Development and evaluation of flood forecasting models for forecast-based financing using a novel model suitability matrix

Jenny Sjåstad Hagen*, Andrew Cutler, Patricia Trambauer, Albrecht Weerts, Pablo Suarez, Dimitri Solomatine

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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 languageEnglish
Article number100076
JournalProgress in Disaster Science
Volume6
DOIs
Publication statusPublished - Apr 2020

Keywords

  • Delft-FEWS
  • Flood forecasting
  • Forecast-based financing
  • Model suitability
  • Neural network
  • Open data

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