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Enabling Collaborative Numerical Modeling in Earth Sciences using Knowledge Infrastructure: Landlab Notebooks
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|Created:||May 20, 2019 at 10:25 p.m.|
|Last updated:|| Jun 19, 2020 at 10:33 p.m.
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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.
To interactively compute with these Notebooks, please see the ReadMe below.
To develop these Notebooks, go to Github: https://github.com/ChristinaB/pub_bandaragoda_etal_ems or https://zenodo.org/badge/latestdoi/187289993
Resource Level Coverage
Software Instructions: Online and Personal Computer
Online Modeling Instructions
To open interactive Jupyter Notebooks with the CUAHSI JupyterHub server, go to the upper right corner of the resource page and click on 'Open With'. Select CUAHSI JupyterHub. You will be connected to a virtual machine with the software environment required to execute the models.
Notebook 1: Educate by exploring rainfall driven hydrographs with Landlab: Explore_routing_tutorial.ipynb
Notebook 2: Replicate an experiment on a watershed subset within regional Landlab landslide model to explore fire impacts. 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: Replicate_landslide_model_for_fire.ipynb
Notebook 3: Reuse ecohydrology model for exploring climate scenarios. The gridded meteorology forcings are pre-processed in the Notebook in NewMexico_observatory_gridmet.ipynb: Reuse_ecohydrology_observatory.ipynb
Personal Computer Installation Instructions
The notebooks included in this resource require the following Python packages:
To ensure that you have the correct packages and versions, run the following command(s) inside a Python terminal:
$ conda list
$ pip list
Creating a Working Environment
We recommend using Anaconda to create a fresh Python environment with all dependencies installed. After installing Anaconda, simply run the commands below with your desired environment name in place of
conda create -n MY_ENVIRONMENT_NAME --file requirements.txt
activate the environment and start a jupyter server
source activate MY_ENVIRONMENT_NAME
Debugging a Working Environment
Are you getting errors? Here are some suggested steps. If you still have issues, email firstname.lastname@example.org or reach out to us (comment on this resource or see emails in HydroShare profiles) and we will invite you to the HydroShare Slack #landlab channel.
PackagesNotFoundError: The following packages are not available from current channels.
Reduce the number of packages that were not available by running the following command
conda config --append channels conda-forge
Bug: Conda vs.Pip Install
If you get errors for a few packages, remove them from the requirements.txt file until you successfully created the conda environment.
conda create -n MY_ENVIRONMENT_NAME --file requirements.txt
Any packages that didn't get installed during creation of conda environment can be pip installed separately in the newly created conda environment. for example:
pip install hs-restclient==1.3.3
Reproducible Quote of the Day:
"The product of mental labor - science - always stands far below its value, because the labor-time necessary to reproduce it has no relation at all to the labor-time required for its original production." Karl Marx
|The content of this resource is derived from||https://zenodo.org/badge/latestdoi/187289993|
|The content of this resource is derived from||https://github.com/ChristinaB/pub_bandaragoda_etal_ems|
|The content of this resource is derived from||https://www.hydroshare.org/resource/70b977e22af544f8a7e5a803935c329c/|
|This resource is referenced by||Bandaragoda, C. J., A. Castronova, E. Istanbulluoglu, R. Strauch, S. S. Nudurupati, J. Phuong, J. M. Adams, et al. “Enabling Collaborative Numerical Modeling in Earth Sciences Using Knowledge Infrastructure.” Environmental Modelling & Software, April 24, 2019. https://doi.org/10.1016/j.envsoft.2019.03.020.|
|The content of this resource is derived from||https://www.hydroshare.org/resource/609b1201e4ac47d89eff56317af07d12/|
|The content of this resource is derived from||https://www.hydroshare.org/resource/bb9e1cc9e8b0487b99576938029fccb0/|
|This resource updates and replaces a previous version||Bandaragoda, C., A. M. Castronova, J. Phuong, E. Istanbulluoglu, S. S. Nudurupati, R. Strauch, N. Lyons (2022). Enabling Collaborative Numerical Modeling in Earth Sciences using Knowledge Infrastructure: Landlab Notebooks, HydroShare, http://www.hydroshare.org/resource/70b977e22af544f8a7e5a803935c329c|
|This resource has been replaced by a newer version||Bandaragoda, C., A. M. Castronova, J. Phuong, E. Istanbulluoglu, S. S. Nudurupati, R. Strauch, N. Lyons, K. Barnhart (2020). Enabling Collaborative Numerical Modeling in Earth Sciences using Knowledge Infrastructure: Landlab Notebooks, HydroShare, http://www.hydroshare.org/resource/5b964154ebf945848087bdc772cc921e|
This resource was created using funding from the following sources:
|Agency Name||Award Title||Award Number|
|National Science Foundation||Collaborative Research: SI2-SSI: An Interactive Software Infrastructure for Sustaining Collaborative Community Innovation in the Hydrologic Sciences||1148453|
|National Science Foundation||Predicting Climate Change impacts on Shallow Landslide Risk at regional scales||1336725|
|National Science Foundation||Collaborative Research: SI2-SSI: Landlab: A Flexible, Open-Source Modeling Framework for Earth-Surface Dynamics||1450412, 1450409, and 1450338|
|National Science Foundation||Community Facility Support: The Community Surface Dynamics Modeling System (CSDMS)||1831623|
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.
|Madhavi Srinivasan||University of Washington|
|David Tarboton||Utah State University||Utah, US||4357973172||ORCID|
|Greg Tucker||University of Colorado at Boulder;Cooperative Institute for Research in Environmental Sciences;Community Surface Dynamics Modeling System (CSDMS)|
|Jordan Adams||Tulane University||Louisiana, US||6107397582|
|Nicole Gasparini||Tulane University|
|Eric Hutton||CSDMS;University of Colorado|
|Daniel Edward James Hobley||Cardiff University||Wales, GB|