raster, knitr, rmarkdown, bookdown, testthat (>= 3.0.0)

Algorithms for Helping Build Dynamic TOPMODEL Implementations
from Spatial Data
person(given = "Paul",
family = "Smith",
role = c("aut", "cre"),
email = "paul@waternumbers.co.uk",
comment = c(ORCID = "0000-0002-0034-3412"))
A set of algorithms based on Quinn et al. (1991) <doi:10.1002/hyp.3360050106> for processing river network and digital elevation data to build implementations of Dynamic TOPMODEL, a semi-distributed hydrological model proposed in Beven and Freer (2001) <doi:10.1002/hyp.252>. The 'dynatop' package implements simulation code for Dynamic TOPMODEL based on the output of 'dynatopGIS'.
rgdal, igraph, knitr, rmarkdown, covr, pkgdown

Implementation of the Dynamic TOPMODEL hydrological model
Peter Metcalfe, based on Fortran code by Keith Beven and Jim Freer
a native R implementation and enhancement of Dynamic TOPMODEL, Beven and Freers' (2001) extension to the semi-distributed hydrological model TOPMODEL (Beven and Kirkby, 1979).
shape, fields, rgeos, maptools, rgdal, sp, spam, hydroGOF,
topmodel, intervals, tools

Implementation of the Dynamic TOPMODEL Hydrological Model
Peter Metcalfe, Keith Beven and Jim Freer
A native R implementation and enhancement of the Dynamic TOPMODEL
semi-distributed hydrological model. Includes some pre-processsing and
output routines.
deSolve, rgeos, maptools, rgdal, zoo, xts, sp, raster,
lubridate, topmodel, methods, grDevices, stats, utils,
graphics, tools

A native R implementation and enhancement of the Dynamic TOPMODEL
semi-distributed hydrological model. Includes some preprocessing, utility and
routines for displaying outputs.
deSolve, maptools, rgdal, rgeos, zoo, xts, sp, raster,
lubridate, topmodel, methods, grDevices, stats, utils,
graphics, tools

Complexity of Short and Coarse-Grained Time Series
While there are many well-established measures for identifying critical fluctuations and phase transitions, these measures only work with many points of measurement and thus are unreliable when studying short and coarse-grained time series. This package provides a measure for complexity in a time series that does not rely on long time series (Kaiser (2017), <doi:10.17605/OSF.IO/GWTKX>).