactinemia, due to the low probability of thyroid dysfunction. Further studies are necessary to confirm these findings and improve clinical practice.
DOI: 10.4211/hs.e2abb2679d0548d381046101699a2ef5
title: Geophysics Dataset Sentinel Meadows, Yellowstone National Park

description: This data set contains raw data files for July 2018 geophysical data collection in Sentinel Meadows, Yellowstone National Park (ERT, Seismic Refraction, and magnetic).

It also includes plotting code for inverted results from SkyTEM dataset collected November 2016.
DOI: 10.4211/hs.b7973d7df99b4f719098d959078ef4c3
title: Spatial patterns and sensitivity of intermittent stream drying to climate variability sampling data

description: Intermittent streams comprise much of the global river network, and are expected to become more prevalent as a result of climate change. Characterizing the expansion and contraction of intermittency in stream networks, and understanding how sensitive these dynamics are to climatic variability, is critical for predicting the trajectory of hydrologic regimes in a changing climate. Here, we consider the spatial patterns of stream intermittency, focusing on wetted channel conditions at the end of the dry season, and identify land cover, physiographic, and climate variables that influence surface water presence and variability across years. We trained statistical models with wetted channel mapping data from 25 streams over 7 years to predict both the spatial and interannual variability of the wetted channel network. The data used to train these models is published here.
DOI: 10.4211/hs.5b9a29f88f12441fae957391de7c3eac
title: WRR_Connectivity_ExperimentalResults

description: These spreadsheets contain the calculations and mineral dissolution rate results for microfluidic experiments conducted with increasing pore network connectivity (dead-end pores) at pH 3 and 5.
DOI: 10.4211/hs.de6d92d314354ea6819157818669fc59
title: Supporting data for Ward et al., (2022) Advancing river corridor science beyond disciplinary boundaries with an inductive approach to catalyse hypothesis generation

description: This entry contains the supporting data for the manuscript:

Ward, A. S., Packman, A., Bernal, S., Brekenfeld, N., Drummond, J., Graham, E., Hannah, D. M., Klaar, M., Krause, S., Kurz, M., Li, A., Lupon, A., Mao, F., Roca, M. E. M., Ouellet, V., Royer, T. V., Stegen, J. C., & Zarnetske, J. P. (2022). Advancing river corridor science beyond disciplinary boundaries with an inductive approach to catalyse hypothesis generation. Hydrological Processes, 36( 4), e14540. https://doi.org/10.1002/hyp.14540
DOI: 10.4211/hs.21e61fe839004fd399439a2a3391a763
title: CUAHSI Statement on Holistic Evaluation of Research in the Hydrologic Sciences

description: This document intends to provide context on norms within the hydrologic science community to provide a framework for understanding what research products and processes are valued by the academic hydrologic sciences community. This will better inform those charged with review and assessment of hydrologic scientists, enabling consideration of traditional as well as new types of contributions to advancing the field of hydrologic sciences. This document does not include other areas of academic contributions including teaching, service, and outreach. The document should be of use to those applying to academic positions, promotions, and tenure; external evaluators and reviewers; review committees and senior faculty; academic and professional leaders; and funding agencies.

This statement was primarily authored by Alejandro Flores, Anne Jefferson, Steve Loheide, Jeanne VanBriesen, and Adam Ward and was approved by a vote of the CUAHSI Board of Directors on April 19, 2021, with all directors, officers, and the CUAHSI executive director concurring.
DOI: 10.15468/dl.79bukv
title: Occurrence Download

description: A dataset containing 7782 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Continent is Europe",
 "Country is Spain",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is one of (Coordinate rounded, Recorded date invalid, Recorded date mismatch, Identified date invalid, Coordinate precision invalid, The taxon ID was not found in the checklist, The scientific name ID was not found in the checklist)",
 "TaxonKey is one of (Arundo donax, )",
 "Year 1970-2025"
 ]
}

 The dataset includes 7782 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049957-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4211/hs.a1e329ad20654e72b7b423f991bf9251
title: NOAA National Water Model Reanalysis Data at RENCI

description: This data release provides the reanalysis streamflow data from versions 1.2, 2.0, and 2.1 of the National Water Model structured for timeseries extraction. The impact of this is that user can query time series for a given NHDPlusV2 COMID without downloading the hourly CONUS files and extracting the sample of relevant values. 

The data is hosted on the RENCI THREDDS Data Server and is accessible via OPeNDAP at the follwoing URLs:

Version 1.2
(https://thredds.hydroshare.org/thredds/catalog/nwm/retrospective/catalog.html?dataset=NWM_Retrospective/nwm_retro_full.ncml)
 - Spans 1993-01-01 00:00:00 to 2017-12-31 23:00:00
 - Contains 219,144 hourly time steps for
 - 2,729,077 NHD reaches

Version 2.0
(https://thredds.hydroshare.org/thredds/catalog/nwm/retrospective/catalog.html?dataset=NWM_Retrospective/nwm_v2_retro_full.ncml)
 - Spans 1993-01-01 00:00:00 to 2018-12-31 00:00:00
 - Contains 227,903 hourly time steps for
 - 2,729,076 NHD reaches

Version 2.1
(https://cida.usgs.gov/thredds/catalog/demo/morethredds/nwm/nwm_v21_retro_full.ncml)
 - Spans 1979-02-02 18:00:00 to 2020-12-31 00:00:00
 - Contains 227,903 hourly time steps for
 - 2,729,076 NHD reaches


Raw Data
(https://registry.opendata.aws/nwm-archive/)
- 227,000+ hourly netCDF files (depending on version)

## DDS

The data description structure (DDS) can be viewed at the NcML page for each respective resource (linked above). More broadly each resource includes:

- A _1D_ time array -  **hours** since 1970-01-01 00:00
- A _1D_ latitude array -  **coordinate** (Y) information
- A _1D_ longitude array - **coordinate** (X) information WGS84
- A _1D_ feature_id array - **NHDPlus V2 COMID** (NWM forecast ID)
- A _2D_ streamflow array - **Q (cms)** [feature_id, time]


## R package

The `nwmTools` R package provides easier interaction with the OPeNDAP resources. Package documentation can be found [here](https://mikejohnson51.github.io/nwmTools/) and the GitHub repository [here](https://github.com/mikejohnson51/nwmTools).

# Collaborators:

[Mike Johnson](https://mikejohnson51.github.io/), [David Blodgett](https://www.usgs.gov/staff-profiles/david-l-blodgett?qt-staff_profile_science_products=3#qt-staff_profile_science_products)

# Support:

This effort is supported by the Consortium of Universities for the Advancement of Hydrologic Science, Inc. under the HydroInformatics Fellowship. See program [here](https://www.cuahsi.org/data-models/hydroinformatics-innovation-fellowship/)

# Publications

 J.M. Johnson, David L. Blodgett, Keith C. Clarke, Jon Pollack. (2020). "Restructuring and serving web-accessible streamflow data from the NOAA National Water Model historic simulations".  _Nature Scienﬁc Data_. (**In Review**)
DOI: 10.4211/hs.b14ea426cca24b46ba2a1637a1f7a5f0
title: Wheat and climate data

description: The purpose of the study was to determine the effect of climate change on wheat yield in Porsuk Creek watershed. Wheat yield analyses was carried out with the help of WOFOST model using the past (2016-2017) and future (2020-2100) climate data produced according to the optimistic (RCP4.5) and pessimistic (RCP8.5) scenarios of HadGEM2-ES global climate model in Porsuk Creek watershed. . As a result of this study, important datas on crop yield estimation have been produced for use by decision makers. In this way; planning of wheat farming will be made.
DOI: 10.4211/hs.de4190f0eff74b09a5e0844a0de482a5
title: Global Inland Fisheries Expert Survey

description: This dataset corresponds with the inland fisheries collaboration between the Land and Water Lab at the University of Florida and Food and Agriculture Organization of the United Nations. An online survey of fisheries professionals distributed in June-September 2020 yielded 536 responses from 93 unique hydrological basins across most major freshwater habitat types. Provided here are the raw survey dataset generated from participant responses, a formatted dataset intended for reuse, a reference key to numeric values and column headers, a reference key to region identifiers, and the script used to generate the formatted dataset and figures used in the paper titled, "A global dataset of inland fisheries expert knowledge."
DOI: 10.4211/hs.a52df87347ef47c388d9633925cde9ad
title: (HS 2) Automate Workflows using Jupyter notebook to create Large Extent Spatial Datasets

description: We implemented automated workflows using Jupyter notebooks for each state. The GIS processing, crucial for merging, extracting, and projecting GeoTIFF data, was performed using ArcPy—a Python package for geographic data analysis, conversion, and management within ArcGIS (Toms, 2015). After generating state-scale LES (large extent spatial) datasets in GeoTIFF format, we utilized the xarray and rioxarray Python packages to convert GeoTIFF to NetCDF. Xarray is a Python package to work with multi-dimensional arrays and rioxarray is rasterio xarray extension. Rasterio is a Python library to read and write GeoTIFF and other raster formats. Xarray facilitated data manipulation and metadata addition in the NetCDF file, while rioxarray was used to save GeoTIFF as NetCDF. These procedures resulted in the creation of three HydroShare resources (HS 3, HS 4 and HS 5) for sharing state-scale LES datasets. Notably, due to licensing constraints with ArcGIS Pro, a commercial GIS software, the Jupyter notebook development was undertaken on a Windows OS.
DOI: 10.4211/hs.538f1a61e49e49af88bbfb9a60c5e176
title: (HS 8) Comparative Evaluation of Data Consistency: Conventional vs. Server-side Methods for Exposing Large Extent Spatial Datasets to Models

description: This HydroShare resource aims to assess data consistency among two server-side methods (GeoServer and THREDDS Data Server) and the conventional data distribution approach (manually collecting and sharing at file-level). The evaluation spans three different-sized watersheds: Coweeta subbasin18, Scotts Level Branch, and Spout Run with 10, 30, and 60 m DEM resolutions, respectively. The workflow for resulting nine case studies, derived from the combination of three methods and three watersheds, are presented in one HydroShare resource (HS 7), yielding a total of nine RHESSys daily streamflow output files.

Within this resource, we include these nine output files and provide three Jupyter notebooks for conducting evaluations. Each notebook is dedicated to a specific watershed and focuses on the three methods, facilitating a comprehensive analysis of data consistency.
DOI: 10.4211/hs.afcc703d884e4f73b598c9e4b8f8a15e
title: (HS 1) Toward Seamless Environmental Modeling: Integration of HydroShare with Server-side Methods for Exposing Large Datasets to Models

description: This HydroShare resource was created to support the study presented in Choi et al. (2024), titled "Toward Reproducible and Interoperable Environmental Modeling: Integration of HydroShare with Server-side Methods for Exposing Large-Extent Spatial Datasets to Models." Ensuring the reproducibility of scientific studies is crucial for advancing research, with effective data management serving as a cornerstone for achieving this goal. In hydrologic and environmental modeling, spatial data is used as model input, and sharing this spatial data is a main step in the data management process. However, by focusing only on sharing data at the file level through small files rather than providing the ability to Find, Access, Interoperate with, and directly Reuse subsets of larger datasets, online data repositories have missed an opportunity to foster more reproducible science. This has led to challenges when accommodating large files that benefit from consistent data quality and seamless geographic extent.

To utilize the benefits of large datasets, the objective of the Choi et al. (2024) study was to create and test an approach for exposing large extent spatial (LES) datasets to support catchment-scale hydrologic modeling needs. GeoServer and THREDDS Data Server connected to HydroShare were used to provide seamless access to LES datasets. The approach was demonstrated using the Regional Hydro-Ecologic Simulation System (RHESSys) for three different-sized watersheds in the US. Data consistency was assessed across three different data acquisition approaches: the 'conventional' approach, which involved sharing data at the file level through small files, as well as GeoServer and THREDDS Data Server. This assessment was conducted using RHESSys to evaluate differences in model streamflow output. This approach provided an opportunity to serve datasets needed to create catchment models in a consistent way that could be accessed and processed to serve individual modeling needs. For full details on the methods and approach, please refer to Choi et al. (2024). This HydroShare resource is essential for accessing the data and workflows that were integral to the study.

This collection resource (HS 1) comprises 7 individual HydroShare resources (HS 2-8), each containing different datasets or workflows. These 7 HydroShare resources consist of the following: three resources for three state-scale LES datasets (HS 2-4), one resource with Jupyter notebooks for three different approaches and three different watersheds (HS 5), one resource for RHESSys model instances (i.e., input) of the conventional approach and observation data for all data access approaches in three different watersheds (HS 6), one resource with Jupyter notebooks for automated workflows to create LES datasets (HS 7), and finally one resource with Jupyter notebooks for the evaluation of data consistency (HS 8). More information on each resource is provided within it.
DOI: 10.4211/hs.0cdad4c81d2545408e43867d48fedfe9
title: Daily hidrometric and stable isotope database at Quebrada Grande rainforest catchment, Costa Rica

description: There is still limited understanding of how waters mix, where waters come from and for how long they reside in tropical catchments. In this study, we used a tracer-aided model (TAM) and a gamma convolution integral model (GM) to assess runoff generation, mixing processes, water ages and transit times (TT) in the pristine humid tropical rainforest Quebrada Grande catchment in central Costa Rica. Models are based on a four-year data record (2016 to 2019) of continuous hydrometric and stable isotope observations. Both models agreed on a young water component of fewer than 95 days in age for 75% of the study period. The streamflow water ages ranged from around two months for wetter years (2017) and up to 9.5 months for drier (2019) years with a better agreement between the GM estimated TTs and TAM water ages for younger waters. Such short TTs and water ages result from high annual rainfall volumes even during drier years with 4,300 mm of annual precipitation (2019) indicating consistent quick near-surface runoff generation with limited mixing of waters and a supra-regional groundwater flow of likely unmeasured older waters. The TAM in addition to the GM allowed simulating streamflow (KGE > 0.78), suggesting an average groundwater contribution of less than 40% to streamflow. The model parameter uncertainty was constrained in calibration using stable water isotopes (δ2H), justifying the higher TAM model parameterization. We conclude that the multi-model analysis provided consistent water age estimates of a young water dominated catchment. This study represents an outlier compared to the globally predominant old water paradox, exhibiting a tropical rainforest catchment with higher new water fractions than older water.