HydroShare: Sharing Diverse Environmental Data Types and Models as Social Objects with Application to the Hydrology Domain

Horsburgh, Jeffery S.; Morsy, Mohamed M.; Castronova, Anthony M.; Goodall, Jonathan L.; Gan, Tian; Hong, Yi; Stealey, Michael; Tarboton, David G.

doi:10.1111/1752-1688.12363

Cited by 95 publications

(66 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…To publish a reproducible version of this research, we used the HydroShare (www.hydroshare.org) cyberinfrastructure platform, designed for reproducing, reusing, and sharing models (Tarboton et al, 2014;Horsburgh et al, 2016;Morsy et al, 2017). Steps that supported reproducibility included using the HydroShare sharing settings with a workflow that started with Private while data and models were developed, Discoverable while research was being shared with colleagues for review, and Public, once our results were accepted for publication.…”

Section: Reproducibilitymentioning

confidence: 99%

A hydroclimatological approach to predicting regional landslide probability using Landlab

Strauch,

Istanbulluoglu,

Nudurupati

et al. 2018

HydroShare Resources

View full text Add to dashboard Cite

Abstract. We develop a hydroclimatological approach to the modeling of regional shallow landslide initiation that integrates spatial and temporal dimensions of parameter uncertainty to estimate an annual probability of landslide initiation based on Monte Carlo simulations. The physically based model couples the infinite-slope stability model with a steady-state subsurface flow representation and operates in a digital elevation model. Spatially distributed gridded data for soil properties and vegetation classification are used for parameter estimation of probability distributions that characterize model input uncertainty. Hydrologic forcing to the model is through annual maximum daily recharge to subsurface flow obtained from a macroscale hydrologic model. We demonstrate the model in a steep mountainous region in northern Washington, USA, over 2700 km 2 . The influence of soil depth on the probability of landslide initiation is investigated through comparisons among model output produced using three different soil depth scenarios reflecting the uncertainty of soil depth and its potential long-term variability. We found elevation-dependent patterns in probability of landslide initiation that showed the stabilizing effects of forests at low elevations, an increased landslide probability with forest decline at midelevations (1400 to 2400 m), and soil limitation and steep topographic controls at high alpine elevations and in post-glacial landscapes. These dominant controls manifest themselves in a bimodal distribution of spatial annual landslide probability. Model testing with limited observations revealed similarly moderate model confidence for the three hazard maps, suggesting suitable use as relative hazard products. The model is available as a component in Landlab, an open-source, Python-based landscape earth systems modeling environment, and is designed to be easily reproduced utilizing HydroShare cyberinfrastructure.

show abstract

Section: Reproducibilitymentioning

confidence: 99%

A hydroclimatological approach to predicting regional landslide probability using Landlab

Strauch,

Istanbulluoglu,

Nudurupati

et al. 2018

HydroShare Resources

View full text Add to dashboard Cite

show abstract

“…The specific study area of the research was the Rocky The metadata framework was implemented within HydroShare and used to share the model program and model instance resources for the example application. HydroShare, as introduced earlier, is an online system for managing resources adhering to a Resource Data Model (Horsburgh et al, 2015;Tarboton et al, 2014a). The HydroShare architecture organized as shown in Figure 4.7 (Heard et al, 2014) consists of open source components including Django, a web application platform, Mezzanine, a content management system meta-framework, and the Integrated RuleOriented Data System (iRODS), an enterprise storage management middleware (Rajasekar et al, 2010).…”

Section: Experimental Use Casementioning

confidence: 99%

“…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 only the scientific publication summarizing a study, but also the data and models used to create the scientific publication (Horsburgh et al, 2015;Tarboton et al, 2014;Tarboton et al, 2013).…”

Section: Chapter 1: Introductionmentioning

confidence: 99%

“…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 (Horsburgh et al, 2015;Tarboton et al, 2014aTarboton et al, , 2014b. HydroShare is a web-based collaborative system developed with the goal of sharing, accessing, and discovering hydrologic data and models (Tarboton et al, 2014a(Tarboton et al, , 2014b.…”

Section: Introductionmentioning

confidence: 99%

“…One of the key steps in designing HydroShare was defining metadata for different resource types (Horsburgh et al, 2015;Tarboton et al, 2014aTarboton et al, , 2014b. While users can upload any digital content as a "generic resource" within HydroShare, these generic resources only support basic metadata elements defined by the Dublin Core metadata framework that are applicable to any data type.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Cyberinfrastructure to Support Flood Modeling from Catchment to Regional Scales

Morsy

View full text Add to dashboard Cite

Flooding events are projected to increase in frequency and intensity in coming years due to climate change. New tools and approaches are needed to assist decision makers in better understanding and addressing societal impacts due to flooding and how to mitigate these impacts.This research addressed three challenges related to flooding impacts: (i) better understanding how distributed stormwater infrastructure can mitigate flooding in urban catchments, (ii) designing and building spatially-detailed, real-time flood warning systems for emergency management purposes, and (iii) designing and building cyberinfrastructure to support reuse and transparency in both flood modeling and hydrologic modeling more broadly. The goal of this research was to address these challenges by conducting three studies. The second study explored building an automated cloud-based system for forecasting flooded roadway and bridge locations at a regional-scale. Because the study area has very low topographic relief, a two-dimensional (2D), computationally-expensive hydrodynamic model is required. This study demonstrated the ability of using instances in a public cloud with powerful graphical processing units (GPUs) to run a large (average of 4 million nodes) 2D hydrodynamic model in a time frame relevant to real-time emergency management applications. The steps required to build this system were (i) creating an automated workflow for obtaining and processing ii forecast rainfall data, (ii) running the 2D model in the cloud, (iii) using geospatial analysis tools to identify flooded bridges, and (iv) presenting the results online for decision makers. The system automates forecast data access and pre-processing, execution of a high-resolution 2D hydrodynamic model, and map-based visualization of model outputs using Amazon Web Services (AWS).The third study advanced approaches for sharing hydrologic models, such as the models created in this dissertation, through community supported cyberinfrastructure. Sharing models is important for scientific reproducibility, reuse, and fidelity. In this study, the first task was to design a metadata framework for hydrologic models that is flexible and applicable across the wide variety of models used by hydrologists. Then the study demonstrated the utility of this framework for sharing, publishing, and reusing models through an implementation within the HydroShare cyberinfrastructure system.In the first study, the results suggest that rain gardens with 30 cm berm heights and a total area equal to 20% of the impervious surfaces within the watershed should provide sufficient storage to mitigate flooding for rain events up to and including a 10 year return period storm event.The results also suggest approximately 15%, 27%, and 38% of the runoff generated from impervious surfaces should be diverted to the rain gardens to mitigate flooding from 2, 5, and 10 year return period storm events, respectively. Given prior work on the adoption of LID approaches for other watersheds, rain gardens could effectivel...

show abstract

Server‐side workflow execution using data grid technology for reproducible analyses of data‐intensive hydrologic systems

Essawy

Goodall

et al. 2016

Earth and Space Science

Self Cite

View full text Add to dashboard Cite

Many geoscience disciplines utilize complex computational models for advancing understanding and sustainable management of Earth systems. Executing such models and their associated data preprocessing and postprocessing routines can be challenging for a number of reasons including (1) accessing and preprocessing the large volume and variety of data required by the model, (2) postprocessing large data collections generated by the model, and (3) orchestrating data processing tools, each with unique software dependencies, into workflows that can be easily reproduced and reused. To address these challenges, the work reported in this paper leverages the Workflow Structured Object functionality of the Integrated Rule-Oriented Data System and demonstrates how it can be used to access distributed data, encapsulate hydrologic data processing as workflows, and federate with other community-driven cyberinfrastructure systems. The approach is demonstrated for a study investigating the impact of drought on populations in the Carolinas region of the United States. The analysis leverages computational modeling along with data from the Terra Populus project and data management and publication services provided by the Sustainable Environment-Actionable Data project. The work is part of a larger effort under the DataNet Federation Consortium project that aims to demonstrate data and computational interoperability across cyberinfrastructure developed independently by scientific communities.

show abstract

HydroShare: Sharing Diverse Environmental Data Types and Models as Social Objects with Application to the Hydrology Domain

Cited by 95 publications

References 23 publications

A hydroclimatological approach to predicting regional landslide probability using Landlab

A hydroclimatological approach to predicting regional landslide probability using Landlab

Cyberinfrastructure to Support Flood Modeling from Catchment to Regional Scales

Server‐side workflow execution using data grid technology for reproducible analyses of data‐intensive hydrologic systems

Contact Info

Product

Resources

About