This dataset represents the extent and location of surface depressions derived from the 10-m resolution dataset from the 3D Elevation Program (3DEP). The levet-set algorithm available through the lidar Python package was used the process the DEM and delineate surface depressions at the HU8 watershed scale.
Reference
Wu, Q., Lane, C. R., Wang, L., Vanderhoof, M. K., Christensen, J. R., & Liu, H. (2019). Efficient Delineation of Nested Depression Hierarchy in Digital Elevation Models for Hydrological Analysis Using Level‐Set Method. JAWRA Journal of the American Water Resources Association , 55(2), 354-368. https://doi.org/10.1111/1752-1688.12689
Environment setup
First, create a conda environment with the required packages:
If you are using Google Colab, you can uncomment the following to install the packages and restart the runtime after installation.
1# %pip install leafmap lonboard
1# %pip install leafmap lonboard
Data access
The dataset was derived from the 10-m resolution dataset from the 3D Elevation Program (3DEP) at HU8 watershed scale. The results were then merged at the HU2 watershed scale. Below is a map of the National Hydrography Dataset (NHD) watershed boundary structure.
The script below can be used to access the data using DuckDB. The script uses the duckdb Python package.
The depression dataset has two variations: all_dep and nfp_dep. The all_dep dataset contains all depressions, while the nfp dataset contains non-floodplain depressions.
All depressions
Find out the total number of surface depression in the contiguous United States (CONUS):
