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foreSIGHT: Systems Insights from Generation of Hydroclimatic Timeseries

A tool to create hydroclimate scenarios, stress test systems and visualize system performance in scenario-neutral climate change impact assessments. Scenario-neutral approaches 'stress-test' the performance of a modelled system by applying a wide range of plausible hydroclimate conditions (see Brown & Wilby (2012) <doi:10.1029/2012EO410001> and Prudhomme et al. (2010) <doi:10.1016/j.jhydrol.2010.06.043>). These approaches allow the identification of hydroclimatic variables that affect the vulnerability of a system to hydroclimate variation and change. This tool enables the generation of perturbed time series using a range of approaches including simple scaling of observed time series (e.g. Culley et al. (2016) <doi:10.1002/2015WR018253>) and stochastic simulation of perturbed time series via an inverse approach (see Guo et al. (2018) <doi:10.1016/j.jhydrol.2016.03.025>). It incorporates 'Richardson-type' weather generator model configurations documented in Richardson (1981) <doi:10.1029/WR017i001p00182>, Richardson and Wright (1984), as well as latent variable type model configurations documented in Bennett et al. (2018) <doi:10.1016/j.jhydrol.2016.12.043>, Rasmussen (2013) <doi:10.1002/wrcr.20164>, Bennett et al. (2019) <doi:10.5194/hess-23-4783-2019> to generate hydroclimate variables on a daily basis (e.g. precipitation, temperature, potential evapotranspiration) and allows a variety of different hydroclimate variable properties, herein called attributes, to be perturbed. Options are included for the easy integration of existing system models both internally in R and externally for seamless 'stress-testing'. A suite of visualization options for the results of a scenario-neutral analysis (e.g. plotting performance spaces and overlaying climate projection information) are also included. Version 1.0 of this package is described in Bennett et al. (2021) <doi:10.1016/j.envsoft.2021.104999>. As further developments in scenario-neutral approaches occur the tool will be updated to incorporate these advances.

Version: 1.2.0
Depends: R (≥ 3.5.0), GA (≥ 3.0.2)
Imports: ggplot2 (≥ 3.3.0), directlabels, cowplot, stats, graphics, grDevices, utils, moments, jsonlite, progress, rcorpora, scales, viridisLite, fields, rlang, lattice, mvtnorm, Matrix, SoilHyP, cmaes, dfoptim, RGN
LinkingTo: Rcpp
Suggests: knitr (≥ 1.8), rmarkdown (≥ 1.18), testthat, evd
Published: 2023-10-19
DOI: 10.32614/CRAN.package.foreSIGHT
Author: Bree Bennett ORCID iD [aut], Sam Culley ORCID iD [aut], Anjana Devanand ORCID iD [aut], David McInerney ORCID iD [aut, cre], Seth Westra ORCID iD [aut], Danlu Guo ORCID iD [ctb], Holger Maier ORCID iD [ths]
Maintainer: David McInerney <david.mcinerney at adelaide.edu.au>
BugReports: https://github.com/ClimateAnalytics/foreSIGHT/issues
License: GPL-3
NeedsCompilation: yes
Materials: NEWS
CRAN checks: foreSIGHT results

Documentation:

Reference manual: foreSIGHT.pdf
Vignettes: Quick Start Guide: Rainwater Tank Case Study
Detailed Tutorial: Climate 'Stress-Testing' using *fore*SIGHT

Downloads:

Package source: foreSIGHT_1.2.0.tar.gz
Windows binaries: r-devel: foreSIGHT_1.2.0.zip, r-release: foreSIGHT_1.2.0.zip, r-oldrel: foreSIGHT_1.2.0.zip
macOS binaries: r-release (arm64): foreSIGHT_1.2.0.tgz, r-oldrel (arm64): foreSIGHT_1.2.0.tgz, r-release (x86_64): foreSIGHT_1.2.0.tgz, r-oldrel (x86_64): foreSIGHT_1.2.0.tgz
Old sources: foreSIGHT archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=foreSIGHT to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.