Distributed Models and Flash Flood Forecasting

1. Distributed Models and Flash Flood Forecasting Lecture 6b

2. Model Errors as a Function of Scale Flash floods 260 This study used observed data; confirms numerical experiments from previous studies Distributed model (uncalibrated). Each point is an average peak flow error from approximately 25 events over an eight year study period Oct 1996-Sept.2004. Log-linear regression for distributed model data Scaling relationship for an uncertainty index (Rq) from Carpenter and Georgakakos (2004) (secondary axis)

3. Distributed Model Improvement Compared to Lumped-model Based FFG on Small Basins • Calculate maximum rainfall-to-FFG ratios for selected events based on mean areal rainfall and mean operational gridded FFG. • Compare rank correlations between rainfall-to-FFG ratios and observed flood peaks for 71 events from September 2000-November 2004. Results from Reed et. al. (2007)

4. State Update Frequency Cowleech Fork Sabine, R. at Greenville, TX (GNVT2) Yellow line: 1 hr FFG with hourly updating Pink line: 1 hour FFG with 12 hourly updating White line: 1 hour MAPX • Update frequency would impact a warning decision in this example. • This suggests the need for a WFO distributed hydrologic model (similar to site specific perhaps).

5. Distributed Hydrologic Model with Threshold Frequencies (DHM-TF) Average Recurrence Intervals Associated with the Maximum Forecasts (1/4/1998) 15 UTC 14 UTC Average Recurrence Interval (Years) Generated in hindcast mode using QPE up to the forecast time and 1 hr nowcast QPF beyond 17 UTC 16 UTC

6. Threshold Frequency Approach Benefits • Relative measure (easier to understand than CMS) • Inherent bias correction • Local information often available to help define thresholds (e.g. engineering design, geomorphology studies) • Can be used when ‘bankfull’ flow is not meaningful (e.g. slot canyons) Limitation • Required data may not be available everywhere

7.       Key: We have something  We have data but it is not well organized  We have only scratched the surface Ungauged Flash Flood Forecasting: Moving Beyond FFG Validation GIS-based Parameterization Soils, slopes, landuse • Prototype hydrologic techniques • Gridded-SAC w/ Kinematic Routing (HL-RDHM) • GFFG • FFPI Hydrologic guidance Local knowledge; drainage design standards; flood stage data; geomorphology data; human impacts data • Warning thresholds • Threshold runoff (TR) • Threshold frequency (TF) Threshold calibration

8. Needs • Develop better validation and verification tools and databases • Choose the best techniques for further development (may be regional differences) • Choose the best resolution and update frequency for implementation • Track success and understand the connection to GPRA goals • Decouple the hydrologic model and the warning threshold • Allows for easy local adjustment and “calibration” of warning thresholds • Provide guidance on where data are adequate to support various techniques • Integrate techniques with forecast precipitation (e.g. MPN) to improve lead times • Improve statistical techniques for DHM-TF approach

9. How to Meet the Needs • Real-time prototype • National/large area retrospective model runs • Validation of modeled flows at numerous small stream USGS stations (treated as ungauged) • Gridded verification with retrospective runs

10. Proposed HL-RDHM-TF/MPN Prototype • HL-RDHM/MPN case studies showed that use of 1-hour QPF produces better simulated flow peaks than ‘0 QPF’ and ‘Persistence’ relative to a ‘Perfect QPF’ scenario • Case studies using warning times from actual events suggest a potential for increased lead times • HL-RDHM-TF/MPN real-time prototype benefits • Determine if the concept will work for WFOs • Further evaluate real-time forcing data quality and data latency issues (radar-gauge-satellite QPE, radar only QPE, short-term QPF) • Evaluate higher temporal and spatial resolution forcing data • Provide a framework to evaluate model enhancements

11. Proposed HL-RDHM-TF/MPN Prototype Focus Area • Why here ? • Well-studied, high profile, flash flood prone area • EMPE/MPN prototype already running in this region • High resolution products are available here (1 km, sub-hourly) • Large number of stream gauges are available for validation (41 in 3500 km2 area) • Can compare with MARFC new gridded FFG approach

12. Large Area Studies with HL-RDHM 4/24/2004 7z Snapshots 1 hour rainfall (mm) Soil Saturation (mm) • Benefit flash flood, water resources, and river forecast applications • Quickly identify data problems • Assess applicability to many areas; provide guidance for implementation • Take full advantage of flash flood verification archives and USGS small station data • Improve models and parameterizations Surface Runoff (mm)

13. HL-RDHM Modules Facilitate Retrospective and Real-time Case Studies Real-time QPE/QPF Simulated historical peaks Archived QPE EMPE MMOSAIC (HL) MPE (MARFC) Initial model states Images Temperature? Real-time or HindCast Historical Use to update states once per day. HL-RDHM Sac, rutpix9 or rutpix9loc, FreqParams, HindCast, localFFG HL-RDHM Sac, rutpix9 or rutpix9loc, AnnPeaks Max forecast peak flows (local or cell-to-cell Max forecast peak frequencies (Local or cell-to-cell) Local FFG Web GRASS