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The University of Mississippi Geoinformatics Center Lance D. Yarbrough, PI Joel S. Kuszmaul, Co-PI

Integration of Global Precipitation Measurement Data Product with the Hydrologic Engineering Center-Hydrologic Modeling System. The University of Mississippi Geoinformatics Center Lance D. Yarbrough, PI Joel S. Kuszmaul, Co-PI. Experiment Collaborators. MRC–RPC team

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The University of Mississippi Geoinformatics Center Lance D. Yarbrough, PI Joel S. Kuszmaul, Co-PI

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  1. Integration of Global Precipitation Measurement Data Product with theHydrologic Engineering Center-Hydrologic Modeling System The University of Mississippi Geoinformatics Center Lance D. Yarbrough, PI Joel S. Kuszmaul, Co-PI

  2. Experiment Collaborators • MRC–RPC team • Lance D. Yarbrough and Joel S. Kuszmaul • Tennessee Technological University • Faisal Hossain • NASA at GSFC • Bob Adler • SSAI at GSFC • George Huffman • University of Connecticut • Amvrossios C. Bagtzoglou

  3. Objectives • Evaluate the effects of spatial downscaling of satellite precipitation data for flood modeling.

  4. Background Realistic flood modeling in medium-large river basins requires rainfall data at hydrologically relevant scales ranging from 1-5 km. However, satellite rainfall data has historically been available at spatial resolutions that can be considered somewhat coarse for predicting the dynamic flood phenomenon (~ 25-100km). As a natural response to this limitation that has persisted for over a decade, hydrologists have devised numerous statistical spatial downscaling schemes till now.

  5. Global Precipitation Measurement (GPM) • Launch: June 2013 • GPM will initiate the measurement of global precipitation, a key climate factor

  6. Hydrologic Modeling System (HEC-HMS)

  7. General Data Flow Diagram

  8. Questions to answer in RPC • Which option is more appropriate: • an error propagation • a probabilistically downscaled? • How much to downscale? • Which product is more beneficial? • What are the implications?

  9. Earth System Models: • Army Corps of Engineers HEC-HMS model • Spatial analysis algorithms • Benefits: • Identify water supply demands • Now-casting of real-time flooding events • Flood hazard assessment • Asset Management and flood mitigation • Decisions Support: • HAZUS-MH (FEMA) • Predictions and Measurements: • Event/Seasonal runoff for modeled basins • Point specific hydrographs • Flood water extent • Earth Observations: • GPM proxy data Expected Impacts

  10. Location of basins • Upper Cumberland River, TN • Upper Yazoo Basin, MS • Pearl River, MS

  11. Upper Cumberland River Basin

  12. Event Selection

  13. Native Scale (0.25°) 3B42 Precipitation Data versus Streamflow 3B41 Precipitation Data versus Streamflow

  14. Uncertainty of Simulated Streamflow Using SREM2D at Native Scale (0.25°) 3B41 Precipitation Data versus Streamflow

  15. Uncertainty of Simulated Streamflow Using SREM2D at Native Scale (0.25°) 3B42 Precipitation Data versus Streamflow

  16. Preliminary Results • 3B42RT with error modeling at native scale is most realistic • 3B41RT yield more confident flow estimates when flood modeling

  17. Upcoming Tasks • Calibrate HEC-HMS model for the last basin in the study • Complete comparison of results for all three basins • Complete and submit manuscripts for peer-review publication

  18. Timeline/Schedule

  19. Publications • Harris, A. , S. Rahman, F. Hossain, L. D. Yarbrough, A. C. Bagtzolgou and G. Easson, 2007. Satellite-based Flood Modeling using TRMM-based rainfall products and Statistical Downscaling, Sensors, 7, pp. 3416–3427.

  20. Poster/Abstract • Rahman, S., A.C. Bagtzoglou, L.D. Yarbrough, R. Adler, G. Huffman, and F. Hossain, 2007. Investigating Satellite Rainfall Based Flood Modeling in Anticipation of GPM: Understanding the Worth of Spatial Downscaling and Satellite Rainfall Uncertainty. Eos Trans. AGU, Fall Meeting Supplement, Abstract IN43B-1176.

  21. Upper Yazoo River Basin

  22. Pearl River Basin

  23. 3B41 Precipitation Data 3B42 Precipitation Data 0.125° 0.0625° 0.03125°

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