Assessment of the Potential Climate Change on Rice Yield in Lower Ayeyarwady Delta of Myanmar Using EPIC Model
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Published:
Apr 11, 2018
Keywords:
Climate change Rice yield EPIC model Ayeyarwady Delta
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Abstract
Climate change has been occurring and its consequences are a threat to rice production and hence food security. In this study, the effect of climate change on rice yield has been assessed by using the Environmental Policy Integrated Climate model under climate change scenarios RCP4.5 (medium emissions) and RCP8.5 (high emissions) and to propose alternative adaptive measures for farmers’ livelihoods in the lower Ayeyarwady Delta. The results show that the average yield increase of early rice are 11.84% and 7.56% and the average yield reduction of late rice are 37.37% and 50.89% under both scenarios. The study found that rice yield reduction will be significantly higher under the RCP8.5 than that of RCP4.5 for both rice. Yield reductions are attributed to increases in mean maximum and minimum temperatures and variation in rainfall pattern. The model result suggests that changing the sowing date is a good option for compensating the future rice yield reduction. The other adaptations that offset the rice yield response to climate change include providing farming machines, irrigation facilities, improving infrastructure, improvement in cultivars that resist disease, pest and drought, better weather forecast and extension systems.
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Mar Lar, N., Arunrat, N., Tint, S., & Pumijumnong, N. (2018). Assessment of the Potential Climate Change on Rice Yield in Lower Ayeyarwady Delta of Myanmar Using EPIC Model. Environment and Natural Resources Journal, 16(2), 45–57. Retrieved from https://ph02.tci-thaijo.org/index.php/ennrj/article/view/118648
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Original Research Articles
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References
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Aggarwal PK, Mall R. Climate change and rice yields in diverse agro-environments of India. II. effect of uncertainties in scenarios and crop models on impact assessment. Climatic Change 2002;52(3):331-43.
Babur M, Babel M, Shrestha S, Kawasaki A, Tripathi N. Assessment of climate change impact on reservoir inflows using multi climate-models under RCPs: the case of Mangla Dam in Pakistan. Water 2016; 8(9):389.
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Lal M, Singh K, Rathore L, Srinivasan G, Saseendran S. Vulnerability of rice and wheat yields in NW India to future changes in climate. Agricultural and Forest Meteorology 1998;89(2):101-14.
Liu J. Modelling Global Water and Food Relations: Development and Application of a GIS-based EPIC Model. [dissertation]. Netherlands, Swiss Federal Institute of Technology Zurich; 2007.
Marshall E, Aillery M, Malcolm S, Williams R. Agricultural production under climate change: the potential impacts of shifting regional water balances in the United States. American Journal of Agricultural Economics 2015;97(2):568-88.
Ministry of Agriculture, Livestock and Irrigation (MOALI). Agriculture and livelihood flood impact assessment in Myanmar, 2015. [Internet]. 2017 [cited 2017 Feb 10]. Available from: https://www.wfp.org /sites/default/files/FinalImpactAssessmentReportfinal. pdf
Mosleh MK, Hassan QK, Chowdhury EH. Application of remote sensors in mapping rice area and forecasting its production: a review. Sensors 2015;15(1):769-91.
Oteng-Darko P, Kyei-Baffour N, Ofori E. Simulating rice
yields under climate change scenarios using the CERES-Rice model. African Crop Science Journal 2012;20(2):401-8.
Pumijumnong N, Arunrat N. Simulating the rice yield change in Thailand under SRES A2 and B2 scenarios with the EPIC model. Journal of Agri-Food and Applied Sciences 2013;1(4):119-25.
Restrepo-Diaz H, Garces-Varon G. Response of rice plants to heat stress during initiation of panicle primordia or grain-filling phases. Journal of Stress Physiology and Biochemistry 2013;9(3):318-25.
Shrestha S. Assessment of climate change impacts on irrigation water requirement and rice yield for Ngamoeyeik Irrigation Project in Myanmar. Journal of Water and Climate Change 2014;5(3):1-16.
Srivastava GC. Crop physiology. New Delhi, India: Biotech Books; 2011.
Stella T, Frasso N, Negrini G, Bregaglio S, Cappelli G, Acutis M, Confalonieri R. Model simplification and development via reuse, sensitivity analysis and composition: a case study in crop modelling. Environmental Modelling and Software 2014;59:44-58.
Tachie-Obeng E, Gyasi E, Adiku S, Abekoe M, Zierrogel G, editors. Farmers’ adaptation measures in scenarios of climate change for maize production in semi-arid zones of Ghana. Proceedings of the 2nd International Conference: Climate Sustainability and Development in Semi-arid Regions; 2010 Aug 16-20; 2010. p. 1-20.
Adhikari VR. Impact of Climate Variation in Paddy Production of Nepal. [dissertation]. Ås, Norway, Norwegian University of Life Sciences; 2015.
Aggarwal PK, Mall R. Climate change and rice yields in diverse agro-environments of India. II. effect of uncertainties in scenarios and crop models on impact assessment. Climatic Change 2002;52(3):331-43.
Babur M, Babel M, Shrestha S, Kawasaki A, Tripathi N. Assessment of climate change impact on reservoir inflows using multi climate-models under RCPs: the case of Mangla Dam in Pakistan. Water 2016; 8(9):389.
Bao Y, Hoogenboom G, McClendon R, Vellidis G. A comparison of the performance of the CSM-CERES-Maize and EPIC models using maize variety trial data. Agricultural Systems 2017;150:109-19.
Bouzaher A, Shogren JF, Holtkamp DJ, Gassman PW, Archer DW, Lakshminarayan P, Carriquiry AL, Reese RA, Kakani D, Furtan WH. Agricultural policies and soil degradation in western Canada: an agro-ecological economic assessment - conceptual framework. CARD Staff Reports: Iowa State University 1996. p. 44.
Candradijaya A, Kusmana C, Syaukat Y, Syaufina L, Faqih A. Climate change impact on rice yield and
adaptation response of local farmers in Sumedang district, West Java, Indonesia. International Journal of Ecosystem 2014;4(5):212-23.
Chun JA, Li S, Wang Q, Lee W-S, Lee E-J, Horstmann N, Park H, Veasna T, Vanndy L, Pros K, Vang S. Assessing rice productivity and adaptation strategies for Southeast Asia under climate change through multi-scale crop modeling. Agricultural Systems 2016;143:14-21.
Climate Change Knowledge Portal (CCKP). Climate change knowledge portal of world bank group [Internet]. 2017 [cited 2017 Feb 10]. Available from: http://sdwebx.worldbank.org/climateportal/index.cfm?page=countryfutureclimate&ThisRegion=Asia&ThisCcode=MMR
Department of Agricultural Land Management and Statistics (DALMS). Report on Land Management and Statistics of Myaungmya Township, Ayeyarwady Region, Myanmar; 2016.
Department of Meteorology and Hydrology (DMH). Myanmar Climate Data. Department of Meteorology and Hydrology, Yangon, Myanmar; 2016.
Department of Population (DOP). The 2014 Myanmar Population and Housing Census: Ayeyarwady Region, Department of Population, Ministry of Immigration and Population, Nay Pyi Taw, Myanmar; 2015.
Gummadi S, Wheeler T, Osborne T, Turner A. Addressing the uncertainties associated in assessing the impacts of climate change on agricultural crop production using model simulations. Academic Research Journal of Agricultural Science and Research 2016;4(5):206-21.
Hilger TH, Herfort J, de Barros I, Gaiser T, Saboya LMF, Ferreira LGR, Leihner DE. Potential of EPIC/ALMANAC to estimate crop yields under Erratic rainfall in NE Brazil. Proceedings of the German-Brazilian Workshop on Neotropical Ecosystems-Achievements and Prospects of Cooperative Research, Hamburg; 2000 Sep 3-8; Hamburg, Geesthacht: Germany; 2000.
Horton R, De Mel M, Peters D, Lesk C, Bartlett R, Helsingen H, Bader D, Capizzi P, Martin S, Rosenzweig C. Assessing Climate Risk in Myanmar. New York, USA: Center for Climate Systems Research at Columbia University, WWF-US and WWF-Myanmar; 2016. p. 1-47.
Intergovernmental Penal on Climate Change (IPCC). Climate Change 2014: Synthesis Report. Part of the Working Group III Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC, Geneva, Switzerland; 2014; p. 151.
Intergovernmental Penal on Climate Change (IPCC). Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Cambridge University Press; 2014. p. 1132.
Jamieson P, Porter J, Wilson D. A test of the computer simulation model ARCWHEAT1 on wheat crops grown in New Zealand. Field crops research. 1991;27(4):337-50.
Janjai S, Masiri I, Laksanaboonsong J. Satellite-derived solar resource maps for Myanmar. Renewable Energy 2013;53:132-40.
Kassie BT, Asseng S, Rotter RP, Hengsdijk H, Ruane AC, Van Ittersum MK. Exploring climate change impacts and adaptation options for maize production in the Central Rift Valley of Ethiopia using different climate change scenarios and crop models. Climatic change 2015;129(1-2):145-58.
Keating BA, Carberry PS, Hammer GL, Probert ME, Robertson MJ, Holzworth D, Huth NI, Hargreaves JNG, Meinke H, Hochman Z, McLean G, Verburg K, Snow V, Dimes JP, Silburn M, Wang E, Brown S, Bristow KL, Asseng S, Chapman S, McCown RL, Freebairn DM, Smith CJ. An overview of APSIM, a model designed for farming systems simulation. European journal of agronomy 2003;18(3-4):267-88.
Kreft S, Eckstein D, Junghans L, Kerestan C, Hagen U. Global climate risk index 2015: who suffers most from extreme weather events? Weather-related loss events in 2013 and 1994 to 2013. German Federal Ministry for Economic Cooperation and Development (BMZ), Germanwatch; 2014. p. 1-32.
Lal M, Singh K, Rathore L, Srinivasan G, Saseendran S. Vulnerability of rice and wheat yields in NW India to future changes in climate. Agricultural and Forest Meteorology 1998;89(2):101-14.
Liu J. Modelling Global Water and Food Relations: Development and Application of a GIS-based EPIC Model. [dissertation]. Netherlands, Swiss Federal Institute of Technology Zurich; 2007.
Marshall E, Aillery M, Malcolm S, Williams R. Agricultural production under climate change: the potential impacts of shifting regional water balances in the United States. American Journal of Agricultural Economics 2015;97(2):568-88.
Ministry of Agriculture, Livestock and Irrigation (MOALI). Agriculture and livelihood flood impact assessment in Myanmar, 2015. [Internet]. 2017 [cited 2017 Feb 10]. Available from: https://www.wfp.org /sites/default/files/FinalImpactAssessmentReportfinal. pdf
Mosleh MK, Hassan QK, Chowdhury EH. Application of remote sensors in mapping rice area and forecasting its production: a review. Sensors 2015;15(1):769-91.
Oteng-Darko P, Kyei-Baffour N, Ofori E. Simulating rice
yields under climate change scenarios using the CERES-Rice model. African Crop Science Journal 2012;20(2):401-8.
Pumijumnong N, Arunrat N. Simulating the rice yield change in Thailand under SRES A2 and B2 scenarios with the EPIC model. Journal of Agri-Food and Applied Sciences 2013;1(4):119-25.
Restrepo-Diaz H, Garces-Varon G. Response of rice plants to heat stress during initiation of panicle primordia or grain-filling phases. Journal of Stress Physiology and Biochemistry 2013;9(3):318-25.
Shrestha S. Assessment of climate change impacts on irrigation water requirement and rice yield for Ngamoeyeik Irrigation Project in Myanmar. Journal of Water and Climate Change 2014;5(3):1-16.
Srivastava GC. Crop physiology. New Delhi, India: Biotech Books; 2011.
Stella T, Frasso N, Negrini G, Bregaglio S, Cappelli G, Acutis M, Confalonieri R. Model simplification and development via reuse, sensitivity analysis and composition: a case study in crop modelling. Environmental Modelling and Software 2014;59:44-58.
Tachie-Obeng E, Gyasi E, Adiku S, Abekoe M, Zierrogel G, editors. Farmers’ adaptation measures in scenarios of climate change for maize production in semi-arid zones of Ghana. Proceedings of the 2nd International Conference: Climate Sustainability and Development in Semi-arid Regions; 2010 Aug 16-20; 2010. p. 1-20.