Effeciantly subset existing ugrid to a smaller ugrid given a bbox or polygon

[saeed-moghimi-noaa]

Hi There,

Is there a suggested tool to perform efficient subset of a large ugrid data set to a new ugrid (xarray) with the consistent connectivity given a bbox or polygon as an input using xugrid tool set? I would like to retain all the properties of the parent mesh such as node coordinates and connectivity and values.

something like:

new_ugrid = subset (large_input_ugrid, bbox)

Thanks.

[Huite]

Hi @saeed-moghimi-noaa

The user guide part on selection should give relevant information on this: https://deltares.github.io/xugrid/examples/selection.html

The .ugrid.sel method will return subsets with valid topologies.

Note that this currently selects by the face coordinates, which may not be what you desire. See issue #182 for a workaround (although to be clear: we should tackle it with a proper solution so it doesn't require a workaround).

Selecting by polygon can be done relatively easily, but also requires more on than step. I'll open an issue for the functionality.

For now, one could use this multi-step approach:

import xugrid as xu
import geopandas as gpd

# Read a polygon into a geodataframe
gdf = gdp.read_file("my-polygon.shp")

# Read the ugrid file containing a single variable
uda = xu.open_dataarray("my-ugrid.nc")

# Burn the vector geometry in to the unstructured topology
burned = xu.burn_vector_geometry(gdf, uda, column="id")  # let's assume there's an id colum with a value of 1

# Use the burned result to select only the values in the polygon, then drop the faces outside of the polygon
selection = uda.where(burned == 1).dropna(uda.ugrid.grid.face_dimension)

There's a bit more info on "burning" vector geometries in this part of the user guide: https://deltares.github.io/xugrid/examples/vector_conversion.html

In all cases, this results in a new, consistent, geometry. In case you want to preserve the original topology, you would use .where instead and "mask" all values outside of the selection by NaN.