Extreme precipitation-streamflow event in the river Araguari basin, Amapá / Brazil

O objetivo da investigação foi analisar vazões extremas ocorridas entre 9 e 14 de abril de 2011 na bacia do Rio Araguari-AP. A metodologia consistiu de três etapas principais: 1) re-análise da precipitação estimada pelo Modelo BRAMS (Brazilian in Development Regional Atmospheric Model System),utilizando como suporte a sinótica do mesmo período; 2) análise de vazão nas seções de monitoramento hidrológico em Porto Platon, Capivara e Serra do Navio (ADCP-Accustic Doppler Profiller Current); 3) análise estatística da série histórica de vazões máximas em Porto Platon utilizando distribuição de Gumbel. Observou-se que o modelo BRAMS capturou parcialmente o padrão do sistema de precipitação quando comparado com a análise sinótica e com os dados da literatura, mas demandando ainda otimização na representação de respostas hidrológicas extremas. Em Porto Platon foi registrada uma vazão recorde de 4036 m3/s, cujo comportamento foi analisado sob a ótica dos mecanismos disponíveis de monitoramento no Estado. Concluiu-se que tais eventos extremos são pouco detectáveis e oferecem riscos consideráveis aos usuários da bacia. A previsão de vazão, baseada na série hidrológica disponível, era de 100 anos de retorno, mas as análises revelaram que este período seria de 360 anos, indicando significativa fragilidade do sistema de previsão de eventos extremos no Estado.The objective of this investigation was to analyse the extreme river flows which have occurred between 9 and 14 April 2011 in the Rio Araguari-AP. The methodology consisted of three main steps: 1) re-analysis of precipitation estimated by the BRAMS (Brazilian Development in Regional Atmospheric Model System) model using the synoptic of the same period as support, 2) analysis of streamflow in sections of hydrological monitoring in Porto Platon, Capivari and Serra do Navio (ADCP-Accustic Profiller Doppler Current); 3) statistic analysis of the time series of maximum river flows in Porto Platon using Gumbel distribution. It was observed that the BRAMS system partially captured the standard precipitation when compared with the synoptic analysis and literature data, but the extreme hydrological responses representation still needs an optimization. In Porto Platon a flow record of 4036 m3 /s was recorded, whose behavior was analyzed from the perspective of the available monitoring mechanisms in the State. It was concluded that such extreme events are poorly detectable and offer considerable risks to users of the basin. The stream flow prediction based on available hydrological series was 100 years recurrence, but the analysis have revealed that this period would be 360 years, indicating significant deficiency of the prediction system of extreme events in the State

Assessment of Precipitation and Evapotranspiration in an Urban Area Using Remote Sensing Products (CHIRP, CMORPH, and SSEBop): The Case of the Metropolitan Region of Belem, Amazon

The aim of this study was to assess precipitation (P) and actual evapotranspiration (ET) by analyzing data from in situ stations compared with remote sensing products. Climate Hazards Center InfraRed Precipitation (CHIRP) and Climate Prediction Center morphing technique (CMORPH) were used for P and Operational Simplified Surface Energy Balance (SSEBop) was used for ET. The P in situ data for six stations were also compared to a reference station in the city. ET was analyzed for a single in situ station. The region chosen for this study was the Metropolitan Area of Belem (MAB), close to the estuary of the Amazon River and the mouth of the Tocantins River. Belem is the rainiest state capital in Brazil, which causes a myriad of challenges for the local population. The assessment was performed using the statistical metrics root-mean-square error (RMSE), normalized root-mean-square error (NRMSE), mean bias error (MBE), coefficient of determination (R2), regression slope, and Nash–Sutcliffe coefficient (NS). For the reference station, the automatic and conventional CHIRP and CMORPH results, in mm/month, were as follows: automatic CHIRP: RMSE = 93.3, NRMSE = 0.32, MBE = −33.54, R2 = 0.7048, Slope = 0.945, NS = 0.5668; CMORPH: RMSE = 195.93, NRMSE = 0.37, MBE = −52.86, R2 = 0.6731, Slope = 0.93, NS = 0.4344; conventional station CHIRP: RMSE = 94.87, NRMSE = 0.32, MBE = −33.54, R2 = 0.7048, Slope = 0.945, NS = 0.5668; CMORPH: RMSE = 105.58, NRMSE = 0.38, MBE = −59.46 R2 = 0.7728, Slope = 1.007, NS = 0.4308. In the MAB region, ET ranges on average between 83 mm/month in the Amazonian summer and 112 mm/month in the Amazonian winter. This work concludes that, although CMORPH has a coarser resolution than CHIRP for the MAB at a monthly resolution, both remote sensing products were reliable. SSEBop also showed acceptable performance. For analyses of the consistency of precipitation time series, these products could provide more accurate information. The present study validates P and ET from remote sensing products with station data in the rain-dominated urban MAB

Remote Sensing Products Validated by Flux Tower Data in Amazon Rain Forest

This work compares methods of climate measurements, such as those used to measure evapotranspiration, precipitation, net radiation, and temperature. The satellite products used were compared and evaluated against flux tower data. Evapotranspiration was validated against the SSEBop monthly and GLEAM daily and monthly products, respectively, and the results were RMSE = 24.144 mm/month, NRMSE = 0.223, r2 = 0.163, slope = 0.411; RMSE = 1.781 mm/day, NRMSE = 0.599, r2 = 0.000, slope = 0.006; RMSE = 36.17 mm/month, NRMSE = 0.401, r2 = 0.002, and slope = 0.026. Precipitation was compared with the CHIRPS data, K67 was not part of the CHIRPS station correction. The results for both the daily and monthly comparisons were RMSE = 18.777 mm/day, NRMSE = 1.027, r2 = 0.086, slope = 0.238 and RMSE = 130.713 mm/month, NRMSE = 0.706, r2 = 0.402, and slope = 0.818. The net radiation validated monthly with CERES was RMSE = 75.357 W/m2, NRMSE = 0.383, r2 = 0.422, and slope = 0.867. The temperature results, as compared to MOD11C3, were RMSE = 2.829 °C, NRMSE = 0.116, r2 = 0.153, and slope = 0.580. Comparisons between the remote sensing products and validation against the ground data were performed on a monthly basis. GLEAM and CHIRPS daily were the data sets with considerable discrepancy