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Enabling Collaborative Numerical Modeling in Earth Sciences using Knowledge Infrastructure: Landlab Notebooks


Authors: Christina Bandaragoda · Anthony Michael Castronova · Jimmy Phuong · Erkan Istanbulluoglu · Sai Siddhartha Nudurupati · Ronda Strauch · Nicole Gasparini · Eric Hutton · Greg Tucker · Daniel Hobley · Katherine Barnhart · Jordan Adams
Owners: Christina Bandaragoda · Jimmy Phuong
Resource type:Generic
Created:Aug 07, 2017 at 3:29 p.m.
Last updated: Oct 29, 2018 at 9:41 p.m. by Christina Bandaragoda

Abstract

The ability to test hypotheses about hydrology, geomorphology, and atmospheric processes is invaluable to research in the Earth and planetary sciences. To swiftly develop experiments using community resources is an extraordinary emerging opportunity to accelerate the rate of scientific advancement. Knowledge infrastructure is an intellectual framework to understand how people are creating, sharing, and distributing knowledge -- which has dramatically changed and is continually transformed by Internet technologies. We are actively designing a knowledge infrastructure system for earth surface investigations. In this paper, we illustrate how this infrastructure can be utilized to lower common barriers to reproducing modeling experiments. These barriers include: developing education and training materials for classroom use, publishing research that can be replicated by reviewers and readers, and advancing collaborative research by re-using earth surface models in new locations or in new applications. We outline six critical elements to this infrastructure, 1) design of workflows for ease of use by new users; 2) a community-supported collaborative web platform that supports publishing and privacy; 3) data storage that may be distributed to different locations; 4) a software environment; 5) a personalized cloud-based high performance computing (HPC) platform; and 6) a standardized modeling framework that is growing with open source contributions. Our methodology uses the following tools to meet the above functional requirements. Landlab is an open-source modeling toolkit for building, coupling, and exploring two-dimensional numerical models. The Consortium of Universities Allied for Hydrologic Science (CUAHSI) supports the development and maintenance of a JupyterHub server that provides the software environment for the system. Data storage and web access are provided by HydroShare, an online collaborative environment for sharing data and models. The knowledge infrastructure system accelerates knowledge development by providing a suite of modular and interoperable process components that can be combined to create an integrated model. Online collaboration functions provide multiple levels of sharing and privacy settings, open source license options, and DOI publishing, and cloud access to high-speed processing. This allows students, domain experts, collaborators, researcher, and sponsors to interactively execute and explore shared data and modeling resources. Our system is designed to support the user experiences on the continuum from fully developed modeling applications to prototyping new science tools. We have provided three computational narratives for readers to interact with hands-on, problem-based research demonstrations - these are publicly available Jupyter Notebooks available on HydroShare.

When you open this resource with the CUAHSI JupyterHub server (upper right, click on Open With, Select JupyterHub), you will launch a Welcome Notebook that will connect you to the CyberGIS virtual machine on the ROGER super computer at the University of Illinois, Urbana-Champagne. When you execute (Run Step 1 and Step 2 only) in the Jupyter Notebook cells on the Welcome Notebook, you will download related data and three Notebooks designed to explore hydrologic research problem solving using data and model integration in HydroShare. Skip Step 3 "Welcome" tutorial steps unless you want to explore how to do work and Save back to HydroShare.

The problem: Researchers need a modeling workflow that is flexible for developing their own code, with easy access to distributed datasets, shared on a common platform for coupling multiple models, usable by science colleagues, and with easy publication of data, code, and scientific studies.

The emerging solution: Collaborate with the CUAHSI HydroShare community to use and contribute to water data software and hardware tools, so that you can focus on your science, be efficient with your time and resources, and build on existing research in multiple domains of water science.

Notebook 1: Educate by exploring rainfall driven hydrographs with Landlab
Explore_routing_tutorial.ipynb

Notebook 2: Watershed subset within regional Landlab landslide model to explore fire impacts
Replicate_landslide_model_for_fire.ipynb
The resource was originally derived from a reproducible demonstration of the landslide modeling results from: Strauch, R., Istanbulluoglu, E., Nudurupati, S. S., Bandaragoda, C., Gasparini, N. M., and Tucker, G. E.: (2018) A hydro-climatological approach to predicting regional landslide probability using Landlab, Earth Surf. Dynam. Discuss., https://doi.org/10.5194/esurf-6-49-2018.

Notebook 3: Reuse ecohydrology model for exploring climate scenarios
Reuse_ecohydrology_observatory.ipynb
The gridded meteorology forcings are pre-processed in the Notebook in NewMexico_observatory_gridmet.ipynb.

Subject Keywords

landlab,climate,landslide,jupyterhub,Thunder

How to cite

Bandaragoda, C., A. M. Castronova, J. Phuong, E. Istanbulluoglu, S. S. Nudurupati, R. Strauch, N. Gasparini, E. Hutton, G. Tucker, D. Hobley, K. Barnhart, J. Adams (2018). Enabling Collaborative Numerical Modeling in Earth Sciences using Knowledge Infrastructure: Landlab Notebooks, HydroShare, http://www.hydroshare.org/resource/70b977e22af544f8a7e5a803935c329c

This resource is shared under the Creative Commons Attribution CC BY.

 http://creativecommons.org/licenses/by/4.0/
CC-BY

  • Downloads require agreement to resource rights statement

  • Sharing status:

    • Public Resource  Public
    • Sharable Resource  Shareable

    Coverage

    Spatial:

     Coordinate System/Geographic Projection:  WGS 84 EPSG:4326
     Coordinate Units:  Decimal degrees
    Place/Area Name: Thunder Creek Watershed

    North Latitude
    48.7055°
    East Longitude
    -120.7658°
    South Latitude
    48.4702°
    West Longitude
    -121.3248°

    Content

    Download All Content as Zipped BagIt Archive
    Learn more about the Bagit archive format

    Authors

    The people or organizations that created the intellectual content of the resource.

    Name Organization Address Phone Author Identifiers
    Christina Bandaragoda University of Washington
    Anthony Michael Castronova CUAHSI MA, US 4357970852
    Jimmy Phuong University of Washington Washington, US
    Erkan Istanbulluoglu University of Washington
    Sai Siddhartha Nudurupati University of Washington - Seattle WA, US 4026170098
    Ronda Strauch University of Washington
    Nicole Gasparini Tulane University
    Eric Hutton
    Greg Tucker
    Daniel Hobley
    Katherine Barnhart University of Colorado at Boulder CO, US
    Jordan Adams Tulane University Louisiana, US 6107397582

    Contributors

    People or organizations that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.

    Name Organization Address Phone Author Identifiers
    Erkan Istanbulluoglu University of Washington
    David Tarboton Utah State University Utah, US 4357973172
    Dan Ames Brigham Young University
    Zhiyu (Drew) Li Brigham Young University
    Sources
    Derived From: http://www.hydroshare.org/resource/609b1201e4ac47d89eff56317af07d12
    Relations
    isPartOf: https://www.hydroshare.org/resource/bb9e1cc9e8b0487b99576938029fccb0/
    This resource belongs to the following collections:
    Title Owners Sharing Status My Permission
    Landlab Tutorials GSA 2017 Christina Bandaragoda · Erkan Istanbulluoglu · Greg Tucker · Nicole Gasparini  Private &  Shareable None
    Landlab Tutorials GSA 2017 Jezra Beaulieu  Private &  Shareable None

    Credits

    This resource was created using funding from the following sources:
    Agency Name Award Title Award Number
    CUAHSI
    National Science Foundation

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