CCAFS meeting Hanoi

Overview of climate variability and likely climate change impacts on agriculture across the Greater Mekong Sub-region

(GMS)

Eitzinger Anton, Giang Linh, Lefroy Rod, Carmona Stephania, Laderach Peter

Project milestones

• Assemble database and quantify impact on crop suitability December 2013

• Engage with partners and share methods and first results March 2014

• Incorporate feedback, rerun analysis and finalize results May 2014

Data collection

Climate grids are constructed for nine climate variables for the period 1901-2009- Temperature, - Diurnal temperature range, - Daily minimum temperature, - Maximum temperatures, - Precipitation,- Wet-day frequency, - Frost-day frequency, - Vapor pressure, and - Cloud cover.

CRU TS climate database 3.10.01

CRU TS climate database 3.10.01

Tmean + 1.8 ˚C to 2 ˚CTmax +1.7˚C to 2.2˚CTmin + 1.6˚C to 2.2˚C

No clear rainfall change pattern …Temperature increased between 1901 to 2009

?

http://www.worldclim.org

Worldclim stations worldwide

47,554 precipitation

24,542 tmean

14,835 tmax y tmin

Sources:•GHCN•FAOCLIM•WMO•CIAT•R-Hydronet•Redes nacionales

Sources:•GHCN•FAOCLIM•WMO•CIAT•R-Hydronet•Redes nacionales

Climate baseline

TemperatureAnnual mean temperature, Mean diurnal range, seasonality, Max of warmest month, Min of coldest month, Annual Range, Mean of Wettest/Driest Quarter, Mean of Warmest/Coldest Quarter

RainfallAnnual, Rainfall of Wettest/Driest Month, Seasonality, Rainfall of Wettest/Driest/Warmest/Coldest Quarter

* current annual mean temperature, current annual rainfall

Not available = natural (forest, wetland, …), protected, water, bare, urban areasLU Change risk = land mixed with pastoralism (forest, herbaceous, wetlands, …)Available = Agriculture (commercial, subsidized, irrigated, …)

Land use change at risk

for agriculture

Land use change• Vegetation Index (MOD13Q1 MODIS Product , 16 days, 250m)

Normalized difference vegetation index (NDVI) … the values are closely related to vegetation type and climatic conditions as well as the predominant land use pattern.

Data noise filtering

Crop-Climate-Suitability modeling using Ecocrop

Crop climate- suitability change by 2050

Histograms of D:\_modeling_OUTPUT\sea\run-1.gdb\banana2chg in zones of D:\Anton\_DAPA\_Projects_ongoing\SEA-CCAFS\geodata\gms_mask.shp

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LAO MMR THA VNM CHN

Histograms of D:\_modeling_OUTPUT\sea\run-1.gdb\potato2chg in zones of D:\Anton\_DAPA\_Projects_ongoing\SEA-CCAFS\geodata\gms_mask.shp

KHM

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LAO MMR THA VNM CHN

Histogram: Banana Potato

Cambodia Laos Myanmar Thailand Vietnam China Cambodia Laos Myanmar Thailand Vietnam China

2 step analysisCompare predicted future suitability change from climate models and Ecocrop maps and existing land use data

A time-series analysis of Land Use change using satellite images to identify change patterns in land use

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2

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1 risk for land use change

2006 20122000

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Expansion of of Maize, Sayabouri

What can be detected? 2

Engage with partners and share methods and first results

Validation of Ecocrop results• Groupwork and Discussion on suitability maps

Actual production area

This area is not suitable

Temperature suit. Rainfall suit.Climate-suitability

Crop x

• Share & discuss methods of climate change impact assessment with partners

• Training on EcoCrop modeling using DIVA-GIS

Presentations & Discussion1. What is the evidence and observed changes in the

climate system and how reliable are climate models and scenarios?

2. How to use climate models & future predictions for Agriculture and modeling?

3. How can we adapt agriculture systems to unknown future conditions?

Overview of climate variability and likely climate change impacts on agriculture across

the Greater Mekong Sub-region (GMS)

Project team:Peter Laderach, Rod Lefroy, Aparna Mani, Linh Giang, Stephania Carmona, Anton Eitzinger

Thank youA.Eitzinger@cgiar.org