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WMA integrated data and tools catalog - Use Cases ()
A use case demonstrates how WMA uses datasets and tools to build workflows and answer science questions in a reproducible and reusable way.
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| Name | Domain | Description | Language |
|---|---|---|---|
3dep-grid-to-line | Topography Stream Characteristics | In this example, a set of NHD stream-segments accessed using the HyRiver package. A USGS 3DEP Elevation dataset is pulled in using the ClimateR-Catalog. Finally, gdptools is used to interpolate the 3DEP elevation to the NHD stream-segments. | Python |
Advanced NHDPlus Network Attributes | Hydrology | Summary of NHDPlus network attributes that are central to the reference fabric, NLDI, and NHDPlus data model generally. Highlights the nhdplusTools package as well as the NHD data use in many aspects of the NHGF | R |
Aggregate gridMET data to NHD Flowlines and sample points | Domain Agnostic | Using the gdptools python package, aggregate gridMET climate data to a NHD Flowline and return the aggregated values at regularly space sample points. | Python |
Aggregation workflow | Hydrology | Constructs a set of basins based on NWIS gage locations to support the WaterWatch replacement effort using the workflow for the development of the National Reference Hydrologic Geospatial Fabric (hydrofabric). | |
Asynchronous Processing via OGC API Processes | Domain Agnostic | This application describes how to execute gdptools processes asynchronously using the OGC processes API via web service calls to pygeoapi. | Python |
Calibrating Hydraulic Models Using River Inundation Polygons | Hydrology Remote Sensing Stream Characteristics | Using DSWE-derived inundation polygons to calibrate or validate hydraulic models like HEC_RAS | Python |
Catchment characteristics ScienceBase collection | Climate Geology Hydrogeology Hydrology Infrastructure Land Cover Soils Stream Characteristics Topography Water Use | Multiple variables of natural and anthropogenic landscape features linked to NHDPlus v2 (stream segments, catchments, and upstream watersheds) within the conterminous United States. These data allow researchers to acquire landscape information for both catchments and full upstream watersheds of specific stream reaches anywhere in the within the conterminous United States without having to perform specialized geospatial processing. | R |
CONUS-extent Surficial Groundwater Model | Hydrogeology | This use case demonstrates and links to a notebook for inspection, analysis, and subsetting models from the Zell and Sanford (2020) CONUS-extent MODFLOW groundwater simulation dataset | Python |
Conversion of the LOCA downscaled climate projection dataset to ZARR | Climate | As a data repository maintainer responsible for providing archived content in analysis ready formats, USGS data managers need to migrate data originally optimized for on premise infrastructure and legacy data services to analysis ready cloud optimized data. This use case is a summary of notes taken while working through such a process on the Localized Constructed Analogues dataset. | Python |
Creating standardized geophysical datasets | Geophysical | Airborne geophysical data are taken from a variety of input formats and standardized into a NetCDF structure using the GSPy tool. This example shows how the GSPy is used to create a GS-structured NetCDF file, which improves the transferability and interoperability of geophysical data. | Python |
Cross Section App | Elevation Riparian zones | This is a Shiny for Python app that uses GDPtools to create cross sections and query gridded datasets. The mapping is done in iPyleaflet and the plots are done with Plotly. On the web map, the user can use Leaflet tools to draw a line or polyline anywhere on the map. Then, using the layer menu, the user can select or deselect gridded datasets to be queried (elevation is always queried by default). Once the layers are selected, the user will use the ‘Submit’ button and GDPtools will process the query and the results will be displayed on the app in a Plotly graph. These graphs are interactive and downloadable. | Python |
Dockerized Deployment of Data Services Through Pygeoapi | Domain Agnostic | Using Pygeoapi to distribute custom analysis-ready data services to the public. | API |
Dockerized Deployment of GeoServer and Analysis Ready Data | Domain Agnostic | Using GeoServer to distribute analysis-ready data to the public via standardized, open source, dynamic services. | API |
Environmental Data Retrieval (EDR) Use Case | Domain Agnostic | Overview of accessing spatio-temporal data via the OGC EDR API via a deployed pygeoapi instance. | Python |
Exploring and utilizing geophysical datasets | Geophysical | Using the GSPy tool, standardized NetCDF files of airborne geophysical data can be easily explored and visualized. This application demonstrates how airborne geophysical data can be used and analyzed for service to WMA studies | Python |
gdptools-climater-catalog | Climate Hydrology | In this notebook we will spatially interpolate a set of variables including actual evapotranspiration (aet), potential evapotranspiration (pet), and Palmer Drought Severity Index (PDSI) from the Terraclimate dataset to a fabric of HUC12 in the Delaware River Basin. The bulk of the processing is done with the Geo Data Processing Tools (GDPTools) python package. A highlight of this use-case is introducing the ClimateR-Catalog of common climate datasets. | Python |
gdptools-conus404 | Climate Hydrology | This notebook demonstrates the use of GDPTools for spatially interpolating (Aggregation) Conus404 data to a set of HUC12s in the Delaware River Basin. | Python |
gdptools-nlcd | Land Cover Hydrology | The 2019 Land Cover product from the National Land Cover Database is interpolated to the Delaware River Basin HUC12s using the Geo Data Processing Tools (gdptools) grid-to-polygon area-weighted statistics tools. | Python |
gdptools-swb-weather | Climate Hydrology | This notebook demonstrates the use of GDPTools and xarray to subset and process CONUS404 data to work as inputs to a soil-water-balance (swb) model. | Python |
Ground water data in cross sections | NA | Add a water table line and geologic stratigraphy to stream cross sections where data exist in the water well database | |
Headwater channel extension from burned area floods | Fire Hydrology River Corridors | Link headwater channel extension – channel initiation and erosion with post wildfire runoff and existing debris flow susceptibility mapping, landslide risk maps, could be link downstream to streamstats “fire aware” and fire aware streamgage network, post fire water quality modeling and remote sensing applications | |
hi-raster-summarization | Hydrology Topography Land Use Land Cover | This notebook demonstrates the use of gdptools for raster summarization for model parameterization inputs | Python |
Integrating aquifers into the reference fabric/HY features framework | Hydrology | Harmonize the underlying aquifer framework to basin geometry and properties generated by a point-of-interest | R |
Mapping GFv2.0 to NHD High-Resolution | Hydrology | Use a combination of the GUI-based tool HydroAdd and custom R package nhdplusTools to hydrographically address (index) points of interest (POIs) to the high-resolution NHD network of streams. POIs previously addressed to medium-resolution NHDPlus v2 and released as GFv2.0 dataset will be re-addressed with the goal of discretizing a stream network into critical, functional sections (flowpaths). Points including confluences, terminal ends, waterbody inlets and outlets, streamgages, and thermoelectric plants will be categorized and addressed with various levels of precision. | R |
National and Regional Rescaling of Geospatial Attributes | Climate Geophysical Hydrogeology Hydrology Infrastructure Land Cover Snow Soils Stream Characteristics Topography | This repository contains a {targets} pipeline to pull existing geospatial attributes that are referenced to NHDPlusv2 COMIDs and to rescale the values to the WBD HUC 12 (10-2020 instance) resolution that is used in the Regional IWAAs Methods for Base Evaluation (RIMBE) project. The pipeline develops these datasets for CONUS whereas the quarto doc implements the same logic for the Delaware River Basin-an example IWS Basin of interest. | R |
Nhdplusv2 attributes to huc12 python | Catchment characteristics | This notebook demonstrates generating weights, or creating a crosswalk between a source GeoDataFrame and a target GeoDataFrame using gdptools. The example here demonstrates calculating weights and interpolating values from NHDPlus version 2 flowline catchment polygons to HUC-12 polygons encompassing the conterminous United States. | Python |
NWWDB-Tools: Estimating aquifer hydraulic properties from pumping tests | Hydrogeology | The NWWDB-Tools Python package contains functionality for estimating aquifer transmissivity and hydraulic conductivity based on the results of of single-well, constant-rate pumping tests. | Python |
NWWDB-Tools: Harmonizing lithologic logs using natural language processing | Hydrogeology | The NWWDB-Tools Python package contains functionality for harmonizing lithologic logs using natural language processing. | Python |
Open Storage Network (OSN) Pod Access | Domain Agnostic | This notebook describes how to access data on the Open Storage Network (OSN) Pod through the AWS command line interface and Python/xarray. | NA |
poly-to-poly-interpolation | Hydrology | This notebook demonstrates the generation and aggregation from one polygon source to another polygon target. The example here demonstrates mapping USGS National Hydrologic Model output to CONUS HUC12s. Calculation of area weighted statistics as shown here is useful process in many water budget or landscape analysis applications. | Python |
PRMS parameter generation | Hydrology | Work with the tools team products to dynamically generate static and dynamic model parameters such as land cover | Python |
Rapid burned gages assessment | Wildfire | Identify stream gages whose upstream contributing areas intersect with historical or active wildfires, modify accumulated geospatial and environmental attributes with weighted percentage of upstream burned area, and use this information to prioritize new siting or to increase monitoring at existing gages and (or) high-value infrastructure. | R |
Regridding baseline data for model calibration and validation | Hydrology | Aggregate NLDAS soil moisture for a baseline dataset for model validation and calibration | Python |
Regridding gridded climate data to NHD HUC12 polygons | Climate | Use the gdptools python package to aggregate gridMET climate forcing dataset to HUC12 polygons within a drainage basin | Python |
sbtools and sciencebasepy packages Use Case: River Corridors on ScienceBase | Domain Agnostic | Demonstration of the sciencebasepy and sbtools python and R packages, respectively, enable powerful querying capabilities in the context of the River Corrdiors on ScienceBase App, sbtools and sciencebasepy is used to curate an inventory of specifically river-corridor related USGS datasets on the backend that is ultimately pushed to the web application for easy, intuitive, and visual exploration of the curated datasets on the front end. | Python and R |
Static landscape characteristics (3DEP) - generate reach-average cross-section for NHD segments | Hydraulics | Use the nldi-cross-section tool to generate a reach-averaged cross-section per NHD segment | Python |
Water Use modeling and GFv2.0 | Water Use | Develop frameworks within the reference fabric for addressing and integrating different types of water use location data (drinking supply service areas, thermoelectric plants, irrigated fields, interbasin transfers) | |
Water well database exploration and subsetting | NA | Explore water well database for relevant data and deliver data | |
What is a "reference hydrologic geospatial fabric"? | Hydrology | With the emergence of continental scale hydrologic modeling by federal, acedemic, and private sector organizations, the need for a shared system of identifiers and network connections for data and model integration has become a pressing need. This use case summary describes use cases that demand a shared “reference hydroglogic geospatial fabric” and uses that need to illustrate the anatomy and key characteristics of such a fabric. | Agnostic |
Zarr-OPeNDAP Use case | Domain Agnostic | Zarr interoperability with OpenDAP | Python |