Collaboration is central to CIROH (https://ciroh.ua.edu/). Advancing the knowledge needed to support research to operations in hydrology depends on collaboration around model and data sharing. It requires open data supporting the integration of information from multiple sources; easy to use, generally accessible, shareable computing; and working together as a team and community. The CUAHSI HydroShare platform was developed to advance water research by enabling communities of researchers to more easily and freely share digital products resulting from their research, not just the scientific publications summarizing a study, but the data, models and workflows used to produce the results, consistent with Findable, Accessible, Interoperable, and Reusable (FAIR) principles of present-day research. HydroShare supports and enables private (e.g., social science) and open data sharing, transparent workflows, and computational reproducibility, thereby improving reliability and trust in research findings. These are crucial as research is transferred into operations.

The goal of this project is to enhance the performance, reliability, usability, and scalability of HydroShare’s linkages with cloud storage and computational systems to fulfill CIROH’s community collaboration and linked computing needs and enable CIROH researchers to easily integrate and analyze national scale datasets required for their research using high-performance and cloud computing systems.

The objectives are to (1) enhance community data access; (2) establish interoperability with scalable computing; (3) demonstrate computational reproducibility; and (4) establish and grow a CIROH Community on HydroShare. Work under objective (1) will use community input to identify, prioritize, and establish easy to use access to multiple high-value community datasets. Work under objective (2) will establish or extend interfaces to high performance computing, leveraging tools for model input preparation such as the CUAHSI Domain Subsetter and I-GUIDE (the Institute for Geospatial Understanding through an enhanced Discovery Environment, https://iguide.illinois.edu). Work under objective (3) will establish and document CIROH community best practices for enhancing the reproducibility of high-performance computing and analysis workflows so that CIROH modeling workflows can be accessed, re-executed, and analyzed by multiple researchers. Work under objective (4) will establish a CIROH “Community” within the HydroShare repository to support collaboration around and sharing of CIROH research products.

Forecasting operations will benefit from the transparency of research products hosted in HydroShare and linked to computing platforms for reproducibility and evaluation. Linking publications, data, and code (often in GitHub), with methods and findings that are well documented and tested will support their evaluation by the National Water Center for operational adoption.

This project runs 6/1/2023 to 5/31/2025.

Groundwater wells are critical infrastructure that enable the monitoring, extraction, and use of groundwater, which has important implications for the environment, water security, and economic development. Despite the importance of wells, a unified database collecting and standardizing information on the characteristics and locations of these wells across the United States has been lacking. To bridge this gap, we have created a comprehensive database of groundwater well records collected from state and federal agencies, which we call the United States Groundwater Well Database (USGWD). Presented in both tabular form and as vector points, the USGWD comprises over 14.2 million well records with attributes such as well purpose, location, depth, and capacity for wells constructed as far back as 1763 to 2023. Rigorous cross-verification steps have been applied to ensure the accuracy of the data. The USGWD stands as a valuable tool for improving our understanding of how groundwater is accessed and managed across various regions and sectors within the United States.

Here we present a geospatial dataset representing local- and regional-scale aquifer system boundaries, defined on the basis of an extensive literature review and published in GebreEgziabher et al. (2022). Nature Communications, 13, 2129, https://www.nature.com/articles/s41467-022-29678-7

The database contains 440 polygons, each representing one study area analyzed in GebreEgziabher et al. (2022). The attribute table associated with the shapefile has two fields (column headings): (1) aquifer system title (Ocala Uplift sub-area of the broader Floridan Aquifer System), and (2) broader aquifer system title (e.g., the Floridan Aquifer System).

• to explore the available data via an interactive app please visit the following URL: https://ucsb.maps.arcgis.com/apps/instant/nearby/index.html?appid=2a238e4ed2434d21b3b53c861a064d8f
• to explore the 3D nature of a dozen aquifer systems please see the following storymap: https://storymaps.arcgis.com/stories/a91f061759e64e44af38daf6cefa4259

Researchers across the country and around the world expend tremendous resources to gather and analyze vast stores of data and populate models to better understand the process they are studying. Each of those researchers has limited money, time, computational capacity, data storage, and ability to put that data to productive use. What if they could combine their efforts to make collaboration easier? What if those collected data sets and processed model outputs could be used collaboratively to help advance knowledge beyond their original purpose? It is these questions that are motivating the movement towards open data, better data management and collaboration and sharing in the use of data and models. In short, researchers are relying more on teamwork to tackle the big problems of the day. This presentation will describe the HydroShare web based hydrologic information system operated by the Consortium of Universities for the Advancement of Hydrologic Science Inc. (CUAHSI) that is available for use as a service to the hydrology community. HydroShare includes a repository for users to share and publish data and models in a variety of formats, and to make this information available in a citable, shareable, and discoverable manner. HydroShare also includes tools (web apps) that can act on content in HydroShare, providing users with a gateway to high performance computing and computing in the cloud. HydroShare has components that support: (1) resource storage, (2) resource exploration, and (3) web apps for actions on resources. The HydroShare data discovery, sharing and publishing functions as well as HydroShare web apps provide the capability to analyze data and execute models completely in the cloud, overcoming desktop platform limitations. We will discuss how these developments can be used to support collaborative research and modeling in Hydrology, where being web based is of value as collaborators can all have access to the same functionality regardless of their computer. We will illustrate the use of HydroShare for collecting and making accessible to the community data from the US National Water Model and 2017 Atlantic Hurricanes Harvey, Irma and Maria that had significant impacts on parts of the US and islands in the Caribbean. HydroShare is being used to assemble, document and archive hydrologic data from these events to support research to improve our understanding of and capability to prepare for and respond to such extreme events in the future.

Presentation at 2018 AWRA Spring Specialty Conference: Geographic Information Systems (GIS) and Water Resources X, Orlando, Florida, April 23-25, http://awra.org/meetings/Orlando2018/.

In the past several decades, field studies have shown that woody plants can access substantial volumes of water from the pores and fractures of bedrock. If, like soil moisture, rock moisture serves as an important source of plant-available water, then conceptual paradigms regarding water and carbon cycling may need to be revised to incorporate bedrock properties and processes. Here we present a lower-bound estimate of the contribution of bedrock water storage to transpiration across the continental United States using distributed, publicly available datasets. Temporal and spatial patterns of bedrock water use across the continental United States indicate that woody plants extensively and routinely access rock moisture for transpiration across diverse climates and biomes. Bedrock water access is not confined to extreme drought conditions. On an annual basis in California, the volumes of bedrock water transpiration exceed the volumes of water stored in human-made reservoirs, and woody vegetation that accesses bedrock water accounts for over 50 per cent of the aboveground carbon stocks in the state. Our findings indicate that, like soil moisture, rock moisture is a critical component of terrestrial water and carbon cycling.

CODE AVAILABLE ON GITHUB: https://github.com/erica-mccormick/widespread-bedrock-water-use FOR MORE INFORMATION, SEE WEBPAGE: https://erica-mccormick.github.io/widespread-bedrock-water-use/

HydroShare is the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI)'s web based hydrologic information system for users to share and publish data and models in a variety of flexible formats, and to make this information available in a citable, shareable and discoverable manner. It enables users to collaborate and work as teams in a web based collaborative environment, thereby enhancing research, education and application of hydrologic knowledge. Hydroshare includes tools (web apps) that can act on content in HydroShare providing users with a gateway to computing and analysis. HydroShare is being developed by a CUAHSI team supported by National Science Foundation awards ACI-1148453, ACI-1148090, EAR-1338606, OAC-1664018, OAC-1664061, OAC-1664119.

This document is adapted from the iUTAH Research Data Policy (Horsburgh and Jones, 2017), which was adopted by a large group of collaborative researchers in Utah working on an NSF-funded research project. It is offered here for potential general use in defining research products and data sharing workflows. This document is intended to be used as an example from which specific data policies, timing, and best practices for data sharing can be defined and adopted for research projects like the Critical Zone Collaborative Network Thematic Cluster projects. Revised by Clara Cogswell, Shannon Syrstad, Jeff Horsburgh 2/17/2022

This collection aggregates educational resources for instructors teaching hydrology, water resources, and related fields. Entries in this collection are owned and managed by the creators of the items within this collection - this entry serves to provide a single location to organize these files.

Attribution of content should be to the authors who have contributed in the 'collection contents', not to this HydroShare entry.

Scientific and management challenges in the water domain require synthesis of diverse data. Many data analysis tasks are difficult because datasets are large and complex; standard data formats are not always agreed upon or mapped to efficient structures for analysis; scientists may lack training for tackling large and complex datasets; and it can be difficult to share, collaborate around, and reproduce scientific work. Overcoming barriers to accessing, organizing, and preparing datasets for analyses can transform the way water scientists work. Building on the HydroShare repository’s cyberinfrastructure, we have advanced two Python packages that make data loading, organization, and curation for analysis easier, reducing time spent in choosing appropriate data structures and writing code to ingest data. These packages enable automated retrieval of data from HydroShare and the USGS’s National Water Information System (NWIS) (i.e., a Python equivalent of USGS’ R dataRetrieval package), loading data into performant structures that integrate with existing visualization, analysis, and data science capabilities available in Python, and writing analysis results back to HydroShare for sharing and publication. While these Python packages can be installed for use within any Python environment, we will demonstrate how the technical burden for scientists associated with creating a computational environment for executing analyses can be reduced and how sharing and reproducibility of analyses can be enhanced through the use of these packages within CUAHSI’s HydroShare-linked JupyterHub server.

This HydroShare resource includes all of the materials presented in a workshop at the 2023 CUAHSI Biennial Colloquium.

A collection of photos of the HydroShare team at various meetings, as well as photo's used on web pages.

Poster for AGU Fall Meeting, December 11, 2023
https://agu.confex.com/agu/fm23/meetingapp.cgi/Paper/1336263

HydroShare (http://www.hydroshare.org) is a web-based repository and hydrologic information system operated by the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) that enables users to share, collaborate around, and publish data, models, scripts, and applications associated with water related research to meet Findable, Accessible, Interoperable, and Reusable (FAIR) open data mandates. The HydroShare repository also links with connected computational systems, enabling users to reproducibly run models and analyses and share documented workflows. This presentation will overview the capabilities and best practices developed for collaboration and sharing of data and other research products along with the use of HydroShare and linked computing. It will focus on successes and challenges in engaging scholars, researchers, and practitioners as individuals and as communities, including lessons learned in sharing data across large scientific communities such as the Critical Zone Collaborative Network. It will also include collaboration functions being developed for the Institute for Geospatial Understanding through an Integrative Discovery Environment (I-GUIDE) and Cooperative Institute for Research to Operations in Hydrology (CIROH), where challenges associated with large scale input/output data preparation, staging, and sub setting along with execution of large-scale models and data are faced.

Presentation given to CUAHSI Informatics Conference, July 26, 2017.

HydroShare is an online, collaboration system for sharing of hydrologic data, analytical tools, and models. It supports the sharing of and collaboration around “resources” which are defined by standardized content types for data formats and models commonly used in hydrology. With HydroShare you can: Share your data and models with colleagues; Manage who has access to the content that you share; Share, access, visualize and manipulate a broad set of hydrologic data types and models; Use the web services application programming interface (API) to program automated and client access; Publish data and models and obtain a citable digital object identifier (DOI); Aggregate your resources into collections; Discover and access data and models published by others; Use web apps to visualize, analyze and run models on data in HydroShare. HydroShare supports web apps to act on resources for cloud (server) based visualization and analysis, including large scale geographic and digital elevation model analysis at the CyberGIS center at the National Center for Supercomputing Applications (NCSA) and capability to execute hydrology models (e.g. SWAT and RHESSys models) and connect to geoscience modeling communities (e.g. Landlab). A pending proposal for the next phase of HydroShare development would extend the capabilities of HydroShare to enhance support for model hypothesis testing using the Structure for Unifying Multiple Modeling Alternatives (SUMMA) approach, advance collaboration capability, integrate with 3rd party consumer cloud storage systems and establish an "App Nursery" to enable community coders to develop web apps linked to HydroShare. This presentation will describe the functionality and architecture of HydroShare comprising: (1) resource storage, (2) resource exploration, and (3) actions on resources by web apps. System components are loosely coupled and interact through APIs, which enhances robustness, as components can be upgraded and advanced relatively independently. The full power of this paradigm is the extensibility it supports, in that anybody can develop a web app that interacts with resources stored in HydroShare. We welcome discussion of the opportunities this enables for interoperability with other cyberinfrastructure tools, to the benefit of the hydrology and hydroinformatics research communities.

HydroShare is a web-based hydrologic information system operated by the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI). Within HydroShare, users can create and share data and models using a variety of file formats and flexible metadata. HydroShare enables users to formally publish these resources as well as create linkages between published data and model resources and peer reviewed journal publications that describe them. Ability to link published data and models with the papers that describe them is a great step in the direction of scientific reproducibility, but is only a first step. HydroShare supports further transparency in the scientific process by enabling scripting of analytical steps via a RESTful application programming interface (API). Using this API, HydroShare users can develop scripts to read data from HydroShare, perform an analytical step (e.g., data processing or visualization), and then write results back to HydroShare. The script itself can then be shared as part of the published dataset in HydroShare, or it can be shared as a Jupyter Notebook that can be executed within the HydroShare environment. Scripts or Jupyter Notebooks can then be executed by others to reproduce the analysis used by the original authors. In this presentation, we discuss how HydroShare can enable best practices for linking publications with data and models and for promoting reproducibility in environmental analyses through sharing of data, models, and scripts that encode the scientific workflow. The HydroShare system is available at http://www.hydroshare.org. Source code for HydroShare is available at https://github.com/hydroshare.

Material for CIROH Developers Conference Workshop, May 29, 2024.

CIROH research necessitates collaboration, data and model sharing, easy to use, generally accessible, shareable computing, and working together as a team and community. The Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) HydroShare platform enables best (FAIR, Findable, Accessible, Interoperable, and Reusable) practices for data sharing and collaboration and for improving reproducibility and reusability of research outcomes through sharing and publishing both the data and models and analyses that underpin research findings. This workshop provided information on using HydroShare for collaboration and data and model sharing in CIROH, including links between HydroShare and CIROH computing.

This resource contains a set of Jupyter Notebooks that provide Python code examples for using the HydroShare Python Client library (hsclient). The hsclient library enables users to automate most of the functions available via HydroShare's web user interface through Python coding. It enables creation of new resources and editing of existing resources. Edits may include changes to metadata elements and/or content files within resources. A link to the GitHub source code repository for hsclient is provided in the related resources section below.

Presentation given to IAHS Scientific Assembly in Port Elizabeth, July 14, 2017

Researchers around the world expend tremendous resources to gather and analyze vast stores of hydrologic data and use them in a myriad of hydrologic models. The goal of HydroShare is to advance hydrologic science by enabling the scientific community to more easily and freely share products resulting from their research, not just the scientific publication summarizing a study, but also the data and models used to create the scientific publication. HydroShare is a web-based hydrologic information system developed with the goal of sharing, accessing and discovering hydrologic data and models with specific functionality aimed at making collaboration easier and supporting reproducibility, and thus trust in research results. HydroShare has been developed with U.S. National Science Foundation support under the auspices of the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) to support the collaboration and community cyberinfrastructure needs of the hydrology research community. Within HydroShare, we have developed new functionality for creating datasets, describing them with metadata, and sharing them with collaborators. We cast hydrologic datasets and models as “social objects” that can be shared, collaborated around, annotated, published and discovered. In addition to data and model sharing, HydroShare supports web application programs (apps) that can act on data stored in HydroShare, just as software programs on your PC act on your data locally. This can free you from some of the limitations of local computing capacity and challenges in installing and maintaining software on your own PC. HydroShare’s web-based cyberinfrastructure can take work off your desk or laptop computer and onto infrastructure or "cloud" based data and processing servers. This presentation will describe HydroShare’s collaboration functionality that enables both public and private sharing with individual users and collaborative user groups, and makes it easier for collaborators to iterate on shared datasets and models, creating multiple versions along the way, and publishing them with a permanent landing page, metadata description, and citable Digital Object Identifier (DOI) when the work is complete. This presentation will also describe the web app architecture that supports interoperability with third party servers functioning as application engines for analysis and processing of big hydrologic datasets.

This dataset consists of water table elevation estimates for the High Plains (Ogallala) Aquifer from 1935 to 2016, updated in 2017 using methods described in the following paper:

Haacker, E.M., Kendall, A.D. and Hyndman, D.W., 2016. Water level declines in the High Plains Aquifer: Predevelopment to resource senescence. Groundwater, 54(2), pp.231-242.

The dataset also includes derived aquifer boundaries and aquifer base elevation, which can be used to derive an estimate of saturated thickness. In addition, county-level information for average water tables, water in storage (saturated thickness x area x specific yield), and variance is included in an Excel file. Please see the ReadMe tab in the Excel file for more information.

How do you manage, track, and share hydrologic data and models within your research group? Do you find it difficult to keep track of who has access to which data and who has the most recent version of a dataset or research product? Do you sometimes find it difficult to share data and models and collaborate with colleagues outside your home institution? Would it be easier if you had a simple way to share and collaborate around hydrologic datasets and models? HydroShare is a new, web-based system for sharing hydrologic data and models with specific functionality aimed at making collaboration easier. Within HydroShare, we have developed new functionality for creating datasets, describing them with metadata, and sharing them with collaborators. In HydroShare we cast hydrologic datasets and models as “social objects” that can be published, collaborated around, annotated, discovered, and accessed. In this presentation, we will discuss and demonstrate the collaborative and social features of HydroShare and how it can enable new, collaborative workflows for you, your research group, and your collaborators across institutions. HydroShare’s access control and sharing functionality enable both public and private sharing with individual users and collaborative user groups, giving you flexibility over who can access data and at what point in the research process. HydroShare can make it easier for collaborators to iterate on shared datasets and models, creating multiple versions along the way, and publishing them with a permanent landing page, metadata description, and citable Digital Object Identifier (DOI). Functionality for creating and sharing resources within collaborative groups can also make it easier to overcome barriers such as institutional firewalls that can make collaboration around large datasets difficult. Functionality for commenting on and rating resources supports community collaboration and quality evaluation of resources in HydroShare.

This presentation was delivered as part of a Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) Cyberseminar in June 2016. Cyberseminars are recorded, and archived recordings are available via the CUAHSI website at http://www.cuahsi.org.

This app is designed to run on Tethys Platform and helps support CUAHSI's HydroShare project. Its purpose is to allow HydroShare users to quickly preview hydrologic geospatial content stored in HydroShare resources.