Abstract
Forecast-based financing is a financial mechanism that facilitates humanitarian actions prior to anticipated floods by triggering release of pre-allocated funds based on exceedance of flood forecast thresholds. This paper presents a novel model suitability matrix that embeds application-specific needs and contingencies at local level on a pilot project of forecast-based financing. The added value of this flexible framework is demonstrated on a set of hydrological and machine learning models. The model suitability matrix facilitates transparency and traceability of subjectivity in model evaluation. This paper advocates a stronger interface between model developers and end users for upscaling of forecast-based financing.
Original language | English |
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Article number | 100076 |
Number of pages | 16 |
Journal | Progress in Disaster Science |
Volume | 6 |
DOIs | |
Publication status | Published - 2020 |
Keywords
- Delft-FEWS
- Flood forecasting
- Forecast-based financing
- Model suitability
- Neural network
- Open data