5-Egypt-Nile River Flows - United Nations Economic and ...css.escwa.org.lb/SDPD/3639/PR-S2-5.pdf ·...

09/06/2015

1

Beirut, Beirut, 88--10 10 June June 20152015

ByBy

DoaaDoaa M. M. AminAmin, PhD, PhD

Water Recourses Research Institute (WRRI), National Water Water Recourses Research Institute (WRRI), National Water

Research Center (NWRC), Ministry of Water Resources & Research Center (NWRC), Ministry of Water Resources &

Irrigation (MWRI), EgyptIrrigation (MWRI), Egypt


�� IntroductionIntroduction

�� Hydrological Models (NFS)Hydrological Models (NFS)

�� Previous Studies Previous Studies

�� Assessment the Drought in Future Climate Change Assessment the Drought in Future Climate Change

ScenariosScenarios

–– Study Area (Blue Nile and Atbara River)Study Area (Blue Nile and Atbara River)

––MethodologyMethodology

––ResultResult

––ConclusionConclusion

––Next Step Next Step

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2


Results of CC Results of CC

Models Models

Preprocessing Preprocessing

MethodMethod

Impacts Impacts

Model Model

Analyzing the Analyzing the

Results and Results and

understanding understanding

the Impactsthe Impacts


Hydrological Hydrological ModelsModels

� Rainfall – Runoff Model (rainfall the source of water)

� Distributed model (to simulate the runoff variability)

� Accurate sub-basins delineation.

� Well Calibrated (to access the hydrological errors itself)

Why Nile Forecasting System ?Why Nile Forecasting System ?

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Nile Forecasting SystemNile Forecasting System

� Hydro-meteorological System

� Developed in 1992, for monitoring, Forecasting and

simulating the flow till HAD

� Upgraded several times 1994, 1998, 2000, 2006, 2009, and

2012

� Precipitation & PET is the primary inputs variable for the NFS

hydrological models

� NFS was evaluated in 2011, through the period (1989-2010)

� The Sub-basins are re-delineated in 2012

� The latest Calibration was in 2012


Rain gauge Data Satellite Images

Rainfall Estimation Models

Rainfall Estimates

Hydrological Models

Simulation and Extended Stream Flow Prediction (ESP)

Historical Climate

GIS

Water Balance

Hill Slope

Routing

Swamp

Lake

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Previous StudiesPrevious Studies

0

20

40

60

80

100

120

Base 2010s 2020s 2030s 2040s 2050s 2060s 2070s 2080s 2090s

To

tal A

nn

ua

l F

low

(B

CM

)

HadCM3 A2 HadCM3 B2

CGCM2 A2 CGCM2 B2

ECHAM4 A2 ECHAM4 B2

OBS Base

Previous Studies (Previous Studies (11))

Lake Nasser Flood & Drought Control Project (2008)

– 6 Transient scenarios (3 GCMs x 2 Emission Scenarios)

– Statistically downscaled using a spatio-temporal weather generator

– Changes at Dongolafrom 2010-2100



Previous Studies Previous Studies ((22))

– 6 ensembles of scenarios (HadCM3 x A1B Emission Scenario)

– RCM downscaled

– DCFs to Modify the NFS daily rainfall

– Changes at key locations on Nile River from 2021-2050

– -19% to +29% for the Blue Nile (Diem)

– -8% to +10% for the White Nile (Malakal)

– -13% to +36% for the Whole Nile (Dongola)

Climate Change Risk Management in Egypt

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– 5ensembles of scenarios (HadCM3 x A1B Emission Scenario)

– RCM downscaled

– DCFs of Temp., Precip., PET, and Evap.

The Impact of Climate Change on the Arab Region using RCM




The Impact of Climate Change on the Arab Region using RCM

Delta Change Factors for Temperature (Differences in Delta Change Factors for Temperature (Differences in °°K) for Selected Scenarios and MonthsK) for Selected Scenarios and MonthsDelta Change Factors for Precipitation (Ratios) for Selected Scenarios and MonthsDelta Change Factors for Precipitation (Ratios) for Selected Scenarios and Months

(DCF is not calculated for Black Areas, White Areas are off Scale)Delta Change Factors for PET (Ratios) for the Selected Scenarios and MonthsDelta Change Factors for PET (Ratios) for the Selected Scenarios and Months

Delta Change Factors for Evaporation (Ratios) for Selected Scenarios and Delta Change Factors for Evaporation (Ratios) for Selected Scenarios and

MonthsMonths

(DCF is not calculated for Black Areas, White Areas are off Scale)

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Assessment the Drought in Future Assessment the Drought in Future

ClimateClimate

� Meteorological droughts are periods of less than normal rainfall over a

specified region

� For assessing meteorological drought, the approach is to apply the

Standardized Precipitation Index (SPI) to different rainfall datasets to

assess its applicability in the study area.

� In terms of hydrological drought, a set of indices will be applied to the

projected Future Flow (SDI, and MWRI flood year classification)


Study Area (Blue Nile & Atbara River)Study Area (Blue Nile & Atbara River)

�� Low specific Low specific dischargedischarge

�� Variable Variable topographytopography

�� High runoff High runoff variabilityvariability

�� High Sensitivity to High Sensitivity to ClimateClimate

Roseires

Khartoum

Didessa

Angar

Temcha

Wama

Basilo

Tamaniat

Diem

Sennar

Ma lakal

Dabana

Beressa

Birr

Chacha

Fettam

Finchaa

Gummara

Guder

Megechi

Muger

Ribb

Sifa

Kesse

Atba ra

Gaba l Awlia

Mogren

Khashm

El-Girba

Hasanab

7

8

9

10

11

12

13

14

15

16

17

18

31 32 33 34 35 36 37 38 39 40

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MethodologyMethodology

RCM ResultsRCM Results

6 ensembles for

Rainfall & PET

(1961-1990)

(2021-2050)

PrePre--processingprocessing

Bias correction of

precipitation &

PET

Hydrological Hydrological

ModelsModels

Hydrological

Models in (NFS)

Assessment Assessment

Drought Drought in the in the

Eastern NileEastern Nile

Drought indices

(SPI, SDI,…)


PrePre--processingprocessing

Bias Correction

The method to bias correct precipitation is based on monthly

means, by applying a multiplicative correction factor

Corr. F = Mean Monthly Precipitation (NFS)

Mean Monthly Precipitation

(base: 1961-1990)

This is a simple bias correction that only guarantees that the mean climate

scenario is similar to the base dataset

09/06/2015

8

Beirut, 8Beirut, 8--10 June 201510 June 2015

Meteorological Drought AssessmentMeteorological Drought Assessment

SPI was calculated for 1, 3, 6, 9, and 12 months lead times to assess

the drought using the catchment rainfall from several sources:

1. For historical rainfall, three datasets(CRU, ERa40, & NFS) are

used and results are compared in terms of drought frequency for a

period starting in 1961 and ending in 1990 or beyond (except for

the NFS dataset which starts in 1992)

2. The baseline rainfall series from the ensemble members (1961-

1990) are first compared to observed rainfall

3. Future rainfall is taken from an ensemble of 6 RCM simulations for

the period 2021-2050


SPI Values and Corresponding Drought Intensity-McKee et al. (1993)

Meteorological Drought AssessmentMeteorological Drought Assessment

SPI Value Drought Intensity

2.0 or more Extremely wet

1.5 to 1.99 Very wet

1.0 to 1.49 Moderately wet

-.99 to .99 Near normal

-1.0 to -1.49 Moderately dry

-1.5 to -1.99 Severely dry

-2 and less Extremely dry

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ResultsResults1- Observed Rainfall Comparisons

0

200

400

600

800

1000

1200

1400

1600

1800

1961

1963

1965

1967

1969

1971

1973

1975

1977

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

To

tal A

nn

ua

l R

ain

fall

(m

m)

CRU ERA40

NFS ERA40-PRECIS

Blue Nile at Khartoum

0

200

400

600

800

1000

1200

1400

1600

1961

1963

1965

1967

1969

1971

1973

1975

1977

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

To

tal A

nn

ua

l R

ain

fall

(m

m)

Atbara at Atbara town

a) Annual “Observed” Rainfall Series


ResultsResults1- Observed Rainfall Comparisons

Blue Nile at Khartoum Atbara at Atbara town

b) Mean Monthly Distribution of “Observed” Rainfall Series

0

50

100

150

200

250

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

Me

an

Mo

nth

ly R

ain

fall

(m

m/m

on

)

CRU

ERA40

NFS

ERA40-PRECIS

0

20

40

60

80

100

120

140

160

180

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

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ResultsResults2- Climate Change Impacts

0

50

100

150

200

250

300

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

Tota

l M

on

thly

Ra

infa

ll (

mm

/m

on

)

Probability of Exceedence

RCM

CRU

ERA40

NFS

ERA40-PRECIS

0

50

100

150

200

250

300

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

Tota

l M

on

thly

Ra

infa

ll (

mm

/m

on

)


Blue Nile - Present (1961-1990) Blue Nile - Future (2021-2050)

a) Impact of Climate Change from 6 RCM Simulations on Rainfall

Frequency Distribution of the Blue Nile and Atbara

(The yellow band indicate the range across the 6 PRECIS simulations)

0

50

100

150

200

250

300

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

Tota

l Mo

nth

ly R

ain

fall

(m

m/

mo

n)


0

50

100

150

200

250

300

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

Tota

l Mo

nth

ly R

ain

fall

(m

m/m

on

)


Atbara - Present (1961-1990) Atbara - Future (2021-2050)



-3

-2

-1

0

1

2

3

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

An

nu

al S

PI


RCM

CRU

ERA40

NFS

ERA40-PRECIS

-3

-2

-1

0

1

2

3

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

An

nu

al SP

I


Blue Nile - Present (1961-1990)

Blue Nile - Future (2021-2050)

Hydrological Year

Hydrological Year

-3

-2

-1

0

1

2

3

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

Mo

nth

ly S

PI


RCM

CRU

ERA40

NFS

ERA40-PRECIS

Monthly SPI

-3

-2

-1

0

1

2

3

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

Mo

nth

ly S

PI


Monthly SPI

-3

-2

-1

0

1

2

3

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

3 M

on

ths S

PI


RCM

CRU

ERA40

NFS

ERA40-PRECIS

3-Monthly SPI

-3

-2

-1

0

1

2

3

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

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55%

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65%

70%

75%

80%

85%

90%

95%

99%

3 M

on

ths S

PI


3-Monthly SPI

09/06/2015

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Blue Nile - Present (1961-1990)

Blue Nile - Future (2021-2050)

9-Monthly SPI

9-Monthly SPI

12-Monthly SPI

12-Monthly SPI

-3

-2

-1

0

1

2

31%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

6 M

on

ths S

PI


RCM

CRU

ERA40

NFS

ERA40-PRECIS

6-Monthly SPI

-3

-2

-1

0

1

2

3

1%

5%

10%

15%

20%

25%

30%

35%

40%

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50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

6 M

on

ths

SP

I


6-Monthly SPI

-3

-2

-1

0

1

2

3

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

9 M

on

ths S

PI


RCM

CRU

ERA40

NFS

ERA40-PRECIS

-3

-2

-1

0

1

2

3

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

9 M

on

th

s S

PI


-3

-2

-1

0

1

2

3

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

12

Mo

nth

s S

PI


RCM

CRU

ERA40

NFS

ERA40-PRECIS

-3

-2

-1

0

1

2

3

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

12

Mo

nth

s S

PI




Atbara - Present (1961-1990)

Atbara - Future (2021-2050)

Hydrological Year

Hydrological Year

Monthly SPI

Monthly SPI

3-Monthly SPI

3-Monthly SPI

-3

-2

-1

0

1

2

3

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

An

nu

al

SP

I


-3

-2

-1

0

1

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1%

5%

10%

15%

20%

25%

30%

35%

40%

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70%

75%

80%

85%

90%

95%

99%

An

nu

al S

PI


-3

-2

-1

0

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1%

5%

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15%

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25%

30%

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99%

Mo

nth

ly S

PI


-3

-2

-1

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1%

5%

10%

15%

20%

25%

30%

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45%

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60%

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70%

75%

80%

85%

90%

95%

99%

Mo

nth

ly S

PI


-3

-2

-1

0

1

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1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

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55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

3 M

on

th

s S

PI


-3

-2

-1

0

1

2

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1%

5%

10%

15%

20%

25%

30%

35%

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65%

70%

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90%

95%

99%

3 M

on

ths

SPI


09/06/2015

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Atbara - Present (1961-1990)

Atbara - Future (2021-2050)

9-Monthly SPI

9-Monthly SPI

12-Monthly SPI

12-Monthly SPI

6-Monthly SPI

6-Monthly SPI

-3

-2

-1

0

1

2

31%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

6 M

on

ths S

PI


-3

-2

-1

0

1

2

3

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

6 M

on

ths

SP

I


-3

-2

-1

0

1

2

3

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

9 M

on

ths

SP

I


-3

-2

-1

0

1

2

3

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

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60%

65%

70%

75%

80%

85%

90%

95%

99%

9 M

on

ths S

PI


-3

-2

-1

0

1

2

3

1%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

99%

12

Mo

nth

s S

PI


-3

-2

-1

0

1

2

3

1%

5%

10%

15%

20%

25%

30%

35%

40%

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65%

70%

75%

80%

85%

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99%

12

Mo

nth

s S

PI



ConclusionConclusion

� CRU has higher flood probabilities than NFS, but similar drought

probabilities.

� SPI reduce the bias from RCM model because it involves

normalization of rainfall distributions.

� The current set of climate simulations indicate a general increase in

rainfall, but this does not exclude the increase of drought probability

for some lead times

� The uncertainty bandwidth increases near the ends of the SPI

probability distributions but not for all lead times

� The SPI proved to be a useful way to characterize meteorological

drought across different catchments and at different time scales

09/06/2015

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Next Step Next Step

Assessment the Hydrological Drought:

1. Identify the suitable hydrological drought Indices

2. Applying these indices on historical data (Observed &

NFS_sim)

3. Applying these indices on the baseline projected flow series

(1961-1990)

4. Applying these indices on the future projected flow that is taken

from an ensemble of 6 RCM simulations for the period 2021-

2050


Suggested Drought IndicesSuggested Drought Indices

1- Standardized Discharge Index (SDI)

This Index SDI requires stream flow volume values

The formula of the SDI is:

SDI = (V-Vmean)/Std

Category SDI Range

Non drought ≥ 0.0

Mild drought -1.0 to 0.0

Moderate drought -1.5 to -1.0

Severe drought -2.0 to -1.5

Extremely Dry < -2.0

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Suggested Drought IndicesSuggested Drought Indices

2- MWRI Drought Classification

The total annual flow of the Nile

over the hydrologic year (1st August

– 31st July), categorized based on

the annual naturalized flow of the

Nile at Aswan.

The average annual natural flow of

the Nile is 84 BCM, therefore the

categories are centred around this

figure

Category Natural Flow at Aswan

Extremely dry < 56

Very dry 56 - 70

Dry 70 - 77

Lightly dry 77 - 81

Near normal 81 - 87

Lightly wet 87 - 91

Wet 91 - 98

Very wet 98 – 112

Extremely Wet > 112


MWRI-Based Flow Classification and Corresponding Naturalized Flow

Ranges (BCM) at Key Locations along the Blue Nile, and the Atbara

Category Khartoum Diem Atbara

Extremely dry < 24.5 < 27.5 < 6.5

Very dry 24.5 – 32.7 27.5 – 36.8 6.5 – 8.7

Dry 32.7 - 36.9 36.8 – 41.5 8.7 – 9.8

Lightly dry 36.9 – 39.2 41.5 – 44.1 9.8 – 10.4

Near normal 39.2 – 42.8 44.1 – 48.1 10.4 – 11.4

Lightly wet 42.8 – 45.1 48.1 – 50.7 11.4 – 12.0

Wet 45.1 – 49.3 50.7 – 55.4 12.0 -13.1

Very wet 49.3 – 57.5 55.4 – 64.7 13.1 -15.3

Extremely Wet > 57.5 > 64.7 > 15.3

09/06/2015

15


DoaaDoaa M. M. AminAmin

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