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1 Water Supply Forecasting Research at UNLV Thomas Piechota, PhD, P.E. Director of Sustainability and Multidisciplinary Research Associate Professor, Department.

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Presentation on theme: "1 Water Supply Forecasting Research at UNLV Thomas Piechota, PhD, P.E. Director of Sustainability and Multidisciplinary Research Associate Professor, Department."— Presentation transcript:

1 1 Water Supply Forecasting Research at UNLV Thomas Piechota, PhD, P.E. Director of Sustainability and Multidisciplinary Research Associate Professor, Department of Civil and Environmental Engineering Kenneth Lamb, P.E. Funded By: NOAA

2 Outline  Climate Variability and the Colorado River Basin  Existing Research Basis  Current Research Goal  Establishing Long Lead Climate/Streamflow teleconnections  Develop Weighted Forecasting Method 2

3 Climate Variability  Linkages of Colorado River basin hydrology with:  Interannual climate variability (2-7 years)  El Niño - Southern Oscillation (ENSO)  Northern Atlantic Oscillation (NAO)  Pacific Ocean Sea Surface Temperatures (SSTs)  Interdecadal climate variability (10-20 years)  Atlantic Multidecadal Oscillation (AMO)  Pacific Decadal Oscillation (PDO)  Motivation: Improved long range(6-24 months in advance) streamflow forecasting 3

4 Climate Indices - Streamflow  Timilsena, Piechota, Tootle, & Singh, 2009

5 Pacific Ocean SST - Streamflow  Tootle & Piechota, 2005

6 Pacific Ocean SST - Snowpack  Aziz, Tootle, Piechota, Gray, 2009 (+) (-) (+)

7 Research Project Goal  Improve the “Out-Year” inputs used by USBR  Identify long-lead climate-streamflow connections  Develop weighted forecast approach 7 ESP OUTLOOK ESP 3-MONTH APR-JUL COORDINATED USBR INTERPOLATION AVERAGE

8 Research Project Goal  Improve the “Out-Year” inputs used by USBR  Identify long-lead climate-streamflow connections  Develop weighted forecast approach 8

9 Analysis  Lagged Rank Sum Testing  SOI, PDO, NAO, AMO  Individually and ENSO-Coupled  Lagged Singular Value Decompostion (SVD)  Pacific Ocean SSTs  Generate weighted forecasts and compare with:  30-Year Average  ESP Outlook 9

10 10 Identify the Strongest Lag

11 Rank Sum Test Results 11

12 12 Developing SST Teleconnection  Singular Value Decompostition (SVD) - Identifies covariance between two datasets Pacific Ocean Sea Surface Temperature Data (1951 – 2003) CRB Naturalized/Unimpaired Streamflow Data (1952 – 2004)

13 13 3-Month SST Avg SVD Results

14 Why This Region?  Yang et al. 2002:  Change in SST is evidence of a strong/weak wintertime jet stream  Why the 1-year lag?  Anybody want a Masters degree? 14

15 15 Forecasting With SST Index  Forecast created using a weighted resampling of the observed data ( )  Four Different Weighting Formulas  3-Month Avg. SST intervals: DJF, JFM, FMA  Predictands: April-July Volume, Yearly Volume

16 16 Assessing Forecast Skill  Linear Error in Probability Space (LEPS) score  Compares forecast to the observed mean  Probability of Observed values compared with probability of Forecasted values: QfQf QOQO PfPf POPO

17 17 Skill Results (DJF | Lag 1 year)  30-yr average skill scores at each location (PRELIMINARY)

18 Conclusions  Improvement to the 30-Year Avg using Hondo  Remaining Work:  Quantify Improvement to the ESP Outlook 18


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