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

A newer version of this resource http://www.hydroshare.org/resource/5b964154ebf945848087bdc772cc921e is available that replaces this version.
An older version of this resource http://www.hydroshare.org/resource/70b977e22af544f8a7e5a803935c329c is available.
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Created: May 20, 2019 at 10:25 p.m.
Last updated: Jun 19, 2020 at 10:33 p.m.
DOI: 10.4211/hs.fdc3a06e6ad842abacfa5b896df73a76
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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

Subject Keywords

Resource Level Coverage


Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
Place/Area Name:
Knowledge Infrastructure Case Studies
North Latitude
East Longitude
South Latitude
West Longitude



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:

landlab 1.6.0 geopandas 0.5.0 dask 1.2.0 ogh 0.2.1 matlplotlib 3.0.3 pandas 0.24.2 ffmpeg 4.1.3 hs_restclient 1.3.3

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 MY_ENVIRONMENT_NAME:

conda create -n MY_ENVIRONMENT_NAME --file requirements.txt

activate the environment and start a jupyter server

source activate MY_ENVIRONMENT_NAME jupyter notebook

Debugging a Working Environment

Are you getting errors? Here are some suggested steps. If you still have issues, email help@cuahsi.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.

Bug: PackagesNotFound

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

Additional Metadata

Name Value
appkey MyBinder

Related Resources

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


Funding Agencies

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.

Name Organization Address Phone Author Identifiers
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

How to Cite

Bandaragoda, C., A. M. Castronova, J. Phuong, E. Istanbulluoglu, S. S. Nudurupati, R. Strauch, N. Lyons, K. Barnhart (2019). Enabling Collaborative Numerical Modeling in Earth Sciences using Knowledge Infrastructure: Landlab Notebooks, HydroShare, https://doi.org/10.4211/hs.fdc3a06e6ad842abacfa5b896df73a76

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