Rice Yield And Dangue Haemorrhagic Fever(DHF) Condition depend upon Climate Data Dr Lai Lai Aung, Assistant Director( Met Service) Dr Khaing Khaing Soe Assistant Director(Public Health) Dr Thin Nwe htwe Staff Officer(Agriculture)
Background Total area 678,500 square KM Latitudes 9.8 N - 29.8 N, Longitudes 92.2 E - 101.1 E. Lies in the Tropic 14 Regions & State Neighbouring Countries China on the northeast, Laos on the east, Thailand on the southeast, Bangladesh on the west, India on the west & northwest the Bay of Bengal to the west & southwest, Andaman Sea at the South INDIA BANGLA DESH BOB ANDA MAN SEA CHINA LAOS THAILAND
The Climate of Myanmar lies in the monsoon region of Asia. roughly divided into three seasons: Summer Season (Mar to mid May), Rainy Season (mid May to Oct), Winter Season (Nov to Feb) the central myanmar area an average annual rainfall, 30 inches coastal region with annual average rainfall, 200 inhes Topography: mountainous area to the north, west and eastern parts, low land and deltaic areas and dry zone area in the central Myanmar areas Population:52 million
Land Utilization in Myanmar (2014-2015) Other Land 24.60% Net Sown Area 17.70% Fallow Land 0.70% Culturable Waste Land 7.80% Other Forests 21.80% Reserved Forests 27.50% 4
Number of Stations over the Country 92 94 96 100 N INDIA 6 6 16 CHINA 7 9 14 14 14 LAOS 10 12 12 8 6 2 3 7 THAILAND ANDAMAN SEA 4 Total:118 100 50 0 50 100
Comparison Rice Yield and Txgt50p (days above average temperature) data for Ayeyarwaddy Region( Pathein) 3900 85 3800 75 3700 65 3600 55 3500 45 3400 3300 35 3200 Rice yield 25 3100 Txgt50p 15 3000 adjusted 5 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Correlation=0.74 Rice yield was related with Txgt50p at the year of 1994,00,2002-07,09
Comparison DHF and HWF(Heat wave frequency) data for Ayeyarwaddy Region( Pathein) 25000 45 20000 Health HWF 40 35 15000 30 25 10000 20 15 5000 10 5 0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 0 Correlation=0.42 DHF was related with HWF at the year of 98,2002, 2005
Comparison Rice yield and Tx90p(amount of hot days) data for Ayeyarwaddy Region( Pathein) 3900 3800 Rice Yield 45 40 3700 3600 Tx90p 35 30 3500 25 3400 20 3300 15 3200 10 3100 5 3000 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 0 Correlation=0.80 Rice yield was related with Tx90p most the year except the year 98,03,04,05
Rainfall Comparison between Normal(1961-1990) & Normal(1981-2010) 600.0 Normal(1961-1990) Normal(1981-2010) 500.0 400.0 300.0 200.0 100.0 0.0 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC (81-10) normal was decreasing at the month of May, June, July and August and it was nearly unchanged for the other months.
Minimum Temperature Comparison between Normal(1961-1990) & Normal(1981-2010) Normal(1961-1990) Normal(1981-2010) 24.0 22.0 20.0 18.0 16.0 14.0 12.0 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC normal minimum temperature was decreasing from month January to May and September to December. It was nearly unchanged at month July and August.
Maximum Temperature Comparison between Normal(1961-1990) & Normal(1981-2010) Normal(1961-1990) Normal(1981-2010) 35.5 34.5 33.5 32.5 31.5 30.5 29.5 28.5 27.5 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC normal maximum temperature was increasing nearly all months except February and December. It was clear that rate of maximum temperature was higher at the month April,May June, July and August compare to other months.
Results Txgt 50p, Tx90p, HWF indices are relevant and beneficial for Rice yield and DHF diseases. Normal maximum temperature is also increasing all month of Myanmar except February and December and minimum temperature were decreasing. Normal rainfall pattern also shifted, it is decreasing in the month of May, June, July and August and rest of month is nearly unchanged.
Myanmar: Health sector overview The Ministry of Health and Sports (Formerly, Ministry of Health) is responsible for enhancing the health status of the population through delivering comprehensive health services pertaining to the promotion of good health, the prevention of disease, and the provision of effective treatment and rehabilitation. It executes these health services through seven departments: 1. Department of Public Health 2. Department of Medical Services 3. Department of Heath Professional Resource Development and Management 4. Department of Medical Research 5. Department of Traditional Medicine 6. Department of Food and Drug Administration 7. Department of Sports and Physical Education
Comparison Health and Txgt50p (days above average temperature) data for Ayeyarwaddy Region( Pathein) correlation=0.63 (98,01,02,05,07) 25000 80 70 20000 60 15000 50 40 10000 30 5000 Health Txgt50p adjusted 20 10 0 0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Comparison DHF and Tx90p(amount of hot days) data for Ayeyarwaddy Region( Pathein) correlation=0.55 (91,93,98,01,02,05,07) 25000 45 40 20000 35 30 15000 25 10000 20 15 5000 Health Tx90p 10 5 0 0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Comparison DHF cases and Txm(mean daily max temp) data for Ayeyarwaddy Region( Pathein) correlation=0.46 (91,93,98,02,05,07) 25000 35 34 20000 33 15000 32 10000 31 30 DHF Cases txm 5000 29 28 0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 27
DHF cases and PRCPTOT (Annual total wet day) (94,97,01,02,07,09) 25000 4000 3500 20000 3000 15000 10000 2500 2000 1500 DHF Cases prcptot 5000 1000 500 0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 0 correlation=0.4
Model Summary Model R R square Adjusted R Square Std. Error of the Estimate 0.731.535.483 4664.89663 a. Predictors: (Constant), Txgt50p, PRCPTOT b. Dependent Variable: DHF
ANOVA Model R df Mean Square F Sig Regression Residual Total 4.503E8 3.917E8 8.420E8.2 18 20 2.251E8 2.176E7 10.345 0.001 a. Predictors: (Constant), Txgt50p, PRCPTOT b. Dependent Variable: DHF
conclusion In this study, we compare Annual DHF cases in Myanmar with Txgt50p (fraction of days with above average temperature), Tx90p (Amount of hot days), Txm (mean daily maxium temperature and PRCPTOT (Annual total wet day). We found that increase in days with above average temperature and increase in wet day are associated with increase in DHF cases. In Myanmar, mountain areas are cold and previously no DHF case and now increase in temperature in mountain area and more DHF cases are found.
Annual Total Wet-day PR with rice yield 3900 3800 3700 3600 3500 3400 3300 3200 3100 4000 3500 3000 2500 2000 1500 1000 500 Rice Yield PRCPTOT 3000 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 0
No. of heavy rain days (30mm) with rice yield 3900 3800 3700 3600 3500 y = 0.4778x + 27.516 50 45 40 35 30 25 3400 3300 3200 3100 3000 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 20 15 10 5 0-5 Rice Yield R30mm Adjusted Linear (R30mm)
Growing Degree Days with Rice Yield 3900 3800 3700 3600 y = 28.102x + 6115.6 7000 6800 6600 6400 3500 3400 3300 3200 3100 6200 6000 5800 5600 5400 Rice Yield GDDgrown Adjusted Linear (GDDgrown) 3000 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 5200
Regression model Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1.567 a.321.231 224.45052 a. Predictors: (Constant), Growing degree days, Number of heavy rain days Model 1 Regression Residual Total ANOVAb Sum of Squares df Mean Square F Sig. 357493.526 2 178746.763 3.548.055 a 755670.508 15 50378.034 1113164.033 17 a. Predictors: (Constant), Growing degree days, Number of heavy rain days b. Dependent Variable: Rice Yield
Results For paddy production, not only climate data influence but also other factors (eg. Varieties, Soil Types, Fertilizer Application, Crop Management and Pest and Diseases, so on). But the climate data can really influence when the drought have the whole growing season or heavy rain (flood) during the harvesting time, so on. The relationship of climate indices and other crops production (maize or pigeon pea), the correlation will be high. And the seasonal data will be beneficial.
Annual mean daily maximum temperature For the year 2099
Annual sum of daily precipitation 1961 2070 2099 To get more accuracy, we need to use much more images and high resolution (30 m and 10 m, 5 m resolution) Predict for drought, flood and cyclone to use in agriculture sector
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