cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4211/hs.a065c17a6a02463ca9e7d69f22baed10
title: Data to Supplement "What will it take to stabilize the Colorado River?"

description: The Colorado River is facing an unprecedented water supply crisis due to a 20% reduction of streamflow compared to the 20th century average and to policies that have allowed 21st century consumptive water use to exceed water supplies. To continue to meet demands, storage in the two largest reservoirs in the United States, Lakes Mead and Powell, have fallen from nearly full in 2000 to a projected level of 25% full by the end of the year. Existing drought management policies have thus far been unable to arrest this decline. If the current drought were to continue, substantially greater reductions in consumptive use will be necessary to avoid the loss of hydropower and avoid unpredictable delivery reductions to water users. To address the imbalance between supply and consumption, we identify combinations of limits on Upper Basin consumptive use alongside reduced deliveries to the Lower Basin and Mexico. These adaptation measures need to be applied swiftly to avoid further decline if the current drought persists. 

This collection is supplementary data and code referenced in the journal article titled "What will it take to stabilize the Colorado River? ". This collection is to preserve and provide access to data used in the study in the interest of transparency and reproducibility of this work.
DOI: 10.4211/hs.3cff266d03404eddafb379a3835d418d
title: Creating and Evaluating CRSS Metrics that Report Conditions for Native Fish of the Grand Canyon

description: The purpose of this report is to address and analyze the native fish populations below the Glen Canyon Dam in the Colorado River Basin. As aridification of this basin continues Lake Powell water storage elevations plummet resulting in negative consequences for native fish species. CRSS will be utilized to model a strategy for outflow release that will optimize conditions for native fish. The rule created in this project will be placed as priority for outflow releases. This rule would be implemented to maintain the status quo of native fish populations as the Colorado River Basin’s recent unprecedented hydrologic conditions persist.
DOI: 10.15468/dl.ubbs3k
title: Occurrence Download

description: A dataset containing 74 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Astianthus viminalis",
 "HasCoordinate is true",
 "BasisOfRecord is Human Observation"
 ]
}

 The dataset includes 74 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049973-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4211/hs.937927473a3a4e66a07a2e2fdd9d581e
title: Águeda.2016Flood - The open dataset of the 2016 Águeda flood event

description: Floods are among the most common natural disasters responsible for severe damages and human losses. Numerically produced data, managed by user-friendly tools for geographically referenced data, has been adopted to increase preparedness and reduce vulnerabilities. This paper describes the locally sensed and numerically produced data that characterize a flood event occurred in February 2016 in the Portuguese Águeda river, shortly referred as Agueda.2016Flood. The data was managed through the RiverCure Portal, a collaborative web platform connected to a validated shallow-water model featuring modelled dynamic bed geometries and sediment transport. The dataset provides a synthesis of topo-bathymetric, hydrometric and numerically-produced data from a calibrated hydrodynamic model. Due to the lack of measured hydrometric data near the city, the numerically produced data is crucial for the complete description of the flood event. The Agueda.2016Flood dataset constitutes a complete validation test for flood forecasting models and a tool to better mitigate floods in this river and in similar rivers. Thus, Agueda.2016Flood is a relevant dataset for River Águeda stakeholders as well as for the community of flood modellers, as it provides a well-documented validation event for forecasting tools.
DOI: 10.4211/hs.eb55a0945d2c4625a9d3ab0d986de3fb
title: WM_betasdam Final data and code

description: Hydrological, biological, geomorphological, and geospatial datasets collected from the Western Mountains (WM) used to develop the Beta Streamflow Duration Assessment Method (SDAM) for the WM. SDAMs are rapid, reach-scale indices or models that use physical and/or biological indicators to predict flow duration class. Three flow duration classes are used in the WM Beta SDAM: perennial, intermittent, and ephemeral. Perennial reaches have continuous surface flow and do not experience drying outside of extreme drought. Intermittent reaches have continuous surface flow for part of the year that is sustained by snowmelt and/or groundwater. Ephemeral reaches have surface flow only during and immediately following precipitation or snowmelt. These datasets are also located at the United States Environmental Protection Agency data repository at: https://doi.org/10.23719/1526066
DOI: 10.4211/hs.f7350813a1de4025a3b8e4d05284dc57
title: Storm surges, Waves, Hydrodynamics and Vegetation Surveys in Franklin Point State Park, MD, USA (2020-2021)

description: These datasets include measurements of hydrodynamic (currents and water levels) and wave conditions, vegetation bio-mechanic characteristics (biomass, stem height, diameter, and density), and topo-bathymetric features during the period of (2020-2021) that were measured in the field during extreme events, regular tidal cycles, and over different seasons. This dataset provides the information for the campaigns in Franklin Point State Park, Maryland, USA. Hydrodynamic measurements were carried out with Acoustic Doppler Current Profilers (ADCPs) (Aquadopp Nortek 2 MHz) and RBR D-wave sensors; vegetation surveys included the measurements of vegetation height, diameter and stem spacing using randomly placed 0.25 m2 quadrats on the ground surface. The sensors, topo-bathy data and vegetation measurement’s locations are georeferenced using a differential GPS Trimble R4. SAV measurements (when present) were carried out by using haphazardly placed 0.25m2 quadrats. At each site, the team will measured 1) total SAV percent cover, 2) percent cover of each individual species, 3) canopy height, 4) epiphyte presence on SAV leaf blades, and 5) water depth. 
This field work is part of the project “EESLR 2019: Quantifying the benefits of natural and nature-based features in Maryland’s Chesapeake and Atlantic Coastal Bays to inform conservation and management under future sea level rise scenarios” funded by NOAA (Award# NA19NOS4780179). The project is a collaboration between George Mason University, the Maryland Department of Natural Resources (DNR) and The Nature Conservancy (TNC). The overall goal of the project is to quantify the wave attenuation and flood reduction benefits of marshes, SAV and other natural and nature-based features (NNBF) along the shores of Maryland’s Chesapeake and Atlantic Coastal Bays. This project will inform management actions by DNR to maintain or enhance the ecosystem services of marshes and other natural features on state-owned lands; re-evaluate Chesapeake Bay SAV restoration goals; improve existing conservation prioritization tools; and provide relatable, local examples to advance efforts by DNR, TNC, Eastern Shore Land Conservancy (ESLC) and others to promote the use of NNBF in county and municipal adaptation plans.
DOI: 10.4211/hs.9740fd0142144c8e8bf43876eedec308
title: Data and Code for “The age of evapotranspiration: lower-bound constraints from distributed water fluxes across the continental United States”

description: Data/code supplement for Age of ET manuscript. 

This includes Python notebooks for querying, processing, and plotting age of ET and related contextual figures, as well as QGIS map. The notebooks were run in the free Colab environment.

The .tif file has the following bands:

0: Flux-weighted average minimum ET age (days)
1: MODIS Landcover
2: Koeppen-Geiger climate type
3: Asynchronicity index
4: Longest dry period (days)
5: Mean annual ET (mm)
6: Mean annual precip (mm)
DOI: 10.4211/hs.57ad7df425b84da2874e9c19e7b34aad
title: Colorado River Basin Accounts: Provoke discussion about more flexible and sustainable operations

description: The purpose of this activity is to provoke participants to discuss more flexible and sustainable Colorado River operations than existing operations that equalize reservoirs and expire in 2026. Participants use a Google Sheet to consume, save, and trade water in 6 basin accounts, protect Lake Powell and Lake Mead, sustain endangered, native fish of the Grand Canyon, and discuss. Follow the requirements and facilitation directions in the readme.md file.

CONTENTS:
1) readme.md - Requirements, facilitation directions, publications, file contents, and more.
2) Basin Accounts Tool - ColoradoRiverBasinAccounts.xlsx. Move into Google Sheets and follow Facilitation Directions (in readme.md). Or open ReadMe-Directions Worksheet.
3) Lets Start - ColoradoRiverBasinAccounts-LetsStart.pdf. Visual directions.
4) Model Guide - https://github.com/dzeke/ColoradoRiverCoding/blob/main/ModelMusings/Support/ModelGuide/ModelGuide-CombinedLakePowellLakeMead.md. Online. 
5) Manuscript - 3-LessonsUseGoogleSheetsZoomToDiscussMoreFlexibleSustainableColoradoRiverOperations.docx. Write up for publication as a journal article.
DOI: 10.4211/hs.c10a97d775804fbc98f4b95047aa6c95
title: Data to Supplement Adapting Colorado River Basin depletions to available water to live within our means

description: An open-source exploratory model is developed to assist in Colorado River long-term planning and management. The exploratory model complements existing simulation models by offering greater flexibility and speed to set up scenarios for uncertain future conditions and generate adaptive policies. The current version of this model includes the two largest reservoirs, two aggregated users, and three aggregated tributaries in the Colorado River Basin. This model is validated against the Colorado River Simulation System (CRSS), an official model currently used for the Colorado River basin. With the exploratory model, we develop and test an adaptive depletion to inflow policy, which is different from existing operating policies in the Colorado River. The adaptive policy takes advantage of the latest inflow information every year and provides a more sustainable way to operate the Colorado River system. This strategy offers a new way to manage the Colorado River system. This collection is to preserve and provide access to data used in the study in the interest of transparency and reproducibility of this work.
DOI: 10.4211/hs.ae5628bf9f914f1e9eae6bc8c9cf0af3
title: Storm surges, Waves, Hydrodynamics and Vegetation Surveys in Karen Noonan Center, MD, USA (2020-2021)

description: Hydrodynamic (currents and water levels) and wave conditions were measured in the field during extreme events, vegetation bio-mechanic characteristics (biomass, stem height, diameter, and density), and topo-bathymetric features. This dataset provides the information for the Karen Noonan Center.
DOI: 10.4211/hs.e02c71690d3d4df9abfaf8ec33f7f9c7
title: Influent Parameter Concentrations, Mass Loading Values, and Influent Flow Values for Evaluating Operations During Dry Weather Flows at California Wastewater Treatment Facilities

description: Wastewater treatment facilities must manage water quality during both average flow and extreme events, including wet and dry weather periods. Constituent concentrations can increase during dry weather flow events, since facilities experience reduced incidental infiltration and influent flows may be lower as a result. A script was developed using self-reported data taken from the California Integrated Water Quality System Project (CIWQS) to clean, filter, and organize a batch dataset of influent flows, constituent concentrations, and constituent mass loadings from California wastewater treatment facilities. The script develops two summary data sheets for each facility: one that contains total suspended solids (TSS) data and one that contains biochemical oxygen demand (BOD) data. Data from 426 wastewater treatment facilities was accessed through CIWQS. 104 facilities had adequate BOD data and 105 facilities had adequate TSS data. These summary sheets can be used to quickly assess an individual facility’s dry weather or baseline influent flows. A separate script uses these sheets to prepare a composite summary of BOD, TSS, and influent flow during recent drought-related water use restrictions and the following period of eased restrictions.
DOI: 10.4211/hs.263f1316f0fd4476b3f1d4a1cb4ab352
title: Biochemical Oxygen Demand and Total Suspended Solids Summaries from California Wastewater Treatment Facilities

description: Biochemical oxygen demand (BOD) and total suspended solids (TSS) are two key water quality parameters for wastewater. In California, facilities submit detailed data to regional and state regulatory agencies to comply with discharge permits. The aggregated data can be used for trends analysis. A script was developed that uses this self-reported data taken from the California Integrated Water Quality System Project (CIWQS) to compile a single composite summary database of yearly wastewater influent flows, constituent concentrations, and constituent mass loadings at individual wastewater treatment facilities. Data from 426 wastewater treatment facilities was accessed through CIWQS. 104 facilities had adequate BOD data and 105 facilities had adequate TSS data. The intended use of the summary sheet is to compare influent flow and constituent values between a period of drought-related water use restrictions and the following period of eased restrictions.
DOI: 10.4211/hs.4b8575d3031c40d4a39f945db8f02ae5
title: Plume Spreading Experiments and Simulations

description: This resource provides experimental data for plume spreading experiments reported in Neupauer et al. (2021), Roth et al. (2021), and Sather et al. (2023). Data from laboratory experiments in all three papers appear in a Data Set, while resources related to numerical simulations in Sather et al. (2023) appear in a Model Instance. README files provide details on file naming conventions and data formatting.

Neupauer, R.M., E.J. Roth, J.P. Crimaldi, D.C. Mays, and L.J. Sather (2021), Demonstration of reversible dispersion in a Darcy-scale push-pull laboratory experiment, Transport in Porous Media, doi:10.1007/s11242-021-01682-3.

Roth, E.J., D.C. Mays, R.M. Neupauer, L.J. Sather, and J.P. Crimaldi (2021), Methods for laser-induced fluorescence imaging of solute plumes at the Darcy scale in quasi-two-dimensional, refractive index-matched porous media, Transport in Porous Media, doi:10.1007/s11242-021-01545-x.

Sather, L.J., E.J. Roth, R.M. Neupauer, J.P. Crimaldi, and D.C. Mays (2023), Experiments and simulations on plume spreading by engineered injection and extraction in refractive index matched porous media, Water Resources Research, doi:10.1029/2022WR032943.
DOI: 10.4211/hs.f085afcf710744898f38b64c00e22a5b
title: Colorado River Basin Accounts: Provoke discussion about more flexible and sustainable operations

description: The purpose of this activity is to provoke participants to discuss more flexible and sustainable Colorado River operations than existing operations that equalize reservoirs and expire in 2026. Participants use a Google Sheet to consume, save, and trade water in 6 basin accounts, protect Lake Powell and Lake Mead, sustain endangered, native fish of the Grand Canyon, and discuss. Follow the requirements and facilitation directions in the readme.md file.

CONTENTS:
1) readme.md - Requirements, facilitation directions, publications, file contents, and more.
2) Basin Accounts Tool - ColoradoRiverBasinAccounts.xlsx. Move into Google Sheets and follow Facilitation Directions (in readme.md). Or open ReadMe-Directions Worksheet.
3) Lets Start - ColoradoRiverBasinAccounts-LetsStart.pdf. Visual directions.
4) Model Guide - https://github.com/dzeke/ColoradoRiverCoding/blob/main/ModelMusings/Support/ModelGuide/ModelGuide-CombinedLakePowellLakeMead.md. Online. 
5) Manuscript - 3-LessonsUseGoogleSheetsZoomToDiscussMoreFlexibleSustainableColoradoRiverOperations.docx. Write up for publication as a journal article.
DOI: 10.4211/hs.0d6999591fb048cab5ab71fcb690eadb
title: EU-MOHP v013.1.1 Dataset

description: The presented dataset EU-MOHP v013.1.1 provides cross-scale information on the hydrologic position (MOHP) of a geographic point within its respective river network and catchment as gridded maps. More precisely, it comprises the three measures “lateral position” (LP) as a relative measure of the position between the stream and the catchment divide, “divide to stream distance” (DSD) as sum of the distances to the nearest stream and divide and “stream distance” (SD) as an absolute measure of the distance to the nearest stream. These three measures are calculated for several hydrologic orders to reflect different spatial scales. Its spatial extent covers major parts of the European Economic Area (EEA39) which also largely coincides with physiographical Europe. Although there are multiple potential use cases, this dataset serves predominantly as valuable static environmental feature or predictor variable for hydrogeological and hydrological modelling such as mapping or forecasting tasks using machine learning. The generation of this dataset uses free open source software only and therefore can be transferred to other regions or input datasets.
DOI: 10.4211/hs.8ea376970c904c6698fc8cfe392689de
title: EU-MOHP v013.1.1 Code

description: This resource contains the code to generate the EU-MOHP v013.1.1 dataset as static code repository. For updates of the code and further information, please visit the corresponding Github repository: https://github.com/MxNl/macro_mohp_feature. The EU-MOHP v013.1.1 dataset can also be found on Hydroshare.
DOI: 10.4211/hs.24f8275d882e4d40809ba901258c17ad
title: Colorado River Basin Accounts: Provoke discussion about more flexible and sustainable operations

description: The purpose of this activity is to provoke participants to discuss more flexible and sustainable Colorado River operations than existing operations that equalize reservoirs and expire in 2026. Participants use a Google Sheet to consume, save, and trade water in 6 basin accounts, protect Lake Powell and Lake Mead, sustain endangered, native fish of the Grand Canyon, and discuss. Follow the requirements and facilitation directions in the readme.md file.

CONTENTS:
1) readme.md - Requirements, facilitation directions, publications, file contents, and more.
2) Basin Accounts Tool - ColoradoRiverBasinAccounts.xlsx. Move into Google Sheets and follow Facilitation Directions (in readme.md). Or open ReadMe-Directions Worksheet.
3) Lets Start - ColoradoRiverBasinAccounts-LetsStart.pdf. Visual directions.
4) Model Guide - https://github.com/dzeke/ColoradoRiverCoding/blob/main/ModelMusings/Support/ModelGuide/ModelGuide-CombinedLakePowellLakeMead.md. Online. 
5) Manuscript - 3-LessonsUseGoogleSheetsZoomToDiscussMoreFlexibleSustainableColoradoRiverOperations.docx. Write up for publication as a journal article.
DOI: 10.4211/hs.973b130a79bb4473bd0ae57850333fec
title: EnviroDIY versus USGS Monitoring Data Comparison

description: This is a repository of data and analysis methods developed in a comparison of water monitoring data reported on Monitor My Watershed and USGS Water Data. The analysis is summarized in a post on EnviroDIY.org: https://www.envirodiy.org/how-do-envirodiy-monitoring-stations-compare-with-usgs-stations/.
DOI: 10.4211/hs.f2f25337561d408f9526c3c6a1c85fc8
title: Duck, NC cross shore coastal ocean bottom temperatures

description: A 9.4 mm armored cable with two single mode and two multimode fibers was deployed in the cross shore coastal ocean from Duck, NC. DAS and DTS were used to measure bottom temperature and strain and connect those measurements to surface signatures of coastal hydrodynamics measured by camera and radar.

DTS data available via Box: https://oregonstate.box.com/s/4ugltcd8ud54ovf8oif9gsys40dpo30w.
DOI: 10.4211/hs.cd13bbac5e6a48c380facd4c2fea55af
title: SI-Manuscript-2022WR032866

description: Supporting Information (SI) for Research Article "A decision support framework for pollution source detection via coupled forward-inverse optimization and multi-information fusion", which contains 
Text S1. Extended methodology: the ANOVA (analysis of variance).
Figure S1. The sensor data shown in pollutant concentration distribution in Case-T1.
Figure S2. The COD sensor data shown in pollutant concentration distribution and decomposition in Case-T2.
Figure S3. The NH sensor data shown in pollutant concentration distribution and decomposition in Case-T2.
Table S1. Standard limit of COD, TP and NH in GB 3838-2002.
Table S2. The non-uniqueness candidate solutions n Case-T2.

The data The simulated data used in the case study（multi-water quality data）
DOI: 10.4211/hs.4eac370d12e142b5aa718e5deb57da39
title: Mt. Fuji hydrogeochemical and microbiological dataset

description: This dataset was published as part of Schilling, O.S., Nagaosa, K., Schilling, T.U., Brennwald, M.S., Sohrin, R., Tomonaga, Y., Brunner, P., Kipfer, R., Kato, K. (2023): Revisiting Mt. Fuji’s groundwater origins helium, vanadium and environmental DNA tracers. Nat. Water 1, doi: 10.1038/s44221-022-00001-4, and contains hydrogeochemical and environmental DNA (eDNA)-based microbiological measurements of groundwater and spring water samples from Mt. Fuji catchment collected between 1979 and 2020. The data consists of over 9,500 individual data points from over 300 sampling sites and represents a compilation of data collected from over 40 published sources and measurements made by the authors within the framework of the study by Schilling et al. 2023. The data are provided as two separate 2 tables: Extended Data Table 1, which contains all the hydrogeochemical data, and Extended Data Table 2, which contains only the eDNA data.