cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4211/hs.7477452a93e04b1099a3879353c2253a
title: Enabling collaboration through data and model sharing with CUAHSI HydroShare: Workshop presented as part of CIROH Developers Conference May 29, 2024

description: Material for CIROH Developers Conference Workshop, May 29, 2024.

CIROH research necessitates collaboration, data and model sharing, easy to use, generally accessible, shareable computing, and working together as a team and community. The Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) HydroShare platform enables best (FAIR, Findable, Accessible, Interoperable, and Reusable) practices for data sharing and collaboration and for improving reproducibility and reusability of research outcomes through sharing and publishing both the data and models and analyses that underpin research findings.  This workshop provided information on using HydroShare for collaboration and data and model sharing in CIROH, including links between HydroShare and CIROH computing.
DOI: 10.4211/hs.b3da4d30956c4fac9a45b5ff219311f1
title: Streamflow Data for Lost Horse and Mill Creeks, Bitteroot Mountains, Western Montana

description: This resource contains discharge data from two streams flowing from the Bitterroot Mountains into the Bitterroot Valley in western Montana. Stage measurements were taken with a Solinst Level Vent 5 vented transducer. Discharge measurements were made using a Flow Tracker.  Discharge measurements were only made during periods when the stream was safely wadeable.

Rating curve created using a power law relationship.

Data Files are csv files with date, stage, inferred discharge and measured discharge.

These gauges were added as part of an investigation of hydrogeodesy in mountain watersheds. GPS data from each site can be downloaded from UNAVCO.
DOI: 10.4211/hs.afbf6f60d6b349f0b61de8387138bee1
title: Streamflow droughts and floods in the US between 1970-2022

description: This dataset contains streamflow drought and flood events for 1002 gauging stations in the Contiguous United States between 1970 and 2022. Drought and floods were identified using methodology outlined in Götte & Brunner (2024) and are characterized by there start and end date. The dataset accompanies the paper "Hydrological drought-to-flood transitions across different hydroclimates in the United States" by Götte & Brunner published in Water Resources Research under DOI 10.1029/2023WR036504.
DOI: 10.25824/redu/nyx5rj
title: Dados sobre análises de elementos inorgânicos e sua bioacessibilidade em pães sem glúten comerciais e a avaliação da fortificação de farinhas de arroz com sulfato ferroso em duas formas: microencapsulada e livre (não encapsulada), utilizadas no processamento de pães sem glúten

description: Os dados são referentes a tese "Pão sem glúten: uma visão geral sobre elementos inorgânicos, bioacessibilidade e os efeitos da fortificação com ferro". No momento, os dados não podem ser disponibilizados por questões de proteção intelectual. Para mais informações, contatar os responsáveis.
DOI: 10.4211/hs.fa1eb51c8756427d9fc50c415b714557
title: Impacts of Urbanization on the Riverine Flooding in Major Cities Across the Eastern United States

description: The increase in the societal and economic impacts of flooding across the eastern United States has brought attention to the potential link between long-term increases in urban areas and changes in the watersheds’ flood response. One outstanding challenge is to isolate the effects of land cover changes from other flood-related factors. To advance our understanding of these processes and their nexus, we utilize a statistical framework in which we use different parameterizations of the Generalized Pareto distribution (GPD) to model sub-daily peak-over-thresholds (POT) events at 102 stream gauges in the following metropolitan areas across the eastern United States: Boston, New York, Philadelphia, Baltimore, Charlotte, Atlanta, Houston, and Tampa. While we keep the shape parameter constant, we allow the scale parameter to: 1) be constant; 2) depend on hourly accumulated rainfall; or 3) be dependent on a combination of hourly accumulated rainfall and the temporal changes in the percentage of the watershed’s developed land. Based on our modeling results, we select the model with the land change as predictor in only 3% of the watersheds. Moreover, the model configuration in which rainfall is the only predictor is selected the most frequently (~80% of the sites) across the eight metropolitan regions. Therefore, our findings indicate that the key flood driver in urban basins across the eastern United States is rainfall, without clear evidence linking long-term changes of impervious area (i.e., urbanization) and the watersheds’ flood response.
DOI: 10.4211/hs.4f88a4b06bc846a1b948d06fe9145223
title: Smartphone evapotranspiration field campaign data

description: This collection contains observations made by smartphone and an additional handheld sensor in order to estimate evapotranspiration. These include luminence, surface temperature, air temperature, air pressure, relative humidity, and wind speed. The dataset also contains hourly routine meteorological observations, as well as evapotranspiration observations by weighing lysimeters and eddy covariance, collected at various sites in The Netherlands, Germany, and Switzerland. The smartphone observations were used to train a simple machine learning algorithm on the observed fluxes.
DOI: 10.4211/hs.15d457e46a5a4c1cb25c3afc9dbd77f7
title: Smartphone evapotranspiration field campaign data Rollesbroich

description: This dataset contains observations made by smartphone and an additional handheld sensor in order to estimate evapotranspiration. These include luminence, surface temperature, air temperature, air pressure, relative humidity, and wind speed. The dataset also contains hourly routine meteorological observations, as well as evapotranspiration observations by a set of 6 weighing lysimeters and eddy covariance, all collected at the Rollesbroich TERENO site, which is operated by the Institute of Bio- and Geosciences of FZ Julich. The smartphone observations were used to train a simple machine learning algorithm on the observed fluxes.
DOI: 10.4211/hs.5a28b74c55c74a7e9ad2b59a0a5d9ab3
title: Simulated and reported groundwater recharge fluxes in 196 locations in arid and semi-arid regions.

description: This dataset contains 196 locations in semi-arid and arid regions where groundwater recharge fluxes were reported based on ground-based methods, and their equivalent simulated groundwater recharge fluxes were estimated using the Richards equation, global soil properties, and daily climate data. For each location, there is a folder that contains the parameters of the soil hydraulic functions and the original climate (Rain (R) and potential evapotranspiration (Ep)) that was used. Long daily R and Ep time series were synthesized according to the original measured climate. Furthermore, the statistics of the long daily time series were modified, mainly the standard deviation and the mean of the R and Ep. For a comprehensive dataset description, please refer to the paper entitled ‘Changes in mean evapotranspiration dominate groundwater recharge in semi-arid regions’.
DOI: 10.4211/hs.b0f021bdc474474bbae9037f89e2c1d2
title: Dataset for "Patterns of intra-seasonal groundwater recharge inferred from streamflow and explained by vadose zone storage deficits"

description: In forested, seasonally dry watersheds, winter rains commonly replenish moisture deficits in the vadose zone before recharging underlying hillslope groundwater systems that sustain streamflow. However, the relative inaccessibility of the subsurface has hindered efforts to include the role of storage deficits, primarily generated by plant-water uptake, in moderating groundwater recharge. Here, we compare groundwater recharge inferred from the storage-discharge relationship with independent, distributed estimates of vadose zone storage deficits across 12 undisturbed California watersheds, thereby tracking the evolution of the deficit-recharge relationship without intensive field instrumentation. We find accrued deficits during the dry season alone insufficiently explain differences in the wet season partitioning of rainfall due to the non-monotonic behavior of the deficit during the subsequent wet season. Tracking the deficit at the storm event-scale within the wet season, however, reveals a characteristic response in groundwater to increasing rainfall not captured in the seasonal analysis, and may improve estimates of the rainfall required to generate recharge and streamflow on a per-storm basis.  Our findings demonstrate the potential for existing public datasets to better capture water partitioning within the subsurface using a combined deficit-recharge approach, though our analysis is currently limited to basins with select characteristics.

CODE AVAILABLE ON GITHUB: https://github.com/noah-beniteznelson/recharge_deficit
DOI: 10.4211/hs.b6d1d853b82247e1aeaf907ac254c99e
title: SMVI Global Flash Droughts Dataset

description: We present a global dataset of flash drought events, meticulously compiled using the Soil Moisture Volatility Index (SMVI), a cutting-edge tool initially applied within the United States. This dataset marks a significant expansion of the SMVI methodology to a global context, offering an essential resource for comprehensively understanding and predicting rapidly evolving drought phenomena. Characterized by detailed information on the onset, duration, and severity of each event, the dataset covers a wide array of climatic zones, thus providing a diverse and inclusive global perspective. A key feature of this dataset is the integration of atmospheric variables, which sheds light on the meteorological factors driving and influencing flash droughts. Such integration allows for an in-depth exploration of the complex interplay between soil moisture and atmospheric conditions, enhancing our understanding of drought dynamics.
DOI: 10.15468/dl.k7xv9k
title: Occurrence Download

description: A dataset containing 1224 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Russian Federation, China, Korea (Democratic People’s Republic of), Korea, Republic of, Japan, Mongolia)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Salix dasyclados"
 ]
}

 The dataset includes 1224 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049996-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4211/hs.92f042f61d9f4adca68ac247148391bc
title: Geospatial Data For Streamflow Monitoring Network Design in Louisiana

description: This resource contains GIS layers necessary to reproduce the analysis of the paper "Stakeholder-Driven Design of a Flood Risk Streamflow Monitoring Network for Louisiana, USA" submitted to the Journal of American Water Resources Association (JAWRA). The analysis of this paper is focused on designing a streamflow gauge monitoring network as part of the Louisiana Watershed Initiative (LWI) program to enhance the hydrologic modeling and monitoring capabilities of the state of Louisiana. The monitoring network is optimized to capitalize on the resources made available by the LWI program while serving the needs of the local, regional, and federal stakeholders in Louisiana as much as possible. The factors taken into the optimization algorithm included the collected feedback from the stakeholders, as well as a variety of geospatial and geomorphic characteristics of the Louisiana stream network. The analysis also used the current and past conditions of stream monitoring (e.g., existing and discontinued USGS locations). A final set of 123 stream gauges were selected to be deployed. The shapefile containing this set of gauges is also included in this resource.
DOI: 10.4211/hs.2c6c1d02c3ec4b97a767c787e1889647
title: High-frequency major ion concentration of the Sangamon River from RiverLab (Aug 2021 – Jun 2023)

description: This resource contains accompanying riverine chemistry data (major cations and anions), discharge data and physiochemical parameters (conductivity, temperature and dissolved oxygen) presented in "Drought constrictions on lateral carbon transport" by Wang et al. The dataset is comprised of a 30-min frequency time series from 2021/08/20 to 2023/06/30 for the Upper Sangamon River obtained from a RiverLab deployment. The discharge data is obtained from USGS (https://waterdata.usgs.gov/nwis/). pH data are available in the accompanying manuscript Extended Data Table 1 and are obtained from the WQP (https://www.waterqualitydata.us/). 

Files are provided in ".csv" format.

CZO site and time range reported in this study:
Sangamon River, IML-CZO (Illinois, USA) - August 20 2021 to June 30 2023

Site description and details of the RiverLab facility are available in the accompanying manuscript and in Wang et al. (2024) (https://doi.org/10.1016/j.scitotenv.2023.167379)
DOI: 10.4211/hs.98104bc112544bd183cb970183cbfbaa
title: Hydrodynamics control nitrous oxide production in eutrophic coastal permeable sediments

description: This is the raw data from the paper with the same title published in JGR Biogeosciences by Fowdar et al, 2024.  The data includes experimental results, model outputs and wave data used in the model simulations.  The File 'N2O experimental data' contains the data from flow through reactor experiments as described in the linked publication in Figure 1.  The file 'model outputs' give the data from the model outputs shown in Figures 2 and 3.  The file 'Werribee wave data' shows the Wave Data used in the model and was sourced from https://vicwaves.com.au.
DOI: 10.4211/hs.4058253204f44d5680ccd7f7ae4b1fde
title: Sources of organic matter to salt marshes: Insights from Oregon, USA

description: Salt marshes are important blue carbon sinks; however, identification of the drivers of carbon burial rates is challenging because estuaries sit at terrestrial and marine interfaces. Here, we address the questions: what are the sources of organic matter (OM) sequestered in Oregon salt marshes, and how do sources change through time? We characterized down-core sediment biogeochemistry (C:N, δ13C, δ15N) for the last century in seven Oregon high marshes and used a mixing model to elucidate differences in OM sources across estuaries and through time. Autochthonous biomass production consistently accounted for half of overall OM accumulation, and the remainder was allochthonous, originating from a combination of estuarine and terrestrial sources. Salt marshes with high sediment loads buried more terrestrial OM, whereas those with low loads and substantial subtidal habitat buried more estuarine-derived OM. When assessed through depth/time, stable isotope trends indicated that decomposition is not the major control. Instead, OM became increasingly more terrestrial in recent decades, especially in salt marshes with low fluvial loads. We hypothesize that salt marshes with low loads took longer to regain lost elevation following coseismic subsidence of the 1700 Cascadia earthquake than salt marshes with higher loads. This result magnifies the role of river floods in sediment and carbon accumulation on the marsh surface. Ultimately, the highest carbon burial rates coincided with highest fractions of terrestrially-sourced OM, though spatiotemporal complexities obscured any potentially significant trends. While the term “blue” typically excludes allochthonous carbon, salt marshes still perform the important ecosystem function of burying OM.
DOI: 10.4211/hs.0f6be4446d0f47519753d85d0e908d42
title: Data Repository for Smith et al. Robust Optimization of Green Infrastructure in RHESSys

description: This repository provides data and supplementary information for the following article submitted to the Journal of Water Resources Planning and Management:
Smith, J.D., J.D. Quinn, and L.E. Band. Comparing robust optimization approaches for addressing hydrologic model uncertainty in infrastructure planning: A green infrastructure example. Submitted to Journal of Water Resources Planning and Management.

See the README.pdf file for a description of all directories and files in the repository.
DOI: 10.4211/hs.c1cfd1cfdb04461289a56970c2fd1d51
title: Peru Watershed Data for the Arequipa Region

description: Surface water quality has been monitored in southern Peru for over a century, but the information is only available from various organizations with considerable delay after official requests. A substantial portion of the data have not been quality assured and were available in difficult-to-access formats such as scanned PDF documents, which made it difficult to evaluate water quality trends. In this project, we gathered all available surface water quality information from five watersheds in the Arequipa Region of southern Peru: Camaná, Chili, Ocoña, Tambo, and Yauca. The effort required entry of more than 130 thousand records of general chemistry, nutrients, and parameters, metals, organic compounds, and biological taxa from 276 stations. The water quality records span the years 2012 to 2021 for most data, but Chili does include data starting from 1905. This paper describes how the water quality data were assimilated and provides one master Excel database so that the surface water quality data can be used for research and decision making.
DOI: 10.4211/hs.e309c3c2c5db4bacb49b3d9a0761ce2b
title: Cape Fear River Basin Water Quantity and Quality Model

description: This resource contains the Cape Fear River Basin Water Quantity and Quality Soil and Water Assessment Tool Model (CFRB WQQ SWAT Model) which was the basis of the publication "Landscape pollution source dynamics highlight priority locations for basin-scale interventions to protect water quality under hydroclimatic variability".

The CFRB WQQ SWAT Model was developed by The Nature Conservancy and Arizona State University to examine risks to water quality from point and non-point sources under current land use and weather conditions from 1982-2019, and to facilitate the evaluation of scenarios, including watershed-scale restoration of forests and wetlands. This model was modified from a Cape Fear River Basin Water Quantity Model developed by the U.S. Geological Survey South Atlantic Water Science Center for a Coastal Carolinas Focus Area Study of water availability and water use.

Materials contained in this resource include:
-CFRB WQQ SWAT Model
-Model data delineating the watershed boundary, model subbasins, reach network, and subbasin outlets, as well as input data including land use, soil, and slope, and reservoir and pond parameters
-Additional simulation input files that permit changing the simulation period
DOI: 10.4211/hs.7a45ee06851e41d99e4affb7110d5f97
title: Water temperature extremes in European mountain rivers

description: This dataset contains the data related to the research paper 'Trends and drivers of water temperature extremes in mountain rivers' by van Hamel and Brunner (2024), which is published in the journal Water Resources Research: https://doi.org/10.1029/2024WR037518. It contains water temperature data for 177 stations in the European Alps, the Pyrenees, the Central Massif and the Scandinavian mountains. All catchments have at least 5 entire years of water temperature observations available for the period 2008-2022. For each catchment, we have extracted extreme water temperature values and extreme events. Extreme values are the days on which the daily mean water temperature exceeds the locally defined, seasonally varying 95th percentile threshold. Extreme events refer to a continuous period of multiple days (minimum 2 days) for which the locally defined, seasonally varying 95th percentile threshold is exceeded. An extreme event is composed of multiple extreme values.
DOI: 10.4211/hs.5192b2f8dc2a4784ad46d227ca3beecf
title: Anthropogenic litter and plastics on Euclid Beach, Cleveland, Ohio

description: In the summer of 2021, surface litter and >2 mm anthropogenic materials within the top 5 cm of beach sediment were repeatedly measured along 10 transects at Euclid Beach, in Cleveland, Ohio. Plastics comprised 79% of litter >50 mm and 100% of smaller visible litter on the beach surface. Surface litter concentrations (0.279 pieces m-2) were relatively low compared to previously studied Great Lakes strandlines, with mechanical grooming and beach visitor usage influencing litter distribution. However, when plastics within the top 5 cm of the beach sediment were included, Euclid Beach microplastics (54.7 pieces m-2) and mesoplastics (45.0 pieces m-2) concentrations were among the highest in the Great Lakes. Plastic production pellets were the most common microplastic morphology, while foamed plastics were the most common mesoplastics. Most plastics in the sediment were too small to be removed by mechanical grooming, but fragmentation of larger, weathered plastics is a potential concern deserving further investigation.

This dataset underpins the analysis in "Anthropogenic litter and plastics across size classes on a mechanically groomed Great Lakes urban beach" by the same authors, in Journal of Great Lakes Research.
DOI: 10.4211/hs.8134f362b45147d8aebf02b71253213e
title: MIrAg-US : Monthly Crop Water Consumption of Irrigated Crops in the United States From 1981 to 2019

description: Irrigated agriculture depends on surface water and groundwater, but we do not have a clear picture of how much water is consumed from these sources by different crops across the US over time. Current estimates of crop water requirements are insufficient in providing the spatial granularity and temporal depth required for comprehensive long-term analysis. To fill this data gap, we utilized crop growth models to quantify the monthly crop water consumption - distinguishing between rainwater, surface water, and groundwater - of 30 of the most widely irrigated annual crops in the US from 1981 to 2019 at 2.5 arc minutes. These 30 crops represent approximately 95% of US irrigated cropland. We found that the average annual total crop water consumption for these 30 irrigated crops in the US was 154.2 km3 (70% blue, 30% green). Corn and alfalfa accounted for approximately 16.7 km3 and 24.8 km3 of average annual blue crop water consumption, respectively, which is nearly two-fifths of the blue crop water consumed in the US. Surface water consumption decreased by 41.2%, while groundwater consumption increased by 6.8%, resulting in a 17.3% decline in blue water consumption between 1981 and 2019. We find good agreement between our results and existing modeled evapotranspiration (ET) products, remotely sensed ET estimates (OpenET), and water use data from the U.S. Geological Survey and U.S. Department of Agriculture. Our dataset and model can help assess the impact of irrigation practices and water scarcity on crop production and sustainability.
DOI: 10.4211/hs.9eaa891ef9c44a19b3d40cdfcb1fe824
title: Water table: WTM steady-state water table simulations for LGM and present day

description: We used the Water Table Model (WTM) to simulate steady-state water tables at the Last Glacial Maximum (LGM, 21,000 calendar years before present), and in the present day. 

This dataset includes two GeoTIFF files (one for each time simulated). These files represent steady-state water table depth, including both groundwater table and lake surfaces. Water table depth is reported in metres relative to the land surface: negative numbers represent groundwater, and positive numbers represent lakes. The WTM does not include ice hydrology, such that lakes atop ice sheets may not be well represented.