cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.dr8nks
title: Occurrence Download

description: A dataset containing 226 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-5.672380 41.133194, -5.674170 41.166228, -5.717843 41.166228, -5.716040 41.133194, -5.672380 41.133194))",
 "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 226 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049942-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4211/hs.379faf0e8f4e4c1f9db8eeb8036cb023
title: Geng and Michael, 2019

description: This includes model files processing codes for nearshore pumping simulations in coastal volcanic aquifers.
DOI: 10.4211/hs.75975f696b1a46959686fc18039baa59
title: Preferential flow enhances pumping-induced saltwater intrusion  in volcanic aquifers

description: This includes model files processing codes for nearshore pumping simulations in coastal volcanic aquifers.
DOI: 10.4211/hs.dcb9c73de83546d79aadf6cffd0a54f4
title: Preferential flow enhances pumping-induced saltwater intrusion  in volcanic aquifers

description: This includes model files processing codes for nearshore pumping simulations in coastal volcanic aquifers.
DOI: 10.4211/hs.5ecff343a4334ecbaac2825a46dc581a
title: Data for Mapping Permeable Media Architecture and Interstitial Flow

description: Porous media are ubiquitous, a key component of the water cycle and locus of many biogeochemical transformations. Mapping media architecture and interstitial flows have been challenging because of the inherent difficulty of seeing through solids. Previous works used particle image velocimetry (PIV) coupled with refractive index-matching (RIM) to quantify interstitial flows, but they were limited to specialized and often toxic fluids that precluded investigating biological processes. To address this limitation, we present a low-cost and scalable method based on RIM coupled PIV (RIM-PIV) and planar laser induced fluorescence (RIM-PLIF) to simultaneously map both media architecture and interstitial velocities. Here, we store and report the data used in "A biologically friendly, low-cost and scalable method to map permeable media architecture and interstitial flow" by Hilliard et al., 2020, in Geophysical Review Letters, DOI: 10.1029/2020GL090462
DOI: 10.4211/hs.fbf812c4d72d4a89b941645ffb69df75
title: Filling the void: the effect of riverbank streambank soil pipes on transient hyporheic exchange during a peak flow event.

description: This is the data repository for the journal article entitled "Filling the void: the effect of riverbank streambank soil pipes on transient hyporheic exchange during a peak flow event," published in Water Resources Research in 2020 by W. Seth Lotts and Erich T. Hester. The repository contains all the data used to produce the figures of Lotts and Hester 2020, input files necessary to reproduce the study, as well as data from other sensitivity analyses not included in the study. A detailed explanation of the repository's file organization, as well as detailed descriptions of file contents can be found in the master readme file in LottsHester2020_Data. Any questions regarding this repository can be directed to Erich Hester at ehester@vt.edu.
DOI: 10.4211/hs.398d546c444b4955bf5f206ba119e399
title: Preferential flow enhances pumping-induced saltwater intrusion  in volcanic aquifers

description: This includes model files processing codes for nearshore pumping simulations in coastal volcanic aquifers.
DOI: 10.4211/hs.2599efbdbdc04e669959da368ee0b7c0
title: hyporheicFoam

description: This file contains the solver, libraries, cases, and utility tools for the simulation of hyporheic flows. The directory ``solver'' contains the hyporheicFoam solver. The directory ``libraries'' contains the dynamic libraries for boundary conditions, reaction models, and other miscellaneous functions. The directory ``utilities'' contains tools for pre- and post-processing. For example, the mapping tool for pressure between the surface and subsurface domains is provided. This tool is necessary to perform sequential simulations. The directory ``cases'' contains the simulation case (which can be specified to run in either sequential or coupled mode through switches in the case files). 

The code is developed with OpenFOAM v5 and should be compatible with other newer versions. To use this code, it is required that OpenFOAM has been properly installed. Current code has only been used in Linux. Porting to Windows and Mac OS have not been done, but possible.
DOI: 10.4211/hs.b8f87a7b680d44cebfb4b3f4f4a6a447
title: Data Repository for 'Bootstrap aggregation and cross-validation methods to reduce overfitting in reservoir control policy search'

description: Policy search methods provide a heuristic mapping between observations and decisions and have been widely used in reservoir control studies. However, recent studies have observed a tendency for policy search methods to overfit to the hydrologic data used in training, particularly the sequence of flood and drought events. This technical note develops an extension of bootstrap aggregation (bagging) and cross-validation techniques, inspired by the machine learning literature, to improve control policy performance on out-of-sample hydrology. We explore these methods using a case study of Folsom Reservoir, California using control policies structured as binary trees and daily streamflow resampling based on the paleo-inflow record. Results show that calibration-validation strategies for policy selection and certain ensemble aggregation methods can improve out-of-sample tradeoffs between water supply and flood risk objectives over baseline performance given fixed computational costs. These results highlight the potential to improve policy search methodologies by leveraging well-established model training strategies from machine learning.
DOI: 10.4211/hs.cefee17cd5c94c2ebfb2681f5cdbdbdc
title: An improved optimization scheme for representing hillslopes and depressions in karst hydrology

description: Understanding hydrological processes is essential for the management of water resources and for promoting catchment sustainability. In karst regions, high spatial heterogeneous landscapes, such as discontinuous soil distribution and complex network of matrices and conduits in hillslopes and depressions, result in different hydrological processes. However, most studies have mainly focused on the effects of the distribution of soil depth and the fast-slow flow in the matrices and conduits on hydrological processes, but they have ignored the different hydrological processes on hillslopes and depressions (HD). This study improved the VarKarst model by adding randomly distributed soil and epikarst depths (RSE), fast-slow flow (FS) and HD in six large catchments (1,213~5,454 km2) and one small catchment (1.25 km2). The combination of FS and HD (Scenario FS+HD) and the combination of RSE, FS, and HD (Scenario RSE+FS+HD) for the improved VarKarst model had the best performance (calibrated and validated KGE ranged from 0.54 to 0.89 and AIC ranged from -336.49 to 669.77) compared with other scenarios (original VarKarst, Scenario RSE, Scenario FS, Scenario HD, and Scenario RSE +FS). Particularly, these two scenarios performed better than the original VarKarst in reproducing the discharge of peaks and recessions. This study confirmed that the combination of HD, RSE, and FS improved VarKarst model for karst topography and the hillslopes. It also suggested that there is a need to separate the hillslopes and depressions for modeling karstic hydrological processes.
DOI: 10.4211/hs.41b8e61a76bf4a2aa15abd1965babecc
title: An improved optimization scheme for representing hillslopes and depressions in karst hydrology

description: Understanding hydrological processes is essential for the management of water resources and for promoting catchment sustainability. In karst regions, high spatial heterogeneous landscapes, such as discontinuous soil distribution and complex network of matrices and conduits in hillslopes and depressions, result in different hydrological processes. However, most studies have mainly focused on the effects of the distribution of soil depth and the fast-slow flow in the matrices and conduits on hydrological processes, but they have ignored the different hydrological processes on hillslopes and depressions (HD). This study improved the VarKarst model by adding randomly distributed soil and epikarst depths (RSE), fast-slow flow (FS) and HD in six large catchments (1,213~5,454 km2) and one small catchment (1.25 km2). The combination of FS and HD (Scenario FS+HD) and the combination of RSE, FS, and HD (Scenario RSE+FS+HD) for the improved VarKarst model had the best performance (calibrated and validated KGE ranged from 0.54 to 0.89 and AIC ranged from -336.49 to 669.77) compared with other scenarios (original VarKarst, Scenario RSE, Scenario FS, Scenario HD, and Scenario RSE +FS). Particularly, these two scenarios performed better than the original VarKarst in reproducing the discharge of peaks and recessions. This study confirmed that the combination of HD, RSE, and FS improved VarKarst model for karst topography and the hillslopes. It also suggested that there is a need to separate the hillslopes and depressions for modeling karstic hydrological processes.
DOI: 10.4211/hs.069f552f96ef4e638f4bec281c5016ad
title: Streamflow regimes for CAMELS dataset

description: Streamflow regime classes identified for the 671 stations in the CAMELS dataset (United States) using functional data analysis: (1) intermittent regime, (2) strong winter regime, (3) weak winter regime, (4) melt regime, and (5) New Year's regime. The textfile contains a table with the USGS gauge ID of each catchment in the CAMELS dataset and their regime class (1-5). More information on the CAMELS dataset can be found in Newman et al. (2015) and Addor et al. (2017). A detailed description on how the regime classes were derived can be found in Brunner et al. (2020).

Addor, N., A. J. Newman, N. Mizukami, and M. P. Clark (2017), The CAMELS data set: Catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21(10), 5293–5313, doi:10.5194/hess-21-5293-2017.
Brunner, M. I., A. Newman, L. A. Melsen, and A. Wood (2020), Functional streamflow regime classes in the United States and their future changes, Hydrol. Earth Syst. Sci. Discuss., under review.
Newman, A. J. et al. (2015), Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: Data set characteristics and assessment of regional variability in hydrologic model performance, Hydrol. Earth Syst. Sci., 19(1), 209–223, doi:10.5194/hess-19-209-2015.
DOI: 10.4211/hs.2258c447dfbc47b485262639f67faf10
title: Hydraulic Architecture of the Brazos River Alluvial Aquifer

description: Geophysical and hydrogeological data can be used to estimate aquifer hydraulic parameters and test alternative conceptual models of subsurface hydrology. Here we confirm the existence of a relic sand-dominated channel-belt in an alluvial floodplain using electrical resistivity tomography and time-domain electromagnetics. After converting the bulk resistivity structure to porosity, we use hydrological modeling to gain new insights into the hydraulics and compartmentalization of a heterogeneous alluvial floodplain aquifer system. We discovered that rainwater infiltration fills the initially dry channel-belt laterally rather than from direct infiltration from above. This new understanding of preferential flow paths around and into sand-dominated channel-belts outlines how the architecture of an alluvial floodplain determines its response to natural hydrologic disturbances, thereby providing an improved basis for making informed decisions about water management strategies.
DOI: 10.4211/hs.5148675c6a5841e686a3b6aec67a38ee
title: Data and models for exploring real-time control of stormwater systems for mitigating flood risk due to sea level rise

description: This resource contains data and models that were used to produce results for a paper published in the Journal of Hydrology. The models are for a neighborhood in Norfolk, Virginia USA that suffers from frequent coastal flooding. The paper describes the use of active stormwater controls to mitigate this problem which will worsen with sea level rise. The particular type of control approach explored was model predictive control (MPC) and the Stormwater Management Model (SWMM) was used to simulate the stormwater system. The swmm_mpc Python package (https://github.com/UVAdMIST/swmm_mpc) was used to simulate MPC in the SWMM model. MPC was simulated for a number of sea level rise scenarios and the amount of flooding was compared to the system with no controls. The Python script that ran swmm_mpc for the sea level rise scenarios is "models/runs/hgv11.py." The results were compiled and plotted with scripts in the "models/results/" directory. 

The citation to the Journal of Hydrology paper is
Jeffrey M. Sadler, Jonathan L. Goodall, Madhur Behl, Benjamin D. Bowes, Mohamed M. Morsy, Exploring real-time control of stormwater systems for mitigating flood risk due to sea level rise, Journal of Hydrology, Volume 583, 2020, 124571, ISSN 0022-1694, https://doi.org/10.1016/j.jhydrol.2020.124571.
DOI: 10.4211/hs.e9de2725c1d442e1bd2ab8e0c4d45efc
title: St. Jones Monitoring Well Data 2017-2018

description: This resource contains water table elevation data for St. Jones National Estuarine Research Reserve in Dover, DE. Monitoring well data from within the coastal wetland captures levels from January - May, 2018; monitoring well data from wells upland of the wetland include water table elevation for March, 2017-December, 2018. The coastal wetland water table elevation data follow from Guimond, J. (2019). St. Jones Data Compilation 2017, HydroShare, https://doi.org/10.4211/hs.8f0b5599b871457ebb47f0bac898f156 and Guimond et al., 2019 (https://doi.org/10.1088/1748-9326/ab60e2).
DOI: 10.4211/hs.55222b131564471cb0337dcc0b8196e0
title: Mississippi River Delta Boring Data

description: Geotechnical boring data in USCS soil classification for Mississippi River Delta.
DOI: 10.4211/hs.3c3a2f3d491c4e4aa4ccb6764806eb8a
title: Additional RHONET Dataset

description: This repository contains an additional dataset for The Hydrometeorological Observation Network in California’s Russian River Watershed: Development, Characteristics and Key Findings from 1997 to 2019 paper submitted to BAMS by Sumargo et al. (2020). This dataset consists of the data used in the case study in the paper as well as CW3E stream gauges' discharge data up to July 2019.
DOI: 10.4211/hs.36fae4f0e04d40ccb08a8dd1df88365e
title: Derived Hydrography of Central America

description: This resource includes three hydrographic geospatial datasets for Central America including: Rivers, Watersheds, and Basin area. These datasets were developed at Brigham Young University by using standard terrain analysis tool in ArcGIS to extract features from digital elevation model data provided by Esri. The datasets were created for the purpose of supporting GEOGLOWS (http://www.geoglows.org) forecasting using ECMWF (https://www.ecmwf.int) ensemble weather/hydrologic model and the RAPID river routing model (http://rapid-hub.org). These datasets are provided free of charge for use for any purpose. If you use these data, please reference this HydroShare resource using the information provided in "How to Cite" at the bottom of this HydroShare landing page.
DOI: 10.4211/hs.291c24a5ce3f41579eb53b2950fb5a61
title: Does the mass balance of the reactive tracers resazurin and resorufin close at the microbial scale?

description: The Resazurin (Raz) – Resorufin (Rru) tracer system is widely used in hydrological studies. In most field experiments a lack of mass balance closure is reported and, to date, it is still unclear what drives incomplete recovery. We designed controlled laboratory experiments varying the initial concentrations of Raz, the test durations, and the type of microorganisms present to quantify mass balances of Raz and Rru in the absence of other suspected causes of incomplete recovery in field experiments (e.g., sorption to sediments and photodecay) in order to test if microbial activity alone could explain incomplete recovery. We used the summation of Raz and Rru concentrations over time to assess mass recovery and variability. The uploaded datasets present Raz and Rru concentrations measured during our experiments.
Results are published in Dallan et al. (2020) - doi: 10.1029/2019JG005435

Files organization:
“EXP_DESCRIPTION.docx” describes experimental set up, sampling and measurement methods.
“DATASET.xlsx” contains data concentrations of Raz and Rru obtained for the 4 experiments. Each sheet refers to one experiment. Table A summarizes experiment set up. Table B shows Raz concentration for the 18 flasks at the different sampling times. Table C shows Rru concentration for the 18 flasks at the different sampling times. Times are expressed in hours [hh], measured from the time of initial Raz addition to the flasks. Concentrations are expressed in micromol per liter [umol/L]
“RECOVERY_DATA.xlsx” contains data calculated from measured concentrations ("DATASET.xlsx"). Each sheet refers to one experiment. Tables S2-S5 summarizes main results about total recovery (Raz + Rru): for each series (50, 100, 200, 300, 400 ppb) and each sampling time k, we reported:
- the average concentration for the 3 replicates of each series [umol/L];
- the standard deviation of the concentrations associated at the 3 replicates [umol/L];
- the recovery percentage at each sampling time k.
In the last two rows, for each i series, we reported:
- the averaged total concentration [umol/L];
- the variability (standard deviation) associated with the recovery percentages.
DOI: 10.4211/hs.a42addcbd59a466a9aa56472dfef8721
title: WQQDB - water quality and quantity data base Germany: metadata

description: The water quality and quantity data base Germany (WQQDB) was collected and put together at the UFZ. 
It is based on a query to all federal states to provide discharge as well as nutrient and basic water quality metrics from their monitoring programs. 
An overview on the providing agencies is given in a CSV-file (data_providers.csv).
This resulted in a collection of water quality and quantity time series from 14 federals states (without Hamburg and Bremen). 

Quality data is available for 6086 stations. Time series are on average 11 years long starting from earliest 1954 (very rare), on average starting 1998. For Nitrate concentrations the average frequency is 7 measurements per year. All time series end 2016 latest.
Data is available for in-situ parameters (water temperature, pH, electrical conductivity, oxygen concentration and saturation), for nutrients (nitrate, nitrite, ammonia, mineral and organic nitrogen, total phosphorous, dissolved phosphate, total organic carbon, dissolved organic carbon) 
and for sulfate, chloride, magnesium, calcium and suspended solids. Not all data is available for all stations.
For some stations measured discharge at the time of sampling is available. Based on spatial match and on stations naming connections to the water quantity stations as well as GRDC runoff data was established for 501 stations.

Quantity data is available on a daily basis for 894 stations. Time series are on average 40 years long starting earlies 1893, on average starting 1973.

The procedure, how data was imported, transformed and initially quality checked can be found in a TXT-file (procedure.txt).

The WQQDB is composed of two parts: 
(1) The raw data archive that is archived in a repository at the UFZ: https://www.ufz.de/record/dmp/archive/7754/de/
(2) The metadata archive that contains information on the stations, time series length, number of measurements, data providers that is stored in HYDROSHARE
DOI: 10.4211/hs.85a681ee364a4f3c83fbcba217dcf2ec
title: Numerical study of solute transport in heterogeneous beach aquifers subjected to tides

description: A numerical study, based on a variably-saturated groundwater flow model within a Monto Carlo framework, was conducted to investigate flow and solute transport in a heterogeneous beach aquifer subjected to tides. The numerical simulations were conducted based on our previous tracer experiments performed in a laboratory beach. Heterogeneity is assumed to be multifractal generated using the Universal Multifractal model. Our results show that heterogeneity greatly alters temporal and spatial evolution of the tracer plume migrating in the beach. The spreading coefficient of the plume shows very dynamic response to tides; it increases as the tidally driven recirculation cell overlaps with the plume, and decreases as the recirculation cell moves far from the plume with tides. Descriptive statistics suggests that heterogeneity enhances spreading of the plume in the beach in an ensemble sense along with significant spatial and temporal variation. Due to heterogeneity, high-spots of the pore-water velocity are formed within the recirculation cell, creating transient preferential flow paths in the beach in response to tides. Contours of the Okubo-Weiss parameter show that coupling with tides, heterogeneity creates vorticity-dominated flow regions and also expands strain-dominated flow regions more downward, indicating complex local-scale mixing in the beach, compared to corresponding homogeneous case. Geologic heterogeneity also alters the spatial extent of the recirculating cell and induces highly variable transit time along the recirculating flow paths. The results provide insights into effects of geologic heterogeneity on seawater-groundwater mixing and associated solute transport processes in tidally influenced coastal aquifers.
DOI: 10.4211/hs.f0091cf90bcc4487bf401ca19783d1eb
title: Oklahoma Soil Moisture Predictions

description: Monthly soil moisture predictions over a region of interest centered on Oklahoma and surrounded areas from January 2000 to September 2012. Data were acquired from the European Space Agency Climate Change Initiative soil moisture product version 4.5, 0.25-degrees spatial resolution. The modeled product aims to fill soil moisture spatial gaps from the original product over the region of Interest. Soil moisture values were calculated based on three methods, e.g. Ordinary Kriging, Regression Kriging and Generalized Linear Model. Reference monthly soil moisture layers were generated based on daily soil moisture estimates over each 0.25-degrees pixel in the region of interest. Three different sampling approaches were considered to model soil moisture estimates, using 100% of available data from the original satellite data, 75% and 50% of available soil moisture estimates respectively. Data were randomly removed to simulate different scenarios of gap presence in the original ESA CCI product. Soil Moisture values were validated by means of 10-fold cross validation and ground-truth validation with records from the North American Soil Moisture Data Base. Detailed methods and code cab be found in: Llamas, R.M; Guevara, Mario; Rorabaugh, Danny; Taufer, Michela; Vargas, Rodrigo. "Spatial Gap-Filling of ESA CCI Satellite-Derived Soil Moisture based on Geostatistical Techniques and Multiple Regression", Remote Sensing (accepted)