APPLICATION OF CLIMATE APPLICATION OF CLIMATE PREDICTION IN RICE PRODUCTIONPREDICTION IN RICE PRODUCTION

IN THE MEKONG RIVER DELTA IN THE MEKONG RIVER DELTA (VIETNAM)(VIETNAM)

Nguyen Thi Hien ThuanNguyen Thi Hien ThuanSub-Institute of Hydrometeorology and Sub-Institute of Hydrometeorology and

Environment Environment of South Vietnamof South Vietnam

IntroductionIntroduction Mekong River Delta (MRD) in Vietnam: Mekong River Delta (MRD) in Vietnam:

Largest rice producing area in VN, 12% of Largest rice producing area in VN, 12% of total country’s cultivated area but 52% of total total country’s cultivated area but 52% of total rice production rice production

Rice production varies depending mostly on Rice production varies depending mostly on climate-related constraints: water availability climate-related constraints: water availability (depending on rainfall), drought/dry spells, (depending on rainfall), drought/dry spells, flood/inundation, salinity intrusionflood/inundation, salinity intrusion

Preliminary studies show the connection Preliminary studies show the connection between El Nino/La Nina phases with climate between El Nino/La Nina phases with climate variablesvariables

ObjectivesObjectives To identify the impacts of ENSO on To identify the impacts of ENSO on

rainfall and temperature over the MRD.rainfall and temperature over the MRD. Case study: To produce climate forecast Case study: To produce climate forecast

for Long An province and provide these for Long An province and provide these forecasts to provincial agricultural sector.forecasts to provincial agricultural sector.

To apply seasonal forecasts into a crop To apply seasonal forecasts into a crop yield simulation model to generate crop yield simulation model to generate crop yield forecasts in Long An province.yield forecasts in Long An province.

To evaluate the seasonal forecasts and To evaluate the seasonal forecasts and crop simulation model outputs.crop simulation model outputs.

Study Study areaarea

104 104.5 105 105.5 106 106.5 107 107.5 1088.5

9

9.5

10

10.5

11

11.5

12

12.5

B .L I E U

B .T R I

C .D A O

C .D O C

C .L A N H

C .L O N G

C .M A U

C .T H O

D .PH U

M .H O A

T .A NM .T H O

P.L O N G

P.Q U O C

R .G I A

S.T R A N G

T .N I N H

T .S.N

V .T A U

X .L O C

L ong An P rovincer

DataData For ENSO relationship study:For ENSO relationship study:

- Rainfall and temperature of 18 met. station in MRD- SSTs, SOI

For crop simulation: Long An provinceFor crop simulation: Long An province- Rainfall, temperature, sunshine duration of 2 met. station in Long An province- Rice crop data: Rice variety, planting - Rice crop data: Rice variety, planting date, crop management datadate, crop management data- Soil properties- Soil properties

-Area: Area: 482,000ha, of which about 482,000ha, of which about 433,000ha are for annual rice crops433,000ha are for annual rice crops

- - ProductionProduction: 1.7 – 2ml ton of : 1.7 – 2ml ton of rice/yearrice/year

- - PopulationPopulation: >80% of population is : >80% of population is engaged in rice producing activitiesengaged in rice producing activities

Why is Long An province?Why is Long An province?

2 communes were 2 communes were selected:selected:

- - Thanh Phu commune of Thanh Phu commune of Ben Luc district Ben Luc district represents salinity represents salinity affected areasaffected areas

- Tan Lap commune of - Tan Lap commune of Tan Thanh district Tan Thanh district (Dong Thap Muoi (Dong Thap Muoi lowland - the Plant of lowland - the Plant of Reeds): is affected by Reeds): is affected by annual flood during annual flood during high water season.high water season.

26 farmers from each 26 farmers from each communes participated communes participated in the surveyin the survey

(total of 52 farmers)(total of 52 farmers)

Met stnHydrol.stnRain gauge

Study the relationship between ENSO and rainfall and temperature of MRD.Study the relationship between ENSO and rainfall and temperature of MRD.

Correlation coefficient between Nino3.4 with mean T and R in MRDCorrelation coefficient between Nino3.4 with mean T and R in MRD    

0 1 2 3 4 5 6 7 81

2

3

4

5

6

7

8

9

10

11

12

0 1 2 3 4 5 6 7 81

2

3

4

5

6

7

8

9

10

11

12

Significant correlation between monthly Significant correlation between monthly ENSO indices and rainfall and ENSO indices and rainfall and temperature (R: 0.4 – 0.7), better temperature (R: 0.4 – 0.7), better correlation during March – July correlation during March – July (temperature) and during February – (temperature) and during February – June (rainfall). June (rainfall).

Highest correlation coefficients are with Highest correlation coefficients are with the lag time of 2 – 3 months for the lag time of 2 – 3 months for temperature and 4-5 months for rainfall.temperature and 4-5 months for rainfall.

Regression equations were established Regression equations were established for each location.for each location.

ENSO effect

Calculated vs. Observed Temperature Anomaly Calculated vs. Observed Temperature Anomaly (left) and Rainfall Anomaly (right) for May (St. (left) and Rainfall Anomaly (right) for May (St.

Tan An, Long An) Tan An, Long An)

R2 = 0.7846

-2

-1

0

1

2

-2 0 2Observed

Cal

cula

ted

R2 = 0.6869

-150

-100

-50

0

50

100

150

200

-200 -100 0 100 200 300Observed

Cal

cula

ted

SurveysSurveys

Two surveys have been carried out. Two surveys have been carried out. 1st survey: 1st survey: - Defined needs for climate forecast Defined needs for climate forecast

information from farmers. information from farmers. - Collected crop management dataCollected crop management data- Questionnaire sheets were distributed to - Questionnaire sheets were distributed to

52 farmers in two selected communes of 52 farmers in two selected communes of two districts of Long An province. two districts of Long An province.

Impacts of different factors on Yield and Necessity ofClimate Forecast Information (by farmers)

Site >>Site >>Tan Lap (Tan Thanh)Tan Lap (Tan Thanh) Thanh Phu (Ben Luc)Thanh Phu (Ben Luc)

CriteriaCriteria Priority levelPriority level Priority levelPriority level11 22 33 44 11 22 33 44

Factors Factors influencing the influencing the

yield:yield:BiologyBiology

TechniqueTechniqueEconomy, PolicyEconomy, Policy

WeatherWeather

12%12%12%12%0%0%

80%80%

68%68%20%20%8%8%8%8%

20%20%60%60%24%24%8%8%

0%0%8%8%60%60%4%4%

18%18%7%7%4%4%

89%89%

29%29%71%71%11%11%7%7%

31%31%14%14%15%15%4%4%

22%22%8%8%7%7%0%0%

Meteorological Meteorological Factors:Factors:

Hot weatherHot weatherStrong windStrong wind

DroughtDroughtSevere rainSevere rain

FloodFlood

18%18%16%16%45%45%14%14%7%7%

33%33%3%3%

20%20%26%26%18%18%

29%29%18%18%12%12%36%36%6%6%

0024%24%8%8%18%18%

4%4%4%4%

89%89%0000

59%59%29%29%11%11%7%7%7%7%

33%33%41%41%

004%4%18%18%

4%4%4%4%000000

When bulletins When bulletins needed?needed?

Winter-SpringWinter-SpringSummer-AutumnSummer-Autumn

SowinSowingg

68%68%3%3%

TilerinTileringg

2%2%12%12%

FlowerinFloweringg

30%30%55%55%

RipeRipe

0%0%30%30%

SowinSowingg

74%74%4%4%

Tilering.Tilering.

0%0%11%11%

FlowerinFloweringg

22%22%85%85%

RipeRipe

4%4%0%0%

When and what kind of forecasts do When and what kind of forecasts do farmers need?farmers need?

onset of the rainy season. onset of the rainy season. Rainfall amount/heavy rainsRainfall amount/heavy rains dry spells during the rainy seasondry spells during the rainy season salinity forecast (for Thanh Phu salinity forecast (for Thanh Phu

commune)commune) water level, water receding rate (for water level, water receding rate (for

Tan Lap commune)Tan Lap commune)

SurveysSurveys

The second survey focused on the use The second survey focused on the use and effectiveness of climate forecast and effectiveness of climate forecast information. Questionnaires and information. Questionnaires and interviews were made to obtain the interviews were made to obtain the information.information.

Forecasting and disseminatingForecasting and disseminatingForecast procedure has been set up and agreed Forecast procedure has been set up and agreed between the forecasting bodies to take the between the forecasting bodies to take the most advantage of all available forecasting most advantage of all available forecasting sources.sources. The forecast period lasted 6 months since the The forecast period lasted 6 months since the 11stst April till the 1 April till the 1stst October 2003. Each October 2003. Each forecasting bulletin contains climate and forecasting bulletin contains climate and hydrological parts (water level and salinity). hydrological parts (water level and salinity). Forecasts with lead times of 10 days, 1 month Forecasts with lead times of 10 days, 1 month and 3 month were prepared in each bulletin.and 3 month were prepared in each bulletin. Forecasts were disseminated directly to the 52 Forecasts were disseminated directly to the 52 farmers and the 20 officials/extension workers farmers and the 20 officials/extension workers

Forecasting and disseminatingForecasting and disseminating

Forecast at

SRHMC

Forecast at LA Prov.

Center

Prov. Extensi

on Center

Input data

Study results

Forecast reference

Local data

District Extension Units

Farmers

Rice crop simulationRice crop simulation

DSSAT 35 software has been used to DSSAT 35 software has been used to simulate yields of different planting dates simulate yields of different planting dates with:with:

Historical weather data 1990-2002Historical weather data 1990-2002 Actual 2003 weatherActual 2003 weather Using climate forecastsUsing climate forecasts

Site Group Plating time

Fertilizer application (kg) Yield (kg/ha)

TanThanh 1 5-10 April 100N - 45 P205 - 50 K20 3570

2 11-15 April 120N - 40 P205 - 50 K20 3300

3 16-20 April 120N - 30 P205 - 40 K20 3150

4 21-25 April 115N - 30 P205 - 30 K20 2900

5 26-30 April 110N - 30 P205 - 40 K20 2830

Ben Luc 1 4-10 May 80N - 40 P205 - 40 K20 4050

2 16-20 May 70N - 45 P205 - 30 K20 3213

3 21-25 May 90N - 55 P205 - 30 K20 3625

4 26-31 May 76N - 45 P205 - 42 K20 3000

Planting dates, fertilizers, yield from Planting dates, fertilizers, yield from survey 1survey 1

Average yields of different planting dates with Average yields of different planting dates with actual weather 1990-2002actual weather 1990-2002

0

1000

2000

3000

4000

5000

April-5 April-11 April-16 April-21 April-26 May-5 May-11 May-16 May-21

Simulated yield in BenLuc Observed yield in BenLuc

Simulated yield in Tan Thanh Observed yield in Tan Thanh

Tan Thanh Tan Thanh Ben Luc Ben Luc Yields of different planting dates with 2003 Yields of different planting dates with 2003 weatherweather

0

2000

4000

6000

Planting dates

Yiel

d kg

/ha)

Observed yield Simulated yield

0

2000

4000

6000

Planting dates

Yiel

d kg

/ha)

Observed yield Simulated yield

UUsing climate forecastsing climate forecast

Simul at ed yeil d in ben l uc using c l imat e for ecast

2000

3000

4000

5000

6000

5/5 11/5 15/5 21/5

2003 May- July June - August

July - September August - October

Simul at ed yeil d in t an t hanh using c l imat e for ecast

0

1000

2000

3000

4000

5000

6000

5/4 11/4 16/4 21/4 26/4

2003 May- July June - August

July - September August - October

EvaluationEvaluation Climate forecasts (10 days, 1 month, 3 Climate forecasts (10 days, 1 month, 3

month – temperature, rainfall, water month – temperature, rainfall, water levels, salinity)levels, salinity)

Occurrence of dry spell in JulyOccurrence of dry spell in July Climate forecasts provided to end users Climate forecasts provided to end users

were highly appreciated. were highly appreciated. Most farmers need 10-day forecasts. Most farmers need 10-day forecasts.

Managerial officials/extension workers Managerial officials/extension workers prefer 1- 3month forecastsprefer 1- 3month forecasts

The contents of the forecasts need to The contents of the forecasts need to be shaped into more concise. be shaped into more concise.

EvaluationEvaluation

Probabilistic forecasts were first Probabilistic forecasts were first introduced – new, not easy to interpret introduced – new, not easy to interpret – farmers require categorical forecasts – farmers require categorical forecasts while officials accept but need more while officials accept but need more training for interpretation.training for interpretation.

Crop simulation can be a useful tool to Crop simulation can be a useful tool to help decision making, using different help decision making, using different kinds of climate inputs, but needs kinds of climate inputs, but needs more calibration and trainingmore calibration and training

Recommendations Recommendations * To continue the detailed study on ENSO impacts * To continue the detailed study on ENSO impacts for the Mekong River Delta so that the findings for the Mekong River Delta so that the findings can be used to establish forecasting tools in can be used to establish forecasting tools in operational work.operational work.    * To improve forecasting capability (climate and * To improve forecasting capability (climate and crop simulation) crop simulation) * To set up forecast-dissemination line to provide * To set up forecast-dissemination line to provide the best possible benefits of climate information the best possible benefits of climate information for users.for users.* To conduct a study on the effects of Climate * To conduct a study on the effects of Climate Change on Water Resources and Coastal Zone of Change on Water Resources and Coastal Zone of the Mekong River Delta.       the Mekong River Delta.       

Acknowledgment

START, IRI and the Packard Foundation are acknowledged for supporting the research

and funding the project.

Thank you Thank you