Use of Climate Projections for Water Supply Planning

Use of Climate Projections for Water Supply PlanningAlison Adams, Ph.D., P.E.NCPP WorkshopAugust 12-16, 2013

It takes a team

FSU/COAPSVasu MisraLydia Stefanovawww.coaps.fsu.edu

UF/WATER INSTITUTEWendy GrahamSyewoon Hwangwww.waterinstitute.uf.edu

TAMPA BAY WATERAlison AdamsTirusew AsefaJeff Geurinkwww.tampabaywater.org

www.floridawca.orgwww.floridaclimateinstitute.org

http://www.coaps.fsu.edu/

http://www.waterinstitute.uf.edu/

http://www.tampabaywater.org/

http://www.floridawca.org/

http://www.floridaclimateinstitute.org/

3

Florida’s Largest Regional Public Water Supplier

Wholesale drinking water to six governments 2.4 Million Residents220-250 mgd annual averageSeasonal to multi-year variable climate

Tampa Bay Water’s Climate Change Assessment Project

…. In this project we are using dynamically and statistically downscaled climate model output to drive hydrologic models and explore potential impacts of climate variability and climate change on water availability and water allocation decisions

4

Water Institute ResearchReanaly

sis GCMs_fu

tureGCMs_re

tro.

Bias-correction

Application for Tampa Bay region

Hydrologic model (IHM)

Downscaling

Raw GCMs or Reanalysis

Bias-corrected GCMs

Observation

Downscaled GCM

Observation

Statistical method;BCSD, SDBC, BCCA, BCSA,

etc.

Dynamical downscalingMM5, RSM, etc.

R1, R2, ERA40, 20CR CMIP3: CCSM, GFDL, HadCM3, etc.

MeanPrec. (Raw-CCSM+RCM: 1969-1999)

-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1. Statistical downscaling – Comparative evaluation of 4 methods (BCSD_daily, BCCA, SDBC,

BCSA)• Hwang and Graham (2013) Hydro. Earth Syst. Sci

– Hydrologic simulation • Submitting to ASABE transaction

2. Evaluation of downscaled reanalysis data• R1+MM5 (Hwang et al., 2011)• R2+RSM (Stefanova et al., 2011)• ERA40+RSM (Stefanova et al., 2011)• 20CR+RSM (DiNapoli and Misra, 2012)

– Hwang et al 2013 Reg. Environ Change

What we have done so far

1. Uncertainty of Bias-correction in climate change impact assessment

2. Evaluated Future Projections through hydrologic model

What we have done so far

Spatial variability (Variograms)

• 3 GCMs + Regional Spectral Model (RSM), CCSM, HadCM3, and GFDL

• Spatial resolution (10kmx10km) over southeastern US• Variables: hourly Prec., humidity, wind speed, etc., daily

Tmax/min data – Daily bias-corrected Prec. data are available

• Retrospective simulation period: 1969-1999• Future simulation (AR4 A2 scenario): 2039-2069

http://coaps.fsu.edu/CLARReS10/index.shtml

Data

Hydrologic implication

Integrated Hydrologic Model• TBW and SWFWMD commissioned the development and application of an integrated surface

water/groundwater model for the Tampa Bay Region. • The Integrated Hydrologic Model (IHM) was developed which integrates the EPA Hydrologic

Simulation Program-Fortran for surface-water modeling with the US Geological Survey MODFLOW96 for groundwater modeling.

Ross et al., 2004 (IHM theory manual)

• Assessment of the utility of dynamically-downscaled regional reanalysis data to predict streamflow in west central Florida – Reanalysis data – robust proxy of historic

atmospheric observations– Verifying accurate prediction of historic climatic

and hydrologic behavior using reanalysis data is an essential first step before using retrospective and future GCM projections to predict potential hydrologic impacts of future climate change

• Assessment of dynamically downscaled GCM future projections

Dynamical Downscaling

• Study period from 1989 to 2001

1. R1+MM5 (Hwang et al., 2011)1986-2008

2. R2+RSM (Stefanova et al., 2011)1979-2001

3. ERA40+RSM (Stefanova et al., 2011)1979-2001

4. 20CR+RSM (DiNapoli and Misra, 2012)1903-2008

IHM calibration/verification period 1989-2006

Bias-corrected reanalysis data for hydrologic model

Wet season Dry season

Comparison of the mean annual cycles of (a) monthly mean and (b) standard deviation of daily precipitation.

Jan FebMar Apr May Jun Jul AugSep Oct NovDec0

2

4

6

8

10(a)Basin_

obsDR_ERA40DR_R2DR_R1

dial

y m

ean

prec

ipita

tion

(mm

)

Jan Feb Mar Apr May Jun Jul AugSep Oct NovDec0

5

10

15

20

25

30(b)Basin_

obsDR_ERA40DR_R2DR_R1

Stde

v. o

f dai

ly pr

ecip

itatio

n (m

m)

Raw results

monthly mean precipitation standard deviation of daily precipitation

Comparison of time series of (a) annual total precipitation and (b) standard deviation of daily precipitation over the year

500

1000

1500

2000

2500

3000(a1)Basin_o

bsDR_ERA40

anua

l tot

al p

recip

itatio

n (X

100m

m)

500

1000

1500

2000

2500

3000(a2)Basin_obs

BCDR_ERA40BCDR_R2

anua

l tot

al p

recip

itatio

n (X

100m

m)

0

5

10

15

20

25(b1)Basin_obs

DR_ERA40DR_R2

stde

v. o

f dai

ly p

recip

itatio

n (m

m)

0

5

10

15

20

25(b1)Basin_obs

BCDR_ERA40BCDR_R2

stde

v. o

f dai

ly p

recip

itatio

n (m

m)

Raw results Bias-corrected results

Comparison of error statistics of monthly areal precipitation predictions

-25

0

25

50(a)

PBIA

S (%

)

> 200%

0

0.3

0.6

0.9

1.2

1.5(b) Alafia R at Lithia

Hillsborough R at Morris BridgeHillsborough R near TampaCypress Creek at WorthingtonCypress Creek near Sulfur springAnclote R near Elfers

RSR

> 4

0

0.2

0.4

0.6

0.8

1(c)

R2

0

0.2

0.4

0.6

0.8

1(d)

NSE

Raw Bias-corrected Raw Bias-

corrected

Comparison of observed vs. simulated mean monthly streamflow

Raw results Bias-corrected results

Raw resultsBias-corrected

results

Comparison of observed vs. simulated annual

time series

Comparison of error statistics of monthly streamflow simulations for each target station; (a) PBIAS, (b) RSR, (c) R2, and (d) NSE

cal

DR_E

RA40

DR_R

2

BCDR

_ERA

40

BCDR

_R2

BCDR

_R1

DR_2

0CR

BCDR

_20C

R

Obs CLARReS10 (Re-analysis+RSM)

MM5 FLAReS1.0

-100

-50

0

50

100 (a)

PBIA

S

cal

DR_E

RA40

DR_R

2

BCDR

_ERA

40

BCDR

_R2

BCDR

_R1

DR_2

0CR

BCDR

_20C

R


MM5 FLAReS1.0

0

0.3

0.6

0.9

1.2

1.5(b)

Alafia R at LithiaHillsborough R at Morris BridgeAnclote R near ElfersCypress Creek at Wor-thington

RSR

cal

DR_E

RA40

DR_R

2

BCDR

_ERA

40

BCDR

_R2

BCDR

_R1

DR_2

0CR

BCDR

_20C

R


MM5 FLAReS1.0

0

0.2

0.4

0.6

0.8

1(c)

R2

cal

DR_E

RA40

DR_R

2

BCDR

_ERA

40

BCDR

_R2

BCDR

_R1

DR_2

0CR

BCDR

_20C

R


MM5 FLAReS1.0

-1.5

-1

-0.5

0

0.5

1(d)

NSE

• Bias correction removed all errors in mean daily, monthly and annual ppt

• Errors in daily std dev were removed but not for monthly and annual totals

• Raw reanalysis data has errors in time series of daily rainfall were not corrected and these errors were aggregrated into monthly and annual timeseries

• Daily ppt timing errors propagated and were enhanced by the non-linear streamflow processes in IHM

• All reanalysis data underestimated streamflow • In the unconfined aquifer region, rainfall errors

lead to underpredicting groundwater levels.

Bias corrected reanalysis data for hydrologic model results

• Ppt errors propagated and enhanced by the non-linear hydrologic processes produced low hydrologic model skill and can have significance water supply planning implications

• Need to reproduce more detailed ppt characteristics than daily rainfall to accurately capture hydrologic behaviors for water supply planning

• Conclusion: Using daily CDF mapping for bias correction is not sufficient for predicting hydrologic behavior. Improvements in RCM physics and parameterization or development of more enhanced bias correction techniques

Results of bias corrected reanalysis data for hydrologic model

• 3 GCMs + Regional Spectral Model (RSM)– CCSM, HadCM3, and GFDL (not available yet)

• Spatial resolution (10kmx10km)over southeastern US

• Variables– hourly Prec., humidity, wind speed, roughness, etc.– daily Tmax/min data – Daily bias-corrected Prec. data are available

• Retrospective simulation period – 1968-2000

• Future simulation (AR4 A2 scenario)– 2038-2070

CLAREnCE10 datahttp://coaps.fsu.edu/CLARReS10/index.shtml

4 Future Bias Correction methods1. Correct using historic bias amount corresponding the ‘magnitude’ of future prediction (CDFm,

Wood et al)

2. Correct using historic bias amount corresponding the ‘Percentile’ of future prediction (EDCDFm, Li et al., 2010)

3. Correct using historic bias percentage corresponding the ‘magnitude’ of future prediction (CDFm_%bias)

4. Correct using historic bias percentage corresponding the ‘Percentile’ of future prediction (EDCDFm_%bias)

3 methods for CDF development1. Monthly CDF (30data)

2. CDF for moving window ( 30 days, 61data)

3. CDF for moving window ( 15 days, 31data)

Total 12 combination of methodologies!

Bias-correction (BC) Methodology

Bias-correction (BC) Methodology Future Bias Correction methods: CDF mapping

CDF: 1

Precipitation

Sim_retro.BC_retro

+

Sim_future

raw 2

raw1

obs

Example 1

3 different CDFs1. Monthly CDF (30 data/yr)2. CDF for moving window ( 15 days, 31 data/yr)3. CDF for moving window ( 30 days, 61 data/yr)

Bias-corrected Sim_future

BC-Sim_future

HadCM3+RSM

Raw results

Bias-corrected resultsJan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

0

2

4

6

8obsRetro. _RawFuture_Raw

mea

n pr

ecip

iata

tion

(mm

)

1. Mean daily precipitation

CCSM+RSM

1 CDFm

3 CDFm_%bias 4 EDCDFm_%bias

2 EDCDFm

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec0

2

4

6


mea

n pr

ecip

iata

tion

(mm

)Raw results

Bias-corrected results

1. Mean daily precipitation

1 CDFm

3 CDFm_%bias

Raw results


2. Std. of daily precipitation

HadCM3+RSM


4

8

12


std.

of d

aily

pre

cipi

atat

ion

(mm

)4 EDCDFm_%bias

2 EDCDFm

CCSM+RSM

1 CDFm

3 CDFm_%bias

Raw results


2. Std. of daily precipitation


4

8

12


std.

of d

aily

pre

cipi

atat

ion

(mm

)4 EDCDFm_%bias

2 EDCDFm

I. Temperature

Spatial distribution of mean temperature (map comparison)

Annual cycle of Monthly mean Tmax and Tmin

Differences between the simulations for 1969~1999 & 2039~2069

MeanTmin. (Raw-HadCM3+RCM: 1969-1999)

-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

14.5

15

15.5

16

16.5

17

17.5

18

18.5

MeanTmax. (Raw-GFDL+RCM: 1969-1999)

-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

14.5

15

15.5

16

16.5

17

17.5

18

18.5

MeanTmin. (Gobs: 1969-1999)

-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

14.5

15

15.5

16

16.5

17

17.5

18

18.5

MeanTmin. (Raw-CCSM+RCM: 1969-1999)

-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

14.5

15

15.5

16

16.5

17

17.5

18

18.5

Tmin spatial distribution

Observation

1969~1999

MeanTmin. (Raw-HadCM3+RCM: 2039-2069)

-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

16.5

17

17.5

18

18.5

19

19.5

20

20.5


-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

16.5

17

17.5

18

18.5

19

19.5

20

20.5

MeanTmin. (Raw-CCSM+RCM: 2039-2069)

-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

16.5

17

17.5

18

18.5

19

19.5

20

20.5

Approx. +2`C =

Approx. +2`C =

Approx. +2`C =

2039~2069

CCSM

HadCM3

GFDL

14.5˚C

18.5˚C

Tmax spatial distribution

MeanTmax. (Gobs: 1969-1999)

-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

27

27.5

28

28.5

29

29.5

30

MeanTmax. (Raw-CCSM+RCM: 1969-1999)

-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

27

27.5

28

28.5

29

29.5

30

Observation

1969~1999

MeanTmax. (Raw-HadCM3+RCM: 1969-1999)

-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

27

27.5

28

28.5

29

29.5

30


-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

27

27.5

28

28.5

29

29.5

30

MeanTmax. (Raw-CCSM+RCM: 2039-2069)

-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

30

30.5

31

31.5

32

32.5

33

Approx. +3`C =

MeanTmax. (Raw-HadCM3+RCM: 2039-2069)

-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

30

30.5

31

31.5

32

32.5

33Approx. +3`C =

Approx. +2`C = MeanTmax. (Raw-GFDL+RCM: 1969-1999)

-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

29

29.5

30

30.5

31

31.5

32

2039~2069

CCSM

HadCM3

GFDL

27˚C

30 ˚C

Raw results

1.1 Mean daily Tmax & Tmin

5

15

25

35

45CCSM

mea

n te

mpe

ratu

re ('

C)

5

15

25

35

45HadCM3

mea

n te

mpe

ratu

re ('

C)

5

15

25

35

45GFDL

obs_Tmax Retro. _TmaxFuture_Tmax obs_TminRetro. _Tmin Future_Tmin

mea

n te

mpe

ratu

re ('

C)Tmax

Tmin

Tmax

Tmin

Tmax

Tmin

Jan MarMay Jul Se

pNov

5

15

25

35

45

CCSM

mea

n te

mpe

ratu

re ('

C)

5

15

25

35

45

HadCM3

mea

n te

mpe

ratu

re ('

C)

Jan MarMay Jul Se

pNov

5

15

25

35

45

GFDL

mea

n Tm

ax ('

C)


Tmax

Tmin

Tmax

Tmin

Tmax

Tmin

0

1

2

3

4Raw results

CCSM (+2.8'C)HadCM3 (+2.3'C)GFDL (+2.0'C)m

ean

chan

ge o

f raw

Tm

ax ('

C)

Raw results

0

1

2

3

4Bias-corrected results

CCSM monthly (2.0'C)CCSM ±15 (2.0'C)CCSM ±30 (1.9'C)HadCM3 monthly (1.8'C)HadCM3 ±15 (1.9'C)HadCM3 ±30 (1.8'C)GFDL monthly (1.4'C)GFDL ±15 (1.4'C)m

ean

chan

ge o

f BC

Tm

ax ('

C)


1.2 Mean temperature change: 2039~2069 – 1969~1999

Tmax

Tmin

0

1

2

3


CCSM monthly (1.8'C)CCSM ±15 (1.9'C)CCSM ±30 (1.8'C)HadCM3 monthly (2.3'C)HadCM3 ±15 (2.3'C)HadCM3 ±30 (2.2'C)GFDL monthly (2.1'C)GFDL ±15 (2.1'C)GFDL ±30 (2.0'C)m

ean

chan

ge o

f BC

Tm

in ('

C)

0

1

2

3

4Raw results

CCSM (+1.8'C)HadCM3 (+2.2'C)GFDL (+2.1'C)m

ean

chan

ge o

f raw

Tm

in ('

C)

II. Precipitation

Spatial distribution of mean precipitation(map comparison)

Annual cycle of Monthly mean precipitiation

Differences between the simulations for 1969~1999 & 2039~2069

2.1 Raw Precipitation results

MeanPrec. (Gobs: 1969-1999)

-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

3.3

3.4

3.5

3.6

3.7

3.8

3.9


-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

MeanPrec. (Raw-HadCM3+RCM: 1969-1999)

-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

3

3.2

3.4

3.6

3.8

4

4.2

4.4

4.6

4.8

5

• Raw CCSM results significantly underestimate the mean precp. by 2.5mm over the region

• Raw HadCM3 and GFDL results overestimate by 1~2mm

• Based on the future scenario, precipitation may decrease or increase

MeanPrec. (Raw-GFDL+RCM: 1969-1999)

-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

3

3.2

3.4

3.6

3.8

4

4.2

4.4

4.6

4.8

5

Observation

1969~1999

CCSM

HadCM3

GFDL

3.9mm

3.3mm ¿

¿

1.8mm

0.8mm

≠Way off!!underestimated


-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

MeanPrec. (Raw-HadCM3+RCM: 2039-2069)

-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

3

3.2

3.4

3.6

3.8

4

4.2

4.4

4.6

4.8

5

MeanPrec. (Raw-GFDL+RCM: 2039-2069)

-83 -82.5 -82 -81.5 -81

27

27.2

27.4

27.6

27.8

28

28.2

28.4

28.6

28.8

29

3

3.2

3.4

3.6

3.8

4

4.2

4.4

4.6

4.8

5

2039~2069

¿

≅

¿

Even lower

Jan Feb

Mar AprMay Jun Jul Aug Se

p OctNov Dec

0

2

4

6

8 HadCM3

Raw results

2.2 Mean daily precipitation


Jan Feb

Mar AprMay Jun Jul Aug

Sep Oct

NovDec

0

2

4

6

8 CCSMobsRetro. _RawFuture_Raw

mea

n pr

ecip

iata

tion

(mm

)

Jan Feb

Mar AprMay Jun Jul Aug

Sep Oct

NovDec

0

2

4

6

8 HadCM3obs

Jan MarMay Jul Se

pNov

0

2

4

6

8 GFDLobsRetro. _Raw

Jan MarMay Jul Se

pNov

0

2

4

6

8 CCSM

obsRetro._monthly CDF Retro._Moving window CDF (±15) Retro._Moving window CDF (±30) Future_monthly CDFFuture_Moving window CDF (±15) Future_Moving window CDF (±30)

mea

n pr

ecip

iata

tion

(mm

)

Jan Feb

Mar AprMay Jun Jul Aug Se

p OctNov Dec

0

2

4

6

8 GFDL

2.3 Mean precipitation change: 2039~2069 – 1969~1999

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec-3

-2

-1

0

1

2

3Raw results CCSM (-0.57mm, -16.2%)

HadCM3 (-0.13mm, -3.8%)GFDL (+0.18mm, 5.2%)

mea

n ch

ange

of r

aw p

reci

p. (m

m)

wet projection

dry projectionRainy wet season


-2

-1

0

1

2


CCSM monthly (-0.8mm, -23.2%)CCSM ±15 (-0.8mm, -22.4%)CCSM ±30 (-0.8mm, -22.3%)HadCM3 monthly (0.1mm, 2.3%)HadCM3 ±15 (0.05mm, 1.4%)HadCM3 ±30 (0.02mm, 0.5%)GFDL monthly (0.4mm, 11%)GFDL ±15 (0.34mm, 9.8%)GFDL ±30 (0.26mm, 7.4%)m

ean

chan

ge o

f BC

pre

cip.

(mm

)

Raw results


III. Hydrologic implications

Annual ET, ET fraction (ET/Precip.)

Mean streamflow

Design flow estimations

3.1 ET estimations

Annual average ET (mm/year) ET fraction (ET/Precp.)

20th

_BC

mon

thly

CDF

±15

CDF

±30

CDF

delta

20th

_BC

mon

thly

CDF

±15

CDF

±30

CDF

delta

20th

_BC

mon

thly

CDF

±15

CDF

±30

CDF

delta

21st 21st 21stcal. CCSM GFDL HadCM3

60

65

70

75

80

85

90

ET/P

(%)

CCSM HadCM3 GFDL

20th

_BC

mon

thly

CDF

±15

CDF

±30

CDF

delta

20th

_BC

mon

thly

CDF

±15

CDF

±30

CDF

delta

20th

_BC

mon

thly

CDF

±15

CDF

±30

CDF

delta

21st 21st 21stcal. CCSM GFDL HadCM3

700

750

800

850

900

950

1000

Evap

otra

nspi

ratio

n (m

m/y

ear)

CCSM HadCM3 GFDL

Retrospective simulation results

3.2 mean streamflow (Alafia River station)

Future simulations


10

20

30

Alafia River Obs (1989-2005)Cal (1989-2005)CCSM_20th_BC1

Mea

n st

ream

flow

(m3s

-1)


10

20

30

Alafia River Obs (1989-2005)Cal (1989-2005)CCSM_21st_BC1

Mea

n st

ream

flow

(m3s

-1)


10

20

30

Alafia River Obs (1989-2005)Cal (1989-2005)HadCM3_21st_BC1

Mea

n st

ream

flow

(m3s

-1)


10

20

30

Alafia River Obs (1989-2005)Cal (1989-2005)GFDL_21st_BC1

Mea

n st

ream

flow

(m3s

-1)

BC1: bias-correction using monthly CDFBC5: bias-correction using 15 CDFBC9: bias-correction using 30 CDF

Streamflow Change(Future-retro.)

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

-20

-10

0

10

20

Alafia River CCSM_21st-20th_BC1CCSM_21st-20th_BC5CCSM_21st-20th_BC9CCSM_21st-20th_delta

Mea

n st

ream

flow

(m3s

-1)


-20

-10

0

10

20

Alafia River HadCM3_21st-20th_BC1HadCM3_21st-20th_BC5HadCM3_21st-20th_BC9HadCM3_21st-20th_delta

Mea

n st

ream

flow

(m3s

-1)


-20

-10

0

10

20

Alafia River GFDL_21st-20th_BC1GFDL_21st-20th_BC5GFDL_21st-20th_BC9

Mea

n st

ream

flow

(m3s

-1)

CCSM

HadCM3

GFDL

3.2 mean streamflow (Alafia River station)

Streamflow Change(Future-retro.)


-20

-10

0

10

20

Alafia River CCSM_21st-20th_BC1CCSM_21st-20th_BC5CCSM_21st-20th_BC9CCSM_21st-20th_delta

Mea

n st

ream

flow

(m3s

-1)


-20

-10

0

10

20

Alafia River HadCM3_21st-20th_BC1HadCM3_21st-20th_BC5HadCM3_21st-20th_BC9HadCM3_21st-20th_delta

Mea

n st

ream

flow

(m3s

-1)


-20

-10

0

10

20

Alafia River GFDL_21st-20th_BC1GFDL_21st-20th_BC5GFDL_21st-20th_BC9

Mea

n st

ream

flow

(m3s

-1)


-2

-1

0

1

2

3

mea

n ch

ange

of B

C p

reci

p. (m

m)

Precipitation Change(Future-retro.)

Retrospective simulation results

3.3 Std. of streamflow (Alafia River station)

Future simulations Streamflow Change(Future-retro.)

BC1: bias-correction using monthly CDFBC5: bias-correction using 15 CDFBC9: bias-correction using 30 CDF


10

20

30

40

50

Alafia River Obs_20thCal (1989-2005)CCSM_20th_BC1

Std.

of d

aily

stre

amflo

w (m

3s-1

)


10

20

30

40

50

Alafia River Obs_20thCal (1989-2005)CCSM_21st_BC1

Std.

of d

aily

stre

amflo

w (m

3s-1

)


10

20

30

40

50

Alafia River Obs_20thCal (1989-2005)HadCM3_21st_BC1HadCM3_21st_BC5

Std.

of d

aily

stre

amflo

w (m

3s-1

)


10

20

30

40

50

Alafia River Obs_20thCal (1989-2005)GFDL_21st_BC1

Std.

of d

aily

stre

amflo

w (m

3s-1

)


-30

-15

0

15

30

Alafia River CCSM_21st_BC1CCSM_21st_BC5CCSM_21st_BC9CCSM_21st_delta

Mea

n st

ream

flow

(m3s

-1)


-30

-15

0

15

30

Alafia River HadCM3_21st_BC1HadCM3_21st_BC5HadCM3_21st_BC9HadCM3_21st_delta

Mea

n st

ream

flow

(m3s

-1)


-30

-15

0

15

30

Alafia River GFDL_21st_BC1GFDL_21st_BC5GFDL_21st_BC9GFDL_21st_delta

Mea

n st

ream

flow

(m3s

-1)

Obs

.Ca

l.20

th_B

Cm

onth

ly C

DF±1

5 CD

F±3

0 CD

Fde

lta20

th_B

Cm

onth

ly C

DF±1

5 CD

F±3

0 CD

Fde

lta20

th_B

Cm

onth

ly C

DF±1

5 CD

F±3

0 CD

Fde

lta

21st 21st 21stCCSM GFDL HadCM3

0

0.6

1.2Alafia River

7Q2_

Low

Flow

(m3/

s)

Obs

.Ca

l.20

th_B

Cm

onth

ly C

DF±1

5 CD

F±3

0 CD

Fde

lta20

th_B

Cm

onth

ly C

DF±1

5 CD

F±3

0 CD

Fde

lta20

th_B

Cm

onth

ly C

DF±1

5 CD

F±3

0 CD

Fde

lta

21st 21st 21stCCSM GFDL HadCM3

0

152

304Alafia River

7Q10

_Hig

hFlo

w (m

3/s)

7Q10 high flow

CCSM

HadCM3GFDL

CCSM

HadCM3GFDL

3.3 Design flow estimation 7Qxx high (low) flow means the average maximum (minimum) flow for seven consecutive days that has probable recurrence interval of once in xx years, respectively.

7Q2 low flow

Conclusions

Used 3 dynamically downscaled GCMs (i.e., CCSM, Had3CM, GFDL), 3 CDF construction strategies for CDF mapping bias-correction, and monthly delta method for future scenarios Differences among GCM projections overwhelmed differences among bias

correction techniques. Temperature Results

All GCMs successfully reproduced spatial distribution and mean climatology of retrospective daily temperature

All consistently estimated 2-3oC increase of mean temperature for future (2039~2069) under future A2 scenario.

Precipitation Results Dynamically downscaled retrospective CCSM predictions are way off! Retrospective HadCM3 and GFDL reproduce seasonal cycle of precipitation.(e.g., wet

summer) Different GCMs produced conflicting precipitation change estimates for future A2

scenarios (some higher, some lower)

Conclusions continued

Hydrologic implications Even with consistent increased temperature estimates, differences

among future precipitation estimates propagate into significant differences in future hydrologic predictions ( i.e. ET, mean streamflow predictions, and 7Q10 estimates).

Precipitation signal overwhelms temperature signal in predicting hydrologic implications of projected future changes.

Q. How many GCMs are required to get an accurate representation of range of possible future precipitation projections and thus range of possible hydrologic change?

Q. Should we continue to use CCSM in our analysis?

Possible Future Work

Consider other climate model products & GHG scenarios… NARCCAP, CMIP5, COAPS products, etc.?

Other methodologies to downscale/bias-correct climate model results? Statistical downscaling methods in order to increase number of GCMs

considered?

Use of Climate Projections for Water Supply Planning

Documents

hydrologic model tbw

water availability

hydrologic behavior

hydrologic models

surfacewater modeling

water allocation decisions

multiyear variable climate

r2 rsm stefanova