Leveraging new models and data to improve flood stage forecast. Improving Flood Stage Forecasting in the Feather River Watershed. September 11 th 2015

Transcription

1 Leveraging new models and data to improve flood stage forecast Improving Flood Stage Forecasting in the Feather River Watershed September 11 th 2015 Mitch Russo, P.E. (DWR) Ashok Bathulla, P.E., CFM (GEI) Ron Manning, P.E. (GEI)

2 River Stage Forecast Preparation Forecasts preparation requires the joint efforts of federal, state, and local agencies DWR/CNRFC products: o Precipitation o Temperature o Reservoir Inflows o River flow & stage hydrographs Legend MajorStreams CNRFC Boundary!( Daily Forecast Points ( Other Forecast Points Reservoirs/Lakes

3 Study Purpose Improve real-time reservoir inflow forecast Improve real-time river stage forecast Improve integration of data among different models Improve flood risk management Improve the use of real-time data to provide flood alerts and warnings Improve state and local emergency preparedness and response

4 Overview 1. Inflow Forecasting using HEC-HMS Data Processing Operational Model Development Inflow Forecasting Results 2. River Stage Forecasting using HEC-RAS Model Development Hydrologic Data Ingestion Stage Forecasting Results

5 Pilot Watershed: Upper Feather River Why the Upper Feather River Watershed? Oroville Reservoir is hub of State Water Project Levee Breaches during historical flood events Oroville and New Bullards Bar jointly operated to manage downstream flooding Feather River Basin: 3,600 sq.mi - Area ~9,000 ft - Elevation Range 3.2 million ac-ft - Annual Average Runoff

6 PART 1: INFLOW FORECASTING (LAKE OROVILLE)

7 Feather River HEC-HMS Model Source: Climate Variability Sensitivity Study (CVSS) (2012) Calibration: January 2006 Flood Event Components: Precipitation, Temperature, and Snow (computed) Data sources: Gridded forecasted from CNRFC Point observed from CDEC HEC-GageInterp (point data to grid)

8 Observed Gridded Precipitation Gage Station

9 Observed Gridded Temperature Gage Station

10 Inflow Forecast Workflow QC & Geo-Process (GageInterp) Observed Point Data (CDEC) Forecast Gridded Data (CNRFC) Data Acquisition Data Processing Model Create HEC- HMS Input Dataset Configure HEC-HMS Compute View & Compare Results

11 Inflow Forecast Workflow QC & Geo-Process (GageInterp) Observed Point Data (CDEC) Forecast Gridded Data (CNRFC) Data Acquisition Data Processing Model Create HEC- HMS Input Dataset Configure HEC-HMS Compute View & Compare Results

12 Inflow Forecast Workflow QC & Geo-Process (GageInterp) Observed Point Data (CDEC) Forecast Gridded Data (CNRFC) Data Acquisition Data Processing Model Create HEC- HMS Input Dataset Configure HEC-HMS Compute View & Compare Results

13 Inflow Forecast Workflow QC & Geo-Process (GageInterp) Observed Point Data (CDEC) Forecast Gridded Data (CNRFC) Data Acquisition Data Processing Model Create HEC- HMS Input Dataset Configure HEC-HMS Compute View & Compare Results

14 Inflow Forecast Workflow Software Tool QC & Geo-Process (GageInterp) Observed Point Data (CDEC) Forecast Gridded Data (CNRFC) Forecasts produced every 6 hours Need operational tool that executes in timely manner Solution: Software Automation Create HEC- HMS Input Dataset Configure HEC-HMS Compute View & Compare Results

15 Inflow Forecast Tool Toolbar Tabulated Graphical

16 Inflow Forecast Result (2012) (cont.) Flow (1,000 cfs) Observed Run 11/29/ /30/ /1/

17 Summary Project Accomplishments Combine different data types into single coherent dataset Converted planning model into an operational tool Greatly improve time efficiency of process Potential Uses Applicable to other models/watersheds Add more detail/resolution to improve the model Add ability to modify forecast data before simulating Caveat: Forecasts only as good as inputs

18 PART 2: RIVER STAGE FORECASTING

19 Feather River HEC-RAS Model Hydraulic vs. Hydrologic routing New step in DWR (JOC) River Stage Forecasting Feather River HEC-RAS model based off of CVFED HEC- RAS model. CVFED RAS model is calibrated and validated to 1997 and 2006 Floods Modified for real-time stage forecasting use: Geometric (extent, configuration, resolution) Computational (calculation options, tolerances, timestep) Software (RAS 5.0)

20 Stage Forecasting Workflow Create Input Dataset Observed & Forecasted Data (CNRFC) Configure HEC-RAS Compute HEC-RAS View & Compare Results

21 Stage Forecasting Workflow Create Input Dataset Observed & Forecasted Data (CNRFC) Configure HEC-RAS Compute HEC-RAS View & Compare Results

22 Stage Forecasting Workflow Create Input Dataset Observed & Forecasted Data (CNRFC) Configure HEC-RAS Compute HEC-RAS View & Compare Results

23 Stage Forecasting Workflow Create Input Dataset Observed & Forecasted Data (CNRFC) Configure HEC-RAS Compute HEC-RAS View & Compare Results

24 Lake Oroville Butte Slough Sutter Buttes Feather River (Upper) Bullards Bar Reservoir Canal Marysville Yuba City Linda Star Bend Feather River (Lower) Olivehurst Nelson Slough Feather Main Stem Fremont Weir

25 Model execution, verification, and results Minor adjustments to improve stability Setup to route 10-day forecast flows Typical run time under 10 minutes Verified for different flow regimes Stage and flow hydrographs at key locations

26 Stage (Ft) Stage at Boyds Landing (2006) Stage hydrographs in Boyds Landing HEC-RAS Routed Observed 12/25/2005 0:00 12/27/2005 0:00 12/29/2005 0:00 12/31/2005 0:00 1/2/2006 0:00 1/4/2006 0:00

27 58 Stage at Yuba City, CA (2011) Stage ( Ft) HEC-RAS Routed 42 Observed 40 3/1/2011 0:00 3/6/2011 0:00 3/11/2011 0:00 3/16/2011 0:00 3/21/2011 0:00 3/26/2011 0:00 3/31/2011 0:00

28 Conclusions Test the implementation of hydraulic routing into the forecast process Test the automation of data transfers among different models Study the improvement in stream flow routing Lay the ground work for near real-time flood inundation mapping

29 Future Work Extend to the remainder of the Sacramento Basin Implementation of hydraulic routing into the Forecasting Process Flood Inundation Mapping Questions?

30 Topographic