A global hydrologic framework to accelerate scientific discovery

Chris R. Vernon, Mohamad I. Hejazi, Sean W.D. Turner, Yaling Liu, Caleb J. Braun, Xinya Li, Robert P. Link

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

With the ability to simulate historical and future global water availability on a monthly time step at a spatial resolution of 0.5 geographic degree, the Python package Xanthos version 1 provided a solid foundation for continuing advancements in global water dynamics science. The goal of Xanthos version 2 was to build upon previous investments by creating a Python framework where core components of the model (potential evapotranspiration (PET), runoff generation, and river routing) could be interchanged or extended without having to start from scratch. Xanthos 2 utilizes a component-style architecture which enables researchers to quickly incorporate and test cutting-edge research in a stable modeling environment prebuilt with diagnostics. Major advancements for Xanthos 2 were also achieved by the creation of a robust default configuration with a calibration module, hydropower modules, and new PET modules, which are now available to the scientific community.

Original languageEnglish
Article number1
JournalJournal of Open Research Software
Volume7
Issue number1
DOIs
StatePublished - 2019
Externally publishedYes

Funding

This research was supported by the U.S. Department of Energy, Office of Science, as part of research in Multi-Sector Dynamics, Earth and Environmental System Modeling Program. The Pacific Northwest National Laboratory is operated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830. The views and opinions expressed in this paper are those of the authors alone.

FundersFunder number
U.S. Department of Energy
BattelleDE-AC05-76RL01830

    Keywords

    • Global hydrology
    • Hydrologic framework
    • Potential evapotranspiration
    • Python
    • River routing
    • Runoff
    • SciPy
    • Xanthos

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