climate change impact assessment and agricultural land...
TRANSCRIPT
Climate change impact
assessment and agricultural
land use decision making in the
Vietnamese Mekong Delta
Nguyen Hieu Trung1, Van Pham Dang Tri1, Truong Chi Quang1,
Huynh Xuan Hiep 2, Alexis Drogoul3
1College of Environment and Natural Resources (CENRes), Can Tho University;
Campus 2, 3/2 street, Ninh Kieu district, Can Tho city, Vietnam. e-mail:
[email protected] of Information and Tele Communication (CITC), Can Tho University.
3 IRD, UMI 209, UMMISCO, IRD France;
Contents
• The Mekong Delta’s agriculture land use
change driving factors.
• CC impact assessment
• Agricultural land use decision making
• the IRD-CTU research team: Decision-
support Research for Environmental
Applications and Models (DREAM)
Fast land use change in MRD
Department of Land Resources, Can Tho University, 2013
Agriculture land use change driving factors
Saline intrusion 1998 (dry year)
Dry season Rainy season
We
st
se
a
• Long river from very high elevation (~4000m) to the sea level (0.5 - 1m).
• 70-80% of the precipitation concentrated into four months annual flood
in rainy season.
• Tides: East sea is semi-diurnal (amplitude: 2.5 – 3.0 m), and West Sea
tide is diurnal (amplitude: 0.4 – 1.2 m) annual saline intrusion in dry
season.
• Autonomous adaptation (farming techniques, new short duration rice,
new crop, aquaculture, integrated farming techniques)
• Plan adaptation (flood and salinity control system)
Over exploitation of ground water (for
urban, industry and rural) Saline
intrusion in ground water and
Land subsidence.
(Source: Erban et al., 2014)
Agriculture land use change driving factors
Existing irrigation projects Planned irrigation projectsExisting, under-construction
and proposed hydro-power
projects
Cross boundary water competition
Agriculture land use change driving factors
Sea level rise: East Sea: Average 4.7
mm/year (1993-2009) Projected to
2050: + 30 cm; 2100: + 70 cm
Future climate change and sea level rise
Agriculture land use change driving factors
• Regional development
• Increase accessibility need:
both physically (e.g. road)
and non-physically (data,
information, knowledge)
• Increase resource demands
(both natural and socio-
economic)
Complex land use and resource
planning an interactive land
use planning approach
Agriculture land use change driving factors
Contents
• The Mekong Delta’s agriculture land use
change driving factors.
• CC impact assessment
• Agricultural land use decision making
• the IRD-CTU research team: Decision-
support Research for Environmental
Applications and Models (DREAM)
CC impact assessment
Basin/regional scale:
• Flood modeling
• Saline intrusion modeling
Sub-ecological scale:
• Flood zone modeling
• Coastal zone modeling
Field scale:
• Crop modeling
Rainfall – Runoff modelSWAT
Integrated Quantity and Quality Model(IQQM)
Water demand
Hydro-power dev.
Agriculture dev.
Hydraulic model Water quality model
(from Kratie, Mike 11)
Upstream scenarios
Mekong delta development scenarios
Sea level rise scenarios
Water management scenarios
Saptial analsys- Land use- Inundation- Salinity intrusion
Results- Changes of inundation area- Changes of saline inundation area
Temporal analysis- Probability- max- min- Averahe
Results- Changes of discharge- Change of salinity level
Socio-economic scenarios
Impact to
saline
intrusion
Upstream
boundary:
flow at
Kratie
Downstream
boundary(SIWRR, 2012)
Scenario 1 - SLR 30 cm
Scenario 2 (worse case) =
Scenario 1 + upstream
projects, dry year)
Scenario 3 = Scenario 2 +
structural intervention
(larger river mouse sluice
gates Saline iso-line (4 g/l)Source: Mekong Future project (Collaboration with CSIRO)
Impacts to saline intrusion (dry season)
(Van Pham Dang Tri, et.al. 2012)
• Longer flood duration (2000
vs 2050)
• Two groups of flooding:
– Upstream of Mekong
Delta by Mekong river
flow.
– Coastal of Mekong Delta
by tide, especially the
west coast (more than 4
months).
Impact to flood (rainy season)
Contents
• The Mekong Delta’s agriculture land use
change driving factors.
• CC impact assessment
• Agricultural land use decision making
• the IRD-CTU research team: Decision-
support Research for Environmental
Applications and Models (DREAM)
(Mekong future project, 2010-2012)
Agricultural land use decision making
Current land use
Biophysical
Land
Evaluation
Suitability and yield/LMU
Available capital Available labor
Available land area
LUTs’ cost/LMU
Require labor/LUT/LMU
Production priceSocio-economic
analysis
• Data management tools
• Land use analysis tools
(Optimization)
• Visualization tools
Soils
, wat
er (
inu
nd
atio
n, s
alin
ity)
LMU
Decision support information (graphs, maps, tables, reports)
LU allocation of scenario 1
Hydraulic models
(Trung, et. al. 2014)
Research theme 5. CLUES project
Agricultural land use decision making
(Trung et. al., 2014)
Contents
• The Mekong Delta’s agriculture land use
driving factors.
• CC impact assessment
• Agricultural land use decision making
• the IRD-CTU research team: Decision-
support Research for Environmental
Applications and Models (DREAM)
the Decision-support Research for
Environmental Applications and
Models (DREAM) research team
– To enhance the cooperation among relevant
colleges (CENRes, CIT, CNS ) and IRD in applying
modern information technology and mathematical
solutions for sustainable development of the VMD.
– Tools for interactive LUP approach could be
applied in the context of the VMD.
Activities of DREAM’s LUP team
• Project: Adaptation to Climate Change: Land-use Innovative Models Applied to
Environmental management (ACCLIMATE)
• Organization of training on ABM (GAMA) + GIS + Hydrological models.
• Insertion of the three Master modules in existing curricula in CTU
• Supervised PhD and MSc subjects from College of Information Technology and
College of Environment and Natural Resources
• A multi-disciplinary research team on LUP in CTU.
• Good facilities for training and research.
• An ABM model (GAMA) on land use decision making.
• A server ready for WebGIS and DBMS.
• Join training and workshop with PEERS project.
• Join publications.
Activities of DREAM’s LUP team
Current land use
Biophysical
Land
Evaluation
Suitability and yield/LMU
Available capital Available labor
Available land area
LUTs’ cost/LMU
Require labor/LUT/LMU
Production priceSocio-economic
analysis
• Data management tools
• Land use analysis tools
(Optimization and ABM)
• Visualization tools
Soils
, wat
er (
inu
nd
atio
n, s
alin
ity)
LMU
Decision support information (graphs, maps, tables, reports)
LU allocation of scenario 1
Participatory planning precision farming
Hydraulic models
Participatory
monitoring
Future development: Interactive and real-time land use management DSS
Sensor network
