Journal of Open Research Software (Jan 2019)

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

DOI
https://doi.org/10.5334/jors.245
Journal volume & issue
Vol. 7, no. 1

Abstract

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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. Funding statement: 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.

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