Reproducible hydrological modeling with CyberGIS-Jupyter: A case study on summa

Fangzheng Lyu, Dandong Yin, Anand Padmanabhan, Youngdon Choi, Jonathan L. Goodall, Anthony Castronova, David Tarboton, Shaowen Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

CyberGIS-Jupyter is a cyberGIS framework for achieving data-intensive, reproducible, and scalable geospatial analytics using Jupyter Notebook based on advanced cyberinfrastructure. As a cutting-edge hydrological modeling framework, the Structure for Unifying Multiple Modeling Alternative (SUMMA) functions as a unified approach to process‐based modeling. The purpose of this research is to investigate the feasibility of coupling CyberGIS-Jupyter with SUMMA to realize reproducible hydrological modeling. CyberGIS-Jupyter is employed to systematically integrate advanced cyberinfrastructure, including two high-performance computers – Virtual ROGER and XSEDE Comet, data management, and execution and visualization of SUMMA-based modeling. By taking advantage of CyberGIS-Jupyter, users can easily tune different parameters for a SUMMA model and submit computational jobs for executing the model on HPC resources without having to possess in-depth technical knowledge about cyberGIS or cyberinfrastructure. Computational experiments demonstrate that the integration of CyberGIS-Jupyter and SUMMA achieves a high-performance and easy-to-use implementation for reproducible SUMMA-based hydrological modeling.

Original languageEnglish (US)
Title of host publicationProceedings of the Practice and Experience in Advanced Research Computing
Subtitle of host publicationRise of the Machines (Learning), PEARC 2019
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450372275
DOIs
StatePublished - Jul 28 2019
Event2019 Conference on Practice and Experience in Advanced Research Computing: Rise of the Machines (Learning), PEARC 2019 - Chicago, United States
Duration: Jul 28 2019Aug 1 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2019 Conference on Practice and Experience in Advanced Research Computing: Rise of the Machines (Learning), PEARC 2019
CountryUnited States
CityChicago
Period7/28/198/1/19

Keywords

  • CyberGIS-Jupyter
  • Geographic Information Science and Systems (GIS)
  • High-Performance Computing
  • Hydrological Modeling
  • Science Gateway

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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  • Cite this

    Lyu, F., Yin, D., Padmanabhan, A., Choi, Y., Goodall, J. L., Castronova, A., Tarboton, D., & Wang, S. (2019). Reproducible hydrological modeling with CyberGIS-Jupyter: A case study on summa. In Proceedings of the Practice and Experience in Advanced Research Computing: Rise of the Machines (Learning), PEARC 2019 [3333052] (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3332186.3333052