Gitdeeper4/chi-model

Seismic Source → NSWE Propagation → Bathymetric Modulation (BECF)
              → Front Stability Tracking (HFSI)
              → Spectral Energy Analysis (SDB, KPR)
              → Shoreline Boundary Resolution (SBSP)
              → Micro-Vorticity Correction (SMVI)
              → CHI Composite Index → Run-up Forecast + Alert

w₁(WCC)=0.18  w₂(KPR)=0.16  w₃(HFSI)=0.17  w₄(BECF)=0.20
w₅(SDB)=0.11  w₆(SBSP)=0.13  w₇(SMVI)=0.05

git clone https://gitlab.com/gitdeeper4/tsu-wave.git
cd tsu-wave
docker-compose up -d

pip install tsu-wave

# 1. Clone
git clone https://gitlab.com/gitdeeper4/tsu-wave.git
cd tsu-wave

# 2. Virtual environment
python3 -m venv venv && source venv/bin/activate

# 3. Dependencies
pip install --upgrade pip
pip install -r requirements.txt

# 4. Compile Fortran NSWE solver
cd src/core && f2py -c nswe_solver.f90 -m nswe_solver && cd ../..

# 5. Configure
cp config/config.example.yml config/config.yml

# 6. Initialize database
python scripts/init_db.py

# 7. Launch
python -m tsuwave.api.main        # API server → :8000
streamlit run tsuwave/dashboard/app.py  # Dashboard → :8501

from tsuwave import TSUWave

# Initialize
tsw = TSUWave()

# Get Composite Hazard Index for a coastal zone
chi = tsw.get_chi(zone="hilo_bay_hawaii")
print(f"CHI: {chi:.3f}")

# Get all seven parameters
params = tsw.get_parameters(zone="hilo_bay_hawaii")
for name, value in params.items():
    print(f"  {name}: {value:.4f}")

# Run-up forecast
forecast = tsw.forecast_runup(zone="khao_lak", source="sumatra")
print(f"Predicted run-up: {forecast['height_m']:.1f} m")
print(f"Lead time: {forecast['lead_time_min']} min")

# Validate against historical event
result = tsw.validate(event="tohoku_2011")
print(f"MAPE: {result['mape']:.1f}%")

# Active events
GET  /api/v1/events/active

# CHI time series for an event
GET  /api/v1/events/{id}/chi

# All 7 parameters
GET  /api/v1/events/{id}/parameters

# Pre-computed BECF for a coastal zone
GET  /api/v1/coastal/{zone}/becf

# On-demand run-up forecast
POST /api/v1/forecast/runup

# Active alerts
GET  /api/v1/alerts/current

# Real-time WebSocket stream
WS   /ws/v1/realtime

tsu-wave monitor                          # Live event monitor
tsu-wave chi --zone hilo_bay              # Compute CHI
tsu-wave validate --event tohoku_2011    # Historical validation

tsu-wave/
├── src/
│   ├── core/           ── Physics Engine (NSWE solver, CHI, BECF, SMVI)
│   ├── ingest/         ── Data Ingestion (DART, tide gauges, bathymetry)
│   ├── signals/        ── Signal Processing (bandpass, STA/LTA, FFT)
│   ├── database/       ── TimescaleDB + Redis cache
│   ├── api/            ── FastAPI REST + WebSocket
│   └── dashboard/      ── Streamlit monitoring UI
├── tests/              ── 47/47 tests passing ✅
├── data/               ── ETOPO1/GEBCO grids, BECF maps, validation events
├── notebooks/          ── 6 Jupyter analysis notebooks
├── config/             ── YAML configuration files
├── deployment/         ── Docker, Kubernetes, Ansible
└── docs/               ── Full documentation suite

Baladi, S., Marchetti, E., Watanabe, K., Petersen, L., & Hassan, A. (2026).
TSU-WAVE: A Multi-Parameter Hydrodynamic Framework for Real-Time Tsunami Wave
Front Evolution, Energy Transfer Analysis, and Coastal Inundation Forecasting
(v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.18679361

@software{baladi2026tsuwave,
  author       = {Baladi, Samir and Marchetti, Elena and Watanabe, Kenji
                  and Petersen, Lars and Hassan, Amira},
  title        = {{TSU-WAVE}: A Multi-Parameter Hydrodynamic Framework for
                  Real-Time Tsunami Wave Front Evolution, Energy Transfer
                  Analysis, and Coastal Inundation Forecasting},
  version      = {1.0.0},
  year         = {2026},
  month        = {February},
  publisher    = {Zenodo},
  doi          = {10.5281/zenodo.18679361},
  url          = {https://doi.org/10.5281/zenodo.18679361}
}