1. Task 2: Mekong ARCC Climate
Change Impact and Adaptation
Study for natural and agricultural
systems
May 2012, Vientiane

2. Aim
• The aim of Task 2 is to undertake a climate change
impact and adaptation study on the water
resources, food security, livelihoods and biodiversity
of the Mekong River Basin

3. Objectives
1) identify vulnerabilities of rural poor and their environment to
climate change vis-à-vis water resources, food
security, livelihoods and biodiversity;
2) provide a scientific evidence base for the selection of case
study sites;
3) identify adaptation strategies to inform development of
community and ecosystem-based adaptation projects; and
4) inform policy makers, development specialists and the global
climate science community on the impacts of climate change
on water resources, food security, livelihoods and biodiversity
of the Mekong Basin.

4. Phases, events & outputs
threat vulnerability adaptation
3. Future
5. Identify
2. Zoning and climate 4.Vulnerability
1. Inception adaption 6. Reporting
trend analysis conditions assessment
options
and threats
Team Inception Team Vulnerability Team Final
working workshop working workshop working workshop
session session session
Baseline assessment Basin & zone Adaptation FINAL
& review of past vulnerability options by REPORT
studies assessment Zones

5. Study technical team
Sector/theme working groups
Sector/theme Members
1. Climate change, water Tarek Ketelsen (lead), Jorma Koponen, Mai Ky Vinh, Oliver Joffre
resources, modelling and GIS
2. Natural systems and Peter-John Meynell (lead), Nguyen Huu Thien, Sansanee
biodiversity Choowaew, Jeremy Carew-Reid,
3. Agriculture Oliver Joffre (lead), Dang Kieu Nhan, Bun Chantrea, Jorma
Koponen
4. Fisheries and aquaculture Rick Gregory (lead) Truong Hoanh Minh, Chavalit Vidthayanon,
Meng Monyrak
5. Livestock Rod Lefroy (remote participant)
6. Socio-economics and John Sawdon (lead), Try Thuon, Sengmanichanh
livelihoods Somchanmavong, Alex Kenny
National working groups
Sector/theme Members
1. Cambodia Try Thuon (lead), Bun Chantrea, Meng Monyrak
2. Lao PDR Sengmanichanh Somchanmavong (lead)
3. Thailand Sansanee Choowaew (lead), Chavalit Vidthayanon
4. Vietnam Nguyen Huu Thien (lead), Dang Kieu Nhan, Truong Hoanh Minh,

6. Assessing climate change threats to agriculture and
subsistence livelihoods
Climate
changes
Hydrological
changes
Agricultural Ecological
zones zones
Species “zones”
Commercial Subsistence Aqua- Traditional Live- Crop wild NTFPs Wild fish Wildlife
crops crops culture crops stock relatives catch
Adaptation options

7. Agricultural systems and climate change continuum

8. CAM method
Source: ICEM, 2012

9. Key assessment concepts
Zones
• Climate change, Ecological, Agricultural
Shifts
• Geographic, Elevation, Seasonal
Hotspots
• Exposure, Sensitivity, Adaptive capacity

10. Climate change overlaid on “zones”
Zones provide the common analytical framework for the study team
Purpose of zoning is to:
• Identify areas of the basin with common bio-physical and
socio-economic characteristics
• Observe “shifts” in the zones with climate change
Three types of zones:
1. Climate change zones – temperature, rainfall
and hydrology
2. Agricultural zones – agricultural land uses and
natural conditions
3. Ecological zones – natural habitat, species and
genetic resources 10

11. Climate
change zones
Areas experiencing
similar climate
change
2050

12. Bioregions

13. Agriculture zones

14. Climate change shifts
Regular climate
1. Geographic shifts – change in area of suitability
2. Elevation shifts (for highly restricted habitats and
species) – change in (i) location and (ii) elevation
3. Seasonal shifts – change in (i) yields, (ii) cropping
patterns
Extreme events
4. Extreme event shifts
 Micro – eg flash flooding and soil loss in uplands
 Macro – eg saline intrusion in Delta; cyclone landfall

15. Geographic shift Shift in zone of suitability
for habitat and crops
Original extent of
natural habitat
Paddy rice
and
commercial
crops
Remaining
natural habitat Subsistence crops and NTF
pockets collection

16. 2050
Elevation shifts

17. Seasonal shifts
Kratie
Increase in flood magnitude
& volume
Quicker onset of flood &
shortening of transition
season Increase in flood duration
Source: ICEM, 2012

18. Climate change “hot spots” – i.e. highly vulnerable areas
• High exposure:
 significant climate change relative to base conditions
 exposure to new climate/hydrological conditions
• High sensitivity:
 limited temperature and moisture tolerance range
 degraded and/or under acute pressure
 severely restricted geographic range
 rare or threatened
• Low adaptive capacity
 Poor connectivity
 Low diversity and tolerances
 Homogenous systems

19. Climate change
THREATS

20. Climate and hydrological changes
Climate changes Hydrological changes
Regular (daily and seasonal) Regular (daily and seasonal)
 Increase in C02  Water availability
 Change in temperature  Runoff and flow
 Change in rainfall  Regular flooding
 Evapotranspiration
Extreme events  Saline intrusion
 Storms  Sea level rise
Rainfall
Extreme events
Wind
 Flooding (fresh and salt water)
Low pressure
 Flash flooding
 Drought
 Storm surge

21. SYSTEM ASSETS AND
SENSITIVITY

22. System assets
Top commercial crops
Vietnam Laos Thailand Cambodia
Rice, paddy Rice, paddy Rice, paddy Rice, paddy
Coffee, green Maize Rubber Cassava
Cashew nuts, with shell Coffee, green Cassava Maize
Cassava Tobacco, Sugar cane Bananas
Fruit trees: Bananas and Traditional crop varieties Wild plants
mangoes  Rice (more than 13,000  Cardamom,
identified in Lao  Rattan and bamboo
Vegetables: Sweet potatoes,  Eggplant (more than 3000  Orchids
tomatoes, beans, chilli in Lao)  Mushrooms
 Papaya
Subsistence crops  Banana (centre of origin) Crop wild relatives
 Lowland and upland rice  Mango (centre of origin)  Glutinous rice (centre of
 Cassava  Pineapple origin
 Maize  Water melon  Eggplant (centre of origin)
 Peanuts  Passion fruits
Centre of origin for: coconut palm, sugarcane, clove, nutmeg, black pepper, onion, cucumber

23. Non cc drivers influencing agriculture trends
• future cropping patterns
• area irrigated,
• crop genetics,
• farm mechanization,
• farm employment,
• fertilizer rates and pesticide use
• Improved agronomic management
• Infrastructure and accessibility

24. Sensitivity assessments: climate tolerances
Optimal growing conditions: Mean annual maximum
temperature

25. Optimal growing conditions: mean annual precipitation

26. Key issues the team needs to resolve
• Deciding on the priority assets (i.e. species and
habitats)
• Linking species to habitats
• Dealing with ecosystem services
• Knowing enough about species and habitat
tolerances to conduct the vulnerability assessment

27. Assessment approach
TASK 2 APPROACH

28. CAM - Basin wide VA assessment framework

29. Key assessment methodologies & tools
CC modeling
Basin zoning
GIS Analysis
Basin land suitability
Hotspot crop yield
modeling

30. Assessment approach
CLIMATE & HYDROLOGICAL
MODELLING

31. Projections of future emissions
and global GHG concentrations
IPCC EMISSION SCENARIOS
A1 B1 A2 B2
Modelling Projections of future atmospheric climate, atmospheric & ocean
dynamics
GCMs – GLOBAL CIRCULATION MODELS
options BCCR-
BCM2.0
FGOALS-
G1.0
CCSM3
GFDL-
CM2.0
CGCM3.1
(T47)
GFDL-
CM2.1
CGCM3.1
(T63)
GISS-
AOM
CNRM-
CM3
GISS-EH
CSIRO -
MK3.0
GISS-ER
ECHMA5/
MPI-OM
INM-
CM3.0
ECHO-G
IPSL-CM4
MICROC3. MICROC3.2 MRI- PCM UKMO- UKMO-
2 (hires) (medres) CGCM2.3. HADCM3 HADGEM
2 1
Downscaled projections of future climate at
the basin-level
CLIMATE DOWNSCALING
DYNAMICAL STATISTICAL PATTERN
(PRECIS)
PRECIS Vietnam 2009 Mekong Basin 2009
Southeast (WeADAPT) (Cai et al, 2008)
Asia 2003
(SEASTART)
Prediction of future hydrological regime
HYDROLOGICAL MODELLING
VMOD VMOD MRC DSS VMOD SLURP CSIRO
Songkhram Mekong Delta Mekong Mekong Mekong Mekong
2004 2008 Basin 2010 Basin 2011 Basin 2011* Basin 2009
(Aalto Uni & (Aalto Uni & (MRC & (Aalto Uni & (QUEST) (18 sub-
SEASTART) SEASTART) IWMI) ICEM) (no Mekong 31 basins)
floodplain)

32. Approaches to modeling climate change:
assessing future threat
• CC modelling:
– allows for the 1. Projections of future emissions
quantification of future
climate change threats 2. Projections of future atmospheric
and ocean dynamics
– Is not perfect but is
based on leading 3. Downscaling projections to the
Mekong Basin
thinking on climate
science
4. Predicting future changes in the
– Assesses the impact of basin hydrological regime
changes in the global 5. Predicting future changes in the
climate system to local Delta floodplain environment & project
site
areas of interest
32

33. Steps in the CC approach:
1 - Selection of appropriate IPCC scenarios
33
Source: CSIRO, 2009

34. Step 2: selection of appropriate GCMs
• Two earlier studies (Cao et al, 2009; Eastham et al, 2008)
reviewed the performance of or used 17/24 IPCC AR4 GCMs
for suitability to the Mekong region
• 6 were chosen based on their ability to replicate daily
historical temperature and rainfall data
• In general, models perform better for temperature than
precipitation
Climate model CO2 Scenario Abbreviation Data period Model resolution (degrees)
CCCMA_CGCM3.1 A1b, B1 ccA, ccB 1850-2300 3.75° x 3.75°
CNRM_CM3 A1b, B1 cnA, cnB 1860-2299 2.8° x 2.8°
GISS_AOM A1b, B1 giA, giB 1850-2100 3° x 4°
MIROC3.2Hires A1b, B1 miA, miB 1900-2100 1.1° x 1.1°
MPI_ECHAM5 A1b, B1 mpA, mpB 1860-2200 1.9° x 1.9°
NCAR_CCSM3 A1b, B1 ncA, ncB 1870-2099 1.4° x 1.4°
34

35. Steps 3 – downscaling projections to the Mekong Basin
Purpose: reduce the geographical scope so that
resolution can be improved
1. Statistical
 Assumes local climate is conditioned by large-
scale (global) climate but does not try to
understand physical causality
 GCM output is compared to observed information
for a reference period to calculate period factors
 Period factors are then used to adjust GCM time-
series
2. RCM (Regional Circulation Models)
 most sophisticated way to downscale GCM data
 Physically based
 25-50km resolution
 Computationally intensive
 Requires detailed understanding of regional
atmospheric and ocean processes
3. Pattern-scaling
 Uses high resolution observation data to scale
GCM data to small areas or monitoring points
 Suitable when there is extensive observation data
 Cannot correct for statistical bias so should only
be used to assess relative changes 35

36. Step 4 – Predicting future changes in the basin hydrological
regime
• VMod model
• area-based distribution of
hydro-meteorological
impacts of climate change
• Computes water balance for
grid cells ~3kmx3km
• Baseline 1981 - 2005
• Can predict changes in:
– Rainfall
– Runoff
– Flows
– Infiltration
– evapotranspiration
36

37. Step 5 – Predicting future changes in the flooding
• MIKE-11
• Uses Vmod to establish
boundary conditions
• Divides the floodplain into
zones (>120 in the delta)
• Calculates small area water
balances
– 25,900 water level points
– 18,500 flow points
• Quantifies the changes in
depth and duration of
flooding due to changes in
upstream hydrology and sea
level rise
37
Source: SIWRR, 2011

38. LAND SUITABILITY

39. Predicting future changes in land suitability
Basin – crop suitability
basin • Agro & eco zoning of basin characteristics
• Historic suitability of basin for a range of
commercial and subsistence crops
• Suitability with climate change
• Assessment of transitions and shifts in
geographical and seasonal suitability
target area
Target areas – crop yields
• Losses in crop yields within transition zones
• Yield potential for new crops in transition
zones

40. Predicting future changes in land suitability
LUSET – Land use suitability evaluation tool
• Developed by IRRI
• evaluates the suitability of each land unit (grid cell)
for a single type of land use type (single crop).
• based on crop requirement, climate, terrain and soil
characteristics.
• Allows for assessing changes in temperature and
rainfall before aggregating suitability

41. Crop requirement: Terrain
(slope and drainage)
Terrain suitability value
Land characteristic:
Terrain (slope and
drainage)
Crop requirement: Soil
characteristics (pH, soil
texture, soil depth, base
saturation)
Soil characteristics Combined weighted Suitability class table and
suitability value suitability value GIS layer
Land characteristic: Soil
characteristics (pH, soil
texture, soil depth, base
saturation)
Crop requirement: Water,
temperature
Land characteristic:
Meteorological Water, temperature
characteristics (rainfall, suitability value
temperature)
Land characteristic:
Irrigation
41

42. Lowland rice

43. upland rice

44. cashew
cashew

45. rubber

46. Coffee (coffea canephora)

47. cassava

48. Black pepper

49. Maize

51. CROP YIELD MODELLING

52. Predicting future changes in agricultural productivity
AquaCrop
• Crop productivity model
developed by FAO
• Water driven
– quantifies the relationship between
crop growth/biomass and crop
transpiration
• Changes in yield compared to
reference/ideal conditions for a
given crop
• emphasizes the fundamental
processes involved in crop
productivity and the responses to
water deficits,
• Can also factor in CO2
concentrations
52
Source: FAO, 2010

53. Maize growth cycle
AquaCrop
• Assesses water
requirements at each
growth phase relative to
a reference norm and
quantifies changes in
biomass => yield
Source: FAO, 2010

54. yield
Establishment | Vegetative | Flowering | Formation | Ripening | Maturity
Reduction in max
canopy cover
Decline in
canopy cover
during
productive
phases (yield
formation/
ripening)
Delay in time to reach max canopy cover
Source: FAO, 2010

55. ADAPTATION

56. Adaptation in zones, habitats and species
Adaptation in vulnerable (hot spot):
• agriculture zones
• ecozones
• habitats
• species:
 Industrial/commercial crops
 Subsistence crops
 Traditional crops
 Crop wild relatives
 NTFPs

57. Adaptation

58. Addressing the adaptation deficit