Transcript Simulating the Population Vulnerable to Drought Related Food

The GLASS Model:
The Use of Population Data in Global
Modeling of Environment and Security
Marcel B. Endejan
Center for Environmental Systems Research
University of Kassel, Germany
Workshop on Gridded Population Data
2-3 May 2000
Overview
• Introduction
• The GLASS Model
– Crisis Probability
– Susceptible / Potentially Affected Population
• Need for gridded population data
• Specification for population data
• Conclusion
Introduction
• Many aspects of
environment
social
political
human
being
natural
economical
– environment
– human security
• Extreme climate events
• Long term changes
• Response of society
• Quantification
 Integrated Model
GLASS Model
Driving
Forces
Environmental
Changes
Environmental
Stress
Slow
Economic
Data
Technology
Data
IMAGE
Climate
Model
Average
Climate
WaterGAP
Model
Year-toYear
Availability
Historical
Climate
Data
Climate
Variability
Generator
Slow
Demographic
Data
Population
Profile
Generator
Population
Profile
Water
Stress
Affected
Population
Average
Water
Availability
Crisis Model
Fast
Climate
Variability
& Extreme
Events
Crisis
Potential
FAO
Crop
Model
Average
Yield
Year-toYear
Yield
Crisis
Signal
Crop
Stress
Susceptible
Population
Security Diagram
Three Concepts
– Degree of a certain stressor
– Susceptibility to this kind of stressor
– Crisis
Crisis Occurrence
e.g. Ethiopia 1973
No Crisis Occured
e.g. Sudan 1953
Environmental
Stressor
Boundary:
High Probability
of Crisis
Boundary:
Low Probability
of Crisis
State Susceptibility
Security Diagram - Indicators
• Stressor
Fraction of country area with water availability
substantially below normal
• Susceptibility
Normalized GDP per cap
GDP’ = 1 - (GDP/100,000 US$)
• Crisis
‘Droughts’ from EM-DAT (~600)
Security Diagram - Example
1
Stressor
0.8
0.2
8000
US$/cap
0
0.92
0.936
0.952
0.968
Susceptibility (GDP’)
0.984
1
country year
reported drought
0
US$/cap
Security Diagram - Crisis Probability
[0.800;1.000[
[0.600;0.800[
Boundary:
high &
low crisis
probability
Water Stressor
[0.400;0.600[
Crisis
Probability
[%]
[0.200;0.400[
10-15
5-10
0-5
[0.936;0.952[ [0.952;0.968[ [0.968;0.984[
[0.920;0.936[
[0.000;0.200[
Susceptibility [1-GDPnorm] [0.984;1.000[
Susceptible Population
• Young (<14) and old (> 60) people with
GDP/cap below poverty line
• Poverty line according to World Bank
–
–
–
–
Developing countries:
1 US$/day (365$/a)
Latin America:
2 US$/day (730)
Eastern Europe+CIS:
4 US$/day (1460)
Industrialized Countries: 14.4 US$/day (5256)
• Income distribution estimated using GINI
index
Susceptible Population
selected countries
3.5E+07
susceptible population [people]
Ethiopia
3.0E+07
South Africa
USA
2.5E+07
Spain
2.0E+07
1.5E+07
1.0E+07
5.0E+06
0.0E+00
1900
1920
1940
1960
year [-]
1980
2000
Need for Gridded Population Data
To improve
• Concept of potentially affected population
– more detailed calculation of susceptible
population
– Affected population = susceptible population in
affected areas
• stressor concept
– more detailed calculation of affected areas
– take water use into consideration
Specification for Population Data
• Gridded population data for different time
intervals needed about
– population density per grid cell
– urban/rural fraction per grid cell
– access to water, food, and other resources
• Currently available
– population density per grid cell
Population Data - Used
• Calculation of domestic water withdrawals
Population density 1995
:cell
Population; total
Population; urban/rural total
:cell
Population;
urban/rural fraction
Population;
access to save drinking
water urban/rural [%]
Domestic water withdrawals
domestic water
withdrawls :cell
Population Data - Used
Domestic Water Withdrawals [m3 / a]
Imgcountry95
Withdom1995
0 - 1E6
1e6 - 10e6
100e6-1e9
1e9-10e9
10e9-100e9
No Data
(c ) A p r il 2 6 th , 2 0 0 0
Ce n te r f or E n vi ro n m e n ta l
S yste m s R e se a r ch ( me )
Un iv e rs ity o f K a s se l
Do m e sti c W a ter W ith d r aw ls 1 9 95
S ou r ce : ta l kci e sin .a p r
Conclusion
• GLASS: Model to quantify the linkage
between environment and human security
• Population data needed to calculate
– water use, food demand (stressor/crisis probability)
– susceptible / potentially affected population
• Gridded population data (time intervals)
– population density
– urban/rural fraction
– access to water, food, and other resources