cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4211/hs.0da288c7ef2b4fd6a06d723848f16bd0
title: Development of reservoir operation model incorporating the pre-release strategy for the flood events

description: Floods are among the most prevalent natural disasters, posing substantial threats to human activities. Using flood forecast information, reservoirs can pre-release water or adjust storage to enhance flood control and water conservation benefits. Yet, the absence of intuitive guidelines for the reservoir operators in making immediate operational decisions under flood events present a significant challenge. The objective of this study is to develop a flood operation model that provides the pre-release guideline to minimize flood damage considering downstream conditions. The developed model includes five Flood Operation Method (FOMs) and tested which FOM fits the best for the Seomjingang Reservoir as a case study. As part of developing the model, this study provides a Graphical User Interface (GUI) that encompasses reservoir characteristics and operational data for multipurpose reservoirs in South Korea. The developed GUI generates the reference graphs and tables that assists the reservoir operators with hourly guidelines to make prompt decisions on the flood control for pre-release and storage usage. This model is applicable if operational information for multipurpose reservoirs in other countries is available. This approach not only enhances reservoir management but also advances the broader dialogue on water resources management, signaling a move towards more secure, efficient, and adaptable strategies for reservoir operations.
DOI: 10.4211/hs.0a9b8dcbbac64fc9b97b8875268518a1
title: Hydrologic Tracer Experiments - Douglas fir and Quaking Aspen

description: Studies have shown that water can reside inside trees for up to several months, but how the duration of long-term stored water relates to species-specific water management strategies is not known. We studied water residence time, tracervelocity, and internal mixing in two tree species with differing water management strategies by injecting deuterated water into Douglas fir (Pseudotsuga menziesii) and trembling aspen (Populus tremuloides) trees and then monitored tracer concentration in leaves collected daily for several weeks post-injection. In a second study, we injected tracer into trees and collected leaves at sub-daily timescales to explore sub-daily patterns of tracer arrival in canopy leaves. For the first experiment, we hypothesized that the tracer would remain in both species for days to weeks and that the tracer would have a longer residence time in the more isohydric Douglas fir trees. For the sub-daily study, we explored if the tracer would arrive at a sharp peak, or be more spread out over time. The tracer resided in the trees for 7-11 days for both species. Interestingly, the tracer reached the canopy leaves of aspen sooner yet remained in trees for longer compared to Douglas fir, which exhibited sharp pulses of tracer breakthrough in canopies. Surprisingly, the tracer arrival in aspens occurred in two distinct pulses, separated by 1-2 days. Combined, the results from both experiments suggest that water inside trees may not flow through trees in simple “in-up-and-out” ways and that there may be some complex mixing of water reservoirs and water-flow pathways in some tree species.
DOI: 10.4211/hs.29a7c696ee4e4766883078ca0d681884
title: YRS Synthetic Forecast Generation Dataset

description: Pre-processed subset of raw HEFS hindcast data for Feather-Yuba system (YRS) configured for compatibility with the repository structure of the versions 1 and 2 synthetic forecast model contained here: https://github.com/zpb4/Synthetic-Forecast-v1-FIRO-DISES  and here: https://github.com/zpb4/Synthetic-Forecast-v2-FIRO-DISES. The data are pre-structured for the repository setup and instructions are included in README files for both GitHub repos on how to setup the data contained in this resource.

Contains HEFS hindcast .csv files and observed full-natural-flow files for the following sites:
ORDC1 - main reservoir inflow to Oroville Lake
NBBC1 - main reservoir inflow to New Bullards Bar
MRYC1L - downstream local flows at Marysville junction

Data also contains R scripts used to preprocess the raw HEFS data. These raw data are too large for easy storage in a public repository (YRS has 30+ modeled sites) but are available upon reasonable request from: Zach Brodeur, zpb4@cornell.edu
DOI: 10.15468/dl.s32de2
title: Occurrence Download

description: A dataset containing 160 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (China, Korea, Republic of, Russian Federation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Salix siuzevii"
 ]
}

 The dataset includes 160 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049994-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4211/hs.6775800f22bd4be9b24e472038294fe7
title: HarvestGRID: High-resolution harvested crop areas of the United States from 1981 to 2019

description: Agriculture plays a vital role in the US, generating billions of dollars in revenue and providing essential resources such as food, fiber, and fuel. At the same time, this sector consumes more water than all other sectors combined, and contributes significantly to greenhouse gas emissions. Accurately mapping cropland areas at a high spatial resolution, and understanding cultivation trends are crucial for promoting sustainable land management. However, it is not always clear where these crops are cultivated at a fine spatial resolution. Existing data sources either provide extensive temporal coverage with low spatial detail or vice versa. To address this, we employed a data-fusion approach, combining strengths of existing data sources. We produced annual irrigated and harvested areas for 30 major crops in the US from 1981 to 2019 at 2.5 arc minutes by combining county level US Department of Agriculture records with gridded land use datasets. We evaluated our dataset by comparing it with existing large-scale gridded cropland data, revealing alignment and divergence across data products depending on the year, area, and crop. Our dataset serves as a critical tool for analyzing and understanding long-term trends in cropland cultivation, thereby contributing to more informed and sustainable agricultural practices
DOI: 10.4211/hs.924ad15a08f64b798c6d81c488b238e7
title: Hydrological alterations in the dewatered stretch of the Volta Grande do Xingu - Data

description: Post-Belo Monte Hydroelectric dam daily flow series for the dewatered stretch, Indicator of Hydrologic Alteration (IHA), and hourly flow of impacted (dewatering) and non-impacted gauges.
This dataset corresponds to the manuscript "Dewatering the Xingu River: Hydrological Alterations and biocultural connections among the Arara Indigenous People in the Volta Grande Region, Brazilian Amazon" (Utsunomiya et al, 2024) of the journal Regional Environmental Change. DOI: 10.1007/s10113-024-02230-7
You can reach authors to learn more about processing and datasets.

Contents:
(1) Metadata
Fluviometric gauges attributes
(2) Post-dam daily flow Mangueiras
The daily flow of the dewatered stretch in the "Mangueiras" gauge (2016-2021) was corrected by double-checking both sources: Hidroweb/ANA and IBAMA (licensing Agency dataset, data from Norte Energia company)
(3) Indicator of Hydrological Alteration
Results of IHA software (parametric) comparing "Mangueiras" (post-dam) and "Altamira" (pre-dam) gauges. Source: Hidroweb/ANA. Results of IHA non-parametric applied for High-flood trigger 14000m3/s (only EFC high flow parameters considered)
(4) Post-dam hourly flow
The hourly flow of the dewatered stretch in "Mangueiras Gauge", impacted, and "UHE Belo Monte Montante", non-impacted (2016-2021, 2017 removed by criteria <80%). Hour data was manually interpolated to the exact hour (criteria up to 15 min of difference). Source: Hidroweb/ANA
DOI: 10.4211/hs.ef07b48ac62b44569792518f249036b8
title: Cobble App: Image processing tool to quantify changes in sediment shape and size due to abrasion during bedload transport

description: Attached is the Cobble App in Matlab developed by Erin Bray, for calculation of cobble shape parameters as reported in Bray et al "Influence of particle lithology, size, and angularity on rates and products of bedload wear: an experimental study" (In Review).

For the Cobble App to work, install Matlab version 2022b; Add the Image Processing Toolbox; Add the Computer Vision System Toolbox.Photo files must be saved in grayscale (no RGB embedded when saving photo files).
Files of photos can be saved as .tif or .tiff (both should work in the cobble app)
All extraneous white edges/borders or dots in files need to be removed (there were some stray white specks in the background of one of the photo files that was reduced to 75% resolution).
The Photo ID string column such as "P1_A1_N_PT" needs to be consistently formatted, with no extra spaces or extra characters, in both the Excel spreadsheet and in the photo file names, with no changes to the file string name even if you reduce the photo resolution to 75%. To use the merge functionality within the Cobble App, which pairs image-based shape parameters with corresponding handheld measurements of mass, diameter of each particle, the Excel spreadsheet needs to always have the identical number of columns and name of columns.
DOI: 10.4211/hs.bd79d57b2a464e5083f3edffa860f6b8
title: Ward et al., ESSD, 2019 - EEMs

description: Excitation-Emission Matrix (EEM) and absorbance spectra for samples collected as part of the campaign detailed here:

A comprehensive set of measurements and calculated metrics describing physical, chemical, and biological conditions in the river corridor is presented. These data were collected in a catchment-wide, synoptic campaign in the H. J. Andrews Experimental Forest (Cascade Mountains, Oregon, USA) in summer 2016 during low-discharge conditions. Extensive characterization of 62 sites including surface water, hyporheic water, and streambed sediment was conducted spanning 1st- through 5th-order reaches in the river network. The objective of the sample design and data acquisition was to generate a novel data set to support scaling of river corridor processes across varying flows and morphologic forms present in a river network. The data are available at https://doi.org/10.4211/hs.f4484e0703f743c696c2e1f209abb842 (Ward, 2019).
DOI: 10.4211/hs.5a4cfdd0a6c142a49b05090d645dcce5
title: Yampa River 2011 DEM - Deerlodge Park

description: The dataset contains a digital elevation model (DEM) derived from a 2011 LiDAR survey of the Yampa River collected by the Utah State University LASSI Service Center. The DEM only contains the Yampa River in Deerlodge Park within Dinosaur National Monument, Colorado. LiDAR data was collected within Yampa Canyon but is not included in this release. Contact the Center for Colorado River Studies at Utah State University for the entire LiDAR dataset. This data release also includes the shapefile for the delineated channel boundaries in 2013 and 2019 in the folder titled "channelBoundaries" and tables S2 and S3 in Leonard et al. (2024). The gibb.m file contains a Matlab function to preform the two-parameter Gaussian likelihood Bayesian model used in Leonard et al. (2024).
DOI: 10.4211/hs.0c197030df3c42ecac652a54d10db728
title: Data for "Contribution of Sedimentary Organic Matter to Arsenic Mobilization Along a Potential Natural Reactive Barrier (NRB) Near a River: The Meghna River, Bangladesh"

description: This repository contains all the measured inorganic and organic data obtained from the sediment samples used in this study, including the experimental data from a water-sediment extraction. 

Study Abstract
Elevated dissolved arsenic (As) concentrations in the shallow aquifers of Bangladesh are primarily caused by microbially-mediated reduction of As-bearing iron (Fe) (oxy)hydroxides in organic matter (OM) rich, reducing environments. Along the Meghna River in Bangladesh, interactions between the river and groundwater within the hyporheic zone cause fluctuating redox conditions responsible for the formation of a Fe-rich natural reactive barrier (NRB) capable of sequestering As. To understand the NRB's impact on As mobility, the geochemistry of riverbank sediment (<3 m depth) and the underlying aquifer sediment (up to 37 m depth) was analyzed. A 24-hr sediment-water extraction experiment was performed to simulate interactions of these sediments with oxic river water. The sediment and the sediment-water extracts were analyzed for inorganic and organic chemical parameters. Results revealed no differences between the elemental composition of riverbank and aquifer sediments, which contained 40 ± 12 g/kg of Fe and 7 ± 2 mg/kg of As, respectively. Yet the amounts of inorganic and organic constituents extracted were substantially different between riverbank and aquifer sediments. The water extracted 6.4 ± 16.1 mg/kg of Fe and 0.03 ± 0.02 mg/kg of As from riverbank sediments, compared to 154.0 ± 98.1 mg/kg of Fe and 0.55 ± 0.40 mg/kg of As from aquifer sediments. The riverbank and aquifer sands contained similar amounts of sedimentary organic matter (SOM) (17,705.2 ± 5157.6 mg/kg). However, the water-extractable fraction of SOM varied substantially, i.e., 67.4 ± 72.3 mg/kg in riverbank sands, and 1330.3 ± 226.6 mg/kg in aquifer sands. Detailed characterization showed that the riverbank SOM was protein-like, fresh, low molecular weight, and labile, whereas SOM in aquifer sands was humic-like, older, high molecular weight, and recalcitrant. During the dry season, oxic conditions in the riverbank may promote aerobic metabolisms, limiting As mobility within the NRB.
DOI: 10.4211/hs.f78bac856a1c420b924a9582b1a4ff8e
title: Data for "Mineralogical Associations of Sedimentary Arsenic within a Contaminated Aquifer Determined through Thermal Treatment and Spectroscopy"

description: This repository contains all the sediment and experimental data used in this study.

Study Abstract
Sedimentary arsenic (As) in the shallow aquifers of Bangladesh is enriched in finer-grained deposits that are rich in organic matter (OM), clays, and iron (Fe)-oxides. In Bangladesh, sediment color is a useful indicator of pore water As concentrations. The pore waters of orange sediments are usually associated with lower As concentrations (<50 µg/L) owing to abundant Fe-oxides which sorb As. Using this color signal as a guide, spectroscopic measurements alongside thermal treatment were extensively utilized for analyzing the properties of both Fe-oxides and clay minerals. This study uses Fourier transform infrared (FTIR) and diffuse reflectance (DR) measurements along with thermal treatment to evaluate the solid-phase associations of As from sediment collected along the Meghna River in Bangladesh. The samples analyzed in this study were chosen to represent the various lithologies present at the study site and included riverbank sands (1 m depth), silt (6 m depth), aquifer sand (23 m depth), and a clay aquitard (37 m depth). The concentrations of sedimentary As and Fe were measured by X-ray fluorescence, and the spectroscopic measurements were taken on the samples prior to the thermal treatment. For the thermal treatment, sediment samples were placed in a preheated furnace at 600 °C for 3 h. The thermal treatment caused a deepening of reddish-brown hues in all samples, and the greatest change in color was observed in the finer-grained samples. The FTIR spectral analysis revealed that the clay minerals were composed primarily of illite, smectite, and kaolinite. The DR results indicate that the majority of Fe in sands was present as goethite; however, in the clay and silt samples, Fe was incorporated into the structure of clay minerals as Fe(II). The amount of structural Fe(II) was strongly positively correlated with the sedimentary As concentrations, which were highest in the finer-grained samples. After thermal treatment, the concentrations of As in the finer-grained samples decreased by an average of 40%, whereas the change in the As concentrations of the sand samples was negligible. These findings indicate that significant proportions of solid-phase As may be retained by OM and Fe(II)-bearing clay minerals.
DOI: 10.4211/hs.2f9c0eed5e0e45c7ad055f1ddf86404a
title: Data for "Diverse sedimentary organic matter within the river-aquifer interface drives arsenic mobility along the Meghna River Corridor in Bangladesh"

description: Study Abstract
In alluvial aquifers with near-neutral pH and high dissolved arsenic (As) concentrations, the presence and character of sedimentary organic matter (SOM) regulates As mobility by serving as an energetically variable source of electrons for redox reactions or forming As–Fe-OM complexes. Near tidally and seasonally fluctuating rivers, the hyporheic zone (HZ), which embodies the mixing zone between oxic river water and anoxic shallow groundwater, may precipitate (or dissolve) iron (Fe)-oxides which sequester (or mobilize) As. To understand what is driving the mobilization of As within a shallow aquifer and riverbank sands adjacent to the tidally fluctuating Meghna River, we characterized the chemical reactivity of SOM from the sands, and a silt and clay layer, underlying the HZ and aquifer, respectively. Dissolved As (50–500 μg/L) and Fe (1–40 mg/L) concentrations increase with depth within the shallow aquifer. Similar vertical As and Fe concentration gradients were observed within the riverbank sands where concentrations of the products of reductive dissolution of Fe-oxides increase with proximity to the silt layer. Compared to all other sediments, the SOM in the clay aquitard contains older, more recalcitrant, terrestrially-derived material with high proportions of aromatic carboxylate functional groups. The shallow silt layer contains fresher SOM with higher proportions of amides and more labile polysaccharide moieties. The SOM in both the riverbank and aquifer is terrestrially-derived and humic-like. The labile SOM from the silt layer drives the microbially mediated reductive dissolution of As-bearing Fe-oxides in the HZ. In contrast, the carboxylate-rich SOM from the clay aquitard maintains dissolved As concentrations at the base of the aquifer by complexing with soluble As and Fe. This highlights that SOM-rich fine (silt or clay) layers in the Bengal basin drive As and Fe mobility, however, the specific processes mobilizing As and Fe depend on the lability of the SOM.
DOI: 10.4211/hs.eb4fcfe84d95474b8cbe3477bcb4e0be
title: Climate, land use, topography, soil, vegetation, and anthropogenic factors for GAGES-II gages (1990-2020)

description: This resource contains 49 factors categorized into five groups: climatic (14), topographic (11), vegetation-related (5), anthropogenic (12), and geologic (7) factors, concerning 383 watersheds within the GAGES-II gages dataset (https:// water.usgs.gov/GIS/metadata/usgswrd/XML/gagesII_Sept2011.xml) across the contiguous United States (CONUS).

The selection of the 383 watersheds out of the 9067 (in the CONUS) from GAGES-II was determined by the availability of daily streamflow data from 1990 to 2020 and its anthropogenic influence. For further details, refer to section 2.1 of https://doi.org/10.1016/j.jhydrol.2024.130984.

The factors represent average values for each watershed spanning 1990 to 2020, calculated using publicly available data. Detailed information on these factors, including their sources and calculation methods, is provided in Tables 1 and 2 of the PDF document (Methodology_factors.pdf). The Excel file (Factors.xlsx) contains the classification of the gages and their associated factor values.

The computation of these factors was conducted for the manuscript authored by Sara Alonso Vicario, George M. Hornberger, Maurizio Mazzoleni, and Margaret Garcia, titled "The Importance of Climate and Anthropogenic Influence in Precipitation Partitioning in the Contiguous United States," published in the Journal of Hydrology, Volume 633 (2024). The manuscript is accessible at https://doi.org/10.1016/j.jhydrol.2024.130984.
DOI: 10.4211/hs.b6788237717c41e0bcc69bcaa851694f
title: ADO Synthetic Forecast Generation Dataset

description: Pre-processed subset of raw HEFS hindcast data for Prado Dam system (ADO) configured for compatibility with the repository structure of the versions 1 and 2 synthetic forecast model contained here: https://github.com/zpb4/Synthetic-Forecast-v1-FIRO-DISES  and here: https://github.com/zpb4/Synthetic-Forecast-v2-FIRO-DISES. The data are pre-structured for the repository setup and instructions are included in README files for both GitHub repos on how to setup the data contained in this resource.

Contains HEFS hindcast .csv files and observed full-natural-flow files for the following sites:
ADOC1 - main reservoir inflow to Prado Dam (ADOC1)

Data also contains R scripts used to preprocess the raw HEFS data contained in the associated public Hydroshare resource here: https://www.hydroshare.org/resource/3b665049965c4a2b88f6f6c1abb0ff94/
DOI: 10.25934/pr00010958
title: A Novel Statistical Framework for Indirect Treatment Comparisons and Meta-analysis for validation with landmark Vedolizumab and Adalimumab trials in Ulcerative Colitis

description: Inflammatory bowel disease (IBD), including ulcerative colitis (UC), is becoming more common worldwide. UC affects the large intestine and can cause symptoms like diarrhea, and rectal bleeding. While two treatments, vedolizumab and adalimumab, have been shown to help people with UC feel better, choosing the best one for each person can be tough. There is limited evidence for a direct comparison of the two treatments. This study will utilize two clinical trials independently assessing these two treatments for indirect comparisons between the two treatments. The findings will be compared with a major trial assessing the medications together to make sure the indirect comparison is consistent with previously established evidence. 

Head-to-head randomized trials are the gold standard for comparing medications, offering the most reliable evidence for treatment decisions. However, they are expensive, time-consuming, and not always practical. However, differences in patient populations across these studies can make these indirect comparisons challenging.

Our research focuses on solving this problem by creating a new method to compare treatment outcomes using patient-level data from different trials. This approach ensures fairer and more accurate comparisons learning from the placebo groups (where patients are given an inactive treatment) in both trials and the treatment outcomes of each trial population. We’ll use data from a landmark head-to-head study comparing Adalimumab and Vedolizumab to verify our method performs similarly.

This new approach could make a big difference in real life. It helps researchers compare treatments even when direct comparisons aren’t available and applies study results to real-world patients. While we’re starting with UC, this method could be used for many other diseases, helping doctors choose the best treatments for a wide range of patients.