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Department of Civil and Environmental Engineering Universidade Federal do Paraná Curitiba, Paraná Brasil Alexandre Guetter Streamflow Prediction Validation.

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Presentation on theme: "Department of Civil and Environmental Engineering Universidade Federal do Paraná Curitiba, Paraná Brasil Alexandre Guetter Streamflow Prediction Validation."— Presentation transcript:

1 Department of Civil and Environmental Engineering Universidade Federal do Paraná Curitiba, Paraná Brasil Alexandre Guetter Streamflow Prediction Validation with the Application of Large Basin Rainfall-Runoff Model Second EUROBRISA Workshop - Dartmoor, Devon, UK - 21-24 July 2009

2 Overview of the Brazilian Hydropower System Total annual power production: 445 TWh Annual rate of increase: 6% State-run companies: 90% Demand: Hydropower (>30 MW): 72.6% Hydropower (<30MW): 1.7% Thermal: 14.7% Nuclear: 2.5% Import: 8.5% Brazil World

3 Second EUROBRISA Workshop - Dartmoor, Devon, UK - 21-24 July 2009 Overview of the Brazilian Hydropower System Electricity Demand per Sector: Industrial: 47% Residential: 22% Services: 14% Other: 17% Hourly Demand Curve Peak at 6 pm (residential) Base: hydro+thermal Peak: hydro

4 Second EUROBRISA Workshop - Dartmoor, Devon, UK - 21-24 July 2009 Power production Integrated System Different regional climates grouped on a continental scale Installed Capacity Southeastern/Midwest: 63% Southern: 17% Northeastern: 14% Northern: 6% Seasonal Precipitation Forecasting Skill Adequate: SU-NE-NO Low: SE

5 Second EUROBRISA Workshop - Dartmoor, Devon, UK - 21-24 July 2009 Hydropower Integrated System Capacidade instalada Energia armazenada máxima Installed Capacity Energy Storage Well-defined rainy season Southeastern/Midwest: SON-DJF Northeastern: FMAM (largest storage) Quasi-uniform rainfall Southern (smallest storage) What do we want to predict: Southeastern: in August if SON will have little rainfall – energy production Southeastern: in November if DJF will be very rainy – flood control Northeastern: in January if FMAM will have little rainfall

6 Second EUROBRISA Workshop - Dartmoor, Devon, UK - 21-24 July 2009 The size of our problem: About 60 large hydropower stations: require seasonal streamflow prediction

7 Second EUROBRISA Workshop - Dartmoor, Devon, UK - 21-24 July 2009 Pilot Study: Streamflow Prediction Validation 20 prediction points in 11 large basins 9 basins with 2 points: the most upstream/downstream hydroplants

8 Second EUROBRISA Workshop - Dartmoor, Devon, UK - 21-24 July 2009 Pilot Study: Activities Naturalized streamflow analysis (1931-2007) Diagnostic study of the association between high/low flows and SST anomalies (what is the climate model skill for such forcings?) Data collection: raingauge mean-areal rainfall (variable period) Large-scale rainfall-runoff model calibration Streamflow assimilation: hydrologic model state updating Validation study: use monthly precipitation forecast as input data for the state-updated rainfall-runoff model (1981-2005)

9 Second EUROBRISA Workshop - Dartmoor, Devon, UK - 21-24 July 2009 Naturalized Streamflow Analysis – Iguaçu River

10 Second EUROBRISA Workshop - Dartmoor, Devon, UK - 21-24 July 2009 Naturalized Streamflow Analysis – Iguaçu River

11 Second EUROBRISA Workshop - Dartmoor, Devon, UK - 21-24 July 2009 High Flows and SST anomalies – Iguaçu River High FlowsLow Flows

12 Second EUROBRISA Workshop - Dartmoor, Devon, UK - 21-24 July 2009 High Flows and SST anomalies – Iguaçu River High FlowsLow Flows

13 ENSO Southern Atlantic Run Updated Hydrologic Model Ensemble Streamflow Forecast Select Precipitation Data from Historic Record Associated with Forecast Climate Category Dynamic Model Forecast Streamflow Forecasting Using Either Resampled or Predicted Rainfall

14 Second EUROBRISA Workshop - Dartmoor, Devon, UK - 21-24 July 2009 Rainfall – Runoff Model

15 Second EUROBRISA Workshop - Dartmoor, Devon, UK - 21-24 July 2009 Rainfall-Runoff Model With State-Updating

16 Second EUROBRISA Workshop - Dartmoor, Devon, UK - 21-24 July 2009 Rainfall-Runoff Model With State-Updating Hydrologic Model State Updating α u e α p : fatores de ponderação, a calibrar U : covariance matrix of input errors W : covariance errors of model parameters M(t) : input data sensitivity matrix N(t) : model parameter sensitivity matrix

17 Second EUROBRISA Workshop - Dartmoor, Devon, UK - 21-24 July 2009 Streamflow Prediction Using Resampled Rainfall

18 * This results are not for the Iguaçu Basin Highest Simulation (1981-2005) Lowest Simulation (1981-2005) Forecast Ensemble Streamflow Prediction Using Climate Model Rainfall Streamflow Prediction Using Resampled Rainfall Second EUROBRISA Workshop - Dartmoor, Devon, UK - 21-24 July 2009

19 Conclusions and Recommendations The diagnostic study of the relationship between high/low flows and SST anomalies was accomplished in year-1; The collection of raingauge precipitation data and the rainfall-runoff model calibration was accomplished in year-2; The streamflow prediction validation using seasonal rainfall prediction has not been completed yet; The sensitivity analysis of energy production to rainfall prediction skill is a task for year-3; Selection of period and basin for joint papers.


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