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FloodCastBench
==============

Synthetic-backed inundation benchmark adapter aligned to the FloodCastBench evaluation ecosystem.

Overview
--------

FloodCastBench is the public inundation adapter used by PyHazards for raster flood prediction benchmarks.

The current implementation is synthetic-backed, but it preserves the raster task and metric surface used by the shared flood evaluator.

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

.. list-table::
   :widths: 28 72
   :stub-columns: 1

   * - Provider
     - FloodCastBench ecosystem surfaced through a PyHazards adapter
   * - Hazard Family
     - Flood
   * - Source Role
     - Inundation Benchmark
   * - Coverage
     - Benchmark-aligned flood inundation samples
   * - Geometry
     - Raster inundation sequences
   * - Spatial Resolution
     - Benchmark-defined raster tiles
   * - Temporal Resolution
     - Short history windows with next-horizon inundation targets
   * - Update Cadence
     - Generated locally for smoke and benchmark-alignment runs
   * - Period of Record
     - Synthetic-backed benchmark adapter
   * - Formats
     - PyTorch tensors via the dataset registry
   * - Registry Entry
     - ``floodcastbench_inundation``

Data Characteristics
--------------------

- Multi-step raster inputs paired with next-horizon inundation targets.
- Registry-backed benchmark adapter rather than a raw external dataset ingestion path.
- Intended for pixel-level evaluation such as IoU and pixel MAE.

Typical Use Cases
~~~~~~~~~~~~~~~~~

- Smoke tests for FloodCast and UrbanFloodCast.
- Shared flood benchmark runs on inundation tasks.
- Regression checks for raster flood prediction outputs.

Access
------

Use the links below to access the upstream source or its public documentation.

- `FloodCastBench repository <https://github.com/HydroPML/FloodCastBench>`_

PyHazards Usage
---------------

Use this adapter when you want the public FloodCastBench-aligned inundation surface exposed by the flood benchmark.

Registry Workflow
~~~~~~~~~~~~~~~~~

Primary dataset name: ``floodcastbench_inundation``

.. code-block:: python

   from pyhazards.datasets import load_dataset

   data = load_dataset(
       "floodcastbench_inundation",
       micro=True,
       history=4,
       channels=3,
   ).load()

   train = data.get_split("train")
   print(train.inputs.shape, train.targets.shape)

Related Coverage
~~~~~~~~~~~~~~~~

**Benchmarks:** :doc:`Flood Benchmark </benchmarks/flood_benchmark>`, :doc:`FloodCastBench </benchmarks/floodcastbench>`

**Representative Models:** :doc:`FloodCast </modules/models_floodcast>`, :doc:`UrbanFloodCast </modules/models_urbanfloodcast>`

Inspection Workflow
-------------------

This dataset is currently surfaced as a registry-backed benchmark adapter,
so there is no standalone inspection CLI documented for it.

Notes
-----

- This is a synthetic-backed benchmark adapter rather than a full FloodCastBench ingestion pipeline.

Reference
---------

- `FloodCastBench <https://github.com/HydroPML/FloodCastBench>`_.