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1 Water Supply Forecasting Research at UNLV 1 Water Supply Forecasting Research at UNLV

1 Water Supply Forecasting Research at UNLV - PowerPoint Presentation

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1 Water Supply Forecasting Research at UNLV - PPT Presentation

Thomas Piechota PhD PE Director of Sustainability and Multidisciplinary Research Associate Professor Department of Civil and Environmental Engineering Kenneth Lamb PE Funded By NOAA Outline ID: 511259

streamflow climate pacific sst climate streamflow sst pacific research weighted forecast ocean variability long oscillation year forecasting piechota svd

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Water Supply Forecasting Research at UNLV

Thomas Piechota, PhD, P.E.Director of Sustainability and Multidisciplinary ResearchAssociate Professor, Department of Civil and Environmental EngineeringKenneth Lamb, P.E.Funded By: NOAASlide2

OutlineClimate Variability and the Colorado River Basin

Existing Research BasisCurrent Research GoalEstablishing Long Lead Climate/Streamflow teleconnections

Develop Weighted Forecasting Method2Slide3

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

3Slide4

Climate Indices - Streamflow

Timilsena, Piechota, Tootle, & Singh, 2009Slide5

Pacific Ocean SST - Streamflow

Tootle & Piechota, 2005Slide6

Pacific Ocean SST - Snowpack

Aziz, Tootle, Piechota, Gray, 2009

(+)

(-)

(-)

(-)

(+)Slide7

Research Project Goal

Improve the “Out-Year” inputs used by USBRIdentify long-lead climate-streamflow connections

Develop weighted forecast approach7ESPOUTLOOK

ESP

3-MONTH

APR-JUL COORDINATED

USBR INTERPOLATION

1976-2005 AVERAGESlide8

Research Project Goal

Improve the “Out-Year” inputs used by USBRIdentify long-lead climate-streamflow connections

Develop weighted forecast approach8Slide9

Analysis

Lagged Rank Sum Testing SOI, PDO, NAO, AMOIndividually and ENSO-Coupled

Lagged Singular Value Decompostion (SVD)Pacific Ocean SSTsGenerate weighted forecasts and compare with:30-Year AverageESP Outlook9Slide10

10

Identify the Strongest Lag Slide11

Rank Sum Test Results

11Slide12

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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)Slide13

13

3-Month SST Avg SVD ResultsSlide14

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?14Slide15

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Forecasting With SST Index

Forecast created using a weighted resampling of the observed data (1976-2005)Four Different Weighting Formulas3-Month Avg. SST intervals: DJF, JFM, FMAPredictands: April-July Volume, Yearly VolumeSlide16

16

Assessing Forecast Skill

Linear Error in Probability Space (LEPS) scoreCompares forecast to the observed meanProbability of Observed values compared with probability of Forecasted values:

Q

f

Q

O

P

f

P

OSlide17

17

Skill Results (DJF | Lag 1 year)

30-yr average skill scores at each location(PRELIMINARY)Slide18

Conclusions

Improvement to the 30-Year Avg using HondoRemaining Work:

Quantify Improvement to the ESP Outlook18