cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4211/hs.440e89b8cc8c4c43bdbc6176e8f38a70
title: Cape Shores Porewater Data Compilation 2014-2015

description: Biogeochemical reactions within intertidal zones of coastal aquifers, induced by the mixing between fresh groundwater and saline seawater, have been shown to alter the concentrations of terrestrial solutes prior to their coastal discharge. In organic-poor sandy aquifers, the input of marine organic matter from infiltrating seawater has been attributed to active biogeochemical reactions within the sediments. However, while the seasonality of surface water organic carbon concentrations (primary production) and groundwater mixing patterns have been well-documented, there has been limited speculation on the contributions of particulate organic carbon pools within the sediments that arise from transient hydrologic conditions. To understand the relationship between physical movements of the circulation cell and the seasonal migration of geochemical patterns, beach porewater and sediment samples from six field sampling events spanning two years were analyzed. While oxygen saturation, oxygen consumption rates, and silica distributions closely followed the seasonally-dynamic salinity, other chemically-reactive parameters (pH, ORP) and nutrient characteristics (N distributions, denitrification rates, reactive organic carbon distributions) were unrelated to contemporaneous salinity patterns. Particulate organic matter was distributed in pools within the aquifer due to the filtration effect of sediments, contributing to the divergence of chemical patterns from salinity patterns via nutrient release and leaching. Together, the results present the asynchronous movement of chemical conditions to salinity patterns due to the divergent transport pathways between solutes and particles arising from transient hydrologic forcing.
DOI: 10.4211/hs.01942b30259b40cabfb7217203349371
title: Identification of Tile Drain Networks using Thermal and RGB Data from Unmanned Aircraft

description: The use of tile drainage is documented as far back as 200 B. C. and continues to be used in poorly drained agricultural regions throughout the world.  Recent increases in annual precipitation throughout the mid-western United States, the potential for future regulation of tile, and more efficient installation methods for plastic tile have accelerated tile installation across the region.  While good for crop production, the eco-hydrologic impacts of this modification have been shown to adversely affect natural drainage networks.  Knowing the location of tile drain networks is essential to developing groundwater and surface water models. The geometry of tile networks installed decades ago has often been lost with time or was never well documented in the first place.  Previous work has recognized that tiles can be observed for certain soil types in visible remote sensing data due to changes in soil albedo. The soil surface directly above the tile appears to have a lower soil moisture content due to strong water table gradients adjacent to tiles, causing a detectable color contrast at the surface.  In this work, small Unmanned Aerial Systems (sUAS) were used to collect high resolution visible and thermal data to map tile drain patterns.   Within less than 96 hours of a 12 mm rain event, a total of approximately 60 hectares of sUAS thermal and RGB data were acquired at two different locations at the Intensively Managed Lands Critical Zone Observatory in Illinois.  Selected thermal images were co-registered with RGB images at known tile locations.  The thermal imagery showed limited evidence of thermal contrast related to the tile, however, it is possible that a contrast could have been detected sooner after the rain event when greater thermal contrasts due to lower soil moisture proximal to tile would be expected.  The RGB data, however, elucidated the tile entirely at one site and provided traces of the tile at the other site. These results illustrate the importance of the timing of sUAS data collection with respect to the precipitation event. Ongoing related work focusing on laboratory and numerical experiments to better quantify feedbacks between albedo, soil moisture, and heat transfer will help predict the optimal timing of data collection for applications such as tile mapping.

Raw project data is available by contacting ctemps@unr.edu
DOI: 10.4211/hs.18f8a253b0d54094a75d675eed30ad6d
title: Data for Continental Hydrologic Intercomparison Project (CHIP), Phase 1: A Large-Scale Hydrologic Model Comparison over the Continental United States

description: This resources contains the data from the manuscript Continental Hydrologic Intercomparison Project (CHIP), Phase 1: A Large-Scale Hydrologic Model Comparison over the Continental United States. 

High-resolution, coupled, process-based hydrology models, in which subsurface, land-surface, and energy budget processes are represented, have been applied at the basin-scale to ask a wide range of water science questions. Recently, these models have been developed at continental scales with applications in operational flood forecasting, hydrologic prediction, and process representation. As use of large-scale model configurations increases, it is exceedingly important to have a common method for performance evaluation and validation, particularly given challenges associated with accurately representing large domains. Here we present phase 1 of a comparison project for continental-scale, high-resolution, processed-based hydrologic models entitled CHIP—the Continental Hydrologic Intercomparison Project. The first phase of CHIP is based on past Earth System Model intercomparisons and is comprised of a two-model proof of concept comparing the ParFlow-CONUS hydrologic model, version 1.0 and a NOAA US National Water Model configuration of WRF-Hydro, version 1.2. The objectives of CHIP phase 1 are: 1) describe model physics and components, 2) design an experiment to ensure a fair comparison, and 3) assess simulated streamflow with observations to better understand model bias. To our knowledge, this is the first comparison of continental-scale, high-resolution, physics-based models which incorporate lateral subsurface flow. This model intercomparison is an initial step toward a continued effort to unravel process, parameter, and formulation differences in current large-scale hydrologic models and to engage the hydrology community in improving hydrology model configuration and process representation.

Tijerina, D.T., Condon, L.E., FitzGerald, K., Dugger, A., O'Neill, M. M., Sampson, K., Gochis, D.J., and Maxwell, R.M. (2021). Continental Hydrologic Intercomparison Project (CHIP), Phase 1: A Large-Scale Hydrologic Model Comparison over the Continental United States. Water Resources Res.  doi: 10.1029/2020WR028931.
DOI: 10.4211/hs.4a46c1445fb144a8a03b00d2e338bcfd
title: Effect of Surface Water Stage Fluctuation on Mixing-Dependent Hyporheic Denitrification in Riverbed Dunes

description: This is the data repository for the journal article entitled "Effect of Surface Water Stage Fluctuation on Mixing-Dependent Hyporheic Denitrification in Riverbed Dunes" published in Water Resources Research in 2019 by Erich T. Hester, Lauren A. Eastes, and Mark A. Widdowson.  The data themselves, as well as information about the data, can be found in several locations:

1) Many data are in the journal article or the associated supplementary information, which are available at the journal website or can be requested by emailing Erich Hester at ehester@vt.edu
2) Many data are available in the files associated with this Hydroshare resource, which are described in the readme.txt file
3) Any questions that are not answered by the above methods can be directed to Erich Hester at ehester@vt.edu
DOI: 10.4211/hs.e29c9283305045338be24a495c781ec9
title: Monterrey Mexico model From OpenAgua

description: Monterrey Mexico model From OpenAgua

This resource includes an SQLite file for the Water Management Data Model (WaMDaM) that stores data for the water allocation model for the Monterrey metropolitan area, Mexico. The model is imported from OpenAgua using the WaMDaM Wizard. For more info, visit OpenAgua here https://www.openagua.org/home
DOI: 10.4211/hs.af71ef99a95e47a89101983f5ec6ad8b
title: WEAP and WASH Bear River Systems Models

description: WEAP and WASH Bear River Systems Models

This resource includes an SQLite file for the Water Management Data Model (WaMDaM) that stores data for two models in the Bear River Watershed in Utah. 

The first model is the Watershed Area of Suitable Habitat (WASH) optimization model that allocates water to maximize watershed habitat areas for the Lower Bear River Watershed (Utah portion) (Alafifi and Rosenberg, 2020). The WASH model uses the General Algebraic Modeling System (GAMS) engine which has no user interface. 

The second model is a WEAP simulation model that allocates water by water right priority within the Bear River Watershed (Utah and Idaho portions). WEAP has a proprietary database and does not support data publication. Both the WASH and WEAP models were developed from a predecessor 2010 Utah Division of Water Resources model for the lower Bear River basin that had a plain text input file and Fortran computational engine which was depreciated. The WASH model disaggregated irrigation demands within Cache Valley, Utah while the WEAP model extended the model domain upstream to Idaho and Bear Lake.
DOI: 10.4211/hs.9282b186cc264dc8996032c60d3577f9
title: University of Arizona CUAHSI Data Services Workshop

description: The contents of this resource include materials from the CUAHSI Data Services Workshop hosted at the University of Arizona. The contents include the presentation powerpoint, a HydroShare Data Discovery Exercise, and a Data Management Plan Evaluation Exercise. If you reuse these materials please contact the author.
DOI: 10.4211/hs.446341bd0a3149abbcf3ec72dffb84a1
title: Brazos River Alluvium Aquifer - Conceptual Model Testing

description: Quantitative characterization of the dynamics of water exchange fluxes between rivers and aquifers is necessary for water resources management, water quality, environment and ecology of the river-aquifer systems. The main uncertain factors for predicting river–aquifer exchange fluxes are aquifer and riverbed properties. In this study, we characterize the flux exchange dynamics between Brazos River Alluvium Aquifer and Brazos River, TX, USA, using alternative conceptual models. Six alternative conceptual models for the connection between the river and the aquifer, having varying aquifer lithology and river incision levels and incorporating processes such as river bed clogging and seepage face flow, are numerically modeled in HYDRUS 2D using small-scale, high-resolution transects across the river. Modeled results are tested against observed heads in three wells and finally a best-fit conceptual model is used to quantify river-aquifer flux exchange dynamics. Additionally we focused on how factors such as aquifer lithology, river channel incision, water table conditions, seepage face boundaries, and low-conductivity river-bed effect hydraulic head distribution and the corresponding flux exchange dynamics. Our results demonstrate that only a small portion of the aquifer close to the river channel is well-connected with the river and a major portion of the aquifer is disconnected. The proposed conceptual model predicts a) much frequent flux reversals (changes between gaining and losing conditions) and b) much smaller amount of recharge and discharges compared to that of the conceptual model which has been assumed by earlier studies; a reduction of 151% in recharge and 116% in discharges. These results suggest that the magnitude and dynamics of water flux exchange between the river and the aquifer are independent of the hydraulic gradients in the wider disconnected aquifer and are determined by the hydraulic gradients in the connected aquifer close to the river. The results also demonstrate that river-aquifer flux exchange is sensitive to aquifer lithology, river incision depth, and river-bed clogging. While different settings of aquifer lithology and river incision can produce very similar heads in the wider aquifer, the hydraulic head distribution close to the river and hence the river-aquifer flux exchange varies quite drastically from model to model. River-bed clogging decreases the magnitude of fluxes and effects hydraulic head in the aquifer, especially in the vicinity of the river channel, depending upon the gaining and losing river conditions. Furthermore, seepage face flow could be of the same order as that of flows through river-bed depending upon aquifer lithology and corresponding river incision depth.
DOI: 10.4211/hs.4badd579d48e412e98a6d242f6f6ad91
title: Offshore pumping impacts onshore groundwater resources and land subsidence

description: This is model files processing codes for offshore pumping simulations
DOI: 10.4211/hs.3766845be72d45969fca21530a67bb2d
title: Addressing Challenges for Mapping Irrigated Fields in Subhumid Temperate Regions by Integrating Remote Sensing and Hydroclimatic Data

description: Preferred citation: 
Xu, T., Deines, J., Kendall, A., Basso, B., and Hyndman, DW. 2019. Addressing Challenges for Mapping Irrigated Fields in Subhumid Temperate Regions by Integrating Remote Sensing and Hydroclimatic Data. Remote Sensing.

We developed annual, 30-m resolution maps of irrigated corn and soybeans for southwestern Michigan from 2001 to 2016 using a machine learning method (random forest). Please see Xu et al. 2019 for full details. The rasters are in UINT 8 format, with 0 indicates rainfed, 1 indicates irrigated, and 3 indicates masked (not row crops according to NLCD before 2007 and not corn or soybeans according to CDL since 2007).
DOI: 10.4211/hs.344b4f3b48e1476d91294fb3ee7fcb30
title: WRSS codes

description: The data belong to a manuscript submitted to the Journal of Water Resources Planning and Management.
DOI: 10.4211/hs.ba3285fc8a7441f69f0c2279cb1502ef
title: Spring Temperature Data Set from New York and New England

description: Title: Dataset: Temperatures and flow rates for some springs in New England, 2017-18

Authors:  Dallas Abbott1, William Menke1, Juliette Lamoureux2, Dionne Hutson2 and Alyssa Marrero3

1Lamont-Doherty Earth Observatory of Columbia University, Palisades, New York
2City College of New York, New York, New York
3Kingsborough Community College, Brooklyn, New York
Summary: In 2017-2018, we visited a suite of about 80 springs in New York and New England (USA).  We measured water temperature with a Lascar EL-WIFI-TP digital temperature logger (0.1°C precision) at the closest accessible point to the source, which was usually the reservoir inside a spring house or the outflow pipe from a spring house.  When both reservoir and outflow pipe were accessible, we found that temperatures agreed to within ±0.2°C.  We also measured the flow rate of the spring with a bucket and a stopwatch, with a repeatability of about ±10%. 

A temperature anomaly ∆T was determined for each spring by subtracting the annual average temperature at the spring site.  Annually averaged temperatures are rarely available for spring sites but are available for airports via the National Oceanic and Atmospheric Administration’s (NOAA’s) National Center for Environmental Information.  We therefore used the annually averaged temperature for the nearest airport (typically ~10-20 km away), corrected to the elevation of the spring using the dry adiabatic lapse rate of 9.8°C/km.

Data was used in the following paper: 

Menke, W., Lamoureux, J., Abbott, D., Hopper, E., Hutson, D. and Marrero, A., 2018. Crustal heating and lithospheric alteration and erosion associated with asthenospheric upwelling beneath southern New England (USA). Journal of Geophysical Research: Solid Earth, 123(10), pp.8995-9008.
DOI: 10.4211/hs.1dc753fcd04146faa76e5b139054d168
title: Active-Passive Water Classification Results over the Awash River Basin, Ethiopia for October 2014-March 2017

description: The “active-passive surface water classification” (APWC) method leverages cloud-based computing resources and machine learning techniques to merge Sentinel 1 synthetic aperture radar and Landsat observations and generate monthly 10-meter resolution waterbody maps.  Merging data from two sensor types reduces the impact of errors associated with the individual sensors.  The skill of the APWC method is demonstrated by mapping surface water change over the Awash River basin in Ethiopia from October 2014 through March 2017.  This period corresponds to the 2015 East African regional drought and 2016 localized flood events.  Errors of omission and commission in the case study area are 7.16% and 1.91%, respectively.  These data were generated using the APWC method on August 18, 2017.
DOI: 10.4211/hs.9515ab9495724125941a09ee5b0e8a2a
title: A Linear Approach to Modeling Stream Temperature in Utah

description: Globally changing temperature and precipitation patterns are causing rapid changes stream temperatures, which in turn drive changes in the life histories and distributions of aquatic biota.  However, large-scale stream temperature datasets have not been developed, and observational data remains limited.  In order to better understand how ongoing thermal regime changes impact aquatic species, managers and researchers need better methods of quantifying stream temperatures at large spatial scales.  Here, a linear regression model is used to develop a relationship between air and stream temperature, then is used to predict stream temperatures across the state of Utah in the month of August.  Model validity was assessed by examining goodness of fit to observation data using R², Nash-Sutcliffe Efficiency index,  and root mean square error-observations standard deviation ratio (RSR).  Impact of outliers were assessed by examining mean absolute error (MAE), root mean square error (RMSE), and residuals.  The approach presented here contributes to the well-described linear air/stream temperature model by providing a study of its performance at large spatial scales.
DOI: 10.4211/hs.1f5551fc98b942a793b97ff9a90b5719
title: Improving Native Species Recruitment in Seed-based Wetland Restoration

description: One of the greatest threats to Great Salt Lake wetlands is the invasion of Phragmites australis. Recent research has highlighted effective control strategies for Phragmites, however natural recolonization of native plants needed to support wetland functions has been limited. Seeding is a feasible restoration option, however seedling mortality is often high. Understanding the mechanisms that drive early seedling outcomes by quantifying regeneration traits can improve our ability to manipulate and predict restoration actions. Additionally, managers involved in wetland restoration need to know how many seeds to sow, which sites should be prioritized for restoration, and when they should seed. I developed a simulation model to explore changes in native and invasive seed germination across initial seeding density, restoration site, and seasonal timing scenarios. Additionally, I incorporated the influence of seed mass on native species germination into my model. This approach represents a starting point for developing an important management tool that can be used to identify targeted, cost-effective wetland restoration strategies following Phragmites treatment.
DOI: 10.4211/hs.b8da9d4b7e964f83bfeeffec7a5e91aa
title: Supporting Data for Buahin et al. 2019: Parallel multi-objective calibration of a component-based river temperature model

description: The files provided here are input files for the river temperature modeling components created for the calibration exercise presented in Buahin et al. 2019, "Parallel multi-objective calibration of a component-based river temperature model" in Environmental Modeling and Software (https://doi.org/10.1016/j.envsoft.2019.02.012). Input files are organized into different folders for the different components.

Folders are organized as follows:

Composition: Contains the coupled model composition files (i.e., *.hcp) used in the HydroCoupleComposer graphical user interface. It describes the components that have been coupled as well as the data exchange connections nodes between them.

CalibrationComponent: Contains the input files for the calibration component specifying the calibration objectives, decision variables, and optimization algorithm to use for calibration.

CSHComponent: Contains input files for the channel solute and heat transport component.

HTSComponent: Contains input files for the hyporheic transient storage component.

ObjectiveFunctionComponent: Contains input files used to specify the objectives to be minimized by the CalibrationComponent.

RHEComponent: Contains input files used in the radiative heat exchange component.

SWMMComponent: Contains input files used in the Stormwater Management Model (SWMM) component.

TimeSeriesProviderComponent: Contains input files used to prescribe time varying input data to other components.
DOI: 10.4211/hs.47a541695a524f5f98cb106c3ac325a1
title: GRACE-based Standardized Drought Indices over East Africa for 2002-2016

description: This dataset contains standardized drought indexes (SIs) over East Africa derived from total water storage anomaly (TWSA) observations from the Gravity Recovery and Climate Experiment (GRACE) mission.  We obtained the RL05M.1 CRI Filtered Version 2 (Wiese et al., 2016, Watkins et al., 2015) monthly mass grids of the NASA JPL global mascon solution from the JPL’s GRACE TELLUS site.  TWSAs for 40 mascons covering East Africa were extracted from the dataset for May, 2002 through August, 2016.  Observations collected between the 10th and 20th day of the month were retained as the SI dataset.  The resulting SI dataset did not contain data for several months due to missing observations in the global mascon solution dataset or because the observation for the month was not between the 10th and 20th day of the month.  The missing values were interpolated and the final SI dataset contains a TWSA value for each mascon for each month from May, 2002 through August, 2016.  1-month, 3-month, and 6-month standardized drought indexes were calculated following the nonparametric approach described by Farahman and AghaKouchak (2015).  This methodology derives the SI using the empirical Gringorten plotting position (Gringorten, 1963).

The SI dataset contains the following fields:
•	ID: mascon ID assigned by NASA JPL
•	Year: year of the SI
•	Month: month of the SI
•	SI1Mo: one-month SI
•	SI3Mo: three-month SI
•	SI6Mo: six-month SI

This dataset was created on April 20, 2017.  Figures mapping the drought indices by year are presented with the dataset.

Farahmand, A., & AghaKouchak, A. (2015). A generalized framework for deriving nonparametric standardized drought indicators. Advances in Water Resources, 76, 140–145. https://doi.org/10.1016/j.advwatres.2014.11.012
Gringorten, I. I. (1963). A plotting rule for extreme probability paper. Journal of Geophysical Research, 68(3), 813–814. https://doi.org/10.1029/JZ068i003p00813
Watkins, M. M., Wiese, D. N., Yuan, D.-N., Boening, C., & Landerer, F. W. (2015). Improved methods for observing Earth’s time variable mass distribution with GRACE using spherical cap mascons: Improved Gravity Observations from GRACE. Journal of Geophysical Research: Solid Earth, 120(4), 2648–2671. https://doi.org/10.1002/2014JB011547
D. N. Wiese, D.-N. Yuan, C. Boening, F. W. Landerer, M. M. Watkins. 2016. JPL GRACE Mascon Ocean, Ice, and Hydrology Equivalent Water Height RL05M.1 CRI Filtered Version 2. Ver. 2. PO.DAAC, USA. Dataset accessed [2017-02-07] at http://dx.doi.org/10.5067/TEMSC-2LCR5.