Presented by: Diane Cooper Arkansas-Red Basin River Forecast Center Hydrologist

1. An Operational Forecast Office Perspective of the National Weather Service Hydrologic Distributed Modeling System (HDMS) Presented by: Diane Cooper Arkansas-Red Basin River Forecast Center Hydrologist Arkansas Red Basin River Forecast Center

2. Objectives • Overview of HDMS • Preliminary Statistical Analysis

3. Many 4x4 km grid cells embedded in the main basin. HDMS, What is it? A Hydrologic Model that takes into account: • Spatial distribution of hydrologic characteristics across a drainage basin including soils, vegetation, land use, slope • Temporal and spatial distribution of rainfall…4X4 km HRAP grids Maintains spatial Precipitation footprint which impacts hydrologic response.

4. Features Of HDMS • Performs routing simulations using the kinematic wave technique • flow velocity in each element is dependent on flow level • Separates the runoff components • Surface flow: includes impervious, surface and direct runoff • Subsurface flow: includes interflow and baseflow

5. Advantages of HDMS • Potential for improved simulations for: • Basins with non-uniform rainfall. • Basins with relatively impervious areas (surface runoff occurs quickly…i.e. highly populated regions). • Prediction of hydrologic variables at interior points. • Output of Gridded soil moisture states. • Potential to improve flash flood forecasting. • Can account for Land-use change (i.e. burn areas).

6. Statistical Analysis How well is HDMS performing compared to the NWSRFS lumped model? Comparisons of HDMS and NWSRFS SQIN to the observed flow data was performed for 14 of the 21 test basins from Early 2002 through August 2005. For a more “consistent” comparison, the Lumped Model SQIN crest time and peak discharge were compared to the hourly observed time series. This is referred to as the Adj. NWSRFS SQIN. • Note: Seven Basins were not included in the analysis due to: • 4 HDMS test basins are not identified in the NWSRFS Lumped model • 2 basins had a very short NWSRFS SQIN timeseries. • 1 Basin the SQIN has not yet been generated.

7. Statistical Analysis Multi-Year Overall Flow • For 7 of the 14 test basins, the overall flow percent bias is lower with the HDMS simulations • For 8 of the 14 basins, the overall Correlation Coefficient ”R” is closer to 1 with most of them at 0.85 and higher. Note: Due to limitations with the statistical analysis software, the Overall simulations do not use the same observed timeseries dataset. HDMS is compared to the 1-hour observed discharge while NWSRFS is compared to a 6-hour timeseries. Hence, flow is “lost” in the 6- hour timeseries.

8. Statistical Analysis Time to Peak Error • For only 3 of the 14 test basins, the HDMS model performed better than the Adj. NWSRFS on the Timing of the Crest. However when taking the standard deviation into account, HDMS had a lower deviation on half of the basins.

9. Statistical Analysis Peak Discharge • For 8 of the 14 basins, the normalized Mean Peak Discharge Error is better with HDMS. • When evaluating the Standard Deviation and the normalized Peak Discharge “Adj” error, 9 of the 14 basins performed better with HDMS. Plots of normalized HDMS peak discharge errors for Events identified between 4/02 through 8/05.

10. A Closer Look at a Calibrated Basin Statistical analysis for Corbin, KS (CBNK1) – period 1/2002 though 8/2005. • Minor improvement from 0.84 (Lumped) to 0.86 (HDMS) in the correlation coefficient “R”. • Improved simulation of the higher flow events, typically these are under simulated. • Time to crest error showed a decrease with a smaller variability: • HDMS error was 1.9 hrs - most crests late • NWSRFS error was 3.3 hrs – most crests early

11. Focusing on the Events Plot of the Peak Discharge Error for the 26 events identified at CBNK1. The Normalizing Factor is the 2-year flood frequency which is 8990 cfs. Both models give a mix of over and under simulations for events that are 6000 cfs and less. However for the larger events, both models dramatically undersimulate the crest. Plot of the Crest Time Error for the 26 events identified at CBNK1. HDMS tended to be late in its timing of the crest while NWSRFS tended to be early.

12. Summary • HDMS appears to perform as well or better than lumped model for most of test basins…especially in the simulation of peak discharge. • HDMS shows promise as a more advanced Hydrologic Model for NWS operations.

13. Contacts • OHD • Lee Cajina Lee.Cajina@noaa.gov • Seann Reed Seann.Reed@noaa.gov • ABRFC • Diane Cooper Diane.Cooper@noaa.gov • WGRFC • Paul McKee Paul.Mckee@noaa.gov

14. Appendix AHDMS Statistical Analysis Data

15. Appendix BNWSRFS Statistical Analysis Data

16. Appendix CAdj. NWSRFS Statistical Analysis Data

17. Reference Information for Appendices A, B and C. Appendix A, B and C are summaries of selected statistical parameters. The Correlation Coefficient “R” and Percent Bias were derived from the multi-year time series analysis. The HDMS simulation was compared to the one hour observed and the NWSRFS simulation was compared to the six hour observed discharge. The NWSRFS “Adj.” information is a comparison of the six hour NWSRFS simulations to the one-hour instantaneous discharge time series. The ELTT2a Peak Error averages, excludes 2 events which both models performed very poorly. Note: “†” indicates the NWSRFS multi-year analysis began in March 2005, and “*” indicated the analysis began in the summer of 2003.) Elsewhere, the multi-year period was from April 2002 through August 2005. The basins shaded in Pink, the Annual Peak Discharge’s period of record is less than 10 years. So the accuracy of the 2-year frequency peak discharge normalization factor is suspect.

18. Appendix DTable of the HDMS Test Basins