The nsink package is an R implementation of the methods described in
Kellogg et. al (2010).
Previous implementation of this approach relied on a manual, vector
based approach that was time consuming to prepare. This approach uses a
hybrid raster-vector approach that takes relatively little time to set
up for each new watershed and relies on readily available data. Total
run times vary, but range from minutes up to 5 hours depending on
options selected. Previous versions took weeks of manual data
manipulation. Thus, nsink was developed to satisfy the need for
quicker implementation of the NSink method as described in Kellogg et.
al (2010).
As of 2022-03-14 user functions for the nsink package are:
nsink_get_huc_id(): A function for searching the name of a USGS Watershed Boundary Dataset Hydrologic Unit (https://www.usgs.gov/core-science-systems/ngp/national-hydrography/watershed-boundary-dataset) and retrieving its 12-digit Hydrologic Unit Code (HUC).nsink_get_data(): Using any acceptable HUC ID (e.g. 2-digit to 12-digit), this function downloads the NHDPlus, SSURGO, NLCD Land Cover, and the NLCD Impervious for that HUC.nsink_prep_data():nsinkneeds data in a common coordinate reference system, from mutliple NHDPlus tables, and from different portions of SSURGO. This function completes these data preparation steps and outputs all data, clipped to the HUC boundary.nsink_calc_removal(): Quantifying relative N removal across a landscape is a key aspects of annsinkanalysis. Thensink_calc_removal()function takes the object returned fromnsink_prep_data()and calculates relative N removal for each landscape sink. See Kellogg et al [-@kellogg2010geospatial] for details on relative N removal estimation for each sink.nsink_generate_flowpath(): This function uses a combination of flow determined by topography, via a flow-direction raster, for the land-based portions of a flow path and of downstream flow along the NHDPlus stream network.nsink_summarize_flowpath(): Summarizing removal along a specified flow path requires relative N removal and a generated flow path. This function uses these and returns a summary of relative N removal along a flow path for each sink.nsink_generate_static_maps(): This function analyzes N removal at the watershed scale by summarizing the results of multiple flow paths. Four static maps are returned: 1)removal efficiency; 2)loading index; 3)transport index; 4)delivery index. Removal efficiency is a rasterized version of thensink_calc_removal()output. Loading index is N sources based on NLCD categories. Transport index is a heat map with the cumulative relative N removal along flow paths originating from a grid of points, density set by the user, across a watershed, highlighting the gradient of downstream N retention. Delivery index is the result of multiplying the loading index and the transport index, and shows potential N delivery from different sources, taking into account the relative N removal as water moves downstream.nsink_plot(): A function that plots each raster in the list returned fromnsink_generate_static_maps().nsink_build(): One of the drivers behind the development of thensinkpackage was to providen-sinkanalysis output that could be used more broadly (e.g. within a GIS). Thensink_build()runs a completensinkanalysis and outputs R objects, shapefiles and/or TIFFs.nsink_load(): Essentially the inverse of thensink_build()function, this function takes a folder of files, likely created bynsink_build(), and reads them into R.
At this time we plan on maintaining the nsink package as a GitHub only
package and thus it won’t be available directly from CRAN. You may use
the install_github() function from the remotes package to install
it. The code below will take care of installing remotes and installing
nsink from the GitHub repository.
install.packages("remotes")
remotes::install_github("usepa/nsink", dependencies = TRUE, build_vignettes = TRUE)And then to load up the package:
library(nsink)All functions are documented, with examples, and that documentation may
be accessed, in R, via the usual help functions. Additionally, an
introduction to the nsink package with a more detailed workflow is
documented in a vignette.
# Load up package
library(nsink)
# Access package level help
help(package = "nsink")
# Access the Introduction to nsink vignette
vignette("intro", package = "nsink")If you would like to contribute to the nsink package, please first
read the CONTRIBUTING. In short,
contributions are happily accepted either via suggestions in the
Issues or via pull request.
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