1. El Vado Dam Hydrologic Evaluation Joseph Wright, P.E. Bureau of Reclamation Technical Services Center Flood Hydrology and Meteorology Group

2. Reclamation Dam Safety 2011-SOD-A: “Conduct a corrective action study to address the hydrologic failure modes under Reclamation’s Safety of Dams Program” The 2010 risk analysis identified three potential failure modes that justify taking risk-reduction actions. The potential failure modes included failure of the emergency spillway in addition to the service spillway.

3. Flood Risk For a Corrective Action Study, Reclamation best practices guidelines require that multiple methods are used to estimate the flood risk. Method 1 – We combined observed historical peak discharge data with estimated pre-historical data and fit a statistical distribution to determine annual peak discharge exceedance probabilities. Method 2 – We developed a stochastic event rainfall- runoff model for the watershed above El Vado Dam.

4. Method 1 - Observed Peak Discharge 97 Observations 101 Years 08285500 – Rio Chama below El Vado 1914 – 1924, 7 Years of Data 08283500 – Rio Chama at Park View 1913, 1925 – 1955, 31 Years of Data 08284100 – Rio Chama near La Puente 1956 – 2014, 59 Years of Data

5. Pre-Historical Peak Discharge A flood terrace was observed and studied at 10 different locations downstream of El Vado Dam on the Rio Chama. Soil stratigraphic relationships suggest a large flood occurred at least once during the past 4,300 to 4,500 years. 2-dimensional hydraulic modeling of the Rio Chama below El Vado Dam suggests the peak discharge of this flood was between 11,000 and 14,000 ft 3 /s. A non-exceedance bound with a discharge between 65,000 and 75,000 ft 3 /s has not occurred during the past 8,000 to 10,000 years.

6. Peak Discharge Timeline

7. Peak Discharge Estimate - EMA

8. Method 2 - Stochastic Rainfall-Runoff Model 1.Develop physical based 1-dimensional rainfall-runoff using hydrologic runoff units (HRU’s) 2.Estimate a precipitation frequency curve using the L- Moments method of regional statistics 3.Randomly sample the frequency precipitation curve as well as a storm pattern to determine an annual maximum storm event 4.Randomly determine the initial model conditions 5.Repeat steps 3 and 4 to develop a simulate time-series of maximum flood events 6.Fit a statistical distribution to the time series of annual maximum events

9. Physical Based Model 18 Subbasins

10. Soils 10 Soil Zones (including Water)

11. Mean Annual Precipitation (MAP) 9 MAP Zones

12. Elevation 10 Elevation Zones

13. HRU’s 900 HRU’s (excluding subs) 16,200 unique HRU’s

14. Regional Precipitation Analysis

15. 154 Precipitation Gages 2,911 station years of data L-Moments was used to determine the L-skewness, and L-kurtosis A Generalized Extreme Value (GEV) distribution was fit to the L-Moments

16. Regional Precipitation Analysis

17. Spatial and Temporal Storm Pattern Storm Date Index Freezing Level Height (ft) Index 1000mb Temperature (deg F) Lapse Rate deg F/1000ft Adjusted Point Precipitation (in) May 25, 19751361982.13.680.57 June 1, 19831400286.13.860.59 May 17, 19841307084.54.020.88 March 12, 1985966065.83.504.41 May 8, 19851321882.23.800.06 August 24, 19921501982.73.382.01 September 21, 19971487684.13.502.17 April 30, 19991223279.13.852.64 September 10, 20031439882.43.504.78 May 22, 20051259781.53.930.27

18. Spatial Storm Pattern – Sep 10,2003

19. Temporal Precipitation Pattern Sep 10, 2003 Storm 18 Sub-basins

20. Sep 10, 2003 Storm Max 24hr Sea Level Temperature = 82.4 deg F Max 24hr Freeze Level = 14,398 ft

21. Runoff Calculation Soil Moisture Storage (Root Zone) Gravitational or Intermediate Vadose Zone Surface Runoff Interflow Deep Percolation Rain + SnowmeltEvapotranspiration

22. Runoff Transformation (HEC-1)

23. Calibrate

24. Monte Carlo Select Month of Occurrence Select Storm Characteristics Repeat n Times Rank All Events in Descending Order of Magnitude Develop Flood Magnitude-Frequency Curves Select All Hydrometeorological, Hydrologic, And Hydraulic Parameters that are Dependent Upon Month of Occurrence Select Remaining Parameters that are Independent of Other Parameters Select Remaining Parameters that are Dependent Upon Other Parameters Do Flood Modeling and Reservoir Routing

25. Rank and Plot Peak Discharge

26. El Vado Peak Discharge

27. El Vado Hydrologic Loading This study defines hydrologic loading as Maximum Routed Reservoir Elevation Each SEFM simulated hydrograph is routed through El Vado Dam (As well as Heron Dam) The initial reservoir water surface elevation is determined by sampling historic data. The historic data is correlated with antecedent precipitation. The maximum routed reservoir elevations are ranked and plotted on a probability plot to determine the frequency-elevation curve.

28. El Vado Hydrologic Loading

29. Questions?