Network Linked Data Index: `dataRetrieval`

This post will demonstrate dataRetrieval functions to query the Network Linked Data Index (NLDI).

The NLDI provides a information backbone to navigate the NHDPlusV2 network and discover features indexed to the network. This process of feature discovery mirrors web-based navigation tools like Google Maps.

Imagine you want to know about UCSB using Google Maps. In asking about the entity ‘UCSB’ we get information related to the feature (links, operating hours, photos) and things nearby.

UCSB via Google Maps

Imagine then that you want to travel from UCSB to UCLA and know you need gas along the way. In Google Maps you might use UCSB as your origin and ask for directions to UCLA that include gas stations along your route.

Gas stations between UCSB and UCLA

The NLDI works to provide the same functionality for the hydrologic network allowing users to discover known features, navigate from those along a route, and find other features on that route. The primary difference being navigation occurs over the hydrologic network rather then a transportation network. This service is now available as part of the dataRetrieval package through the findNLDI function.

Like any routing service, there are three types of information you can provide findNLDI. These include:

a feature to discover
direction(s) to travel from that feature
types of features to search for along the way

Each of these is discussed below using the following packages:

library(dplyr) # Data frame manipulation
library(ggplot2) # Plotting
library(patchwork) # Arranging plots
library(dataRetrieval) # The star of the show!

What’s available?

First, we need to know what features are indexed in the NLDI. The most current offerings can be found using get_nldi_sources, and new features are regularly added. At the time of writing (2024-11-05), 17 data sets have been indexed to the NHDPlus and cataloged in the NLDI.

get_nldi_sources()

source	sourceName	features
ca_gages	Streamgage catalog for CA SB19	https://api.water.usgs.gov/nldi/linked-data/ca_gages
census2020-nhdpv2	2020 Census Block - NHDPlusV2 Catchment Intersections	https://api.water.usgs.gov/nldi/linked-data/census2020-nhdpv2
epa_nrsa	EPA National Rivers and Streams Assessment	https://api.water.usgs.gov/nldi/linked-data/epa_nrsa
geoconnex-demo	geoconnex contribution demo sites	https://api.water.usgs.gov/nldi/linked-data/geoconnex-demo
gfv11_pois	USGS Geospatial Fabric V1.1 Points of Interest	https://api.water.usgs.gov/nldi/linked-data/gfv11_pois
huc12pp	HUC12 Pour Points NHDPlusV2	https://api.water.usgs.gov/nldi/linked-data/huc12pp
huc12pp_102020	HUC12 Pour Points circa 10-2020	https://api.water.usgs.gov/nldi/linked-data/huc12pp_102020
nmwdi-st	New Mexico Water Data Initative Sites	https://api.water.usgs.gov/nldi/linked-data/nmwdi-st
npdes	NPDES Facilities that Discharge to Water	https://api.water.usgs.gov/nldi/linked-data/npdes
nwisgw	NWIS Groundwater Sites	https://api.water.usgs.gov/nldi/linked-data/nwisgw
nwissite	NWIS Surface Water Sites	https://api.water.usgs.gov/nldi/linked-data/nwissite
ref_dams	geoconnex.us reference dams	https://api.water.usgs.gov/nldi/linked-data/ref_dams
ref_gage	geoconnex.us reference gages	https://api.water.usgs.gov/nldi/linked-data/ref_gage
vigil	Vigil Network Data	https://api.water.usgs.gov/nldi/linked-data/vigil
wade	Water Data Exchange 2.0 Sites	https://api.water.usgs.gov/nldi/linked-data/wade
WQP	Water Quality Portal	https://api.water.usgs.gov/nldi/linked-data/wqp
comid	NHDPlus comid	https://api.water.usgs.gov/nldi/linked-data/comid

Feature/Origin discovery

Features can be requested in two primary ways: Using the the native data set identifier, and using a location. The core feature set of the NLDI include the NHD flowlines, USGS NWIS locations, WQP locations, and HUC12 pour points. Each of these are available as arguments in findNLDI and can be used to request a feature object.

By Identifier

As an illustrative example, NHDPlus features can be requested by their COMID from the NHDPlusV2 data set.

findNLDI(comid = 101)

#> $origin
#> Simple feature collection with 1 feature and 3 fields
#> Geometry type: LINESTRING
#> Dimension:     XY
#> Bounding box:  xmin: -94.64845 ymin: 31.0838 xmax: -94.62997 ymax: 31.09915
#> Geodetic CRS:  WGS 84
#> # A tibble: 1 × 4
#>   sourceName    identifier comid                                        geometry
#>   <chr>         <chr>      <chr>                                <LINESTRING [°]>
#> 1 NHDPlus comid 101        101   (-94.64845 31.09915, -94.64803 31.09871, -94.6…

The returned simple features object contains the native data set identifier (“identifier”), sourceName of the native data set, and the indexed NHD COMID (in this case a duplicate since an NHD feature was requested). In the example above, we see the geometry column is of type LINESTRING. To keep dataRetrieval lightweight, the sf package is not a dependency. Instead, if sf is not installed - or no_sf = TRUE - only the sourceName, comid, and identifier will be returned.

findNLDI(comid = 101, no_sf = TRUE)

#> $origin
#>      sourceName identifier comid
#> 1 NHDPlus comid        101   101

To provide another example, we can request the NLDI representation of USGS NWIS gauge 11120000 in both a sf and “non-sf” way. Features indexed to the NHDPlus are returned as POINT objects. If sf is enabled, the sourceName, identifier, X, Y and geometry (sfc) are returned. If sf is not available, the geometry is dropped but the X and Y values are retained.

# local sf installation
findNLDI(nwis = "11120000")

#> $origin
#> Simple feature collection with 1 feature and 8 fields
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: -119.8118 ymin: 34.42472 xmax: -119.8118 ymax: 34.42472
#> Geodetic CRS:  WGS 84
#> # A tibble: 1 × 9
#>   sourceName               identifier  comid measure reachcode name      X     Y
#>   <chr>                    <chr>       <chr>   <dbl> <chr>     <chr> <dbl> <dbl>
#> 1 NWIS Surface Water Sites USGS-11120… 1759…    92.5 18060013… ATAS… -120.  34.4
#> # ℹ 1 more variable: geometry <POINT [°]>

# No sf use/installation
findNLDI(nwis = "11120000", no_sf = TRUE)

#> $origin
#>                 sourceName    identifier    comid  measure      reachcode
#> 1 NWIS Surface Water Sites USGS-11120000 17595429 92.50523 18060013000423
#>                        name         X        Y
#> 1 ATASCADERO C NR GOLETA CA -119.8118 34.42472

Any NLDI feature found with get_nldi_source can be requested by passing a type/ID pair as a list to the origin argument. This will allow the networking capabilities offered in dataRetrieval to grow naturally with the NLDI itself. For example, we can use the origin argument to request features that don’t offer a specific parameter.

# Water Data Exchange 2.0 Site CA_45206
findNLDI(origin = list("wade" = "CA_45206"))

#> named list()

Location (longitude/latitude)

If you don’t know a feature ID, a longitude/latitude (X,Y) pair or a sf/sfc POINT object can be passed to the location argument. Doing so will identify the NHDPlus catchment the location fall within and will return the associated NHDPlusV2 flowline.

# Request by coordinates
findNLDI(location = c(-115, 40))

#> $origin
#> Simple feature collection with 1 feature and 3 fields
#> Geometry type: LINESTRING
#> Dimension:     XY
#> Bounding box:  xmin: -115.0326 ymin: 40.04013 xmax: -115.0182 ymax: 40.05183
#> Geodetic CRS:  WGS 84
#> # A tibble: 1 × 4
#>   sourceName    identifier comid                                        geometry
#>   <chr>         <chr>      <chr>                                <LINESTRING [°]>
#> 1 NHDPlus comid 946060315  946060315 (-115.0182 40.05183, -115.0185 40.05176, -…

# Request by sf/sfc POINT object
ucsb <- sf::st_sfc(sf::st_point(c(-119.8458, Y = 34.4146)), crs = 4326)
findNLDI(location = ucsb)

#> $origin
#> Simple feature collection with 1 feature and 3 fields
#> Geometry type: LINESTRING
#> Dimension:     XY
#> Bounding box:  xmin: -119.8823 ymin: 34.40438 xmax: -119.8256 ymax: 34.4179
#> Geodetic CRS:  WGS 84
#> # A tibble: 1 × 4
#>   sourceName    identifier comid                                        geometry
#>   <chr>         <chr>      <chr>                                <LINESTRING [°]>
#> 1 NHDPlus comid 948060316  948060316 (-119.8823 34.41072, -119.8822 34.4106, -1…

From any feature (comid, huc12, nwis, wqp, origin) or location, four modes of navigation are available and include:

UT: Upper Tributary
UM: Upper Mainstream
DM: Downstream Tributary
DD: Downstream Diversions

A example view of these navigation types can be seen below for NWIS site 11109000.

NLDI Navigation Options

One or more modes of navigation can be supplied to the nav argument. For example we can ask to navigate along the upper mainstem (UM) from COMID 101.

summarize.nldi <- function(input) {
  data.frame(
    name = names(input),
    class = sapply(input, class)[1],
    row.names = NULL
  ) %>%
    mutate(feature_count = ifelse(class == "sf", sapply(input, nrow),
      sapply(input, length)
    ))
}


findNLDI(comid = 101, nav = "UM") %>%
  summarize.nldi()

#>           name class feature_count
#> 1       origin    sf             1
#> 2 UM_flowlines    sf            14

Or along the upper mainstem (UM) and upper tributary (UT) of COMID 101.

findNLDI(comid = 101, nav = c("UM", "UT")) %>%
  summarize.nldi()

#>           name class feature_count
#> 1       origin    sf             1
#> 2 UM_flowlines    sf            14
#> 3 UT_flowlines    sf           325

In both cases the returned named list includes the origin and the flowlines along the requested navigation. If sf is not enabled, the returned object for a flowpath navigation is a vector of COMIDs.

findNLDI(comid = 101, nav = c("UM", "DM"), no_sf = TRUE) %>%
  summarize.nldi()

#>           name      class feature_count
#> 1       origin data.frame             3
#> 2 UM_flowlines data.frame            14
#> 3 DM_flowlines data.frame            43

Like the gas station example, any of the features listed in get_nldi_sources can be searched for along the network, for example, we can find all NWIS gauges, on the upper tributary, of COMID 101.

findNLDI(comid = 101, nav = "UT", find = "nwis") %>%
  summarize.nldi()

#>          name class feature_count
#> 1      origin    sf             1
#> 2 UT_nwissite    sf             2

Of course, more than one resource can be requested, for example, lets replicate the previous search, this time adding Water Quality Points to the returned list:

findNLDI(comid = 101, nav = "UT", find = c("nwis", "wqp")) %>%
  summarize.nldi()

#>          name class feature_count
#> 1      origin    sf             1
#> 2 UT_nwissite    sf             2
#> 3      UT_WQP    sf            29

Note that flowlines are no longer the default return for navigation once a new feature is requested. To retain flowlines, the must be explicitly requested.

findNLDI(comid = 101, nav = "UT", find = c("nwis", "flowlines")) %>%
  summarize.nldi()

#>           name class feature_count
#> 1       origin    sf             1
#> 2  UT_nwissite    sf             2
#> 3 UT_flowlines    sf           325

Upstream Basin Boundary

The Upstream Basin Boundary is a unique object that can be found for any feature by adding “basin” to find. Basins are only geometries with no specific attribute data. Therefore basins can only be returned if sf is installed. Otherwise, the result will be a 0 column data.frame

# with sf
findNLDI(comid = 101, find = "basin") %>%
  summarize.nldi()

#>     name class feature_count
#> 1 origin    sf             1
#> 2  basin    sf             1

# No sf
findNLDI(comid = 101, find = "basin", no_sf = TRUE) %>%
  summarize.nldi()

#>     name      class feature_count
#> 1 origin data.frame             3
#> 2  basin data.frame             0

Distance Constraints

In some cases, particularly for DM and DD navigation, the network can extend for hundreds of kilometers. You can limit (or extend) the distance of your search using the distance_km argument. As the name implies the value provided should be the maximum kilometers you want to search for features. The default for distance_km is 100.

# Default 100 km
findNLDI(comid = 101, nav = "DM", find = c("nwis", "wqp")) %>%
  summarize.nldi()

#>          name class feature_count
#> 1      origin    sf             1
#> 2 DM_nwissite    sf             1
#> 3      DM_WQP    sf             5

# Extended 200 km search
findNLDI(comid = 101, nav = "DM", find = c("nwis", "wqp"), distance_km = 200) %>%
  summarize.nldi()

#>          name class feature_count
#> 1      origin    sf             1
#> 2 DM_nwissite    sf             8
#> 3      DM_WQP    sf            17

Basic `dataRetrieval` integration

Last, as this functionality is being added to the dataRetrieval package, lets see a basic example of how the NLDI tools provide a discovery mechanism for working with the dataRetrieval tools. Here we will take a location that is near Fountain Creek in Colorado Springs, Colorado.

In this example we will use that location as the origin, navigate upstream along the mainstem, search for NWIS gauges, and use the identified siteIDs to query streamflow records from January 1^st, 2020 to the current day.

# Upstream nwis, flowlines, and basin
fountainCreek <- findNLDI(
  location = c(-104.780837, 38.786796),
  nav = "UM",
  find = c("nwis", "basin", "flowlines")
)

summarize.nldi(fountainCreek)

#>           name class feature_count
#> 1       origin    sf             1
#> 2        basin    sf             1
#> 3  UM_nwissite    sf            57
#> 4 UM_flowlines    sf            33

# Identify NLDI sites with daily values "dv"
#     and record streamflow ("00060")
#     and recorded flows in 2020
find <- whatNWISdata(sites = gsub(
  "USGS-", "",
  fountainCreek$UM_nwissite$identifier
)) %>%
  filter(
    data_type_cd == "dv",
    parm_cd == "00060",
    end_date > as.Date("2020-01-01")
  ) %>%
  mutate(identifier = paste0("USGS-", site_no)) %>%
  inner_join(fountainCreek$UM_nwissite, by = "identifier") %>%
  sf::st_as_sf()

# Extract Streamflow for identified sites
Q <- readNWISdv(find$site_no,
  parameterCd = "00060",
  startDate = "2020-01-01"
) %>%
  renameNWISColumns()

# Plot!
ggplot() +
  geom_line(
    data = Q,
    aes(x = Date, y = Flow, col = site_no),
    size = .5
  ) +
  facet_wrap(~site_no, nrow = 4) +
  theme_minimal() +
  scale_color_brewer(palette = "Set1") +
  theme(legend.position = "none") +
  ggplot() +
  geom_sf(data = fountainCreek$basin, col = NA) +
  geom_sf(data = fountainCreek$UM_flowlines, col = "blue", alpha = .5) +
  geom_sf(data = find, aes(col = site_no)) +
  scale_color_brewer(palette = "Set1") +
  theme_void() +
  labs(
    title = "2020 Streamflow",
    caption = "Fountain Creek, Colorado"
  ) +
  theme(
    legend.position = "none",
    plot.title = element_text(face = "bold", hjust = .5)
  )

Mike Johnson

2024-11-05

Navigation Analogy

What’s available?

Feature/Origin discovery

By Identifier

Location (longitude/latitude)

Navigation

Searching along the Navigation

Upstream Basin Boundary

Distance Constraints

Basic `dataRetrieval` integration

Network Linked Data Index: `dataRetrieval`

Mike Johnson

2024-11-05

Navigation Analogy

What’s available?

Feature/Origin discovery

By Identifier

Location (longitude/latitude)

Navigation

Searching along the Navigation

Upstream Basin Boundary

Distance Constraints

Basic dataRetrieval integration

Basic `dataRetrieval` integration