ARTÍCULO
TITULO

UTILIZAÇÃO DE PREVISÕES DE PRECIPITAÇÃO DE MODELOS ATMOSFÉRICOS WRF, GFS E GEFS NA BACIA HIDROGRÁFICA DO RIO AVE (PORTUGAL) PARA GESTÃO OPERACIONAL DE UM SISTEMA DE DRENAGEM

José Luis da Silva Pinho    
António Pereira    
Rolando Faria    

Resumen

Os sistemas de previsão e alerta utilizados na gestão de recursos hídricos e operação de sistemas de drenagem tiveram desenvolvimentos significativos nos últimos anos. Esses desenvolvimentos resultaram da disponibilidade de informações meteorológicas em tempo real, em particular de medições por sensores em satélites, medição através de radar meteorológico e de previsões de modelos atmosféricos para diferentes horizontes temporais. Todos os modelos de previsão ambiental são incertos e essa incerteza é variável no tempo e no espaço. Este trabalho tem como objetivo apresentar os resultados da avaliação da evolução do erro associado a diferentes previsões de curto prazo. A plataforma Delft-FEWS (Flood Early Warning System) foi utilizada para proceder à importação e processamento de dados de observações e previsões disponíveis para a bacia do rio Ave, localizada no norte de Portugal. Os dados meteorológicos medidos foram obtidos no Sistema Nacional de Informações de Recursos Hídricos (SNIRH), em quatro estações meteorológicas instaladas na bacia em estudo e dados de refletividade medidos pelo radar meteorológico operado pela Meteogalicia. As previsões avaliadas correspondem às precipitações simuladas por modelos atmosféricos desenvolvidos pela National Oceanic and Atmospheric Administration (NOAA) e Meteogalicia, nomeadamente os modelos Global Forecast System (GFS), Global Ensemble Forecast System (GEFS) e Weather Research and Forecasting, (WRF) operado pela Meteogalicia. A incerteza associada às precipitações previstas foi avaliada considerando horizontes de previsão de um a quatro dias. Os melhores resultados foram obtidos para o modelo WRF durante eventos de precipitação ocorridos entre janeiro de 2017 e maio de 2018 e apresentaram médias de erros relativos que variaram entre 7% (um dia de previsão) e 29% (quatro dias). O sistema implementado permite, assim, do ponto de vista operacional, antecipar com antecedência de dois dias eventos extremos. USE OF PRECIPITATION FORECASTS FROM WRF, GFS AND GEFS ATMOSPHERIC MODELS AT RIVER AVE BASIN (PORTUGAL) FOR OPERATIONAL MANAGEMENT OF A DRAINAGE SYSTEMABSTRACTThe forecasting and warning systems used in water resources management and drainage systems operation have had significant developments in recent years. These developments resulted from the availability of meteorological information in real time, in particular from measurements by sensors in satellites, measurement through meteorological radar and forecasts of atmospheric models for different time horizons. All environmental forecasting models are uncertain and this uncertainty varies over time and space. This work aims to present the results of the evaluation of the evolution of the error associated with different short-term forecasts. The Delft-FEWS (Flood Early Warning System) platform was used to import and process observation and forecast data available for the river Ave basin, located in northern Portugal. The measured meteorological data were obtained from the National Water Resources Information System (SNIRH), at four new meteorological stations installed in the basin and radar reflectivity data measured by the meteorological radar operated by Meteogalicia. The forecasts evaluated correspond to the rainfall simulated by atmospheric models developed by the National Oceanic and Atmospheric Administration (NOAA) and Meteogalicia, namely the Global Forecast System (GFS), Global Ensemble Forecast System (GEFS) and Weather Research and Forecasting (WRF) model operated by Meteogalicia. The uncertainty associated with the predicted rainfall was evaluated considering forecast horizons of one to four days. The best results were obtained for the WRF model during precipitation events that occurred between January 2017 and May 2018 and presented average relative errors that varied between 7% (one forecast day) and 29% (four days). The implemented system thus allows, from an operational point of view, to forecast extreme events in advance of two days.

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