1111 Uncertainty Assessment of Radar Rainfall Estimates on Streamflow Simulation - an Application in Southern Brazil

Wednesday, 25 January 2017
4E (Washington State Convention Center )
Aline Schneider Falck, SIMEPAR, Curitiba, Brazil; and C. Beneti, L. Calvetti, R. L. Neundorf, R. T. Inouye, C. Oliveira, B. B. Maske, D. L. Herdies, J. Tomasella, V. Maggioni, F. L. R. Diniz, D. A. Vila, and R. Caram

The performance of hydrological forecast models depends on the reliability and availability of real-time precipitation data. Due to its high spatial-temporal resolution, the availability of radar precipitation estimates is an option as an additional tool  for monitoring and as input of hydrological forecast models. However, radar rainfall estimates have errors associated, for example: echoes from the local topography, conversion of reflectivity in precipitation rate (e.g., Z-R relationship), among others. In this context, we evaluated the use of radar ensemble precipitation estimates generated through the errors associated with its measure, and as a tool in streamflow simulation. To achieve this goal, we calibrated the MHD-INPE hydrological model using high-resolution quantitative precipitation estimates (QPE) developed by the Paraná Meteorological System (SIMEPAR) over upper Iguaçu Basin in Brazil. The QPE method, named Siprec, uses the Poisson´s Equation to merge radar, satellite and rain gauges with 0.04o x 0.04o spatial resolution updated each hour. Then we used the Two Dimensional Satellite Rainfall Error Model (SREM2D), developed by Hossain and Anagnastou (2006), to simulate the error propagation of the radar precipitation estimation. This model quantified the error in space, time, and magnitude. Results showed that SREM2D has the potential to create realistic precipitations ensembles according to the spatial and temporal error structure provided.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner