hydroGOF is an R package that provides S3 functions implementing both statistical and graphical goodness-of-fit measures between observed and simulated values, mainly oriented to be used during the calibration, validation, and application of hydrological models.
Missing values in observed and/or simulated values can be automatically removed before the computations.
Bugs / comments / questions / collaboration of any kind are very welcomed.
Installing the latest stable version from CRAN:
install.packages("hydroGOF")
Alternatively, you can also try the under-development version from Github:
if (!require(devtools)) install.packages("devtools")
library(devtools)
install_github("hzambran/hydroGOF")
If you find an error in some function, or want to report a typo in the documentation, or to request a new feature (and wish it be implemented :) you can do it here
citation("hydroGOF")
To cite hydroGOF in publications use:
Zambrano-Bigiarini, Mauricio (2024). hydroGOF: Goodness-of-fit functions for comparison of simulated and observed hydrological time series. R package version 0.5-4. URL:https://cran.r-project.org/package=hydroGOF. doi:10.5281/zenodo.839854.
A BibTeX entry for LaTeX users is
@Manual{hydroGOF,
title = {hydroGOF: Goodness-of-fit functions for comparison of simulated and observed hydrological time series},
author = {Zambrano-Bigiarini, Mauricio},
note = {R package version 0.5-4},
year = {2024}, url = {https://cran.r-project.org/package=hydroGOF},
doi = {10.5281/zenodo.839854},
}
Here you can find an introductory vignette illustrating the use of several hydroGOF functions.
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R: a statistical environment for hydrological analysis (EGU-2010) abstract, poster.
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Comparing Goodness-of-fit Measures for Calibration of Models Focused on Extreme Events (EGU-2012) abstract, poster.
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Using R for analysing spatio-temporal datasets: a satellite-based precipitation case study (EGU-2017) abstract, poster.