PRAISE-ME: Probabilistic Rainfall Nowcasting for Landslide Early Warning

A methodology for probabilistic rainfall nowcasting, based on a coupling between a stochastic model and a Numerical Weather Prediction model. The hybrid model, named PRAISE-ME, was developed by Davide Luciano De Luca of the University of Calabria and applied to a landslide case study in Montenero di Bisaccia, Central Italy, from March 2006. The model provides quantitative predictions intended for integration into Rainfall-Runoff or Landslide prediction models.

Use Cases

• Improving flood and landslide early warning systems based on the described probabilistic rainfall predictions.
• Coupling stochastic and Numerical Weather Prediction models for improved hydrological-scale forecasting as described.
• Providing probabilistic inputs for empirical landslide forecasting models like FLaIR, as illustrated in the application case.

Strengths

• Describes a specific, integrated modeling methodology (PRAISE-ME) for a clear application domain.
• Includes a real-world application case study for a documented landslide event in Montenero di Bisaccia, March 2006.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Davide Luciano De Luca, University of Calabria, via paperswithcode.

Collection Method

Proposed methodology coupling a stochastic model with a Numerical Weather Prediction model.

Time Range

Includes a case study from March 2006.

Freshness

Last updated date is unknown.

Geography

Case study focused on Montenero di Bisaccia, Central Italy.