NHDPlusTools Data Access Overview

dblodgett@usgs.gov

Since it’s original release in 2019, data access in nhdplusTools has evolved and grown considerably. This vignette, prepared for a workshop in Summer 2024 shows the diversity of data available with nhdplusTools in one holistic overview.

The function naming in nhdplusTools related to data access uses three common terms:
1. “download” will generally download complete data sets for use locally. 2. “get” will pull a data subset from a web service. 3. “subset” will pull a subset from a local file and, when available, a web service.

Dataset function index.

The following summarizes specific data access functions available for the datasets that nhdplusTools has supporting functionality for.

Network Linked Data Index integration

The Network Linked Data Index plays a key role in discovery nhdplusTools. It provides access to an easy network navigation and basin boundary delineation tool. Behind the scenes, the NLDI is based on the network of the NHDPlusV2 – so has some special functionality related directly to that dataset. Functions that utilize the NLDI include:

In the demo below, we’ll choose a stream gage and show how to access data related to it from all the datasets that nhdplusTools works with as well as use some of the NLDI functionality in question.

For the sake of demonstration, we’ll look at the Wolf River at Langlade, WI – site ID “04074950”.

nhdplusTools allows us to start from a stream gage to build a subset of NHDPlusV2 data. Below, we’ll do just that and plot the results on a default map.


demo_dir <- nhdplusTools_data_dir()

site_id <- "USGS-04074950"


# use dataRetrieval::get_nldi_sources() to find other nldi sources

site <- list(featureSource = "nwissite",
             featureID = "USGS-04074950")

site_feature <- get_nldi_feature(site)

upstream_network <- navigate_nldi(site, 
                                  mode = "UT", distance_km = 9999)

demo_data <- file.path(demo_dir, "data_demo.gpkg")

dataset <- subset_nhdplus(as.integer(upstream_network$UT_flowlines$nhdplus_comid), 
                          nhdplus_data = "download", # download from a service
                          output_file = demo_data, # write the data to disk
                          return_data = TRUE, # return the data rather
                          flowline_only = FALSE, overwrite = TRUE)
#> All intersections performed in latitude/longitude.
#> Reading NHDFlowline_Network
#> Spherical geometry (s2) switched off
#> Spherical geometry (s2) switched on
#> Writing NHDFlowline_Network
#> Reading CatchmentSP
#> Spherical geometry (s2) switched off
#> Found invalid geometry, attempting to fix.
#> Spherical geometry (s2) switched on
#> Writing CatchmentSP
#> Spherical geometry (s2) switched off
#> although coordinates are longitude/latitude, st_intersects assumes that they
#> are planar
#> Spherical geometry (s2) switched on
#> Spherical geometry (s2) switched off
#> although coordinates are longitude/latitude, st_intersects assumes that they
#> are planar
#> Spherical geometry (s2) switched on
#> Spherical geometry (s2) switched off
#> although coordinates are longitude/latitude, st_intersects assumes that they
#> are planar
#> Spherical geometry (s2) switched on

names(dataset)
#> [1] "NHDFlowline_Network"    "CatchmentSP"            "NHDArea"               
#> [4] "NHDWaterbody"           "NHDFlowline_NonNetwork"

sapply(dataset, nrow)
#>    NHDFlowline_Network            CatchmentSP                NHDArea 
#>                    389                    370                     20 
#>           NHDWaterbody NHDFlowline_NonNetwork 
#>                    473                      8

old_par <- par(mar = c(0, 0, 0, 0))

plot_nhdplus(outlets = list(featureSource = "nwissite",
                            featureID = "USGS-04074950"), 
             nhdplus_data = demo_data, flowline_only = TRUE)
#> Zoom set to: 10

The above is the original way NHDPlusTools supported access NHDPlusV2 data. A dedicated web service subset utility is available in get_nhdplus – which is what subset_nhdplus() calls behind the scenes.

Here we grab the basin for our site and request NHDPlus with its geometry as the Area of Interest.


basin <- get_nldi_basin(site)

subset <- get_nhdplus(AOI = basin, realization = "flowline")
#> Spherical geometry (s2) switched off
#> although coordinates are longitude/latitude, st_intersects assumes that they
#> are planar
#> Spherical geometry (s2) switched on

par(mar = c(0, 0, 0, 0))

plot(sf::st_geometry(basin))
plot(sf::st_geometry(subset), col = "blue", add = TRUE)

For NHDPlusHR data, which is much denser than NHDPlusV2, nhdplusTools supports downloading four-digit Hydrologic Unit Code staged geodatabases. The function get_huc() is useful to discover the code needed here.


wolf_huc <- get_huc(basin, type = 'huc04')
#> Spherical geometry (s2) switched off
#> although coordinates are longitude/latitude, st_intersects assumes that they
#> are planar
#> Spherical geometry (s2) switched on

nrow(wolf_huc)
#> [1] 2

# it straddles hucs? Not really.

par(mar = c(0, 0, 0, 0))
plot(sf::st_geometry(basin), col = "grey")
plot(sf::st_geometry(wolf_huc), add = TRUE)


wolf_huc <- get_huc(site_feature, type = "huc04")
#> Spherical geometry (s2) switched off
#> although coordinates are longitude/latitude, st_intersects assumes that they
#> are planar
#> Spherical geometry (s2) switched on

nrow(wolf_huc)
#> [1] 1

# better!!
par(mar = c(0, 0, 0, 0))
plot(sf::st_geometry(wolf_huc))
plot(sf::st_geometry(basin), col = "grey", add = TRUE)


outdir <- file.path(nhdplusTools_data_dir(), "hr_access_demo")

dir.create(outdir)
#> Warning in dir.create(outdir):
#> 'C:\Users\dblodgett\AppData\Roaming\R\data\R\nhdplusTools\hr_access_demo'
#> already exists

download_dir <- download_nhdplushr(outdir, wolf_huc$huc4)

list.files(download_dir)
#> [1] "NHDPLUS_H_0403_HU4_GDB.gdb" "NHDPLUS_H_0403_HU4_GDB.jpg"
#> [3] "NHDPLUS_H_0403_HU4_GDB.xml"

If we had asked for more HUC4 codes, additional gdb files would be in the directory we specified.

With this, we can use one of the two functions for access NHDPlusHR data to load data from the directory. Here, we use the more complete get_nhdplus() and set check_terminals=TRUE which uses make_standalone() to ensure that the nhdplus attributes are complete and self-consistent within the subset of data returned.


nhdplushr <- get_nhdplushr(
  download_dir, 
  layers = c("NHDFlowline", "NHDPlusCatchment", "NHDWaterbody", 
             "NHDArea", "NHDLine", "NHDPlusSink", "NHDPlusWall", 
             "NHDPoint", "NHDPlusBurnWaterbody", "NHDPlusBurnLineEvent",
             "HYDRO_NET_Junctions", "WBDHU2", "WBDHU4","WBDHU6", 
             "WBDHU8", "WBDHU10", "WBDHU12", "WBDLine"), 
  check_terminals = TRUE)
#> Warning in CPL_read_ogr(dsn, layer, query, as.character(options), quiet, : GDAL
#> Message 1: organizePolygons() received a polygon with more than 100 parts. The
#> processing may be really slow.  You can skip the processing by setting
#> METHOD=SKIP, or only make it analyze counter-clock wise parts by setting
#> METHOD=ONLY_CCW if you can assume that the outline of holes is counter-clock
#> wise defined

sapply(nhdplushr, nrow)
#>          NHDFlowline     NHDPlusCatchment         NHDWaterbody 
#>                53834                51815                34138 
#>              NHDArea              NHDLine          NHDPlusSink 
#>                 1283                  207                  582 
#>          NHDPlusWall             NHDPoint NHDPlusBurnWaterbody 
#>                 2031                   73                25146 
#> NHDPlusBurnLineEvent  HYDRO_NET_Junctions               WBDHU2 
#>                51938                53555                    1 
#>               WBDHU4               WBDHU6               WBDHU8 
#>                    1                    2                   18 
#>              WBDHU10              WBDHU12              WBDLine 
#>                  107                  629                 2031

At a lower level, we can use get_hr_data() to access particular layers. Here, rename=TRUE causes the nhdplushr names to be normalized to nhdplusTools conventions using align_nhdplus_names().

NOTE: “NHDPlusID” from nhdplushr is replaced with the name “COMID”. This attribute is merely a unique integer identifier and should not be assumed to relate to anything outside the context of a given dataset.


nhdplushr <- get_hr_data(list.files(download_dir, pattern = ".gdb", full.names = TRUE),
                         layer = "NHDFlowline", rename = TRUE)

names(nhdplushr)
#>  [1] "Permanent_Identifier"        "FDate"                      
#>  [3] "Resolution"                  "GNIS_ID"                    
#>  [5] "GNIS_Name"                   "LENGTHKM"                   
#>  [7] "REACHCODE"                   "FlowDir"                    
#>  [9] "WBArea_Permanent_Identifier" "FTYPE"                      
#> [11] "FCODE"                       "MainPath"                   
#> [13] "InNetwork"                   "VisibilityFilter"           
#> [15] "Shape_Length"                "COMID"                      
#> [17] "VPUID"                       "Enabled"                    
#> [19] "Shape"                       "StreamLeve"                 
#> [21] "StreamOrde"                  "StreamCalc"                 
#> [23] "FromNode"                    "ToNode"                     
#> [25] "Hydroseq"                    "LevelPathI"                 
#> [27] "Pathlength"                  "TerminalPa"                 
#> [29] "ArbolateSu"                  "Divergence"                 
#> [31] "StartFlag"                   "TerminalFl"                 
#> [33] "UpLevelPat"                  "UpHydroseq"                 
#> [35] "DnLevel"                     "DnLevelPat"                 
#> [37] "DnHydroseq"                  "DnMinorHyd"                 
#> [39] "DnDrainCou"                  "FromMeas"                   
#> [41] "ToMeas"                      "RtnDiv"                     
#> [43] "Thinner"                     "VPUIn"                      
#> [45] "VPUOut"                      "AreaSqKM"                   
#> [47] "TotDASqKM"                   "DivDASqKm"                  
#> [49] "MaxElevRaw"                  "MinElevRaw"                 
#> [51] "MaxElevSmo"                  "MinElevSmo"                 
#> [53] "Slope"                       "SlopeLenKm"                 
#> [55] "ElevFixed"                   "HWType"                     
#> [57] "HWNodeSqKm"                  "StatusFlag"

# Great Lakes coast are flowlines -- remove for visuals
gl_coast <- c(get_DM(nhdplushr, 60002700000331),
              get_DM(nhdplushr, 60002700049157))
#> defaulting to comid rather than permanent_identifier
#> defaulting to comid rather than permanent_identifier

plot_data <- dplyr::filter(nhdplushr, FCODE != 56600 & StreamOrde > 2 & !COMID %in% gl_coast)

par(mar = c(0, 0, 0, 0))
plot(sf::st_geometry(wolf_huc))
plot(sf::st_geometry(basin), col = "grey", add = TRUE)
plot(sf::st_geometry(plot_data), lwd = plot_data$StreamOrde / 3, col = "blue", add = TRUE)


par(mar = c(0, 0, 0, 0))
plot(sf::st_geometry(basin), col = "grey")
plot(sf::st_geometry(plot_data), lwd = plot_data$StreamOrde / 2, col = "blue", add = TRUE)

BONUS DEMO: Say we want to know where our stream gage is on the river in question…

get_flowline_index() and disambiguate_flowline_indexes() are your friends.


potential_matches <- get_flowline_index(nhdplushr, 
                                        points = site_feature, 
                                        search_radius = units::as_units(500, "m"),
                                        max_matches = 5)
#> defaulting to comid rather than permanent_identifier
#> Warning in match_crs(x, points, paste("crs of lines and points don't match.", :
#> crs of lines and points don't match. attempting st_transform of lines
#> Warning in index_points_to_lines.hy(x, points, search_radius = search_radius, :
#> converting to LINESTRING, this may be slow, check results

potential_matches
#>   id          COMID      REACHCODE REACH_meas       offset
#> 1  1 60002700035364 04030202000126    34.9737 0.0002166323
#> 2  1 60002700000908 04030104001542    49.1370 0.0177673341
#> 3  1 60002700036849 04030104001542    81.5378 0.0224609122
#> 4  1 60002700035750 04030104000533    31.4940 0.0244823037
#> 5  1 60002700034888 04030104000136   100.0000 0.0247855142

site_meta <- dataRetrieval::readNWISsite(gsub("USGS-", "", site_feature$identifier))

sqmi_to_sqkm <- 2.59

da_df <- data.frame(id = 1, drainagearea = site_meta$drain_area_va * sqmi_to_sqkm)

# uses nearest drainage area match
disambiguate_flowline_indexes(potential_matches,
                              flowpath = dplyr::select(nhdplushr, COMID, TotDASqKM),
                              hydro_location = da_df)
#> # A tibble: 1 × 5
#>      id   COMID REACHCODE      REACH_meas   offset
#>   <dbl>   <dbl> <chr>               <dbl>    <dbl>
#> 1     1 6.00e13 04030202000126       35.0 0.000217

If what you really need is the base NHD, which is now a static dataset, the pattern is just the same as with nhdplushr using download_nhd().


outdir <- file.path(nhdplusTools_data_dir(), "nhd_access_demo")

dir.create(outdir)
#> Warning in dir.create(outdir):
#> 'C:\Users\dblodgett\AppData\Roaming\R\data\R\nhdplusTools\nhd_access_demo'
#> already exists

download_dir <- download_nhd(outdir, wolf_huc$huc4)

list.files(download_dir)
#> [1] "NHD_H_0403_HU4_GDB.gdb" "NHD_H_0403_HU4_GDB.jpg" "NHD_H_0403_HU4_GDB.xml"

nhd_gdb <- list.files(download_dir, pattern = ".gdb", full.names = TRUE)

sf::st_layers(nhd_gdb)
#> Driver: OpenFileGDB 
#> Available layers:
#>                 layer_name                 geometry_type features fields
#> 1        ExternalCrosswalk                            NA        1      6
#> 2                 NHDFCode                            NA      126     13
#> 3     NHDFeatureToMetadata                            NA   277698      2
#> 4                  NHDFlow                            NA    67048      4
#> 5           NHDFlowlineVAA                            NA    53733     22
#> 6              NHDMetadata                            NA      312     21
#> 7  NHDProcessingParameters                            NA        5      2
#> 8  NHDReachCodeMaintenance                            NA    62818      6
#> 9   NHDReachCrossReference                            NA    78278     11
#> 10       NHDSourceCitation                            NA      350     13
#> 11               NHDStatus                            NA        0      3
#> 12 NHDVerticalRelationship                            NA        0      3
#> 13                CLIPPOLY                 Multi Polygon        0      2
#> 14            NHDWaterbody              3D Multi Polygon    34143     13
#> 15         NHDPointEventFC                         Point     2705     14
#> 16                NHDPoint                      3D Point       74      8
#> 17          NHDLineEventFC             Multi Line String        0     16
#> 18                 NHDLine          3D Multi Line String      207     10
#> 19             NHDFlowline 3D Measured Multi Line String    53850     16
#> 20          NHDAreaEventFC                 Multi Polygon        0     14
#> 21                 NHDArea              3D Multi Polygon     1283     12
#> 22                 WBDLine             Multi Line String     2970      7
#> 23                  WBDHU8                 Multi Polygon       18     14
#> 24                  WBDHU6                 Multi Polygon        2     14
#> 25                  WBDHU4                 Multi Polygon        1     14
#> 26                  WBDHU2                 Multi Polygon        1     14
#> 27                 WBDHU16                 Multi Polygon        0     19
#> 28                 WBDHU14                 Multi Polygon        0     19
#> 29                 WBDHU12                 Multi Polygon      629     19
#> 30                 WBDHU10                 Multi Polygon      107     16
#> 31     HYDRO_NET_Junctions                         Point    53573      1
#> 32      HYDRO_NET_BUILDERR                            NA       21      3
#> 33                N_1_Desc                            NA   107423      5
#> 34               N_1_EDesc                            NA       40      2
#> 35             N_1_EStatus                            NA        1      2
#> 36               N_1_ETopo                            NA       14      2
#> 37              N_1_FloDir                            NA        1      2
#> 38               N_1_JDesc                            NA       40      2
#> 39             N_1_JStatus                            NA        1      2
#> 40               N_1_JTopo                            NA      105      2
#> 41              N_1_JTopo2                            NA        1      2
#> 42               N_1_Props                            NA        9      2
#>                 crs_name
#> 1                   <NA>
#> 2                   <NA>
#> 3                   <NA>
#> 4                   <NA>
#> 5                   <NA>
#> 6                   <NA>
#> 7                   <NA>
#> 8                   <NA>
#> 9                   <NA>
#> 10                  <NA>
#> 11                  <NA>
#> 12                  <NA>
#> 13                 NAD83
#> 14 NAD83 + NAVD88 height
#> 15 NAD83 + NAVD88 height
#> 16 NAD83 + NAVD88 height
#> 17 NAD83 + NAVD88 height
#> 18 NAD83 + NAVD88 height
#> 19 NAD83 + NAVD88 height
#> 20 NAD83 + NAVD88 height
#> 21 NAD83 + NAVD88 height
#> 22                 NAD83
#> 23                 NAD83
#> 24                 NAD83
#> 25                 NAD83
#> 26                 NAD83
#> 27                 NAD83
#> 28                 NAD83
#> 29                 NAD83
#> 30                 NAD83
#> 31 NAD83 + NAVD88 height
#> 32                  <NA>
#> 33                  <NA>
#> 34                  <NA>
#> 35                  <NA>
#> 36                  <NA>
#> 37                  <NA>
#> 38                  <NA>
#> 39                  <NA>
#> 40                  <NA>
#> 41                  <NA>
#> 42                  <NA>

nhd_fline <- sf::read_sf(nhd_gdb, "NHDFlowline")

We’ll wait to plot this up until after we’ve done some work with 3DHP. As of writing, the 3DHP is more or less the same as the NHD but in a new database schema. The get_3dhp() uses a web service to pull data for subsets much the same as the other get_* functions. See vignette("get_3dhp_data.Rmd") for more on how to work with 3DHP data.


sub_3dhp <- get_3dhp(basin, type = "flowline")
#> Getting features 0 to 2000 of 2199
#> Getting features 2000 to 2199 of 2199

plot(sub_3dhp)
#> Warning: plotting the first 10 out of 35 attributes; use max.plot = 35 to plot
#> all


sub_3dhp <- st_compatibalize(sub_3dhp, nhd_fline)

par(mar = c(0, 0, 0, 0))
plot(sf::st_geometry(basin), col = "grey")
plot(sf::st_geometry(sf::st_zm(sub_3dhp)), col = "skyblue", lwd = 2.5, add = TRUE)
plot(sf::st_geometry(sf::st_zm(nhd_fline)), col = "blue", lwd = 0.1, add = TRUE)

A brand new, May 2024, feature in nhdplusTools is access to the geoconnex.us reference feature server. The reference feature server provides easy access to representations of datasets that people use to cross reference other data. discover_geoconnex_reference() provides access to a full table of what’s available.


unique(discover_geoconnex_reference()[c("id", "title")])
#> # A tibble: 18 × 2
#>    id            title                                                          
#>    <chr>         <chr>                                                          
#>  1 hu02          HU02                                                           
#>  2 hu04          HU04                                                           
#>  3 hu06          HU06                                                           
#>  4 hu08          HU08                                                           
#>  5 hu10          HU10                                                           
#>  6 nat_aq        USGS National Aquifers                                         
#>  7 principal_aq  USGS Principal Aquifers                                        
#>  8 sec_hydrg_reg USGS Secondary Hydrogeologic Regions                           
#>  9 gages         Reference Gages                                                
#> 10 mainstems     Reference Mainstems                                            
#> 11 dams          Reference Dams                                                 
#> 12 pws           Public Water Systems                                           
#> 13 states        States                                                         
#> 14 counties      Counties                                                       
#> 15 aiannh        American Indian/Alaska Native Areas/Hawaiian Home Lands (AIANN…
#> 16 cbsa          Core-based statistical areas (CBSA)                            
#> 17 ua10          Urban Areas                                                    
#> 18 places        Places

Each of these sets of “reference features” includes a “uri” which is a persistent way to identify these features and will always lead you back to a representation of the feature when you look it up.

For example, let’s get a subset of data for our Wolf River basin.


wolf_gages <- get_geoconnex_reference(basin, type = "gages")
#> Starting download of first set of features.

geoconnex_gage <- dplyr::filter(wolf_gages, 
                                provider_id == gsub("USGS-", "", site_feature$identifier))

wolf_mainstems <- get_geoconnex_reference(basin, type = "mainstems")
#> Starting download of first set of features.

wolf_mainstem <- dplyr::filter(wolf_mainstems, uri == geoconnex_gage$mainstem_uri)

par(mar = c(0, 0, 0, 0))
plot(sf::st_geometry(basin), col = "grey")
plot(sf::st_geometry(wolf_mainstems), lwd = 0.5, col = "blue", add = TRUE)
plot(sf::st_geometry(wolf_mainstem), lwd = 3, col = "blue", add = TRUE)
plot(sf::st_geometry(wolf_gages), pch = 2, cex = 0.75, add = TRUE)
plot(sf::st_geometry(geoconnex_gage), pch = 17, cex = 1.5, add = TRUE)

The Watershed Boundary Dataset contains hydrologic units that are used as cataloging units for the country. It was developed and improved over the last twenty years and is nearing a complete static state. There are three prominent versions of it available – a snapshot available as part of the NHDPlusV2, a snapshot available as part of and retrieved with get_huc(), and the latest (soon to be final) snapshot available using download_wbd().


wbd_dir <- file.path(nhdplusTools_data_dir(), "wbd_access_demo")
  
wbd_out <- download_wbd(wbd_dir)
#> Compressed WBD file already exists ...
#> Extracting data ...
#> Error in zip::unzip(file, exdir = outdir, overwrite = FALSE) : 
#>   zip error: Cannot open zip file `C:\Users\dblodgett\AppData\Roaming\R\data\R\nhdplusTools\wbd_access_demo\WBD_National_GDB.zip` for reading in file zip.c:141
#> WBD data extracted to: C:\Users\dblodgett\AppData\Roaming/R/data/R/nhdplusTools/wbd_access_demo/WBD_National_GDB.gdb

# zip::unzip doesn't always work
if(length(wbd_out == 0)) {
  f <- list.files(wbd_dir, pattern = ".zip", full.names = TRUE)  
  
  utils::unzip(f, exdir = wbd_dir)
}

wbd_gdb <- list.files(wbd_dir, pattern = ".gdb", full.names = TRUE)

sf::st_layers(wbd_gdb)
#> Driver: OpenFileGDB 
#> Available layers:
#>                     layer_name     geometry_type features fields
#> 1                      WBDHU12     Multi Polygon   103025     20
#> 2             NWISDrainageLine Multi Line String   127876     12
#> 3                       WBDHU8     Multi Polygon     2413     15
#> 4  NonContributingDrainageLine Multi Line String        0     10
#> 5                       WBDHU4     Multi Polygon      245     15
#> 6                      WBDHU16     Multi Polygon     7202     20
#> 7  NonContributingDrainageArea     Multi Polygon        0     12
#> 8             NWISDrainageArea     Multi Polygon     2733     19
#> 9                       WBDHU6     Multi Polygon      405     15
#> 10                      WBDHU2     Multi Polygon       22     15
#> 11                     WBDHU14     Multi Polygon     8138     20
#> 12                     WBDLine Multi Line String   395030      8
#> 13                     WBDHU10     Multi Polygon    18867     17
#> 14           FeatureToMetadata                NA   441934      3
#> 15           ExternalCrosswalk                NA        0      7
#> 16                       HUMod                NA       23      5
#> 17           MetaProcessDetail                NA     1805     16
#> 18            MetaSourceDetail                NA     1808     27
#> 19        ProcessingParameters                NA        2      2
#> 20                UpdateStatus                NA        0      2
#>                 crs_name
#> 1  NAD83 + NAVD88 height
#> 2  NAD83 + NAVD88 height
#> 3  NAD83 + NAVD88 height
#> 4  NAD83 + NAVD88 height
#> 5  NAD83 + NAVD88 height
#> 6  NAD83 + NAVD88 height
#> 7  NAD83 + NAVD88 height
#> 8  NAD83 + NAVD88 height
#> 9  NAD83 + NAVD88 height
#> 10 NAD83 + NAVD88 height
#> 11 NAD83 + NAVD88 height
#> 12 NAD83 + NAVD88 height
#> 13 NAD83 + NAVD88 height
#> 14                  <NA>
#> 15                  <NA>
#> 16                  <NA>
#> 17                  <NA>
#> 18                  <NA>
#> 19                  <NA>
#> 20                  <NA>