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fuse: an R package implementing the Framework for Understanding Structural Errors

DOI status

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The Framework for Understanding Structural Errors (FUSE) was developed by Clark et al. (2008) and is a state-of-the-art modelling toolbox. It includes 1248 hydrological model structures, amongst which some well established models for rainfall-runoff simulations (i.e. PRMS, SACRAMENTO, TOPMODEL and ARNO/VIC, also defined as parent models). Each model is characterised by a different architecture of the upper and lower soil layers and parameterisation of processes such as: evaporation, vertical percolation, interflow, base flow and surface runoff.

Fuse takes as input rainfall and potential evapotranspiration time series (areal averages over the river catchment area) and returns a simulated time series of river discharges. It can be used to understand the variability of expected hydrological responses based on model structures.

This package is a re-implementation of the framework described in Clark et al. (2008) and based on the Fortran code provided by M. Clark in 2011. The package consists of two modules: Soil Moisture Accounting module (fusesma.sim) and Gamma routing module (fuserouting.sim). It also contains default parameter ranges (fusesma.ranges and fuserouting.ranges) and three data objects: fuse_hydrological_timeseries (sample input dataset), parameters (sample parameters) and modlist (list of FUSE model structures).

Dependencies

The fuse package, as well as the examples in the vignette, depend on a number of CRAN packages. Check for missing dependencies and install them:

packs <- c("dplyr", "zoo", "tgp", "stats", "utils", "BH", "Rcpp", "testthat",
           "qualV", "devtools")
new.packages <- packs[!(packs %in% installed.packages()[, "Package"])]
if(length(new.packages)) install.packages(new.packages)

Installation

You can install this package from Github with devtools:

devtools::install_github("cvitolo/fuse")

Load the package:

library("fuse")

Usage

The simplest way to test fuse is to use the dummy data provided with this package, sample the parameter range using the built-in function generateParameters() and run the model with 1 model structure (e.g. TOPMODEL):

# Load the dummy data
data(fuse_hydrological_timeseries)

# Sample the parameter range
parameters <- generateParameters(1)

# Run fuse
streamflow <- fuse(DATA = fuse_hydrological_timeseries,
                   mid = 60,       # Model structure = TOPMODEL
                   deltim = 1,     # Daily time step
                   ParameterSet = parameters)

plot(streamflow, xlab = "", ylab = "Streamflow [mm/day]")

For details and more complex examples (e.g. multi-model ensemble), please refer to the vignette.

Fortran users are advised to refer to the latest version of fuse available here.

Meta

  • Code contributions are welcome! Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
  • Please report any issues or bugs.
  • License: GPL-3
  • Get citation information for the fuse package in R doing citation(package = 'fuse')
  • This package was reviewed by Maëlle Salmon for the Journal of Open Source Software, see review here.