Coupling Numerical Weather Prediction and Hydrological Modelling for Runoff Forecast in Southern Brazil

Hydrological modelling is largely applied to forecast the effects of extreme rainfall on runoff dynamics. Little research has been done on coupling numerical weather prediction (NWP) and hydrological modelling to forecast runoff in southern Brazil given the limited hydrometeorological and NWP data a...

Full description

Bibliographic Details
Main Authors: Andre Luis da Silva Bertoncini, Francisco Henrique de Oliveira, Pedro Luiz Borges Chaffe, Jairo Valdati
Format: Article
Language:Portuguese
Published: Universidade Federal de Pernambuco 2016-10-01
Series:Revista Brasileira de Geografia Física
Subjects:
Online Access:https://periodicos.ufpe.br/revistas/rbgfe/article/view/233900
Description
Summary:Hydrological modelling is largely applied to forecast the effects of extreme rainfall on runoff dynamics. Little research has been done on coupling numerical weather prediction (NWP) and hydrological modelling to forecast runoff in southern Brazil given the limited hydrometeorological and NWP data available for the region. In this study, we evaluate a coupling method of NWP and a semi-distributed hydrological model to forecast runoff for a humid subtropical catchment (286 km²) in southern Brazil, state of Santa Catarina, municipality of Vidal Ramos. The HEC-HMS hydrological model was manually calibrated and validated using data of 2013. Four post-processing techniques of rainfall estimates were applied on rainfall products of two NWP models (BRAMS and GFS), providing rainfall input data for forecasting runoff. Then, a scenario of runoff forecast of an event in June 2014 was analyzed. We found the tested coupling method was able to forecast runoff with a lead time of 24 hours in which the best post-processing technique of rainfall is the “poor man ensemble” between the 90th quantile sampling of BRAMS and the mean of the GFS product. Hence, the validation of NWP products must be done carefully to avoid the propagation of uncertainties through a flood forecasting system.
ISSN:1984-2295