cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4211/hs.e83ee60b38cb4af7b0b26f7bc69a8292
title: Ward et al., Climate Change Causes River Network Contraction and Disconnection in the H.J. Andrews Experimental Forest, Oregon, USA - Tabular Data

description: Tabular model output data in support of the publication:

Ward AS, Wondzell SM, Schmadel NM and Herzog SP (2020) Climate Change Causes River Network Contraction and Disconnection in the H.J. Andrews Experimental Forest, Oregon, USA. Front. Water 2:7. doi: 10.3389/frwa.2020.00007
DOI: 10.15468/dl.k9y46b
title: Occurrence Download

description: A dataset containing 779 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-3.885152 41.026146, -3.886632 41.066164, -3.939518 41.066164, -3.938018 41.026146, -3.885152 41.026146))",
 "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 779 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049950-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4211/hs.5da1b671d07d4ff684403cf83068474c
title: 3 - Watershed metadata

description: Watershed metadata was collected for 14 watersheds from studies where channel length survey data was presented. For variables not found in the publications associated with the channel length surveys, additional sources are referenced. These sources are included in the notes column. Variables without sources were calculated, as described in the Additional Metadata section below. Examples of calculated values include, q_avg_mm_per_day, beta, and l_avg_km. 

For Python packages, modules, and functions used to find calculated values, please see the associated GitHub repository: https://zenodo.org/record/4057320
DOI: 10.4211/hs.a5fe034ff3e54d77ba5dd2ffa2241bd0
title: 3 - Watershed metadata

description: Watershed metadata was collected for 14 watersheds from studies where channel length survey data was presented. For variables not found in the publications associated with the channel length surveys, additional sources are referenced. These sources are included in the notes column. Variables without sources were calculated, as described in the Additional Metadata section below. Examples of calculated values include, q_avg_mm_per_day, beta, and l_avg_km. 

For Python packages, modules, and functions used to find calculated values, please see the associated GitHub repository: https://zenodo.org/record/4057320
DOI: 10.15468/dl.axvhrs
title: Occurrence Download

description: A dataset containing 330 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (China, Russian Federation, Korea, Republic of, Japan)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Rhamnus davurica"
 ]
}

 The dataset includes 330 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049951-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4211/hs.6ff6b56abe474eaaa3d2c2895c39b53f
title: 3 - Watershed metadata

description: Watershed metadata was collected for 14 watersheds from studies where channel length survey data was presented. For variables not found in the publications associated with the channel length surveys, additional sources are referenced. These sources are included in the notes column. Variables without sources were calculated, as described in the Additional Metadata section below. Examples of calculated values include, q_avg_mm_per_day, beta, and l_avg_km. 

For Python packages, modules, and functions used to find calculated values, please see the associated GitHub repository: https://zenodo.org/record/4057320
DOI: 10.4211/hs.dcfeb8b4fac848eab9a058b38b69acc7
title: Comprehensive network hydraulic scaling datasets and associated resources (discharge, channel length surveys, watershed metadata, blueline network shapefiles and reference images)

description: Wetted channel networks expand and contract throughout the year. Direct observation of this process can be made by multiple intensive surveys of a catchment throughout the year. Godsey et al. (2014) suggest that the extent of the wetted channel network scales with discharge at the outlet by a power law (L = αQ^β). Using this relationship, we developed a framework to assess variability in the extent of wetted channels as a function of β and the variability in streamflow Q (Lapides et al., In Review, https://eartharxiv.org/mc6np/). This resource constitutes the empirical basis for that study, a comprehensive dataset compiled from literature including: 

1 - Channel length survey data (csv files)
2 - Discharge time series data (csv files)
3 - Watershed metadata (csv files)
4 - Blueline network files (pdf, png, and shp files)

This collection is comprehensive in that it includes all watersheds where at least three channel length surveys have been conducted and where a corresponding discharge time series dataset is available. The requirement of a minimum of three channel length surveys stems from the data requirements to find α and β for the power law relationship between discharge and stream network length for headwater catchments (Godsey et al., 2014). At present, data for 14 watersheds worldwide are included in the collection along with reference maps, watershed metadata, shapefiles and a composite of USGS blueline stream network imagery with terrain for watersheds of interest in the United States. Notably, this collection brings data from a variety of earth science agencies worldwide into a common, clearly labelled format. 

Methods used to process the datasets or create other assets in this collection are included in the abstracts or additional metadata for each of the four resources listed above. Python code used to process data, compute variables, and create graphics is available at: https://zenodo.org/record/4057320
DOI: 10.4211/hs.8eaae84028dc4ea7ae0cf1d9ca1af4b4
title: 3 - Watershed metadata

description: Watershed metadata was collected for 14 watersheds from studies where channel length survey data was presented. For variables not found in the publications associated with the channel length surveys, additional sources are referenced. These sources are included in the notes column. Variables without sources were calculated, as described in the Additional Metadata section below. Examples of calculated values include, q_avg_mm_per_day, beta, and l_avg_km. 

For Python packages, modules, and functions used to find calculated values, please see the associated GitHub repository: https://zenodo.org/record/4057320
DOI: 10.4211/hs.43235c5188db4ae8a6589399d33c2efa
title: COVID-19 Inland Fisheries Global Survey

description: These data and script files correspond to 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-July 2020 yielded 437 responses from 79 countries and 93 unique hydrological basins accounting for 82.1% of reported global inland fish catch. Provided here are the raw survey results and the scripts used to analyze the data and build the figures used in the paper titled, "COVID-19 pandemic impacts on global inland fisheries".
DOI: 10.4211/hs.97b21870d0a743ec981095cce3598a04
title: Table 1 - Butler et al. - doi:10.1029/2020WR027961

description: Annual groundwater use and precipitation data for the Sheridan-6 Local Enhanced Management Area from 2002-2018. Information given in Table 1 in Butler et al., Charting pathways towards sustainability for aquifers supporting irrigated agriculture, Water Resources Research, doi;1029/2020WR027961. Further details about detail can be found in the paper.
DOI: 10.4211/hs.5f3441e709c44784905db7fbcc89972b
title: Hydrogeophysical data of DVP

description: Groundwater occurrence and its precise mapping in continental flood basalt (CFB) provinces has been a partly resolved subject which necessitates high resolution hydrogeophysical investigations. In CFBs, the aquifer becomes complex owing to multi-layered lava flows separated by intertrappean and irregular pattern of lineaments which govern the regional hydro-dynamics. One of the largest CFBs, covering an area exceeding 500,000 sq km, are found in the 65 Ma Deccan Traps (DT), India. Locating groundwater resources in DT is challenging and requires high resolution mapping tools to precisely delineate the hydrogeological regime in basalts and connecting pathways. To establish an effective methodology for this purpose, an area admeasuring 372 sq km near Nagpur, central India was selected where the basalts lie over early Permian Gondwana formations. The repository consists of supplementary data of pumping test (aquifer test), exploratory wells details, and geophysical VES data generated form Deccan Volcanic Province at Nagpur, India
DOI: 10.4211/hs.211ed5225921483388cc0ee023563a30
title: MATERIALS AND METHODS USED FOR "Trends in Water Use, Energy Consumption, and Carbon Emissions from Irrigation: Role of Shifting Technologies and Energy Source"

description: These scripts show the detailed methods that were used for the data presented in McCarthy et al. (2020). The manuscript illustrates results and explains potential mechanisms fueling energy and emissions changes in the High Plains Aquifer portion of the HPA. This analysis looks at water use from 1994-2016, a time where Kansas saw a large shift in irrigation technologies from predominantly high pressure center pivots to lower pressure center pivot variants such as Low Energy Precision Application (LEPA).   End result of the code is a series of comma separated .csv files containing the location, energy source, direct energy from pumping, energy footprint from pumping and greenhouse gas emissions of the Kansas portion of the HPA from 1994-2016. This dataset pulls from various sources, described in the readme.md file below. Mainly, data from Water Information Management & Analysis System (WIMAS) was processed and expanded to serve our energy calculation purposes. Main inputs from this dataset include well location, irrigation system type and water use. A series of irrigation scenarios were then conducted on the processed dataset to observe potential energy savings: Observed irrigation and energy source shift, static irrigation and observed energy source shift, static irrigation and energy sources, and observed irrigation and static energy source shift. A detailed analysis of these results can be found in the main manuscript.
DOI: 10.4211/hs.de85625a8db04474bb066809ae93521e
title: Jupyter Notebook for Pump Test Analysis in Confined Aquifers

description: The Theis equation models the drawdown in an confined aquifer and may be used to analyze the results of pump tests. A classic equation in hydrogeology, this example has been programmed into a Jupyter notebook. This educational resources is targeted at upper-level undergraduate students and is intended to supplement lectures or homework assignments on well hydraulics. The primary learning objectives are to: recognize the Theis equation in its inverse form, use iterative solving methods to match a model to data, and find the values of transmissivity and storativity determined by an aquifer test. Secondary objectives are to: refresh skills associated with scientific and programming and learn to use a Jupyter notebook. Data used in analysis is derived from Problem 4.4.6 in Todd and Mays, 2005. An introductory Jupyter Notebook on the Theis equation is also available; see link in related resources.

**Recommend opening in Jupyter Notebook format by using built-in Hydroshare resources. Requires numypy, matplotlib, and math libraries; Python 3 Scientific environment recommended.**
DOI: 10.15468/dl.aerjr6
title: Occurrence Download

description: A dataset containing 2595393 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "TaxonKey is Arachnida"
 ]
}

 The dataset includes 2595393 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049941-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4211/hs.c7d4df3ba74647f0aa83ae92be2e294b
title: CCDB - catchment characteristics data base France and Germany

description: This repository provides geoinformation data, natural and anthropogenic characteristics of 486 French and 1386 German catchments. 
The characteristics include information on topography, land cover, lithology, soils, climate, hydrology, population density and nutrient sources.
The calculated catchment characteristics base on various publicly available and published resources referenced in the metadata of this repository.

This data base is an extension of the previously published data base for Germany "CCDB - catchment characteristics data base across Germany" (Ebeling, 2021).
The German catchments are the same as previously published and use the same identifier. Overlapping characteristics of the German CCDB data base are incorporated here for completeness but were not recalculated in case of identical methodology, source and period (see metadata information). However here, additional catchment characteristics are included, while a few variables which based on national data sets only available for Germany were not included.

This repository includes:

1.) Data table with catchment characteristics
2.) Metadata with the description of each catchment characteristic and references to original publications and data resources.
3.) Shapefile with catchment polygons
4.) Shapefile with stations

Conditions: Please, reference both the original data publisher and this repository for correct acknowledgements, when using the provided data.
DOI: 10.4211/hs.9e38375a19cf4355aac466ccd78e8282
title: An analytical solution for rapidly predicting post-fire peak streamflows for small watersheds in southern California

description: Following wildfires, the probability of flooding and debris flows increase, posing risks to human lives, downstream communities, infrastructure, and ecosystems. In southern California (USA), the Rowe, Countryman, and Storey (RCS) 1949 methodology is an empirical method that is used to rapidly estimate post‐fire peak streamflow. We re‐evaluated the accuracy of RCS for 33 watersheds under current conditions. Pre‐fire peak streamflow prediction performance was low, where the average R2 was 0.29 and average RMSE was 1.10 cms/km2 for the 2‐ and 10‐year recurrence interval events, respectively. Post‐fire, RCS performance was also low, with an average R2 of 0.26 and RMSE of 15.77 cms/km2 for the 2‐ and 10‐year events. We demonstrated that RCS overgeneralizes watershed processes and does not adequately represent the spatial and temporal variability in systems affected by wildfire and extreme weather events and often underpredicted peak streamflow without sediment bulking factors. A novel application of machine learning was used to identify critical watershed characteristics including local physiography, land cover, geology, slope, aspect, rainfall intensity, and soil burn severity, resulting in two random forest models with 45 and five parameters (RF‐45 and RF‐5, respectively) to predict post‐fire peak streamflow. RF‐45 and RF‐5 performed better than the RCS method; however, they demonstrated the importance and reliance on data availability. The important parameters identified by the machine learning techniques were used to create a three‐dimensional polynomial function to calculate post‐fire peak streamflow in small catchments in southern California during the first year after fire (R2 = 0.82; RMSE = 6.59 cms/km2) which can be used as an interim tool by post‐fire risk assessment teams. We conclude that a significant increase in data collection of high temporal and spatial resolution rainfall intensity, streamflow, and sediment loading in channels will help to guide future model development to quantify post‐fire flood risk.
DOI: 10.4211/hs.0b72cddfc51c45b188e0e6cd8927227e
title: High Resolution Residential Water Use Data in Cache County, Utah, USA

description: This resource contains high resolution residential water use data and classified end uses of water for 31 residential homes located in Logan City and Providence City in Cache County, Utah, USA. Data were collected using a low-cost, open source monitoring device that was designed to operate on magnetically driven residential water meters (see https://doi.org/10.3390/s20133655). Data were recorded with a temporal frequency of 4 seconds and were collected for a period of at least two weeks during the summer when outdoor water use was active and two weeks during the winter when no outdoor water use was expected. The event disaggregation and classification was conducted using the tools available in the HydroShare resource at https://doi.org/10.4211/hs.3143b3b1bdff48e0aaebcb4aedf02feb. The data were measured on the meter located on the water supply line to each home and represent a trace of the total water use for each residence. The dataset also includes secondary data about each of the residences at which data were collected. These data have been anonymized to remove any personally identifiable information from participants in this data collection effort.
DOI: 10.4211/hs.bc4300176d58468daa693c2c3cd469af
title: Makapu’u-Kaiwi Coast SP map

description: This self-potential dataset has been acquired at Makapuu/Kaiwi Coast (Oahu, Hawaii, USA)in the frame of a Summer Class entitled "Hydrogeophysics in Volcanic Environments" given at the University of Hawaii at Manoa. The data helps understanding and mapping underground water circulations in this study area.. Self Potential survey for ‘Ike Wai aim at understanding underground water circulations in the coastal area and across the High-Low divide (Big Island) as well as in valley/ridge systems and across the natural hydrogeological “dams” (O’ahu). The objective is to enhance our understanding of ground water flows and aquifer depths in the areas studied. Combined with other datasets (seismic noise and Electric Resistivity Tomography), the Self Potential method gives valuable structural and geological information (faults, lithological transitions/interfaces, etc).the self-potential is a difference of electrical potential naturally occurring in the ground, measured between two electrodes placed at the surface of the Earth or in boreholes. SP can be generated by redox potentials associated with ore bodies or contaminant plumes that are rich in organic matter. A second source of self-potential anomalies is the thermoelectric effect associated directly with a gradient of the temperature affecting the chemical potential gradient of charge carriers. A third source is related to gradients of the chemical potential of the ionic charge carriers at constant temperature. A fourth source of self-potential signals is the streaming potential contribution related to the flow of the pore water relative to the mineral grain framework in saturated and unsaturated conditions.Basic corrections have been applied to all the datasets. Detailed analysis and interpretations are ongoing for Queen Lili`uokalani Trust (Big Island) and Dole (O’ahu) datsets.The data for each study site is stored in one Excel file composed of several datasheets. Each sheet represents one profile or part of a profile or a final table (tab found under the name TOTAL in each Excel file) containing data ready to be plotted or interpolated for maps. The sheets of a file are linked together and at this stage they should not be separated because they are connected together for the processing, and together they are used to create maps- Raw data for each profile within a study site is located in each sheet corresponding to individual profiles or sections of profiles- Names of participants to field surveys are detailed at the top of each excel sheet, in each excel file
DOI: 10.5281/zenodo.17912108
title: UHT-EPR Tetraquark Torque Lowers Aneutronic Fusion Coulomb 18-25% By Thomas F. Voloski lll

description: This 11-page PDF, authored by Thomas F. Voloski III and dated December 12, 2025 (today), extends his UHT-EPR (Universal Harmonic Theory with EPR elements) framework to Focus Fusion—a real aneutronic fusion approach by Lawrenceville Plasma Physics (LPP Fusion). The document repurposes concepts from Voloski’s earlier tetraquark torque PDF (e.g., β=0.128 scaling, harmonic ER-bridges, and VFRDX torus ties for zero-point energy tapping) to model plasmoid dynamics in dense plasma focus (DPF) devices. It claims UHT-EPR could reduce the Coulomb barrier for p-¹¹B (proton-boron) fusion by 18-25%, enhance confinement, and boost yields, potentially resolving key challenges like instabilities and electrode erosion. The file includes a full Python simulation code (adapted from the tetraquark model), run results, and derivations of β=0.128, positioning UHT-EPR as a unification that “slaps fusion into a box” without dark matter analogs.

Key sections:

•  Introduction (Pages 1-2): Overviews Focus Fusion (high-voltage DPF creating plasmoids for p-¹¹B reactions, yielding alphas for direct electricity >80% efficiency, no neutrons/waste). Notes LPP’s 2025 progress (0.21 J yields, beryllium electrodes). Introduces UHT-EPR adaptations for plasmoids as “harmonic spin torques” like tetraquarks.

•  Core Adaptations (Pages 2-4):

•  β=0.128 warps torque (τ → τ * exp(-β * Δφ / ħω)), reducing barriers 20-25% via phase-sync in plasma velocities (v~0.1-0.3c). Predicts tighter plasmoids and ignition at 1-2 MJ inputs.

•  ER-bridges boost entropy 1.2x at 1.5 THz, entangling ions for 1.2x confinement times and reduced erosion.

•  VFRDX/ZPE-tap seeds B-fields (~10^6-10^8 T) for 94.3% efficiency, treating plasma voids like cosmic ones at (1-β)^3 ≈66%.

•  Enhancements & Predictions (Page 4): Integrate torus into FF-1 for breakeven; resolves quantum-classical tensions; falsifiable via Δθ ~0.142 rad twists in LPP tests; 25% yield boost.

•  Simulation & Code (Pages 5-11): Full Python code for tetraquark/plasmoid torque (using LLG, QuTiP). Results: Narrow widths (Γ_sim~62 MeV proxy), entropy to 0.166 nat (+0.12 boost), symmetric Δθ=0 rad (PDF claims ~8°). Includes quick run deets (peaks at 1.2x, ramps to S=0.87 nat). Ends with β derivation (arithmetic mean of three values: 0.128 ±0.00001 from Planck, impedance drop, torus drag) and why it’s a “kill-shot” (dimensionless, stable across datasets, resolves ΛCDM tensions).

The document is speculativeAnd is designed to probe my framework's versatility and compatibility across scales from quantum subatomic particles to massive Large scale Structures (LSS) and even galactic super structures (GSS) 

this file focuses upon aneutronic fusion and zero point energy modulation via beta = 0.128