.. This file is generated by scripts/render_model_docs.py. Do not edit by hand.

FloodCast
=========

Overview
--------

``floodcast`` is the first public inundation model in the staged PyHazards flood roadmap.

At a Glance
-----------

.. grid:: 1 2 4 4
   :gutter: 2
   :class-container: catalog-grid

   .. grid-item-card:: Hazard Family
      :class-card: catalog-stat-card

      .. container:: catalog-stat-value

         Flood

      .. container:: catalog-stat-note

         Public catalog grouping used for this model.

   .. grid-item-card:: Maturity
      :class-card: catalog-stat-card

      .. container:: catalog-stat-value

         Implemented

      .. container:: catalog-stat-note

         Catalog maturity label used on the index page.

   .. grid-item-card:: Tasks
      :class-card: catalog-stat-card

      .. container:: catalog-stat-value

         1

      .. container:: catalog-stat-note

         Inundation

   .. grid-item-card:: Benchmark Family
      :class-card: catalog-stat-card

      .. container:: catalog-stat-value

         :doc:`Flood Benchmark </benchmarks/flood_benchmark>`

      .. container:: catalog-stat-note

         Primary benchmark-family link used for compatible evaluation coverage.


Description
-----------

``floodcast`` is the first public inundation model in the staged PyHazards flood roadmap.

The adapter uses shared raster tensors so it can be benchmarked through the ``flood.inundation`` evaluator without dataset-specific glue code.

Benchmark Compatibility
-----------------------

**Primary benchmark family:** :doc:`Flood Benchmark </benchmarks/flood_benchmark>`

**Mapped benchmark ecosystems:** :doc:`FloodCastBench </benchmarks/floodcastbench>`

External References
-------------------

**Paper:** `Large-scale flood modeling and forecasting with FloodCast <https://doi.org/10.1038/s41586-024-08028-8>`_ | **Repo:** `Repository <https://github.com/HydroPML/FloodCast>`__

Registry Name
-------------

Primary entrypoint: ``floodcast``

Supported Tasks
---------------

- Inundation

Programmatic Use
----------------

.. code-block:: python

   import torch
   from pyhazards.models import build_model

   model = build_model(name="floodcast", task="regression", in_channels=3, history=4)
   preds = model(torch.randn(2, 4, 3, 16, 16))
   print(preds.shape)

Notes
-----

- Outputs are next-horizon inundation depth rasters.