cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4211/hs.cdeba87d39d948f6bdc91aefec6d1a1a
title: Data For Integrated Water Management Under Different Water Rights Institutions and Population Patterns: Methodology and Application

description: This HYDROSHARE link contains the data used for the research entitled: "Integrated Water Management Under Different Water Rights Institutions and Population Patterns: Methodology and Application". In this article, we develop a methodology to evaluate how population location under alternative water institutions and climate scenarios impacts water demands, shortages, and derived economic values. We apply this methodology to the South Platte River Basin (SPRB) in Northeastern Colorado under three scenarios with ~1,800 simulations. Results suggest that while water rights institutions have a negligible impact on total volumetric shortages relative to climate change, they have substantial distributional and economic implications. Results also suggest that continuous population growth in upstream cities yields the lowest water shortages if per capita use decreases with urbanization. However, if we assume that per capita demands do not decrease with population density, an equal distribution of population to upstream and downstream regions yields the lowest water shortage and highest economic value. These findings indicate the need that planning efforts must account for return flows and development patterns throughout a watershed in order to reduce water shortages and promote economic prosperity. Questions should be directed to "ahmed.gharib24@alumni.colostate.edu".
DOI: 10.4211/hs.c33ce80f5ae44fe6ab2e5dd3c128eb0b
title: Effective Precipitation Dataset for the Irrigated Croplands of the Western United States from 2000 to 2020

description: This repository hosts the monthly effective precipitation datasets for the irrigated croplands of the Western United States at 2 km spatial resolution from 2000 to 2020.

Related article: Hasan, M. F., Smith, R. G., Majumdar, S., Huntington, J. L., Alves Meira Neto, A., & Minor, B. A. (2025). Satellite data and physics-constrained machine learning for estimating effective precipitation in the Western United States and application for monitoring groundwater irrigation. Agricultural Water Management, 319, 109821. https://doi.org/10.1016/j.agwat.2025.109821

GitHub repo: https://github.com/mdfahimhasan/WestUS_Peff
DOI: 10.4211/hs.c9614e389e324b7ba92d5c33247504a1
title: Immersive Modeling of Water Banking Elicits Local Knowledge to Get More Water to Great Salt Lake

description: The purpose of this immersive online collaborative model is to give collaborators the opportunity to explore, pick at, and possibly improve water banking strategies to get more water to the declining Great Salt Lake (GSL). There are five roles in this immersive model: three agricultural users, one urban user, and the bank. During a model session, collaborators immerse in and personify water user roles for a water bank in Cache Valley, UT (collaborators often play roles different than themselves).  Each collaborator articulates a strategy for their user to consume and bank water. Over the course of a model session, collaborators can adapt their strategies in response to their available water, others’ choices, and the real-time discussion of choices. Through the model sessions and discussions, we want to learn:

i. Why do people decide to consume, conserve, bank, and deliver water within the immersive modeling environments?
ii. Which new insights do participants take away from a model session?
iii. Which improvements do they suggest in modeling and in implementation?
iv. How can an immersive online collaborative modeling approach support the adoption of water banking including delivering water to GSL?

Till May 2025, 29 farmers, ranchers, practitioners, and experts participated in 9 sessions. Each collaborator participated in only one session.
This resource shares the final version of the immersive model, collaborators entries into the model in each session, and notes from the discussion.
Contents of this resource:
1) CacheValleyWaterBank.xlsx – Final version of the model file in Excel. Download, move into Google Drive, invite people to join, and follow the remaining instructions on the first worksheet named “Directions.”
2) ImmersiveModelingWaterBankingGSL.pdf – A 2 page summary of study containing background, key results, and new strategies to get more water to Great Salt Lake.
3) Radme.md- A markdown document which contains background on the model, and instructions on how to guide an immersive modeling activity.
4) Masuscript.pdf – A preprint of the corresponding paper that is presently under peer review in the journal Water Resources Research.

Folders
5) ModelFilesandNotes – Folder containing the completed Excel model file and notes taken for each modeling session. The file Result.xlsx organizes and summarizes into themes notes taken during model session.
6) FiguresCode – Folder containing the subfolders to replicate the figures and results in the study. The file Instructions_to_replicate_results.docx provides instructions to replicate the figures in the study.
7) IRB - documents required to share with potential collaborators that were required by Utah State University's Institutional Review Board (IRB).
DOI: 10.4211/hs.5d76f60e040f479d88c677dbdf155c4c
title: Morphology of brine-seawater interface and spatial distribution of submarine groundwater discharge windows in the muddy coast

description: Electrical survey (ERT, CRP), multibeam sonar survey, and the sediments parameters were conducted offshore of the Laizhou Bay, China.

The three files attached below contains the ERT/CRP/multibeam sonar survey data and sediments types and parameters in the beach and neritic zone aquifer system in the south bank of Laizhou Bay.
1) Electrical survey raw data recording.
2) Multibeam sonar survey data.
3) Sediments types and parameters in the beach and neritic zone aquifer system in the south bank of Laizhou Bay.
DOI: 10.4211/hs.2128fa0d406347dfa3fce7ed7ecb5b60
title: Morphology of brine-seawater interface and spatial distribution of submarine groundwater discharge windows in the muddy coast

description: Electrical survey (ERT, CRP), multibeam sonar survey, and the sediments parameters were conducted offshore of the Laizhou Bay, China.

The three files attached below contains the ERT/CRP/multibeam sonar survey data and sediments types and parameters in the beach and neritic zone aquifer system in the south bank of Laizhou Bay.
1) Electrical survey raw data recording.
2) Multibeam sonar survey data.
3) Sediments types and parameters in the beach and neritic zone aquifer system in the south bank of Laizhou Bay.
DOI: 10.4211/hs.a3bf484a94f04d5caa5f5a4fc5225e9f
title: Peru Watershed Data for the Arequipa Region

description: Surface water quality has been monitored in southern Peru for over a century, but the information is only available from various organizations with considerable delay after official requests. A substantial portion of the data have not been quality assured and were available in difficult-to-access formats such as scanned PDF documents, which made it difficult to evaluate water quality trends. In this project, we gathered all available surface water quality information from five watersheds in the Arequipa Region of southern Peru: Camaná, Chili, Ocoña, Tambo, and Yauca. The effort required entry of more than 130 thousand records of general chemistry, nutrients, and parameters, metals, organic compounds, and biological taxa from 276 stations. The water quality records span the years 2012 to 2021 for most data, but Chili does include data starting from 1905. This paper describes how the water quality data were assimilated and provides one master Excel database so that the surface water quality data can be used for research and decision making.
DOI: 10.4211/hs.1347210139a945048a1a3ecd93f81dd2
title: Dry Lake Transect Snow Depth 2023

description: In the winter and spring of 2023, seven transects were established to collect data at varying positions on the north and south facing slopes as well as the flat terrain. The spatial distribution of these transects were designed to capture changes in snow properties related to aspect and position on slope including the base, middle, and top of slopes. The flat terrain transect was taken by traversing a circle around the SNOTEL station whereas all other transects were ~20 m in length perpendicular to the fall line (i.e., parallel to slope contours). These data were collected approximately once every month from January to May, resulting in 5 survey dates. All transects included GPR data collected with surface-coupled, common offset GPR units pulled over the snow surface. Following the GPR, depth measurements were collected in the track of the GPR at 2-meter spacing. Snow pits were also dug when time allowed to estimate bulk snow density.
DOI: 10.4211/hs.8e87b814ce7541e68f9c2a12a9882c09
title: Dry Lake Observed Density 2023

description: In the winter and spring of 2023, seven transects were established to collect data at varying positions on the north and south facing slopes as well as the flat terrain. The  spatial distribution of these transects were designed to capture changes in snow properties related to aspect and position on slope including the base, middle, and top of slopes. The flat terrain transect was taken by traversing a circle around the SNOTEL station whereas all other transects were ~20 m in length perpendicular to the fall line (i.e., parallel to slope contours). These data were collected approximately once every month from January to May, resulting in 5 survey dates. All transects included GPR data collected with surface-coupled, common offset GPR units pulled over the snow surface. Following the GPR, depth measurements were collected in the track of the GPR at 2-meter spacing.  Snow pits were also dug when time allowed to estimate bulk snow density.
DOI: 10.4211/hs.b84c4fe4a4d04e77ade1bbae4a0c74f3
title: Dry Lake Ground Penetrating Radar TWT 2023

description: In the winter and spring of 2023, seven transects were established to collect data at varying positions on the north and south facing slopes as well as the flat terrain. The  spatial distribution of these transects were designed to capture changes in snow properties related to aspect and position on slope including the base, middle, and top of slopes. The flat terrain transect was taken by traversing a circle around the SNOTEL station whereas all other transects were ~20 m in length perpendicular to the fall line (i.e., parallel to slope contours). These data were collected approximately once every month from January to May, resulting in 5 survey dates. All transects included GPR data collected with surface-coupled, common offset GPR units pulled over the snow surface. Following the GPR, depth measurements were collected in the track of the GPR at 2-meter spacing.  Snow pits were also dug when time allowed to estimate bulk snow density.
DOI: 10.4211/hs.56e0ac25249d4451845a843eb3154954
title: Alluvial River Width Variability

description: Data compilations of bankfull downstream hydraulic geometry for alluvial rivers, lidar derived high-resolution spatial series of bankfull width for 67 sites, and hydrograph metrics for sites with USGS hydrographs. This compilation is composed of three datasets: (1) a compilation of alluvial river geometry at bankfull for a variety of hydraulic attributes; (2) x, y, and z coordinates of channel bank lines for a selection of sites and their associated river widths derived from high-resolution lidar topography; and (3) statistics describing the hydrographs for a subset of the larger compilation. These data are divided into two primary sets, the larger compilation and a smaller set of sites where the bankfull width was derived from lidar topography. For the high-resolution dataset, the data are available as the coordinates of the bank lines, spatial series of distance downstream and bankfull width, and the spatial series filtered for quality.
DOI: 10.4211/hs.e631d6807c464f52b700cd5d9e4fbb43
title: Stable Silicon Isotope Fractionation Reflects the Routing of Water Through a Mesoscale Hillslope

description: This resource provides accompanying discharge and hydrologic data (silicon, sodium, silicon stable isotopes, and discharge and irrigation fluxes) presented in 'Stable Silicon Isotope Fractionation Reflects the Routing of Water Through a Mesoscale Hillslope', Earth and Planetary Letters, https://doi.org/10.1016/j.epsl.2024.119098 
This dataset was collected at the Landscape Evolution Observatory (LEO) in Tucson, Arizona from 2022-2023. Discharge chemistry and flux are reported for each of the three LEO hillslopes.

Files are provided in ".csv" format.
DOI: 10.4211/hs.12bfe992364e4a8cb57995bbf0a30e14
title: EXO2 Control Level 1 Water Quality Data at Provo River near Woodland 2021-2023

description: This dataset contains quality control level 1 (QC1) data for all of the variables measured by the EXO2 at Provo River near Woodland for the time period 2021-2023. The file contains QC1 data for water temperature, specific conductance, pH, dissolved oxygen, turbidity, chlorophyll A, blue green algae, and fDOM. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors.
DOI: 10.4211/hs.ee6c09de183f40b6941374ecba52048c
title: Spatial and Temporal Bayesian Hierarchical Model Over Large Domains with Application to Holocene Sea Surface Temperature Reconstruction in the Equatorial Pacific [Dataset]

description: This dataset is used as input for implementing a space-time Bayesian hierarchical model (BHM) to reconstruct annual Sea Surface Temperature (SST) during the Holocene over a large domain based on SST at limited proxy locations in the equatorial (10°N-10°S) Pacific. The dataset consists of 2° gridded annual mean SST between 1854 and 2014, the paleo proxy SST data from 28 locations, locations of spatial knots, and the location of points used to calibrate the model.
DOI: 10.4211/hs.7346a1e37bb04090bf8d8c1f5a4e2a4b
title: Gallatin County Groundwater Nitrate and Water Levels

description: Gallatin County, Montana has been experiencing rapid residential development with extensive reliance on onsite (septic) wastewater systems. Groundwater in the alluvial valley of the county surrounding the Gallatin River and tributaries is relatively shallow and vulnerable to increasing concentrations of nitrate and potentially other contaminants from anthropogenic sources. This data resource includes groundwater nitrate concentrations from three different sources combined and made publicly available for the first time. The resource includes tabulated nitrate concentration point data as well as a geospatial component including the mapped concentrations and spatially interpolated nitrate concentrations. The resource also includes static water levels measured at the time of new well drilling and spatially interpolated depth to groundwater based on those data. Groundwater nitrate data continues to become available through new testing and curation of past records, so parallel future data resources will include more information.
The purpose of the spatially interpolated nitrate concentration map is to identify locations where nitrate concentrations are elevated over a relatively continuous area, where multiple proximal sample locations show concentrations above 3 mg/L. Nitrate concentrations can be highly variable across space and depth within aquifers. The identified areas are not the only places in the Gallatin Valley where nitrate concentrations are above 3 mg/L, nor are all groundwaters within the designated areas above 3 mg/L. These results are a simplified summary of nitrate data compiled as of July 25th, 2024 and this analysis will continue to be refined over time.
DOI: 10.4211/hs.d0c0122256244124acaf8e46a1f4b3a6
title: Distinguishing hydraulically-distinct floodplain types from high resolution topography with implications for broad-scale flood routing (data)

description: Floodplains can have a significant impact on the routing of flood waves across the landscape, yet their representation in broad-scale water resource and flood prediction models are limited. To identify hydraulically-relevant floodplains at scale, we develop a workflow that automates the extraction of reach-averaged morphologic features from high resolution topographic data hypothesized to define a zone within the floodplain that conveys floodwaters distinctly from the surrounding landscape. This zone is identified from departures in hydraulic geometry with stage. Working in the topographically diverse Lake Champlain Basin in Vermont, USA, we apply the workflow to 2,629 reaches and use the extracted features to cluster settings similar in their proposed ability to route floodwaters.   In total we identified eight clusters of reach types, two that were pre-sorted and largely lack a floodplain, and six that reflect variability in floodplain features, which were parsed out from the K-medoids clustering analysis. Clusters of floodplain types had distinct impact on the routing of synthetically-derived hydrographs, evaluated using the  Muskingum-Cunge  routing model. From these clusters we propose a Hydraulic Floodplain Classification, which is comparable to other geographically-defined systems but unique in its focus on the potential of the landscape to influence flood routing. The automated workflow may be repeated in other regions with high resolution topographic datasets, offering an improvement in the functionality of continental to global floodplain mapping efforts. Identification of hydraulically-effective zones has implications for improved watershed management to meet flood resiliency goals, and to improve flood predictions and warnings.
DOI: 10.4211/hs.8b76906c4b604c458fbcb5ea7c8c0be7
title: Rapid inundation mapping using NWM, satellite observations, and a convolutional neural network - Demonstrated on California Atmospheric Rivers 2023

description: This dataset supports the analysis presented in our paper (https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024GL109424) on flood prediction using the Novel Water Model-Convolutional Neural Network (NWM-CNN). Aimed at enhancing flood forecasting and resilience, this collection encompasses a comprehensive compilation of flood events across California during the Atmospheric River events during the water year 2023. Included are NWM-CNN predictions, Sentinel-1 flood observations, and historical flood damage reports for Sacramento County, California, during the significant 2023 atmospheric river event and over the past decades.

The dataset is structured to facilitate a detailed examination of the NWM-CNN model's performance in predicting surface water area with high temporal resolution and accuracy. By integrating satellite imagery with hydrodynamic modeling, the NWM-CNN model represents a significant advancement in flood modeling, offering an effective tool for damage assessment, flood forecasting, and supporting parametric insurance solutions.

Key components of the dataset include:
* NWM-CNN Predictions: Model predictions at a 250m grid cell resolution.
* Sentinel-1 Flood Observations: Satellite-derived flood extents used for comparison against model predictions.
* Flood Damage Reports: Historical records of flood damage within Sacramento County, providing a ground-truth comparison for model efficacy.

Code to analyze this data is available here:
Jonathan Frame. (2024). jmframe/NWM_CNN_california_AR_2023: GRL Paper Proof 1 (1.0.0). Zenodo. https://zenodo.org/records/13153247.  DOI: 10.5281/zenodo.13153247

By making this data publicly available, we aim to contribute to the collective efforts in reducing the impacts of climate disasters through improved access to scientific information and resources.
DOI: 10.4211/hs.605df180d40e47f28ffb8fac29ffec5f
title: Central Lowlands Post-Settlement Alluvium Data

description: Data to accompany: 
Impacts of geographic variability and geologic history on the distribution of post-settlement alluvium (PSA) across the upper Midwest, USA.
Alison M. Anders and Bruce L. Rhoads
Catena CATENA_108939
Accepted for Publication 11 Mar 2025

A shapefile of the watersheds included in a meta-analysis of post-settlement alluvium in the Central Lowlands/Midwest USA is included as a zipped archive. A data table with PSA thickness, landscape, climate and soils data from the watersheds is provided as a text file.
Accelerated floodplain sedimentation related to agricultural development of uplands has produced post-settlement alluvium (PSA) along rivers throughout the upper Midwest, U.S.A. Landscape characteristics in the region vary geographically in relation to differences in geologic history, yet the extent to which this geographic variability influences PSA accumulation remains unexplored. This study uses existing data to assess how non-dimensional PSA thickness varies with landscape characteristics and climate. Geographic variability is associated with three subregions: 1) areas glaciated during the Late Wisconsin Episode (LWE), 2) areas glaciated during Pre-Illinois and Illinois Episodes (PI&IE), and 3) the Paleozoic Plateau (PP), an area where evidence of Quaternary glaciation is highly localized and does not influence geomorphic characteristics of the landscape. These subregions differ significantly in average geomorphic characteristics, including mean watershed slope (WS), mean local relief (LR), fraction of non-contributing area (NCA), pre-settlement drainage density (DD), and mean normalized river steepness (KSN).  Non-dimensional PSA thickness also differs significantly among the subregions, increasing systematically with landscape age; it also is significantly positively correlated with LR, KSN and WS, and significantly negatively correlated with NCA. Non-visibly distinct PSA is present in some LWE watersheds characterized by significantly lower KSN and WS relative to other LWE watersheds in which PSA is visibly distinct. These results indicate that PSA thickness and visibility reflect inherited landscape characteristics, emphasizing the importance of geographic setting, geological history, and geomorphic context for understanding historical river sediment dynamics. Spatial variability in PSA thickness also serves as an indicator of river system sensitivity to human-induced land-use change, which informs river management strategies.
DOI: 10.4211/hs.438b751c1ff84555a36592345fcfa6b7
title: Great Salt Lake Salinity, Climate, and Inflow Data

description: This resource includes a salinity dataset for the Great Salt Lake that was compiled from all publicly available datasets and Great Salt Lake data pertaining to: evaporation, river inflow, and UPRR causeway bridge exchange flows. It also includes data collected during an experiment performed at the Utah Water Research Laboratory used to develop an equation to convert specific conductance to salinity;  derived specifically for Great Salt Lake ion composition and salt concentration. This resource is part of a study "Seasonal Water and Salt Cycling in the Great Salt Lake after Opening the New Causeway Breach" which compiled and analyzed available salinity data and evaluated primary drivers of salinity change at the Great Salt Lake including: evaporation, causeway bridge bi-directional flow exchange, river inflow, and evaporation. The analysis was performed from January 2017 to September 2023.