cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4211/hs.b28565ed451a4b3dadc2973cfcf29ed3
title: Evaluation of Decreased Flows in the Grand Canyon to Benefit Native Fish Species

description: The current flow regime of the Colorado River through the Grand Canyon, as altered by dam construction and operations, has led to declines in native fishes such as humpback chub (Gila cypha) and razorback sucker (Xyrauchen texanus) in the river. The native fish are heavily impacted by changes in flow regime, lack of seasonal warm temperatures, and introduction of invasive species. In an effort to model some possible improvements for fish, especially in their larval stages, we worked with CRSS and a model designed to predict water temperature by river mile to test the impacts of redistributed flow regimes on the native fish. Three scenarios were run in the model to determine the hydraulic and thermal effect of shifting flows and maintaining Pearce Ferry Rapid. First the model was run with no changes and acts as the base scenario for comparison. The second scenario was aimed to shift springtime releases from Glen Canyon Dam (GCD) to earlier in the year. Finally, the third was aimed at maintaining the pool elevation of Lake Mead below 1,135 feet and includes the shifted delivery schedule. Scenarios 2 and 3 were found to produce the lowest mean discharge for the month of May. Additionally, scenario 2 proved most reliable at reducing the mean discharge in May below 10,000 ft3/s. In the end, though minimal variation in river temperatures were achieved, all three scenarios provided acceptable thermal regimes in areas of the Grand Canyon.

Please note this model incorporates results from a temperature model developed by Dibble, K. L., C. B. Yackulic, J. C. Schmidt, T. A. Kennedy, and K. R. Bestgen. This model is still in review. For more information regarding how the temperature model was developed, please contact Kimberly Dibble with the USGS at kdibble@usgs.gov.
DOI: 10.4211/hs.8207c26f492e49f0be33e7a2427ccfea
title: Hyporheic exchange studies in H.J. Andrews Watersheds 01 and 03, summer 2010

description: A series of hyporheic exchange studies were conducted in watersheds 01 and 03 during the summer of 2010 using saline tracers coupled with electrical resistivity to image the temporal and spatial extent of the hyporheic zone during baseflow recession.  A series of four 48-hr tracer tests were conducted in each watershed on a rotational schedule with each tracer test starting approximately 2 weeks following the start of the previous test in each watershed.  Each tracer injection was targeted to enrich the stream electrical conductivity by ~100 uS/cm.  Electrical resistivity surveys were conducted on up to 6 transects of electrodes (12 electrodes per transect) in each watershed for each test.  Resistivity surveys were collected, on a high temporal frequency ranging from continuous to every 4 hrs, for pre-injection, injection, and post-injection until conductivity measurements in the shallow groundwater well network returned to pre-injection magnitudes.  During each injection conductivity magnitudes were measured in the stream and each accessible groundwater well in the watershed using a handheld conductivity meter on a frequency ranging from near continuous (~15-30 min), during tracer start-up and shutoff, to every 2-6 hrs depending on position within the tracer test.  Hydraulic head data was collected approximately every 15 minutes by downwell pressure transducers from a select set of groundwater wells in each watershed for nearly the full summer 2010.   

These data were published in a series of papers outlined below.
DOI: 10.4211/hs.f54ee4688be141088bc460ac91940d3b
title: Multiwell Aquifer Storage and Recovery System Modeling

description: As more ASR systems are employed for management of water resources, the skillful operation of multiwell ASR systems has become very important to improve their performance. In this study, we developed MODFLOW and MT3DMS models to simulate a multiwell ASR system in a synthetic aquifer to assess effects of hydrogeological and operational factors on the performance of the multiwell ASR system. We evaluated a simplified (dual well) ASR system in comparison with complex system (3, 4, 5 and 7 well systems). Recovery and energy efficiencies were calculated using the model simulations. Factors such as higher hydraulic conductivity and longitudinal dispersivity significantly reduced the recovery and energy efficiencies of the system. In contrast, increasing the volume of recharged water increased the recovery efficiency, however the energy efficiency was reduced. Recovery and energy efficiencies also plummet when there is an increase in the underlying regional gradient and the designed storage duration. Operating the system multiple times can yield higher volume of potable water, but the energy efficiency may not vary significantly after the second operating cycle. Single well systems and multiwell systems exhibit similar responses to changes in physical factors, although operational factors have a more pronounced effect on the multiwell systems. One of the major findings was that fewer wells in a multiwell ASR system can yield higher volume of potable water and better output with respect to the electrical power being consumed. The results provide design engineers with guidelines for optimizing performance of the multiwell ASR systems.
DOI: 10.4211/hs.18a8a07f3f414563bca9def7a551a535
title: Hourly Precipitation Data for Beltsville, MD, USA (2012/05/01-2012/05/31)

description: This resource includes hourly precipitation data collected by National Oceanic and Atmospheric Administration's (NOAA's) and downloaded from the National Climate Data Center (NCDC) from station located in Beltsville, MD. These data were collected to with the purpose of obtain important inputs for some further research about hydrologic modeling. Samples were collected automatically through code in Python. Methods implemented for sample collection and analysis are described within the resource.
DOI: 10.4211/hs.38e6ec942aa143b2af93fdb74d91db83
title: Going with the (Fish) Flow: Contrasting Implementation of Additional Environmental Fish Flows and Natural Flows in Select Reservoirs of the Upper Colorado River Basin

description: The Green River is the Colorado River’s largest tributary, contributing a substantial volume of water to the Colorado River Basin that may be retained in reservoirs and utilized to generate hydroelectric power while maintaining important riparian and ecological habitat. Recently, two environmental fish flows for Flaming Gorge Dam along the Upper Green River have been proposed. The primary objective of this study was to assess the effect of these proposed environmental fish flows, in addition to a “run-of-the-river" alternative, on reservoir storage and hydropower generation at Fontenelle, Flaming Gorge, and Lake Powell Reseroirs. Results obtained from Colorado River Simulation Software (CRSS) multi-run simulation models reveal that, for the years 2020-2060, implementation of both proposed environmental fish flows at Flaming Gorge Dam will decrease average monthly storage by 1.6% and increase annual hydropower generation by 0.1%. The environmental fish flow promoting elevated summer baseflows to advantage native Colorado pikeminnow had greater influence on these findings than did the environmental fish flow aimed to disadvantage non-native smallmouth bass. Over the same time period, the “run-of-the-river” alternative will decrease average monthly storage 2.2% and decrease annual hydropower generation 2.7%. These results provide Colorado River Basin water managers, scientists, and stakeholders with additional context regarding the potential future implementation these alternatives.

See readme.txt for explanation of resource contents.
DOI: 10.4211/hs.04bfa3d95bd74ed9a5ac24e976b7701f
title: An example of Design Flow calcualtions for given Return Periods (EV1 Distribution)

description: Design flow studies for specific return periods are sometimes desired for hydraulic and hydrology researches. This project was focusing on automatic design flow calculations for a given USGS gaging station with code written in Python. The code was created with the help of the Jupyter Notebook with Anaconda 5.1 from Mygeohub. Ev1 distribution was applied for flow calculation. Peak flow data was downloaded from USGS by its URL.
DOI: 10.4211/hs.a84d6530dc8c43f69402e448969f3a89
title: Direct measurements of total and dynamic water storage in unsaturated bedrock via borehole NMR

description: Dataset required to replicate analysis in the manuscript Direct measurements of total and dynamic water storage in unsaturated bedrock via borehole NMR. Here we provide (i) metadata describing borehole conditions and logging dates, (ii) NMR and neutron well logging and repeat measurement results, and (iii) estimates of instrument uncertainty, total storage, dynamic storage, and depth of dynamic storage.
DOI: 10.4211/hs.3bd8663ab1f0471986b07c7be98c93ba
title: Introduction to Environmental Engineering (Water/Wastewater Focus)

description: Lecture notes, problem sets,  group assignment, syllabus, and schedule for Introduction to Environmental Science taught at Indiana University. Course materials developed Fall 2016 semester.
DOI: 10.4211/hs.918ff6bd408c4976bf329bcfbd498454
title: Lateral Inflow Data and SWOT Discharge Algorithm, MetroMan

description: Code and input/output files for a version of the SWOT discharge algorithm, MetroMan (Durand et al. 2014), used for the study, "Integrating lateral inflows into a SWOT Mission river discharge algorithm." This data is part of a case study incorporating lateral inflows into MetroMan for an 80 km section of the Muskingum River during a July 2013 20-day storm event.
DOI: 10.15468/dl.x6na9u
title: Occurrence Download

description: A dataset containing 580 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-5.581411 41.020409, -5.583534 41.060389, -5.636369 41.060389, -5.634225 41.020409, -5.581411 41.020409))",
 "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 580 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049944-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4211/hs.abf67aad0eb64a53bf787d369afdcc84
title: Creating Curve Number Grid using PyQGIS through Jupyter Notebook in mygeohub

description: This resource serves as a template for creating a curve number grid raster file which could be used to create corresponding maps or for further utilization,  soil data and reclassified land-use raster files are created along the process, user has to provided or connect to a set of shape-files including boundary of watershed, soil data and land-use containing this watershed, land-use reclassification and curve number look up table. Script contained in this resource mainly uses PyQGIS through Jupyter Notebook for majority of the processing with a touch of Pandas for data manipulation. Detailed description of procedure are commented in the script.
DOI: 10.4211/hs.203aa39e82b9423684e754a001530b71
title: CE59700_HW5

description: This Resource is created for Homework 5 of CE 59700, course held at 2020 Spring semester in Purdue University. The goal of this homework is to forecast streamflow series by a first order exponential model. USGS gage 03335500, Wabash River at Lafayette, is the target gagee in this homework. Our streamflow forecasting model is built by object-oriented programming skill. The error of prediction is reported with respect to different parameter of model. The further optimization process would be taken in the following class of CE 59700. 

Task of HW5 is to split your streamflow dataset into training set and validation set. The prediction made by your model is compared to the validation set split in the beginning. This procedure is known as the training process, which is popular in optimization problem. Create a function to report the mean square error of your model. Fit your model with training set and change alpha value manually. Find the best model which returns the minimum MSE value. Turn in the alpha value and the MSE value you get.
DOI: 10.4211/hs.c4c01c5f856546c3b2ddef15bf86c783
title: Supporting Hydrogeologic data of Araihazar, Bangladesh

description: This companion resource to a published Water Resources Research paper contains the following hydrogeologic data: (i) 33 borehole data used to generate a 3D lithostratigraphic model (Figure S5); (ii) average hydraulic head data used for a groundwater flow model calibration (Figure S7); (iii) long-term barometric pressure corrected head data retrieved from pressure transducers (Figure S13c); (iv) arsenic time-series measurements for a subset of wells (Figure 6); and (iv) dissolved arsenic, methane, tritium, and sediment reflectance data displayed in Figure 12. All figures in the paper were generated using the open source programming language of R. An example R script to reproduce Figure 12 is provided.
DOI: 10.4211/hs.0983ec823ac64088b25882a6e99341ab
title: Northwestern Clay Sand Laboratory Experiments Phase 1

description: Fine particles (0.1-100 microns) are ubiquitous within the water column. 
Observations on the interactions between suspended fine particles and sediment beds remain limited, reducing our ability to understand the interactions and feedbacks between fine particles, morphodynamics and hyporheic flow. 
We performed laboratory experiments to explore changes in bedform morphodynamics and hyporheic flow following the progressive addition of kaolinite clay to the water column above a mobile sand bed. 
We characterized these interactions by taking high-frequency time series measurements of bed topography and freestream clay concentration combined with solute injections and bed sediment cores to characterize subsurface properties.
Deposition of initially suspended clay resulted in a decrease of bedform height, celerity and sediment flux by 14%, 22% and 29% when 1000g was accumulated within the bed (equal to clay/sand mass ratio of 0.4\% in the bed). 
The hyporheic exchange flux decreased by almost a factor of 2 for all clay additions, regardless of the amount of clay eventually deposited in the bed.
Post experiment sediment cores showed clay accumulation within and below the mobile layer of the bedforms, with the peak concentration occurring at the most frequent bedform scour depth. 
These results demonstrate the tight coupling between bed sediment morphodynamics, fine particle (clay) deposition, and hyporheic exchange. 
Suspended and bed load transport rates are diminished by the transfer of suspended load to the sediment via hyporheic exchange. This coupling should be considered when estimating sediment transport rates.
DOI: 10.4211/hs.044de7ea0e9c4196998c870fadd2b047
title: Quantifying Structural Deficit in the Lower Colorado River Basin

description: This document examines the structural deficit of Lake Mead in the Colorado River Basin. The structural deficit is the difference between how much water was agreed to be released and how much water is actually used. Using calculated and actual Colorado River Simulation System (CRSS) data, we were able to determine the change in storage and then create a reasonable reservoir value.
DOI: 10.4211/hs.024d498535ff42e9ad88432a219e6134
title: Data for "Managed vs Natural Recharge of pre-Alpine Phreatic Aquifers", Udine (Italy)

description: This dataset includes: 
1) time series data collected during the MAR test carried out at Mereto di Tomba, Udine;  
2) the digital elevation model of the regional and local study area
3) the finitite-element grid developed to simulate the groundwater flow at the regional and local scale
DOI: 10.4211/hs.9f981ae4e68b4f529cdd7a5c9013e27e
title: Gap-Free Global Annual Soil Moisture: 15km Grids for 1991-2018

description: Soil moisture is key for quantifying soil-atmosphere interactions and the ESA-CCI (European Space Agency-Climate Change Initiative) provides historical (>30 years) satellite soil moisture global grids with spatial resolution of ~27km. This dataset is incomplete (contains gaps) due to conditions such as dense vegetation or extremely dry surfaces. Here we provide a framework to increase the spatial resolution and fill gaps (reporting associated uncertainty) of the ESA-CCI (v4.5) soil moisture dataset. The outcome is a new dataset of gap-free global mean annual soil moisture and uncertainty
for 28 years (1991-2018) across 15km grids. We compare the performance of machine learning odels using only terrain parameters (e.g., slope, wetness index) against predictions using terrain parameters, bioclimatic information, and soil type classes. We use independent field information from the International Soil Moisture Network (ISMN, n=13376) and in-situ precipitation records (n=171) only for model evaluation purposes. Using only terrain parameters to predict soil moisture results in a parsimonious approach comparable with a more complex model that includes additional bioclimatic and soil information. The correlation between observed and predicted soil moisture values varies from r=0.69 to r=0.87 with root mean squared errors (RMSE) around 0.03 and 0.04 m3/m3. Our soil moisture predictions improve: (a) the correlation with the ISMN (when compared with the original ESA-CCI product) from r=0.30 (RMSE=0.09 m3/m3 ) to r=0.66 (RMSE=0.05 m3/m3 ); and (b) the 
correlation with local precipitation records across boreal (from r=<0.3 up r=0.49) or tropical areas (from r=<0.3 to r=0.46) which are currently poorly represented in the ISMN. Temporal trends show a decline of global annual soil moisture using: a) data from the ISMN (-1.5 [-1.8, -1.24]%, b) associated locations from the original ESA-CCI dataset (- 0.87[-1.54, -0.17]%), c) associated locations from predictions based on terrain parameters (-0.85[-1.01, -0.49]%), and d)associated locations from predictions including bioclimatic and soil type classes (-0.68[-0.91, -0.45]%). Our parsimonious downscaled soil moisture predictions are independent of climate variables and vegetation indexes, to avoid potential spurious correlations in future research, and they complement information about soil moisture dynamics worldwide.
DOI: 10.15468/dl.64z3dv
title: Occurrence Download

description: A dataset containing 2450429 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is one of (Contopus virens)",
 "BasisOfRecord is one of (Human Observation, Observation, Occurrence evidence)",
 "Year is greater than or equal to 1951",
 "Year is less than or equal to 2024",
 "Month is greater than or equal to April",
 "Month is less than or equal to July",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 2450429 records from 87 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049923-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4211/hs.26dbc260405b4bb9b3ac16ec55432684
title: Variability in epilimnion depth estimations in lakes

description: Variability in epilimnion depth estimations in lakes
Analysis codes and output codes available
For input codes please contact author harriet.wilso@dkit.ie or available from Lough Feeagh and Lake Erken data providers: 

Lough Feeagh: http://data.marine.ie/geonetwork/srv/eng/catalog.search#/metadata/ie.marine.data:dataset.2817
Lake Erken : available on request
DOI: 10.4211/hs.d0603a13c262485daf25c3406024d703
title: Test for versioning published resource

description: This is a test. I'm creating a resource with some content to be published with doi. 
This will then be added to a test collection which is also published with doi. 
The test collection with then be added to a second test collection, which is published with doi. 
Then I will version this resource and republish. 
I will see if I need to version the collection to expose the updated core resource.  
If I have to version the containing collection, I will do that and republish. 
Then I will check the second test collection to see if it has to be versioned to expose the updated first collection. 
This test mimics the data structure of the Harvey Data Archive, which has collections of collections of resources. Some of the innermost resources have to be versioned due to changes in linked data hosted by FEMA, which were reorganized since the Harvey Data Archive was published.
DOI: 10.4211/hs.a117dcf84604475699d9f600a9b448d2
title: Test Collection Inner

description: Collection used for testing versioning with published/DOI resources. 

This collection contains a test resource.
This collection is contained within one other collection, "Test Collection Outer"
DOI: 10.4211/hs.95267ff3162b4d07bc230e3b807f89df
title: Test Collection Outer

description: Test collection for versioning published/DOI resources. 

This collection contains "Test Collection Inner", which is a collection containing "Test for versioning published resource"
DOI: 10.5281/zenodo.17915227
title: Dataset for: Functional imaging of nine distinct neuronal populations under a miniscope in freely behaving animals

description: This record contains raw and processed data supporting:"Functional imaging of nine distinct neuronal populations under a miniscope in freely behaving animals"

Imaging modalities:- Miniscope calcium imaging (nVoke2)- In vivo multiplexed confocal spectral imaging (LSM 980)

Folder descriptions:

4FluorophoreData/: Reduced-complexity experiments using four retrograde fluorophores, organized by animal ID.



Inscopix/: CNMF-E spatial maps and anatomical reference images, organized by imaging day

ZEISS/: Confocal spectral images and imported ROIs


9FluorophoreData/: Full Neuroplex experiments using nine injected fluorophores (plus GCaMP), organized by animal ID.



Behavior/: Timestamped behavioral probabilities for each session

Inscopix/: CNMF-E spatial maps and anatomical reference images, organized by imaging day

ZEISS/: Confocal spectral images and imported ROIs

ProcessedData/: ROI definitions, raw and normalized spectral fingerprints, and fluorophore assignments


CalibrationData/: Optical calibration and validation datasets.



ArgoSlide: Fluorescent calibration slide data used for image-to-image registration and GRIN lens aberration characterization

Hek293Cells: In vitro spectral imaging data from HEK293T cells expressing individual fluorophores, used to generate pure fluorophore spectral fingerprints


 

Corresponding analysis code available at:

GitHub - Neurocipher/PythonPipeline: Python pipeline for Neurocipher