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Integrating Climate Data Into Forecasting
Hydrologic Inflow
TWCA
June 20, 2019
Tarrant Regional Water District
in collaboration with
Hydros Consulting
One of 3
Large Raw
Water
Suppliers in
North
Central
Texas
1
2
INTEGRATED
PIPELINE
PROJECT
3
• “It's tough to make predictions, especially
about the future.” – Yogi Berra
• Uncertainty exists in water planning
• Climate variation
• Population growth
• Relatively Short Hydrologic Records
• Modeling Tools
4
5
Dallas Fort Worth Monthly Climate Normals
SOURCE: ACIS NOAA REGIONAL CLIMATE CENTER
6
Source: United States Drought Monitor, Image Source: LM Otero/AP
2011 Drought
More than 85%
of the state in
the D4 Category
Drought of
Multiple Years
Eradicated in a
Month
Drought
Briefly
Returned in
2018
Abundance
of rain
since
October
2018
Climate Reanalysis Data
Image Sources: NASA Global Modeling and Assimilation Office & UCAR COSMIC
• MERRA-2 Data from NASA
• Monthly Data (~70,000,000 Data Points)
• “Assimilated” Observations from Ground, Air, & Space
• https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/
Example: GPS OccultationAssimilated Data Sources
9
Atmospheric Variables Used at TRWD
• Wide range of predictors available for each month that correlate to the
inflow at TRWD’s Reservoirs
• The number of predictors vary from 15 in September to 246 in May
Image Source: NASA Global Modeling and Assimilation Office
Parameter Description
Relative Humidity
Zonal (E-W) Wind
Meridional (N-S) Wind
Product of Wind Speed Anomalies
Covariance of Relative Humidity and Zonal Wind
Covariance of Relative Humidity and Meridional Wind
Geopotential Height
Temperature
10
Correlations to the Arctic Oscillation (AO)
Found in the Predictors
Image Sources: Google Earth and the National Climatic Data
Center, National Oceanic and Atmospheric Administration
March Predictors
Greenland
May Predictors
Correlations to the North Atlantic
Oscillation (NAO) Found in the
Predictors
Image Sources: Google Earth & Ideo.Columbia.edu
May Predictors
+NAO
-NAO
L
Zonal (W-E) Wind
Geopotential Height
El Nino Southern Oscillation (ENSO)
The Other Half of the ENSO Equation => Air Pressure
• The changes in ocean temps during El Niῆo & La Niῆa are accompanied by even larger
changes in air pressure. This is tracked by the Southern Oscillation Index (SOI), and is
calculated based on the differences in air pressure anomalies between Tahiti & Darwin,
Australia.
Image Sources: Google Earth & The National Weather Service
Image Source: Google Earth
Correlations to ENSO Found in the Predictors
TahitiDarwin
Covariance of
Relative Humidity
& Zonal Wind
Covariance of
Relative Humidity
& Zonal Wind
Wind Speed
Anomalies
Meridional N-S
Wind
Covariance of
Relative Humidity
& Zonal Wind
RiverWare Implementation
• Generate Forecast
• Climate State Probability Distribution
• Dry, Avg, Wet, Very Wet binning
• Generate 100 Markov Chain Traces
• Number of Traces for Each Bin Match
Probability Distribution
• Observed Hydrologic Data Resampled
• Historical Transition Probabilities Used
to Simulate Likely Climate Progression
• 100 Runs Simulated in RiverWare Planning Model
• Review Results
MERRA-2 Data
Global Downscaling
Forecasting Script
Dry/Avg/Wet/Very Wet
Markov Chain Trace
Selection
RiverWare MRM Run
RiverWare Output
644
645
646
647
648
649
650
651
652
653
654
655
656
6/1/2018
7/1/2018
8/1/2018
9/1/2018
10/1/2018
11/1/2018
12/1/2018
1/1/2019
2/1/2019
3/1/2019
4/1/2019
5/1/2019
6/1/2019
Elevation(ft-msl) Eagle Mountain Elevations for 100 Traces
Operations Planning and Communication
644
645
646
647
648
649
650
651
652
653
654
655
656
6/1/2018 7/1/2018 8/1/2018 9/1/2018 10/1/2018 11/1/2018 12/1/2018 1/1/2019 2/1/2019 3/1/2019 4/1/2019 5/1/2019 6/1/2019
Elevation(ft-msl)
Eagle Mountain Elevations Statistical Probability June 2018 Forecast
Actual 1% 5% 25% 50% 75% 95% 99%
Actual
Operations Planning and Communication
641
643
645
647
649
651
653
655
9/1/2018
10/1/2018
11/1/2018
12/1/2018
1/1/2019
2/1/2019
3/1/2019
4/1/2019
5/1/2019
6/1/2019
7/1/2019
8/1/2019
9/1/2019
Elevation(ft-msl)
Eagle Mountain Elevations Statistical Probability for Sep 2018 Forecast
Actual 1% 5% 25% 50% 75% 95% 99%
Actual
19
Thank You for The Opportunity
Courtney.Jalbert@trwd.com
Laura.Blaylock@trwd.com
carron@hydrosconsulting.com

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Integrating Climate Data Into Forecasting Hydrologic Inflow - Laura Blaylock and Courtney Jalbert

  • 1. Integrating Climate Data Into Forecasting Hydrologic Inflow TWCA June 20, 2019 Tarrant Regional Water District in collaboration with Hydros Consulting
  • 2. One of 3 Large Raw Water Suppliers in North Central Texas 1
  • 4. 3 • “It's tough to make predictions, especially about the future.” – Yogi Berra • Uncertainty exists in water planning • Climate variation • Population growth • Relatively Short Hydrologic Records • Modeling Tools
  • 5. 4
  • 6. 5 Dallas Fort Worth Monthly Climate Normals SOURCE: ACIS NOAA REGIONAL CLIMATE CENTER
  • 7. 6
  • 8. Source: United States Drought Monitor, Image Source: LM Otero/AP 2011 Drought More than 85% of the state in the D4 Category Drought of Multiple Years Eradicated in a Month Drought Briefly Returned in 2018 Abundance of rain since October 2018
  • 9. Climate Reanalysis Data Image Sources: NASA Global Modeling and Assimilation Office & UCAR COSMIC • MERRA-2 Data from NASA • Monthly Data (~70,000,000 Data Points) • “Assimilated” Observations from Ground, Air, & Space • https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/ Example: GPS OccultationAssimilated Data Sources
  • 10. 9 Atmospheric Variables Used at TRWD • Wide range of predictors available for each month that correlate to the inflow at TRWD’s Reservoirs • The number of predictors vary from 15 in September to 246 in May Image Source: NASA Global Modeling and Assimilation Office Parameter Description Relative Humidity Zonal (E-W) Wind Meridional (N-S) Wind Product of Wind Speed Anomalies Covariance of Relative Humidity and Zonal Wind Covariance of Relative Humidity and Meridional Wind Geopotential Height Temperature
  • 11. 10
  • 12. Correlations to the Arctic Oscillation (AO) Found in the Predictors Image Sources: Google Earth and the National Climatic Data Center, National Oceanic and Atmospheric Administration March Predictors Greenland May Predictors
  • 13. Correlations to the North Atlantic Oscillation (NAO) Found in the Predictors Image Sources: Google Earth & Ideo.Columbia.edu May Predictors +NAO -NAO L Zonal (W-E) Wind Geopotential Height
  • 14. El Nino Southern Oscillation (ENSO) The Other Half of the ENSO Equation => Air Pressure • The changes in ocean temps during El Niῆo & La Niῆa are accompanied by even larger changes in air pressure. This is tracked by the Southern Oscillation Index (SOI), and is calculated based on the differences in air pressure anomalies between Tahiti & Darwin, Australia. Image Sources: Google Earth & The National Weather Service
  • 15. Image Source: Google Earth Correlations to ENSO Found in the Predictors TahitiDarwin Covariance of Relative Humidity & Zonal Wind Covariance of Relative Humidity & Zonal Wind Wind Speed Anomalies Meridional N-S Wind Covariance of Relative Humidity & Zonal Wind
  • 16. RiverWare Implementation • Generate Forecast • Climate State Probability Distribution • Dry, Avg, Wet, Very Wet binning • Generate 100 Markov Chain Traces • Number of Traces for Each Bin Match Probability Distribution • Observed Hydrologic Data Resampled • Historical Transition Probabilities Used to Simulate Likely Climate Progression • 100 Runs Simulated in RiverWare Planning Model • Review Results MERRA-2 Data Global Downscaling Forecasting Script Dry/Avg/Wet/Very Wet Markov Chain Trace Selection RiverWare MRM Run
  • 18. Operations Planning and Communication 644 645 646 647 648 649 650 651 652 653 654 655 656 6/1/2018 7/1/2018 8/1/2018 9/1/2018 10/1/2018 11/1/2018 12/1/2018 1/1/2019 2/1/2019 3/1/2019 4/1/2019 5/1/2019 6/1/2019 Elevation(ft-msl) Eagle Mountain Elevations Statistical Probability June 2018 Forecast Actual 1% 5% 25% 50% 75% 95% 99% Actual
  • 19. Operations Planning and Communication 641 643 645 647 649 651 653 655 9/1/2018 10/1/2018 11/1/2018 12/1/2018 1/1/2019 2/1/2019 3/1/2019 4/1/2019 5/1/2019 6/1/2019 7/1/2019 8/1/2019 9/1/2019 Elevation(ft-msl) Eagle Mountain Elevations Statistical Probability for Sep 2018 Forecast Actual 1% 5% 25% 50% 75% 95% 99% Actual
  • 20. 19 Thank You for The Opportunity Courtney.Jalbert@trwd.com Laura.Blaylock@trwd.com carron@hydrosconsulting.com