# U.S. Data and Package Basics

#### dblodgett@usgs.gov

## TL;DR

Pick an outlet location and download some data.

    # Uncomment to install!
    # install.packages("hydrogeofetch")

    library(hydrogeofetch)
    library(sf)

    start_point <- st_sfc(st_point(c(-89.362239, 43.090266)), crs = 4269)
    start_comid <- discover_nhdplus_id(start_point)

    flowline <- navigate_nldi(list(featureSource = "comid",
                                   featureID = start_comid),
                              mode = "upstreamTributaries",
                              distance_km = 1000)

    subset_file <- tempfile(fileext = ".gpkg")
    subset <- subset_nhdplus(comids = as.integer(flowline$UT$nhdplus_comid),
                             output_file = subset_file,
                             nhdplus_data = "download",
                             flowline_only = FALSE,
                             return_data = TRUE, overwrite = TRUE)

    flowline <- subset$NHDFlowline_Network
    catchment <- subset$CatchmentSP
    waterbody <- subset$NHDWaterbody

    ## Or using a file:

    flowline <- sf::read_sf(subset_file, "NHDFlowline_Network")
    catchment <- sf::read_sf(subset_file, "CatchmentSP")
    waterbody <- sf::read_sf(subset_file, "NHDWaterbody")

    plot(sf::st_geometry(flowline), col = "blue")
    plot(start_point, cex = 1.5, lwd = 2, col = "red", add = TRUE)
    plot(sf::st_geometry(catchment), add = TRUE)
    plot(sf::st_geometry(waterbody), col = rgb(0, 0, 1, alpha = 0.5), add = TRUE)

Or fetch an NWIS site as the starting point and generate a plot. Data is returned and/or stored in a local file for later use.

    # ?plot_nhdplus for more
    plot_data <- plot_nhdplus(
      outlets = list(featureSource = "nwissite", featureID = "USGS-05428500"),
      gpkg = subset_file, overwrite = TRUE)

This vignette covers a range of utilities the hydrogeofetch package offers for working with data in a U.S. context.

The first thing you are going to need to do is go get some data to work with. `hydrogeofetch` provides the ability to download small subsets of the NHDPlus directly from web services. For large subsets, greater than a few thousand square kilometers, you can use `download_nhdplusv2()`.

If you are working with the whole National Seamless database, `hydrogeofetch` has some convenience functions you should be aware of. Once you have it downloaded and extracted, you can tell the hydrogeofetch package where it is with the `nhdplus_path()` function.

This vignette stages its data in a working directory. Set `work_dir` to wherever you want downloaded and sample data to live.

    work_dir <- file.path(hydrogeofetch_data_dir(), "nhdpt_v_cache")

    dir.create(work_dir, showWarnings = FALSE, recursive = TRUE)

    nhdplus_path(file.path(work_dir, "natseamless.gpkg"))

    basename(nhdplus_path())

If you don’t need or want all the geometry for the flowlines, consider using `get_vaa()`. It allows you to retrieve specific NHDPlus attributes with very little overhead. It also supports access to an updated set of network attributes that incorporate numerous network updates from national hydrologic modeling projects.

    vaa <- get_vaa()
    names(vaa)
    nrow(vaa)

### NHDPlus HiRes

NHDPlus HiRes is an in-development dataset that introduces much more dense flowlines and catchments. In the long run, `hydrogeofetch` will have complete support for NHDPlus HiRes. So far, `hydrogeofetch` will help download and interface NHDPlus HiRes data with existing `hydrogeofetch` functionality. It’s important to note that `hydrogeofetch` was primarily implemented using NHDPlusV2 and any use of HiRes should be subject to scrutiny.

For the demo below, a small sample of HiRes data is staged into `work_dir` (the working directory set above) and read from there. The first line shows how you can download additional data (just change `download_files` to `TRUE`).

    download_nhdplushr(nhd_dir = "download_dir",
                       hu_list = c("0101"), # can mix hu02 and hu04 codes.
                       download_files = FALSE) # TRUE will download files.

    out_gpkg <- file.path(work_dir, "nhd_hr.gpkg")
    hr_data <- get_nhdplushr(work_dir,
                             out_gpkg = out_gpkg)
    (layers <- st_layers(out_gpkg))
    names(hr_data)
    unlink(out_gpkg)

    hr_data <- get_nhdplushr(work_dir,
                             out_gpkg = out_gpkg,
                             layers = NULL)
    (layers <- st_layers(out_gpkg))
    names(hr_data)

## Discovery and Subsetting

One of the primary workflows `hydrogeofetch` is designed to accomplish can be described in three steps:

1. what NHDPlus catchment is at the outlet of a watershed,
2. figure out what catchments are up or downstream of that catchment, and
3. create a stand alone subset for that collection of catchments.

Say we want to get a subset of the NHDPlus upstream of a given location. We can start with `discover_nhdplus_id()` First, let’s look at a given point location. Then see where it is relative to our flowlines.

    lon <- -89.36
    lat <- 43.09

    start_point <- sf::st_sfc(sf::st_point(c(lon, lat)),
                              crs = 4269)

    plot(sf::st_geometry(flowline))
    plot(start_point, cex = 1.5, lwd = 2, col = "red", add = TRUE)

OK, so we have a point location near a river and we want to figure out what catchment is at its outlet. We can use the `discover_nhdplus_id()` function which calls out to a web service and returns an NHDPlus catchment identifier, typically called a COMID.

If we set `raindrop = TRUE`, we can also get a elevation derived downslope trace to the nearest flowline and some additional info. See `get_raindrop_trace()` for more on this functionality.

    start_comid <- discover_nhdplus_id(start_point, raindrop = TRUE)
    start_comid

    plot(sf::st_geometry(start_comid))
    plot(sf::st_geometry(flowline), add = TRUE, col = "blue", lwd = 2)
    plot(start_point, cex = 1.5, lwd = 2, col = "red", add = TRUE)

If you have the whole National Seamless database and want to work at regional to national scales, skip down to the Local Data Subsetting section.

### Web Service Data Subsetting

`hydrogeofetch` supports discovery and data subsetting using web services made available through the Network Linked Data Index (NLDI) and the Water Mission Area pygeoapi. The code below shows how to use the NLDI functions to build a dataset upstream of our `start_comid` that we found above.

The NLDI can be queried with any set of watershed outlet locations that it has in its index. We call these “featureSources”. We can query the NLDI for an identifier of a given feature from any of its “featureSources” and find out what our navigation options are as shown below.

    dataRetrieval::get_nldi_sources()$source

    nldi_feature <- list(featureSource = "comid",
                         featureID = as.integer(start_comid$comid)[1])

    get_nldi_feature(nldi_feature)

We can use `get_nldi_feature()` as a way to make sure the featureID is available for the chosen “featureSource”. Now that we know the NLDI has our comid, we can use the “upstreamTributaries” navigation option to get all the flowlines upstream or all the features from any of the “featureSources” as shown below.

    flowline_nldi <- navigate_nldi(nldi_feature,
                                   mode = "upstreamTributaries",
                                   distance_km = 1000)

    plot(sf::st_geometry(flowline), lwd = 3, col = "black")
    plot(sf::st_geometry(flowline_nldi$origin), lwd = 3, col = "red", add = TRUE)
    plot(sf::st_geometry(flowline_nldi$UT), lwd = 1, col = "red", add = TRUE)

The NLDI only provides geometry and a comid for each of the flowlines. The `subset_nhdplus()` function has a “download” option that allows us to download four layers and all attributes as shown below.

    output_file_download <- file.path(work_dir, "subset_download.gpkg")

    output_file_download <-subset_nhdplus(comids = as.integer(flowline_nldi$UT$nhdplus_comid),
                                          output_file = output_file_download,
                                          nhdplus_data = "download", return_data = FALSE,
                                          overwrite = TRUE)

    sf::st_layers(output_file_download)

    flowline_download <- sf::read_sf(file.path(work_dir, "subset_download.gpkg"),
                                     "NHDFlowline_Network")

    plot(sf::st_geometry(dplyr::filter(flowline_download,
                                       streamorde > 2)),
         lwd = 7, col = "darkgrey")
    plot(sf::st_geometry(flowline_nldi$UT),
         lwd = 3, col = "red", add = TRUE)

This plot illustrates the kind of thing that’s possible (filtering to specific stream orders) using the attributes that are downloaded.

Before moving on, one more demonstration of what can be done using the NLDI. Say we knew the USGS gage ID that we want NHDPlus data upstream of. We can use the NLDI to navigate from the gage the same as we did for our comid. We can also get back all the nwis sites the NLDI knows about upstream of the one we chose!

    nldi_feature <- list(featureSource = "nwissite",
                         featureID = "USGS-05428500")

    flowline_nldi <- navigate_nldi(nldi_feature,
                                   mode = "upstreamTributaries",
                                   distance_km = 1000)

    output_file_nwis <- file.path(work_dir, "subset_download_nwis.gpkg")

    output_file_nwis <-subset_nhdplus(comids = as.integer(flowline_nldi$UT$nhdplus_comid),
                                      output_file = output_file_nwis,
                                      nhdplus_data = "download",
                                      return_data = FALSE, overwrite = TRUE)

    sf::st_layers(output_file_download)

    flowline_nwis <- sf::read_sf(output_file_nwis,
                                     "NHDFlowline_Network")

    upstream_nwis <- navigate_nldi(nldi_feature,
                                   mode = "upstreamTributaries",
                                   data_source = "nwissite",
                                   distance_km = 1000)

    plot(sf::st_geometry(flowline_nwis),
         lwd = 3, col = "blue")
    plot(sf::st_geometry(upstream_nwis$UT_nwissite),
         cex = 1, lwd = 2, col = "red", add = TRUE)

### Local Data Subsetting

While web service data access is very convenient, some use cases make working with web services impossible or cumbersome such that working with local data is preferable. hydrogeofetch supports such workflows with hybrid, web-service and local, workflows.

With the starting COMID we found with `discover_nhdplus_id()` above, we can use hydroloom’s `navigate_hydro_network()` to retrieve a collection of COMIDs along the upstream-with-tributaries network path.

    UT_comids <- hydroloom::navigate_hydro_network(flowline, start_comid$comid[1], "UT")
    UT_comids

If you are familiar with the NHDPlus, you will recognize that now that we have this list of COMIDs, we could go off and do all sorts of things with the various flowline attributes. For now, let’s just use the COMID list to filter our `fline` `sf` `data.frame` and plot it with our other layers.

    plot(sf::st_geometry(flowline))
    plot(start_point, cex = 1.5, lwd = 2, col = "red", add = TRUE)
    plot(sf::st_geometry(dplyr::filter(flowline, comid %in% UT_comids)),
         add=TRUE, col = "red", lwd = 2)

Say you want to save the network subset for later use in R or in some other GIS. The `subset_nhdplus()` function is your friend. If you have the whole national seamless database downloaded, you can pull out large subsets of it like shown below (this queries for data from the local geodatabase without loading the whole thing into memory). If you don’t have the whole national seamless, look at the second example in this section.

    output_file <- file.path(work_dir, "subset.gpkg")

    output_file <-subset_nhdplus(comids = UT_comids,
                                 output_file = output_file,
                                 nhdplus_data = nhdplus_path(),
                                 return_data = FALSE, overwrite = TRUE)

    sf::st_layers(output_file)

Now we have an output geopackage that can be used later. It contains the network subset of catchments and flowlines as well as a spatial subset of other layers as shown in the status output above. To complete the demonstration, here are a couple more layers plotted up.

    catchment <- sf::read_sf(output_file, "CatchmentSP")
    waterbody <- sf::read_sf(output_file, "NHDWaterbody")

    plot(sf::st_geometry(flowline))
    plot(start_point, cex = 1.5, lwd = 2, col = "red", add = TRUE)
    plot(sf::st_geometry(dplyr::filter(flowline, comid %in% UT_comids)),
         add=TRUE, col = "red", lwd = 2)
    plot(sf::st_geometry(catchment), add = TRUE)
    plot(sf::st_geometry(waterbody), col = rgb(0, 0, 1, alpha = 0.5), add = TRUE)

## Indexing

Indexing functions have moved to the hydroloom package. Use hydrogeofetch to fetch flowline data and hydroloom to index points to those flowlines.

    hydroloom::index_points_to_lines(flowline, start_point)

`index_points_to_lines()` works with a list of points too. For demonstration purposes, we can use the gages in our subset from above.

    gage <- sf::read_sf(output_file, "Gage")

    hydroloom::index_points_to_lines(flowline, sf::st_geometry(gage), precision = 10)

See the hydroloom indexing documentation and the migrating from nhdplusTools article for more.