# NHGF STAC Catalog Datasets

The National Hydrologic Geospatial Fabric (NHGF) STAC catalog provides access to numerous climate and hydrologic datasets through the SpatioTemporal Asset Catalog (STAC) specification.

```{list-table} NHGF STAC catalog datasets
:header-rows: 1
:stub-columns: 1
:width: 100
:widths: auto

* - Dataset
  - Description
  - Collection ID
  - Temporal Coverage
  - Spatial Coverage

* - [CONUS404](https://registry.opendata.aws/wrf-se-ak-ar-conus404/)
  - High-resolution daily meteorological data from WRF model at 4km resolution with 40 years of daily values
  - conus404-daily
  - 1979-2022
  - Continental US, Alaska

* - [GridMET](https://www.climatologylab.org/gridmet.html)
  - Daily meteorological data for continental US including temperature, precipitation, humidity, wind
  - gridMET
  - 1979-2022
  - Continental US

* - [LOCA2](https://gdo-dcp.ucllnl.org/downscaled_cmip_projections/)
  - Localized Constructed Analogs (LOCA) downscaled CMIP6 climate projections
  - LOCA2
  - Historical & Future
  - North America

* - [MACA](https://www.climatologylab.org/maca.html)
  - Multivariate Adaptive Constructed Analogs climate projections (VIC hydrology)
  - maca-vic, macav2
  - Historical & Future
  - Continental US

* - [BCCA/BCSD](https://gdo-dcp.ucllnl.org/downscaled_cmip_projections/)
  - Bias Corrected Constructed Analogs and Spatially Downscaled climate projections
  - bcca, bcsd_mon_vic, bcsd_obs, cmip5_bcsd
  - Historical & Future
  - Continental US

* - [PRISM v2](https://www.prism.oregonstate.edu/)
  - Parameter-elevation Regressions on Independent Slopes Model climate data
  - PRISM_v2
  - 1895-present
  - Continental US

* - [TopoWx](https://www.scrim.psu.edu/resources/topowx/)
  - High-resolution gridded daily minimum and maximum temperature
  - TopoWx2017
  - 1948-2016
  - Continental US

* - [SSEBop ET](https://earlywarning.usgs.gov/ssebop/modis)
  - Operational Simplified Surface Energy Balance actual evapotranspiration
  - ssebopeta
  - 2000-present
  - Continental US

* - [Stage IV](https://www.emc.ncep.noaa.gov/mmb/ylin/pcpanl/stage4/)
  - Multi-sensor precipitation estimates from NCEP
  - stageiv_combined
  - 2002-present
  - Continental US

* - [Alaska ET](https://www.usgs.gov/centers/alaska-science-center)
  - Alaska-specific evapotranspiration estimates
  - alaska_et_2020
  - Various
  - Alaska

* - [Western US Hydrology](https://www.usgs.gov/mission-areas/water-resources)
  - Western US hydrologic modeling datasets
  - WUS_HSP
  - Various
  - Western US

* - [Puerto Rico](https://www.usgs.gov/centers/caribbean-florida-water-science-center)
  - Climate and hydrologic data for Puerto Rico
  - PuertoRico, puerto_rico
  - Various
  - Puerto Rico

* - [Hawaii](https://www.usgs.gov/centers/pacific-islands-water-science-center)
  - Climate data for Hawaiian Islands
  - hawaii_2018
  - Various
  - Hawaii

* - [Red River](https://www.usgs.gov/mission-areas/water-resources)
  - Regional climate projections for Red River basin
  - RedRiver, red_river_2018
  - Various
  - Red River Basin

* - [Climate Resilience](https://www.usgs.gov/climate)
  - Climate resilience and adaptation datasets
  - cprep
  - Various
  - Continental US

* - [Sea Level Rise](https://www.usgs.gov/centers/coastal-marine-hazards-and-resources-center)
  - Sea level rise projections and coastal impacts
  - slr2d
  - Various
  - US Coastal Areas

* - [ICLUS](https://www.epa.gov/gcx/iclus-integrated-climate-and-land-use-scenarios)
  - Integrated Climate and Land Use Scenarios
  - iclus
  - 2000-2100
  - Continental US

* - [PACIS](https://www.usgs.gov/climate-climate-variability-and-change/science/pacific-islands-climate-science-center)
  - Pacific Islands Climate Science datasets
  - pacis
  - Various
  - Pacific Islands

* - [WICCI](https://wicci.wisc.edu/)
  - Wisconsin Initiative on Climate Change Impacts
  - wicci
  - Various
  - Wisconsin/Upper Midwest

* - [MOWS](https://www.usgs.gov/mission-areas/water-resources)
  - Modeling of Watershed Systems
  - mows
  - Various
  - Various basins

* - [California BCM](https://ca.water.usgs.gov/projects/reg_hydro/)
  - California Basin Characterization Model
  - CA-BCM-2014
  - Various
  - California

* - [SERAP](https://www.usgs.gov/centers/southeast-climate-adaptation-science-center)
  - Southeast Regional Assessment Project
  - serap
  - Various
  - Southeastern US

* - [TTU](https://www.depts.ttu.edu/nwi/)
  - Texas Tech University regional climate datasets
  - TTU_2019
  - Various
  - Texas/Southwest

* - [Cooper](https://www.usgs.gov/mission-areas/water-resources)
  - Regional hydrologic modeling datasets
  - cooper
  - Various
  - Various regions

* - [GMO](https://www.usgs.gov/mission-areas/water-resources)
  - Geospatial modeling and optimization datasets
  - GMO, GMO_New
  - Various
  - Various regions

* - [FLET](https://www.usgs.gov/mission-areas/water-resources)
  - Flow and Load Estimation Tool datasets
  - FLET
  - Various
  - Various basins

* - [Permafrost](https://www.usgs.gov/centers/alaska-science-center)
  - Alaska/Arctic permafrost modeling datasets
  - AIEM_permafrost
  - Various
  - Alaska/Arctic

* - [Notaro](https://nelson.wisc.edu/sage/faculty-staff/notaro-michael.php)
  - Regional climate analysis datasets
  - notaro_2018
  - Various
  - Great Lakes region

```

## Data Access

All NHGF STAC datasets are accessible through:

- **STAC API**: [https://api.water.usgs.gov/gdp/pygeoapi/stac](https://api.water.usgs.gov/gdp/pygeoapi/stac)

## Usage with gdptools

`NHGFStacData` is a factory that auto-detects whether a STAC collection is Zarr-backed or
GeoTIFF-backed and returns the appropriate class (`NHGFStacZarrData` or `NHGFStacTiffData`).
Use the `get_stac_collection()` helper to retrieve a collection by its ID.

### Zarr example (CONUS404 daily data)

```python
from gdptools import NHGFStacData
from gdptools.helpers import get_stac_collection

collection = get_stac_collection("conus404_daily")
user_data = NHGFStacData(
    source_collection=collection,
    source_var=["PWAT"],
    target_gdf=watersheds,
    target_id="huc12",
    source_time_period=["2020-01-01", "2020-01-31"],
)
# user_data is an NHGFStacZarrData instance
```

### GeoTIFF example (NLCD land cover)

```python
collection = get_stac_collection("nlcd-LndCov")
user_data = NHGFStacData(
    source_collection=collection,
    source_var=["LndCov"],
    target_gdf=watersheds,
    target_id="huc12",
    source_time_period=["2021-01-01", "2021-12-31"],
)
# user_data is an NHGFStacTiffData instance
```

See the [User Data Classes](user_input_data_classes.md) documentation for the full API reference.