Evaluating Satellite Rainfall Products for Hydrological Applications Mekonnen Gebremichael, and Dawit Zeweldi Civil & Environmental Engineering Department University of Connecticut

Evaluating Satellite Rainfall Products (PERSIANN) Outline Introduction The Approach The Study Region Evaluating Satellite Rainfall Products (PERSIANN) Performance Statistics Evaluating Utility in Hydrological Applications A Blueprint Conclusions

Introduction Two validation approaches: Evaluating against independent rainfall observations 2. Evaluating error propagation in hydrological applications

Introduction High-resolution satellite rainfall products analyzed: PERSIANN, CMORPH (to follow) PERSIANN IR-PMW merged algorithm: Neural Network 4-km hourly over the United States Validation Approach Evaluation against NEXRAD radar rainfall observations Evaluation in hydrological applications (to follow) Study region Little Washita watershed in Oklahoma, USA Good quality NEXRAD data; subject of several major experiments (NASA, USDA, etc.)

Introduction: The Little Washita Watershed Area ~ 600 km2

Introduction: Inter-annual variability

Performance Statistics: 4-km, hourly time scale Bias

Performance Statistics: watershed-averaged, hourly time scale DJF JJA

Performance Statistics: e-folding distance

Performance Statistics of the Largest Storm

Performance Statistics of Storms Storm Duration Storm rainfall , mm E-folding distance: eP / eN Peak Storm Rate: qP / qN RMSE mm Correlation Beginning Ending NEXRAD PERSIANN 06/04/02:22 06/05/02:16 37.31 47.62 8.60 0.92 6.11 0.57 08/11/04:07 08/11/04:14 30.07 26.46 8.17 0.62 2.76 0.63 03/03/04:18 03/04/04:23 53.82 58.12 0.89 0.94 8.59 10/07/04:09 10/07/04:18 36.21 28.16 0.70 2.82 0.40 09/19/02:04 09/19/02:13 24.90 14.95 4.26 1.34 8.45 0.23 05/17/02:07 05//17/02:12 36.59 18.78 0.41 0.42 3.20 05/14/03:03 05/14/03:13 21.56 9.30 1.07 0.46 5.74 10/08/02:06 10/09/02:22 72.46 15.84 0.55 0.26 7.16 0.48 10/28/02:19 10/29/02:06 30.73 13.40 0.71 0.79 5.07 0.25 09/08/02:16 09/09/02:19 44.95 5.49 0.09 8.00 0.76

Performance Statistics: Scaling with Temporal Scale DJF JJA What is the appropriate space-time scale?

Raster-Grid Models (e.g. MIKE SHE) Hydrological Application Which is the hydrologic model apt for the satellite rainfall observations? Numerical simulations of catchment hydrologic processes require a method for representing a basin. Methods can be categorized as lumped versus distributed modeling (contours, grids, polygons, TINs). Raster-Grid Models (e.g. MIKE SHE) Predictive performance of hydrologic models as a function of model complexity and data availability (Grayson and Bloschl 2001). versus Basin-Averaged Models (e.g. HEC-HMS)

Performance Statistics: A Blueprint for Hydrological Applications Reference Rainfall Products Hydrologic Model Simulated Watershed Response Observed Hydrologic Model Error Satellite Rainfall Products Simulated Watershed Response Rainfall Error Propagation Hydrologic Model

Conclusions Need for rigorous validation of high-resolution satellite rainfall products, at various space-time scales, for different regimes Need for identifying hydrologic model complexity level apt for satellite-rainfall inputs, and sensitivity to space-time resolutions

Thank you