Rainfall uncertainty in flood forecasting: Belgian case study of rivierbeek


Abstract:

Rainfall forecast errors are the key sources of uncertainty in flood forecasting. To quantify this uncertainty operational flood forecasting centers make use of rainfall forecasts obtained by ensemble pbkp_redicting systems (EPS). The EPS forecasts are generated by perturbing the initial conditions of numerical weather pbkp_rediction models. Question, however, remains whether these EPS cover the real forecast uncertainty range and whether the EPS-based uncertainty estimates are similar to the ones obtained by statistical methods. Both questions are addressed in this research based on data of a flood forecasting system in Belgium. Comparison is made between the uncertainty bounds generated by EPS and by a Monte Carlo-based statistical method after historical forecasted rainfall uncertainty analysis. The latter analysis calculates the error between forecasted and observed catchment rainfall, taking into account the dependency on lead time and rainfall depth. The forecasted rainfall errors are described by truncated normal distributions, which allow to calculate the full uncertainty distribution on a deterministic rainfall forecast. It is concluded that the EPS may underestimate the influence of the total forecasted rainfall uncertainty. For the Belgian case study of the Rivierbeek, the forecasted rainfall uncertainty explains 30% of the total river flow forecast uncertainty.

Año de publicación:

2014

Keywords:

  • flood forecasting
  • rainfall
  • Ensemble pbkp_rediction system
  • UNCERTAINTY

Fuente:

scopusscopus

Tipo de documento:

Article

Estado:

Acceso restringido

Áreas de conocimiento:

  • Hidrología
  • Hidrología
  • Ciencia ambiental

Áreas temáticas:

  • Geología, hidrología, meteorología