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Modeling ENSO impact on rice production in the Mekong River Delta


Autoři: Bui Tan Yen aff001;  Nguyen Huu Quyen aff002;  Trinh Hoang Duong aff003;  Duong Van Kham aff004;  T. S. Amjath-Babu aff005;  Leocadio Sebastian aff005
Působiště autorů: Soil and Fertilizer Research Institute, Hanoi, Vietnam aff001;  Climate Research and Forecasting Division, Viet Nam Institute of Meteorology, Hydrology And Climate Change, Hanoi, Vietnam aff002;  Agricultural Meteorology Division, Viet Nam Institute of Meteorology, Hydrology And Climate Change, Hanoi, Vietnam aff003;  Research Center for Agrometeorology, Viet Nam Institute of Meteorology, Hydrology And Climate Change, Hanoi, Vietnam aff004;  CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), International Rice Research Institute (IRRI), Hanoi, Vietnam aff005
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0223884

Souhrn

The Mekong River Delta is the rice production hub in South-east Asia and has a key role in determining rice prices in the world market. The increasing variability in the local climate due to global climate changes and the increasing severity of the ENSO phenomenon threatens rice production in the region, which has consequences for local and global food security. Though existing mapping efforts delineate the consequences of saline water intrusion during El Niño and flooding events during La Niña in the basin, research to predict future impacts in rice production is rather limited. The current work uses ORYZA, an ecophysiological model, combined with historical climate data, climate change scenarios RCP4.5 and 8.5 and climate-related risk maps to project the aggregate productivity and rice production impacts by the year 2050. Results show that in years of average salinity intrusion and flooding, the winter-spring rice crop in the MRD would experience an average annual decrease of 720,450 tons for 2020–2050 under the RCP4.5 scenario compared to the baseline of 2005–2016 average and another 1.17 million tons under the RCP8.5 scenario. The autumn-winter crop would decrease by 331,480 tons under RCP4.5 and 462,720 tons under RCP8.5. In years of severe salinity intrusion and flooding, the winter-spring rice crop would decrease by 2.13 million tons (10.29% lower than the projection for an average year) under RCP4.5 and 2.5 million tons (13.62%) under RCP8.5. Under severe conditions, the autumn-winter crop would have an average decrease of 1.3 million tons (7.36%) under RCP4.5 and 1.4 million tons (10.88%) for the RCP8.5 scenario. Given that most of the rice produced in this area is exported, a decline in rice supply at this scale would likely have implications on the global market price of rice affecting global food security. Such decline will also have implications for the rural economy and food security of Vietnam. Suggestions for corrective measures to reduce the impacts are briefly discussed.

Klíčová slova:

Climate change – Crops – El Niño-Southern Oscillation – Flooding – Rice – Salinity – Seasons – Oryza


Zdroje

1. Clauss K, Ottinger M, Leinenkugel P, Kuenzer C. Estimating rice production in the Mekong Delta, Vietnam, utilizing time series of Sentinel-1 SAR data. International Journal of Applied Earth Observation and Geoinformation. 2018;73:574–85. doi: 10.1016/j.jag.2018.07.022

2. GSO. Statistical Yearbook of Vietnam. General Statistics Office. Hanoi, Vietnam: Statistical Publishing House; 2017.

3. Slayton T. Rice Crisis Forensics: How Asian Governments Carelessly Set the World Rice Market on Fire. SSRN Electronic Journal. 2009:43. doi: 10.2139/ssrn.1392418

4. Zhang Y, Qian Y, Dulière V, Salathé EP, Leung LR. ENSO anomalies over the Western United States: present and future patterns in regional climate simulations. Climatic Change. 2011;110(1–2):315–46. doi: 10.1007/s10584-011-0088-7

5. Räsänen TA, Kummu M. Spatiotemporal influences of ENSO on precipitation and flood pulse in the Mekong River Basin. Journal of Hydrology. 2013;476:154–68. doi: 10.1016/j.jhydrol.2012.10.028

6. DCP. Report on droughts, salinity intrusion and response solutions. Hanoi, Vietnam: Department of Crop Production. Ministry of Agriculture and Rural Development; 2016.

7. Hoa LTV, Haruyama S, Nhan NH, Cong TT, Long BD. The Historical Flood in 2000 in Mekong River Delta, Vietnam: A Quantitative Analysis and Simulation. Geographical Review of Japan. 2007;80(12):663–80. doi: 10.4157/grj.80.663

8. Khong TD, Young MD, Loch A, Thennakoon J. Mekong River Delta farm-household willingness to pay for salinity intrusion risk reduction. Agricultural Water Management. 2018;200:80–9. doi: 10.1016/j.agwat.2017.12.010

9. Yen BT, Son NH, Tung LT, Amjath-Babu TS, Sebastian L. Development of a participatory approach for mapping climate risks and adaptive interventions (CS-MAP) in Vietnam’s Mekong River Delta. Climate Risk Management. 2019;24:59–70. doi: 10.1016/j.crm.2019.04.004

10. Delgado JM, Merz B, Apel H. A climate-flood link for the lower Mekong River. Hydrology and Earth System Sciences Discussions. 2011;8(6):10125–49. doi: 10.5194/hessd-8-10125-2011

11. IMHEN. Monthly announcement of hydro-meteorological conditions. Hanoi, Vietnam: The Vietnam Institute of Meteorology, Hydrology and Climate Change, 2018. Available from: http://www.imh.ac.vn/

12. SIWRR. Monthly report on water resources and salinity intrusion in Mekong River Delta. Ho Chi Minh city: Southern Institute of Water Resources Research (SIWRR), 2018. Available from: http://www.siwrr.org.vn/

13. van Groenigen KJ, van Kessel C, Hungate BA. Increased greenhouse-gas intensity of rice production under future atmospheric conditions. Nature Climate Change. 2012;3(3):288–91. doi: 10.1038/nclimate1712

14. Naylor RL, Battisti DS, Vimont DJ, Falcon WP, Burke MB. Assessing risks of climate variability and climate change for Indonesian rice agriculture. Proc Natl Acad Sci U S A. 2007;104(19):7752–7. Epub 2007/05/08. doi: 10.1073/pnas.0701825104 17483453; PubMed Central PMCID: PMCPMC1876519.

15. Sakamoto T, Van Nguyen N, Kotera A, Ohno H, Ishitsuka N, Yokozawa M. Detecting temporal changes in the extent of annual flooding within the Cambodia and the Vietnamese Mekong Delta from MODIS time-series imagery. Remote Sensing of Environment. 2007;109(3):295–313. doi: 10.1016/j.rse.2007.01.011

16. Ha NTT, De Bie CAJM, Ali A, Smaling EMA, Hoanh CT. Mapping the irrigated rice cropping patterns of the Mekong delta, Vietnam, through hyper-temporal SPOT NDVI image analysis. International Journal of Remote Sensing. 2011;33(2):415–34. doi: 10.1080/01431161.2010.532826

17. Bouman B, Kropff M, Tuong TP, Wopereis MCs, ten Berge HFM, van Laar HH. ORYZA2000: modeling lowland rice; 2003.

18. Wopereis MCs, Bouman B, Tuong TP, ten Berge HFM, Kropff M. ORYZA-W: Rice growth model for irrigated and rainfed environments; 1996.

19. Li T, Angeles O, Marcaida M III, Manalo E, Manalili MP, Radanielson A, et al. From ORYZA2000 to ORYZA (v3): An improved simulation model for rice in drought and nitrogen-deficient environments. Agric For Meteorol. 2017;237–238:246–56. Epub 2017/05/05. doi: 10.1016/j.agrformet.2017.02.025 28469286; PubMed Central PMCID: PMCPMC5391805.

20. Thuc T, Thang NV, Huong HTL, Khiem MV, Hien NX, Phong DH. Climate change and sea level rise scenarios for Vietnam. Hanoi, Vietnam: Vietnam Publishing house of Natural resources, Environment and Cartographic.; 2016. Available from: http://www.imh.ac.vn/files/doc/KichbanBDKH/KBBDKH_2016.pdf

21. Vanuytrecht E, Raes D, Hsiao T, Fereres E, Heng L, García-Vila M, et al. AquaCrop: FAO’S crop water productivity and yield response model; 2014.

22. Diepen CA, Wolf J, Keulen H, Rappoldt C. WOFOST: a simulation model of crop production. Soil Use and Management. 1989;5(1):16–24. doi: 10.1111/j.1475-2743.1989.tb00755.x

23. Stella T, Negrini G, Frasso N, Bregaglio S, Confalonieri R. A new generation of SUCROS-type models: an example for WOFOST and rice simulations; 2012.

24. Horie T, Nakagawa HN., Centeno G, Kropff M. The rice simulation model SIMRIW and its testing;1995.

25. Vilayvong S, Banterng P, Patanothai A, Pannangpetch K. CSM-CERES-Rice model to determine management strategies for lowland rice production. Scientia Agricola. 2015;72(3):229–36. doi: 10.1590/0103-9016-2013-0380

26. Jones JW, Hoogenboom G, Porter CH, Boote KJ, Batchelor WD, Hunt LA, et al. The DSSAT cropping system model. European Journal of Agronomy. 2003;18(3–4):235–65. doi: 10.1016/s1161-0301(02)00107-7

27. Krishnan P, Swain DK, Chandra Bhaskar B, Nayak SK, Dash RN. Impact of elevated CO2 and temperature on rice yield and methods of adaptation as evaluated by crop simulation studies. Agriculture, Ecosystems & Environment. 2007;122(2):233–42. doi: 10.1016/j.agee.2007.01.019

28. Setiyono TD, Quicho ED, Holecz FH, Khan NI, Romuga G, Maunahan A, et al. Rice yield estimation using synthetic aperture radar (SAR) and the ORYZA crop growth model: development and application of the system in South and South-east Asian countries. International Journal of Remote Sensing. 2018:1–32. doi: 10.1080/01431161.2018.1547457

29. Nelson A, Setiyono T, Rala A, Quicho E, Raviz J, Abonete P, et al. Towards an Operational SAR-Based Rice Monitoring System in Asia: Examples from 13 Demonstration Sites across Asia in the RIICE Project. Remote Sensing. 2014;6(11):10773–812. doi: 10.3390/rs61110773

30. ISDR, WorldBank, WHO, UNISDR, GFDRR. Strengthening of hydrometeorological services in Southeast Asia. Country assessment report for Vietnam. Geneva, Switzerland: United Nations Office for Disaster Risk Reduction; 2013.

31. CMH. List of hydro-meteorological stations of Vietnam Hanoi, Vietnam: Vietnam Center of Hyro-Meteorological Data; 2007 [cited 2017 23 May]. Available from: http://cmh.com.vn/article/201-Danh-sach-cac-tram-khi-tuong.html.

32. Chieu TT, Phong TA, Pho NC, Nhan NV, Khanh PQ. Soil map of the Mekong Delta at scale of 1:250,000 National Institute of Agricultural Planning and Projection (NIAPP); 1989.

33. NIAPP. Soil map of provinces in the Mekong River Delta at scale of 1:50,000. Hanoi, Vietnam: Ministry of Agriculture and Rural Development (MARD); 2004.

34. Endo H, Kitoh A, Ose T, Mizuta R, Kusunoki S. Future changes and uncertainties in Asian precipitation simulated by multiphysics and multi-sea surface temperature ensemble experiments with high-resolution Meteorological Research Institute atmospheric general circulation models (MRI-AGCMs). Journal of Geophysical Research: Atmospheres. 2012;117(D16):n/a-n/a. doi: 10.1029/2012jd017874

35. Khiem MV, Redmond G, McSweeney C, Thuc T. Evaluation of dynamically downscaled ensemble climate simulations for Vietnam. International Journal of Climatology. 2014;34(7):2450–63. doi: 10.1002/joc.3851

36. Nguyen KC, Katzfey JJ, McGregor JL. Downscaling over Vietnam using the stretched-grid CCAM: verification of the mean and interannual variability of rainfall. Climate Dynamics. 2013;43(3–4):861–79. doi: 10.1007/s00382-013-1976-5

37. Tran Pv, Hiep NV, Long TT, Trung NQ, Thanh ND, Laux P, et al. Seasonal Prediction of Surface Air Temperature across Vietnam Using the Regional Climate Model Version 4.2 (RegCM4.2). Advances in Meteorology. 2014;2014:1–13. doi: 10.1155/2014/245104

38. Nam PQ, Thang VV, Kien TB, Khiem MV, Hiep NV, Phong NB, et al. Projection of heat waves over Vietnam using clWRF model. Vietnam Scientific and Technical Hydro- Meteorological Journal. 2015;656:28–32.

39. Pachauri K, United R, Barros R, Broome J, Cramer, Christ, et al. Synthesis Report IPCC AR5. 2015.

40. Fer I, Tietjen B, Jeltsch F, Wolff C. Accounting for El Niño-Southern Oscillation influence becomes urgent for predicting future East African ecosystem responses. Biogeosciences Discussions. 2017:1–45. doi: 10.5194/bg-2017-49

41. Yuan S, Peng S, Li T. Evaluation and application of the ORYZA rice model under different crop managements with high-yielding rice cultivars in central China. 2017. 115–25 p.

42. Jiang Z, Raghavan SV, Hur J, Sun Y, Liong S-Y, Nguyen VQ, et al. Future changes in rice yields over the Mekong River Delta due to climate change—Alarming or alerting? Theoretical and Applied Climatology. 2018. doi: 10.1007/s00704-017-2169-7 30996503

43. ICEM. USAID Mekong ARCC Climate Change Impact and Adaptation Study for the Lower Mekong Basin. Bangkok, Thailand: International Centre for Environmental Management. USAID Mekong ARCC Project. 2014.


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