fp-hyde (Hydrological Data Engines) is part of the FloodPROOFS modelling and forecasting chain developed by CIMA Research Foundation and the c-hydro initiative.
It provides the data-processing core of the FloodPROOFS system, organizing and transforming hydrological, meteorological, and geospatial datasets for use in forecasting, risk assessment, and decision-support applications.
HyDE manages the entire data workflow — from raw inputs (e.g., rainfall, temperature, soil moisture) to structured datasets used by the Hydrological Model Continuum (HMC) and analysis tools (HAT).
- 🛰️ Input Management — handles multi-source meteorological and hydrological datasets (gridded, station-based, remote sensing).
- 🧩 Data Preprocessing — temporal and spatial interpolation, resampling, and harmonization.
- 🗺️ Geospatial Support — full GIS integration (raster/vector) with NetCDF, GeoTIFF, and shapefile support.
- 📦 Flexible Configuration — YAML/JSON configuration for reproducible workflows.
- 🔄 Integration with FloodPROOFS Chain — serves as input engine for HMC (model) and HAT (analysis).
- 🧠 Modular Architecture — easy to extend with new drivers and plugins.
- 📊 Event-based and Continuous Mode — process both historical archives and real-time feeds.
fp-hyde/
│
├── app/ # Main application scripts (processing routines)
├── bin/ # Command-line tools and launcher scripts
├── docs/ # Documentation and manuals
├── tools/ # Utility modules and support functions
├── examples/ # Example configurations and demo data
└── README.md # This file
- Operating System: Linux (Debian/Ubuntu recommended)
- Python: 3.8 or newer
- Additional tools:
- Fortran 2003+ (optional, for linked model components)
- QGIS ≥ 2.18
- R ≥ 3.4.4 (for downstream analysis modules)
- Libraries:
netCDF4,h5py,numpy,pandas,gdal,matplotlib,scipy, etc.
-
Clone the repository:
git clone https://github.com/c-hydro/fp-hyde.git cd fp-hyde -
(Optional but recommended) Create a virtual environment:
python3 -m venv venv source venv/bin/activate -
Install dependencies:
pip install -r requirements.txt
-
Configure environment variables (paths, data directories, etc.) as described in the
docs/folder.
---##
Execution examples are provided as shell wrappers inside the repository (under app/app_map/...).
Use these scripts as the source of truth for invocation, arguments, and environment handling.
For instance:
- ECMWF 0.1° NWP: app_nwp_ecmwf_0100.sh
Explore adjacent folders for other models and data types (e.g., ICON, LAMI-2i, observations). The scripts document the expected configuration files and runtime options for each application.
HyDE is the data layer of the FloodPROOFS ecosystem:
- HyDE – data acquisition, harmonization, and preprocessing
- HMC – distributed hydrological model
- HAT – analysis and visualization toolkit
Together, these components enable operational flood forecasting, impact assessment, and risk-management services.
- Real-time flood forecasting for regional protection agencies
- Seasonal hydrological analysis and drought assessment
- Validation and quality control of meteorological datasets
- Event reanalysis and hydrological benchmarking
Contributions are welcome!
Please:
- Fork the repository
- Create a feature branch (
git checkout -b feature/my-feature) - Commit your changes
- Open a pull request
Check the CONTRIBUTING.md (if available) or contact the maintainers for more details.
Distributed under the European Union Public Licence (EUPL 1.2).
See the LICENSE file for details.
CIMA Research Foundation
📍 Savona, Italy
🌐 https://www.cimafoundation.org
✉️ info@cimafoundation.org
Developed and maintained under the c-hydro initiative to support open and reproducible hydrological forecasting.