THE AS25 PROJECT: AN IA APPROACH FOR
VULNERABILITY AND ADAPTATION ASSESSMENT
IN WESTERN CHINA
(Presentation at the AIACC Asia Regional Workshop)
March 22-27, 2003, Bangkok, Thailand
By Yongyuan Yin
International Institute for Earth System Science, Nanjing University,
Adaptation and Impacts Research Group, Environment Canada,
and Sustainable Development Research Institute (SDRI)/UBC
Email: yongyuan.yin@sdri.ubc.ca
Outline
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Overview: the AIACC AS25 project
Updated Achievements
IA Research Methodology
Data Collection by RS & GIS
• Sensitivity Identification, Vulnerability &
Adaptive Capacity Assessment
• Barriers Experienced
• Link to National Communication
• Capacity Building and Multi-Stakeholder
Involvement
• Acknowledgement
Project Objectives:
The purpose of the project is to develop an integrated approach
(IA) for identifying regional vulnerabilities to climate variations
and change, and for prioritising adaptation options to deal with
climate change vulnerability. In particular, the project will
addresses the following questions:
1) How vulnerable is Western China to current climate variations
and future climate change in some key sectors?
2) What can the vulnerabilities of these key sectors to present
climate variations teach us about future vulnerability? And
3) What are the desirable adaptation options to deal effectively
with future climate changes?
Updated Achievements
 Established a Steering Committee and a Expert
Committee for the project.
 Enhanced research capacity by involving CMA.
 Developed a conceptual IA approach for
identification of the societal vulnerabilities to
climate stimuli and desirable adaptation
options to deal with system vulnerabilities.
 Conducted research in some components of the
project: AIACC training, data collection,
climate scenario develop by RCM, and so on.
Updated Achievements
 Undertaken a training workshop in Lanzhou (shared
with a CIDA project) and a team meeting in Nanjing
 Identified regional concerns in resource management
and climate stresses
 Improved understanding of the interactions between
regional sustainability and climate change.
 Trained young scientists and graduate students to
design and apply IA methods in a real world context.

Research Methodology
The IA approach will combine computer
modelling and non-model based methods
including a series of training workshops,
survey, expert judgement, community
engagement, multi-stakeholder consultation,
ecological simulation modelling, geographical
information system (GIS), remote sensing,
fuzzy set classification, goal programming,
and multi-criteria decision making (MCDM).
Research Methodology
1. Climate scenarios and extremes


Prof. Ding Yihui: RCM of China
CIDA C5 project CC Scenario Workshop
2. Socio-economic scenarios
 Dr. Shuming Bao: Database of China
 National West China Development Strategy
3. Data collection: RS, GIS, field work, literature
review, and survey
 Dr. Zhongmin Xu: Vulnerability Methods
Remote Sensing Land Use and Land Cover
Dynamics of Zhangye Region in Western China
(Source: Qi et al., 2002)
Image Processing Methods:
• Unsupervised classification
• Supervised classification
• Continuous field: fractional vegetation
• Change detection of urban expansion
Image Sources
Three Landsat images over a span of 25
years have been used
Results: land cover change
Agricultural land expansion is obvious
Potential sensitivity matrix showing the climate variables with
the greatest forcing and activities with the broadest sensitivity
in Western China (Modified from: Hennessy and Jones, 1999)
High
Climate and related
variables (forcing)
Activities (sensitivity)
Rainfall - variability
Drought
Evaporation
Soil moisture
Stream flow
Water supply, cropping, Grazing
Water management, cropping, Grazing
Water supply, cropping, Grazing
cropping, irrigation salinity
water supply
Moderate Temperature - min
Wind
Irrigation
Cropping
Soil erosion, sand storm
cropping, irrigation salinity, soil erosion
Low
Cropping, properties
cropping yield, carbon sequestration
Hail
CO2
Vulnerability and Adaptive
Capacity Assessment
Methods
Environmental Risk = exposure frequency (probability)  consequence
Consequence = F{intensity, sensitivity, adaptive capacity}
• Selecting Vulnerability and Adaptive Capacity
Indicators
• Identifying Critical Thresholds for Indicators
• Setting Priorities to Vulnerability Indicators
• Vulnerability Classification by the Fuzzy Set Model
• Adaptive Capacity Classification by the Fuzzy Set
Model
Vulnerability and adaptive capacity indicators
Sectors Indicators
Water resources
VI water demand, water storage stress, water stress, hydropower,
EI water supply climate variables, Palmer drought severity index,
low flow event frequency and duration,
ACI
economic return, industry productivity, regulated annual supply,
institutional frameworks
Agriculture
VI population growth, water resource consumption, arable land loss,
food consumption
EI cold snap, heat stress days, monsoon pattern, accumulated degree days,
water supply, Palmer drought severity index
ACI
farm income, agricultural product price, agricultural production,
Ecosystems
VI soil erosion, desertification, sand storm, population growth rate, population density
EI water supply, high winds Number of days, sand storms, Palmer drought severity index,
heat stress days, cold snap days,
ACI
forest area protection, emission reduction of CO2, ecological protection
-------------------------Note: VI=vulnerability indicator; EI= Exposure indicators; ACI=adaptive capacity
indicator
Prioritizing Adaptation Options or Policies
Adopt a multi-criteria decision making
technique, Analytic Hierarchy Process
(AHP), to identify desirable adaptation
options to reduce climate vulnerabilities
and to improve adaptive capacity.
Barriers Encountered
• To obtain China GEF Office
endorsement;
• To communicate and cooperate among
researchers in various institutes and
regions; and
• To collect a large amount of data and to
develop new methods for vulnerability
and adaptation assessment.
Link to China National Communications
• Involving and consulting with Chinese
government officials and experts who are
responsible for preparing the NC;
• Holding training courses and policy workshops
(regional and local decision makers) to improve
China’s capacity about various IA methods,
vulnerability and adaptation tools, ecosystem
sustainability, and database establishment; and
• Sharing information and results of the AS25
project with agencies and people responsible for
NC.
Capacity Building
• Young scientists were trained at a workshop (shared
with the CIDA Carbon Sequestration project) to apply
computer based models to assess climate change
impacts and to evaluate adaptation options.
• The workshop also involved multi-stakeholder and
experts to present their concerns and suggestions on
climate and resource related issues.
• Many farmers were interviewed individually and asked
to complete a survey in a one-on-one interview or in a
small group workshop-type setting in Heihe region
during summer of 2002.
Acknowledgements
The research project and participation of this
workshop have been made possible through
the financial support of the AIACC,
Adaptation and Impacts Research
Group/Environment Canada, and Sustainable
Development Research Institute/University
of British Columbia.