Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 28, issue 22
Articles | Volume 28, issue 22
https://doi.org/10.5194/hess-28-5049-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-5049-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 28, issue 22
Research article
 | 
26 Nov 2024
Research article |  | 26 Nov 2024

Drivers of global irrigation expansion: the role of discrete global grid choice

Sophie Wagner, Fabian Stenzel, Tobias Krueger, and Jana de Wiljes

Supplement

https://doi.org/10.5194/hess-28-5049-2024-supplement

Data sets

SophieWag/isea3h_irrigation: Update (Version v2) Sophie Wagner https://doi.org/10.5281/zenodo.12542249

Model code and software

ggpubr: ggplot2 Based Publication Ready Plots, R package version 0.6.0 A. Kassambara https://CRAN.R-project.org/package=ggpubr

RColorBrewer: ColorBrewer Palettes, R package version 1.1-3 E. Neuwirth https://CRAN.R-project.org/package=RColorBrewer

scales: Scale Functions for Visualization, R package version 1.3.0 H. Wickham et al. https://CRAN.R-project.org/package=scales

data.table: Extension of 'data.frame', R package version 1.16.0 T. Barrett et al. https://CRAN.R-project.org/package=data.table

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Short summary
Statistical models that explain global irrigation rely on location-referenced data. Traditionally, a system based on longitude and latitude lines is chosen. However, this introduces bias to the analysis due to the Earth's curvature. We propose using a system based on hexagonal grid cells that allows for distortion-free representation of the data. We show that this increases the model's accuracy by 28 % and identify biophysical and socioeconomic drivers of historical global irrigation expansion.
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