Package | Description | Status |
---|---|---|
Hydrodata | Access NWIS, HCDN 2009, NLCD, and SSEBop databases | |
PyGeoOGC | Send queries to any ArcGIS RESTful-, WMS-, and WFS-based services | |
PyGeoUtils | Convert responses from PyGeoOGC's supported web services to datasets | |
PyNHD | Navigate and subset NHDPlus (MR and HR) using web services | |
Py3DEP | Access topographic data through National Map's 3DEP web service | |
PyDaymet | Access Daymet for daily climate data both single pixel and gridded |
PyNHD is a part of Hydrodata software stack and provides access to WaterData and NLDI web services. These two web services can be used to navigate and extract vector data from NHDPlus V2 database such as catchments, HUC8, HUC12, GagesII, flowlines, and water bodies. Moreover, PyNHD gives access to an item on ScienceBase called Select Attributes for NHDPlus Version 2.1 Reach Catchments and Modified Network Routed Upstream Watersheds for the Conterminous United States. This item prvoides over 30 attributes at catchment-scale based on NHDPlus ComIDs. These attributes are avilable in three categories:
- Local (local): For individual reach catchments,
- Total (upstream_acc): For network-accumulated values using total cumulative drainage area,
- Divergence (div_routing): For network-accumulated values using divergence-routed.
A list of these attributes for each characteristic type can be accessed using nhdplus_attrs
function.
Additionally, PyNHD offers some extra utilities for processing the flowlines:
prepare_nhdplus
: For cleaning up the dataframe by, for example, removing tiny networks, adding ato_comid
column, and finding a terminal flowlines if it doesn't exist.topoogical_sort
: For sorting the river network topologically which is useful for routing and flow accumulation.vector_accumulation
: For computing flow accumulation in a river network. This function is generic and any routing method can be plugged in.
These utilities are developed based on an R
package called
nhdplusTools.
You can try using PyNHD without installing it on you system by clicking on the binder badge below the PyNHD banner. A Jupyter notebook instance with the Hydrodata software stack pre-installed will be launched in your web browser and you can start coding!
Please note that since Hydrodata is in early development stages, while the provided functionaities should be stable, changes in APIs are possible in new releases. But we appreciate it if you give this project a try and provide feedback. Contributions are most welcome.
Moreover, requests for additional functionalities can be submitted via issue tracker.
You can install PyNHD using pip
after installing libgdal
on your system
(for example, in Ubuntu run sudo apt install libgdal-dev
):
$ pip install pynhd
Alternatively, PyNHD can be installed from the conda-forge
repository
using Conda:
$ conda install -c conda-forge pynhd
Let's explore the capabilities of NLDI
. We need to instantiate the class first:
from pynhd import NLDI, WaterData, NHDPlusHR
import pynhd as nhd
First, let’s get the watershed geometry of the contributing basin of a
USGS station using NLDI
:
nldi = NLDI()
station_id = "01031500"
basin = nldi.get_basins(station_id)
The navigate_byid
class method can be used to navigate NHDPlus in
both upstream and downstream of any point in the database. Let’s get ComIDs and flowlines
of the tributaries and the main river channel in the upstream of the station.
flw_main = nldi.navigate_byid(
fsource="nwissite",
fid=f"USGS-{station_id}",
navigation="upstreamMain",
source="flowlines",
distance=1000,
)
flw_trib = nldi.navigate_byid(
fsource="nwissite",
fid=f"USGS-{station_id}",
navigation="upstreamTributaries",
source="flowlines",
distance=1000,
)
We can get other USGS stations upstream (or downstream) of the station and even set a distance limit (in km):
st_all = nldi.navigate_byid(
fsource="nwissite",
fid=f"USGS-{station_id}",
navigation="upstreamTributaries",
source="nwissite",
distance=1000,
)
st_d20 = nldi.navigate_byid(
fsource="nwissite",
fid=f"USGS-{station_id}",
navigation="upstreamTributaries",
source="nwissite",
distance=20,
)
Now, let’s get the HUC12 pour points:
pp = nldi.navigate_byid(
fsource="nwissite",
fid=f"USGS-{station_id}",
navigation="upstreamTributaries",
source="huc12pp",
distance=1000,
)
Next, we retrieve the medium- and high-resolution flowlines within the bounding box of our
watershed and compare them. Moreover, Since serveral web services offer access to NHDPlus database,
NHDPlusHR
has an argument for selecting a service and also an argument for automatically
switching between services.
mr = WaterData("nhdflowline_network")
nhdp_mr = mr.bybox(basin.geometry[0].bounds)
hr = NHDPlusHR("networknhdflowline", service="hydro", auto_switch=True)
nhdp_hr = hr.bygeom(basin.geometry[0].bounds)
Moreover, WaterData
can find features within a given radius (in meters) of a point:
eck4 = "+proj=eck4 +lon_0=0 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs"
coords = (-5727797.427596455, 5584066.49330473)
rad = 5e3
flw_rad = mr.bydistance(coords, rad, loc_crs=eck4)
flw_rad = flw_rad.to_crs(eck4)
Since NHDPlus HR is still at the pre-release stage let's use the MR flowlines to
demonstrate the vector-based accumulation.
Based on a topological sorted river network
pynhd.vector_accumulation
computes flow accumulation in the network.
It returns a dataframe which is sorted from upstream to downstream that
shows the accumulated flow in each node.
PyNHD has a utility called prepare_nhdplus
that identifies such
relationship among other things such as fixing some common issues with
NHDPlus flowlines. But first we need to get all the NHDPlus attributes
for each ComID since NLDI
only provides the flowlines’ geometries
and ComIDs which is useful for navigating the vector river network data.
For getting the NHDPlus database we use WaterData
. Let’s use the
nhdflowline_network
layer to get required info.
wd = WaterData("nhdflowline_network")
comids = flw_trib.nhdplus_comid.to_list()
nhdp_trib = wd.byid("comid", comids)
flw = nhd.prepare_nhdplus(nhdp_trib, 0, 0, purge_non_dendritic=False)
To demostrate the use of routing, let's use nhdplus_attrs
function to get list of available
NHDPlus attributes
char = "CAT_RECHG"
area = "areasqkm"
local = nldi.getcharacteristic_byid(comids, "local", char_ids=char)
flw = flw.merge(local[char], left_on="comid", right_index=True)
def runoff_acc(qin, q, a):
return qin + q * a
flw_r = flw[["comid", "tocomid", char, area]]
runoff = nhd.vector_accumulation(flw_r, runoff_acc, char, [char, area])
def area_acc(ain, a):
return ain + a
flw_a = flw[["comid", "tocomid", area]]
areasqkm = nhd.vector_accumulation(flw_a, area_acc, area, [area])
runoff /= areasqkm
Since these are catchment-scale characteristic, let’s get the catchments then add the accumulated characteristic as a new column and plot the results.
wd = WaterData("catchmentsp")
catchments = wd.byid("featureid", comids)
c_local = catchments.merge(local, left_on="featureid", right_index=True)
c_acc = catchments.merge(runoff, left_on="featureid", right_index=True)
More examples can be found here.
Contributions are very welcomed. Please read CONTRIBUTING.rst file for instructions.