Systems Insights from Generation of Hydroclimatic Timeseries
Calibrate GR4J rainfall runoff model parameters
Converts "old" reference climate data format (<V1.2) to "new" format w...
Create foreSIGHT reference climate object from time information and cl...
Creates exposure space of hydroclimatic targets for generation of scen...
Example perturbed stochastic climates for Scott Creek.
modSimulator
Calculates the average value of a non-rainfall time series on dry-days
Calculates the average value of a non-rainfall time series on wet-days
Calculates the correlation between two time series
Calculates the coefficient of variation (sdev/mean) value of a non-rai...
Calculates the coefficient of variation (sdev/mean) value of a non-rai...
Plots the location of points in a two-dimensional exposure space
Plots the differences in performance metrics from two system options
Calculates the inter-quantile range
Calculates seasonality ratio
Calculates total of time series
Calculates the lag-1 autocorrelation for wet days
Calculates the day of year corresponding to the wettest 6 months
Calculates the ratio of wet season to dry season rainfall, based on we...
Produces time series of hydroclimatic variables for an exposure space.
Produces a summary object containing the metadata of a full simulation
System model wrapper GR4J
modCalibrator
A function to calculate difference performance from simulated tank beh...
Calculates a quantile value
Calculates the number of days above a threshold (often used for temper...
Multi-site rainfall observations in the Barossa Valley used in example...
Draws a boxplot with the whiskers at specified probability limits
Calculates the attributes of the hydroclimate time series
Calculates system metrics for and observed and baseline stochastic cli...
foreSIGHT: A package for Systems Insights from Generation of Hydroclim...
Calculates average of time series
Calculates average dry spell duration (below threshold)
Calculates the average dwell time, i.e. average time for below median ...
Calculates average wet spell duration (below threshold)
Calculates the lag-1 autocorrelation
Calculates the coefficient of variation (mead/sd)
Calculates average rainfall on wet days (above threshold)
Calculates the number of frost days
Calculates maximum dry spell duration (below threshold)
Calculates maximum wet spell duration (above threshold)
Calculates normalised quantile (quantile divided by mean)
Calculates number of wet days (above threshold)
Plots changes in attributes for a specified perturbed attribute
Plots performance for one-at-a-time (OAT) perturbations in attributes
Plots a performance space using the system performance and scenarios a...
Plots contours of the number of performance thresholds exceeded in the...
Creates summary plots of the biases in the scenarios
Runs a system model and outputs the system performance
Creates tied attributes which tie seasonal changes in attributes to an...
Post-processing to apply changes in temporal structure of annual preci...
Synthetic sub-daily rainfall data
Observations for demo tank model examples and vignette
Wrapper function for a rain water tank system model
Prints the definition of an attribute
Prints the list of built-in attribute functions
Prints the default optimisation arguments
Prints the names and bounds of the parameters of the stochastic models
Prints the available stochastic model options
Prints the names of the performance metrics of the rain water tank sys...
Writes a sample controlFile.json file
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.