Download Characterizing the uncertainty of climate change impacts using a

Assessing the impacts of
climate change on Atbara
flows using bias-corrected
GCM scenarios
SIGMED and MEDFRIEND
International Scientific Workshop
Relations man / environment and
sediment transport: a spatial
approach
Algeria 7&8 June 2011
Mohamed Elshamy
Outline
1. Uncertainty Cascade
2. The Nile Basin & Previous CC studies
3. Study Area & Methodology
4. Results
5. Conclusions
Uncertainty Cascade
Emissions
Concentrations
Observations
Radiative Forcing
Global Climate Models
Regional Details (Downscaling)
Impact Models (e.g. Hydrology)
The Nile Basin
35
30
 Large area (2.9 x 106 km2)
 Low specific discharge
 Spans several climate
regions
 Variable topography
 High runoff variability
 High Sensitivity to Climate
Cairo
EGYPT
LIBYA
25
Aswan
20
Dongola
Atbara
CHAD
Mogren
Gabal Awlia
15
Khashm
El-Girba
Sennar
SUDAN
ERITRIA
Khartoum
Roseires
Diem
10
Malakal
Hillet Doleib
LakeNo
CENTRAL
ETHIOPIA
AFRICAN
REP.
Mongalla
5
Paara UGANDA
Pakwach
Masindi
D.R. CONGO
KENYA
Jinja
0
RWANDA
BURUNDI
TANZANIA
-5
20
25
30
35
40
Previous Studies (1)
Lake Nasser Flood & Drought Control Project
(2008)
120
100
Total Annual Flow (BCM)
– 6 Transient scenarios
(3 GCMs x 2 Emission
Scenarios)
– Statistically
downscaled using a
spatio-temporal
weather generator
– Changes at Dongola
from 2010-2100
80
60
40
20
HadCM3 A2
CGCM2 A2
ECHAM4 A2
OBS Base
HadCM3 B2
CGCM2 B2
ECHAM4 B2
0
Base 2010s 2020s 2030s 2040s 2050s 2060s 2070s 2080s 2090s
Elshamy, M.E., Sayed, M.A.-A. and Badwy, B., 2009. Impacts of climate change on Nile flows at Dongola using
statistically downscaled GCM scenarios. Nile Water Science & Engineering Magazine 2: 1-14
Previous Studies (2)
Elshamy et al. (2009)
20
18
Ensemble Mean 2081-98
Observed 1961-90
16
Flow (BCM)
– 17 GCMs x A1B
scenario
– Statistically
downscaled using Bias
Correction Method
– Blue Nile Flow
Changes: -60% to +45%
22
14
12
10
8
6
4
2
0
Jan Feb Mar Apr May Jun
Jul
Aug Sep Oct Nov Dec
Elshamy, M.E., Seierstad, I.A. and Sorteberg, A., 2009. Impacts of climate change on Blue
Nile flows using bias-corrected GCM scenarios. Hydrol. Earth Syst. Sci., 13(5): 551-565.
The Atbara Basin
Climate: Semi-Arid/Arid
Area:200 000 km2
Mean Rainfall: 500 mm/yr
Mean PET: 1730 mm/yr
Mean Flow: 8.5 BCM/yr
(1961-1990)
Very Sensitive to Climate
The Atbara Basin
Sensitivity to Climate
200
Atbara
150
Kagera
100
100
80
50
60
0
-40
-30
-20
Flow Change %
Flow Change %
Gilgel Abbay
-10
0
-50
-40
-100
-30
10
20
40
20
Preciptation Change %
40
PET Change %
0
-20
-10
-20
-150
-40
-200
30
-60
-80
-100
0
10
20
30
40
Methodology
Coarse Daily GCM
Rainfall
Bias Correction Downscaling
Fine-Scale Daily Rainfall
Hydrological Model
Flow at Atbara
17 GCMs
x 1 Scenario
Compatible PET Scenarios
Bias Correction Downscaling
 Bias
correction for downscaling rainfall
(based on fitting the gamma distribution to
daily rainfall)
 Simple bias correction for PET (ratio)
 NFS & HBV for hydrological modeling
 An ensemble approach (17 GCMs – A1B)
 Baseline 1961-90, Future 2081-2098,
Daily rainfall data & Monthly PET data
Nile Forecast System (NFS)
Satellite Images
Rain gauge Data
Rainfall Estimation Models
Water Balance
Rainfall Estimates
Hill Slope
Routing
Hydrological
Models
Swamp
Lake
Simulation and Extended
Stream Flow
Prediction (ESP)
Historical
Climate
GIS
HBV Hydrological Model
From soil moisture routine
dUZ
Precipitation on lakes
P
Lake
evaporation
UPPER ZONE
EA=EPOT
UZ
Water balance equation, upper zone:
KUZ1
Q11
d UZ = dUZ - PERC - Q11 - Q10
UZ1
KUZ
Q10
Lake area in % (LA)
PERC
Water balance equation, lower zone:
LOWER ZONE
d LZ = PERC + (P – EPOT)*LA/100 - Q2
LZ
KLZ
Runoff, Q
Q2
PARAMETERS IN THE RESPONSE
FUNCTION :
LZ
KLZ
KUZ
KUZ1
: Water level, lower zone
: Time constant, lower zone, 1/t
: Time constant, upper zone, 1/t
: Time constant, upper zone, 1/t
UZ
UZ1
: Water level, upper zone
: Threshold for quick flow, mm
PERC : Percolation to lower zone, mm/day
RUNOFF COMPONENTS :
Q = Q10 + Q11 + Q2
Q10 = MIN (UZ, UZ1)*KUZ
Q11 = MAX (0, (UZ - UZ1)*KUZ1))
Q2 = KLZ*LZ
Monthly NSE = 0.69 & 0.83 for NFS & HBV respectively
Jan-1990
Jan-1989
Jan-1988
Jan-1987
Jan-1986
Jan-1985
Jan-1984
Jan-1983
NFS
Jan-1982
Jan-1981
Jan-1980
OBS
Jan-1979
Jan-1978
Jan-1977
7.0
Jan-1976
Jan-1975
Jan-1974
Jan-1973
Jan-1972
Jan-1971
Jan-1970
Jan-1969
Jan-1968
Jan-1967
Jan-1966
Jan-1965
Jan-1964
Jan-1963
Jan-1962
Jan-1961
Monthly Flow (BCM/mon)
Model Performance
8.0
HBV
6.0
5.0
4.0
3.0
2.0
1.0
0.0
The GLUE Framework
• GLUE: Generalized Likelihood Uncertainty
Estimation
• GLUE rejects the concept of a single
optimal model and parameter set
• Assumes all model structures and
parameter sets have a likelihood of being
accepted
• Likelyhood depends performance as
measured by a selected criteria
Results: Rainfall Changes
220
200
Rainfall (mm/month)
180
Mean
Mean 2081-98
1961-1990
Mean
OBS 1961-90
160
140
120
100
80
60
40
20
0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Results: PET Changes
310
Temperature (°K)
305
300
295
290
285
Mean
Mean1961-1990
2081-98
OBS
Mean 1961-90
280
Jan Feb Mar Apr May Jun Jul Aug Sep
Sep Oct
Oct Nov
Nov Dec
Dec
Results: Flow Changes - NFS
7
Mean
Mean Monthly Flow (BCM)
6
Median
Max
5
Min
OBS
4
3
2
1
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Sep
Oct
Oct
Nov
Nov
Dec
Dec
Results: Flow Changes - HBV
7
Mean Monthly Flow (BCM)
6
5
4
3
2
1
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Sep
Oct
Oct
Nov
Nov
Dec
Dec
Conclusions
• GCMs agree on Temperature rise (2-5.3 °C) leading
to 3-17% increase in PET
• GCMs disagree on precipitation changes (-36% to
+39%)
• High Sensitivity of Basin leads to extreme flow
change ranges: -76% to +97% from both NFS & HBV
• Ensemble mean flow is reduced by 25% & 6% for
NFS & HBV respectively
• Hydrological models add another uncertainty
• GLUE provides a framework to propagate the
uncertainty from scenarios to impacts
• Probabilities are now attached to the uncertainty
bounds
• Small sample size lead to small difference between
GLUE bounds and max/min bounds