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Rain-Fed Rice Yield Fluctuation to Climatic Anomalies in Bangladesh

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Abstract

To examine the rain-fed Aman rice yield fluctuation due to climatic anomalies overtimes in Bangladesh, we used climate-induced yield index (CIYI), ensemble empirical mode decomposition (EEMD), step-wise multiple regression, isotopic signature, wavelet transform coherence (WTC) and random forest (RF) model. In this work, daily multiple source climatic data which were collected between 1980 and 2017, from 18 weather stations and five atmospheric circulation indices were used for this purpose. The key findings were as follows; by employing principal component analysis (PCA), six temporal variability modes were identified as six corresponding sub-regions with various Aman rice CIYI fluctuations. The Aman rice CIYI in different sub-regions represented a noteworthy 3–4-year quasi-oscillation using the EEMD. The key climate variables (KCVs) including the potential evapotranspiration and cloud cover in September, the minimum temperature in August, and precipitation in July, August, and October were the best rice yield prediction signals in these sub-regions. The results suggest that Aman rice yield could likely decline by 33.59%, and 3.37% in the southwestern and southeastern regions, respectively, if KCV increased by 1 °C or 1%. The RF model suggests that the Indian Ocean Dipole (IOD) significantly influenced the rice yield. Isotopic signatures were employed to confirm the fluctuation and anti-amount effect during the Aman rice-growing period in Bangladesh. The results obtained in this study could be used as a guideline for sustainable mitigation and adaptation measures in managing agro-meteorological hazards in Bangladesh.

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References

  • Adarsh, S., & Reddy, M. J. (2016). Multiscale characterization of streamflow and suspended sediment concentration data using Hilbert-Huang transform and time dependent intrinsic correlation analysis. Modeling Earth Systems and Environment, 2(4), 1–17.

    Article  Google Scholar 

  • Ahmed, M. K., Alam, M. S., Yousuf, A. H. M., & Islam, M. M. (2017). A long-term trend in precipitation of different spatial regions of Bangladesh and its teleconnections with El Nino/southern oscillation and Indian Ocean dipole. Theoretical Applied Climatology, 129(1–2), 473–486.

    Article  Google Scholar 

  • Alizadeh, F., Roushangar, K., & Adamowski, J. (2019). Investigating monthly precipitation variability using a multiscale approach based on ensemble empirical mode decomposition. Paddy and Water Environment, 17(4), 741–759.

    Article  Google Scholar 

  • Amin, M., Zhang, J., & Yang, M. (2015). Effects of climate change on the yield and cropping area of major food crops: a case of Bangladesh. Sustainability, 7(1), 898–915.

    Article  Google Scholar 

  • Ara, I., Lewis, M., & Ostendorf, B. (2016). Spatio-temporal analysis of the impact of climate, cropping intensity and means of irrigation: an assessment on rice yield determinants in Bangladesh. Agriculture & Food Security, 5(1), 12.

    Article  Google Scholar 

  • Ashok, K., Behera, S.K., Rao, S.A., Weng, H. and Yamagata, T. (2007). El Niño Modoki and its possible teleconnection. Journal of Geophysical Research: Oceans, 112(C11)

  • Auffhammer, M., Ramanathan, V., & Vincent, J. R. (2012). Climate change, the monsoon, and rice yield in India. Climatic Change, 111(2), 411–424.

    Article  Google Scholar 

  • Banglapedia. (2003). National encyclopedia of Bangladesh. Dhaka: Asiatic Society of Bangladesh.

    Google Scholar 

  • Basak, J. K., Ali, M. A., Islam, M. N., & Rashid, M. A. (2010). Assessment of the effect of climate change on boro rice production in Bangladesh using DSSAT model. Journal of Civil Engineering (IEB), 38(2), 95–108.

    Google Scholar 

  • Breiman, L. (2001). Random forests. Machine Learning, 45(1), 5–32.

    Article  Google Scholar 

  • Capra, A., & Scicolone, B. (2012). Spatiotemporal variability of drought on a short–medium time scale in the Calabria Region (Southern Italy). Theoretical Applied Climatology, 110(3), 471–488.

    Article  Google Scholar 

  • Challinor, A. J., et al. (2014). A meta-analysis of crop yield under climate change and adaptation. Nat. Clim. Change, 4, 287–291.

    Article  Google Scholar 

  • Chen, Y. Z., Li, G. and C., Li, Q. L., (2016). Analysis of spatial distribution evolution and determinants of rapeseed production in China. Journal of Hunan Agricultural University (Social Sciences) 17(2), 009–015 (in Chinese with English abstract)

  • Connolly, D. (2004). Evaluating the influence of different vegetation biomes on the global climate. Climate Dynamics, 23(3–4), 279–302.

    Google Scholar 

  • Craig, H. (1961). Isotopic variations in meteoric waters. Science, 133, 1702–1703.

    Article  CAS  PubMed  Google Scholar 

  • Dubache, G., Ogwang, B. A., Ongoma, V., & Islam, A. R. M. T. (2019). The effect of Indian Ocean on Ethiopian seasonal rainfall. Meteorology and Atmospheric Physics, 131(6), 1753–1761. https://doi.org/10.1007/s00703-019-00667-8.

    Article  Google Scholar 

  • Endo, N., Matsumoto, J., Hayashi, T., Terao, T., Murata, F., Kiguchi, M., et al. (2015). Trends in precipitation characteristics in Bangladesh from 1950 to 2008. SOLA, 11, 113–117. https://doi.org/10.2151/sola.2015-027.

    Article  Google Scholar 

  • Fang, S. B. (2011). Exploration of method for discrimination between trend crop yield and climatic fluctuant yield. Journal of Nature Disasters, 6, 13–18. ((in Chinese)).

    Google Scholar 

  • Guo, A., Chang, J., Wang, Y., Huang, Q., Guo, Z., & Zhou, S. (2018). Bivariate frequency analysis of flood and extreme precipitation under changing environment: case study in catchments of the Loess Plateau, China. Stochastic Environmental Research and Risk Assessment, 32(7), 2057–2074.

    Article  Google Scholar 

  • Huang, J., Islam, A. R. M. T., Zhang, F., & Hu, Z. (2017). Spatiotemporal analysis the precipitation extremes affecting rice yield in Jiangsu province, southeast China. International Journal of Biometeorology, 61(10), 1863–1872.

    Article  PubMed  Google Scholar 

  • Huang, J., Ma, H., Sedano, F., Lewis, P., Liang, S., Wu, Q., et al. (2019). Evaluation of regional estimates of winter wheat yield by assimilating three remotely sensed reflectance datasets into the coupled WOFOST–PROSAIL model. European Journal of Agronomy, 102, 1–13.

    Article  Google Scholar 

  • Huang, J., Zhou, H., Zheng, F., & Li, Y. (2020). Responses of yield fluctuation of winter oilseed rape to climate anomalies in south China at provincial Scale. International Journal of Plant Production. https://doi.org/10.1007/s42106-020-00102-8.

    Article  Google Scholar 

  • Huang, J., Zhou, L., Zhang, F., et al. (2021). Responses of yield variability of summer maize in Henan province, north China, to large-scale atmospheric circulation anomalies. Theoretical Applied Climatology. https://doi.org/10.1007/s00704-020-03504-w.

    Article  Google Scholar 

  • Intergovernmental Panel on Climate Change (IPCC). (2014). Climate change 2014: the synthesis report of the fifth assessment report of the intergovernmental panel on climate change. Cambridge: Cambridge University Press.

    Google Scholar 

  • Islam, A. R. M. T., Shen, S., Hu, Z., & Rahman, M. A. (2017). Drought hazard evaluation in Boro paddy cultivated areas of western Bangladesh at current and future climate change conditions, advances in meteorology. Advance Meteorology. https://doi.org/10.1155/2017/3514381.

    Article  Google Scholar 

  • Islam, A. R. M. T., Shen, S., & Yang, S. (2018). Predicting design water requirement of winter paddy under climate change condition using frequency analysis in Bangladesh. Agricultural Water Management, 195, 58–70. https://doi.org/10.1016/j.agwat.2017.10.003037.

    Article  Google Scholar 

  • Islam, A. R. M. T., Shen, S., Yang, S., Hu, Z., & Chu, R. (2019). Assessing recent impacts of climate change on design water requirement of Boro rice season in Bangladesh. Theoretical Applied Climatology. https://doi.org/10.1007/s00704-019-02818-8.

    Article  Google Scholar 

  • Islam, A. R. M. T., Shen, S., Yang, S., Hu, Z., & Rahman, M. A. (2020). Spatiotemporal rice yield variations and potential agro-adaptation strategies in Bangladesh: a biophysical modeling approach. Sustainable Production and Consumption, 24, 121–138. https://doi.org/10.1016/j.spc.2020.07.005.

    Article  Google Scholar 

  • Islam, A. R. M. T., Tasnuva, A., Sarker, S. C., Rahman, M. M., Mondal, M. S. H., & Islam, M. M. U. (2014). Drought in Northern Bangladesh: social, agroecological impact and local perception. International Journal of Ecosystem, 4(3), 150–158.

    Google Scholar 

  • Kukal, M. S., & Irmak, S. (2018). Climate-driven crop yield and yield variability and climate change impacts on the US Great Plains agricultural production. Scientific Reports, 8(1), 1–18.

    Article  Google Scholar 

  • Li, C., Wang, R., Xu, J., Luo, Y., Tan, M. L., & Jiang, Y. (2018). Analysis of meteorological dryness/wetness features for spring wheat production in the Ili River basin, China. International Journal of Biometeorology, 62(12), 2197–2204.

    Article  PubMed  Google Scholar 

  • Li, T., et al. (2015). Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions. Global Change Biology, 21, 1328–1341.

    Article  CAS  PubMed  Google Scholar 

  • Liaw, A., & Wiener, M. (2002). Classification and regression by random Forest. R News, 2(3), 18–22.

    Google Scholar 

  • Limsakul, A. (2019). Impacts of El Niño-Southern Oscillation (ENSO) on rice production in Thailand during 1961–2016. Environment and Natural Resources Journal, 17(4), 30–42.

    Article  Google Scholar 

  • Liu, Y., Lu, H., Yang, S., & Wang, Y. (2016). Impacts of biochar addition on rice yield and soil properties in a cold waterlogged paddy for two crop seasons. Field Crops Research, 191, 161–167.

    Article  Google Scholar 

  • Lobell, D. B., Burke, M. B., Tebaldi, C., Mastrandrea, M. D., Falcon, W. P., & Naylor, R. L. (2008). Prioritizing climate change adaptation needs for food security in 2030. Science, 319(5863), 607–610.

    Article  CAS  PubMed  Google Scholar 

  • Pattanayak, A., & Kumar, K. S. K. (2014). Weather sensitivity of rice yield: evidence from India. Climate Change Economics, 5(4), 1450011.

    Article  Google Scholar 

  • Polong, F., Chen, H., Sun, S., & Ongoma, V. (2019). Temporal and spatial evolution of the standard precipitation evapotranspiration index (SPEI) in the Tana River Basin, Kenya. Theoretical and Applied Climatology, 138(1–2), 777–792.

    Article  Google Scholar 

  • Quadir, D.A., (2007). The impact of climate variability on the yield of rain-fed rice of Bangladesh. SAARC Meteorolog. Research Centre (SMRC)

  • Rahman, M. S., Azad, M. A. K., Hasanuzzaman, M., Salam, R., Islam, A. R. M. T., Rahman, M. M., & Hoque, M. M. M. (2021). How air quality and COVID-19 transmission change under different lockdown scenarios? A case from Dhaka city, Bangladesh. Science of the Total Environment, 762, 143161. https://doi.org/10.1016/j.scitotenv.2020.143161.

    Article  CAS  Google Scholar 

  • Rahman, M. S., & Islam, A. R. M. T. (2019). Are precipitation concentration and intensity changing in Bangladesh overtimes? Analysis of the possible causes of changes in precipitation systems. Science of the Total Environment, 690, 370–387.

    Article  CAS  Google Scholar 

  • Rahman, M. A., Kang, S., Nagabhatla, N., & Macnee, R. (2017). Impacts of temperature and rainfall variation on rice productivity in major ecosystems of Bangladesh. Agriculture & Food Security, 6(1), 10.

    Article  Google Scholar 

  • Rashid, H. E. (1991). Geography of Bangladesh. Dhaka: University Press.

    Google Scholar 

  • Rashid, M.H. and Islam, M.S., (2007). Adaptation to climate change for sustainable development of Bangladesh agriculture. Bangladesh Country Paper. Asian and Pacific Centre for Agricultural Engineering and Machinery (APCAEM), Beijing

  • Ray, D. K., Gerber, J. S., MacDonald, G. K., & West, P. C. (2015). Climate variation explains a third of global crop yield variability. Nature Communications, 6, 5989.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Ray, D. K., Ramankutty, N., Mueller, N. D., West, P. C., & Foley, J. A. (2012). Recent patterns of crop yield growth and stagnation. Nature Communication, 3, 1293.

    Article  Google Scholar 

  • Rezaie-Balf, M., Maleki, N., Ki, S., et al. (2019). Forecasting daily solar radiation using CEEMDAN decomposition-based MARS model trained by crow search algorithm. Energies, 12, 1416. https://doi.org/10.3390/en12081416.

    Article  Google Scholar 

  • Roberts, M. G., Dawe, D., Falcon, W. P., & Naylor, R. L. (2009). El Niño-Southern Oscillation impacts on rice production in Luzon, the Philippines. Journal of Applied Meteorology and Climatology, 48(8), 1718–1724.

    Article  Google Scholar 

  • Saha, T. R., & Quadir, D. A. (2016). Variability and trends of annual and seasonal thunderstorm frequency over Bangladesh. International Journal of Climatology, 36(14), 4651–4666.

    Article  Google Scholar 

  • Salam, R., Islam, A. R. M. T., & Islam, S. (2019). Spatiotemporal distribution and prediction of groundwater level linked to ENSO teleconnection indices in the northwestern region of Bangladesh. Environment Development and Sustainability. https://doi.org/10.1007/s10668-019-00395-4.

    Article  Google Scholar 

  • Salam, R., Islam, A. R. M. T., Shill, B. K., Alam, G. M. M., Hasanuzzaman, M., Hossain, M. M., et al. (2021). Nexus between vulnerability and adaptive capacity of drought-prone rural households in northern Bangladesh. Natural Hazards. https://doi.org/10.1007/s11069-020-03900-5.

    Article  Google Scholar 

  • Sarker, M. A. R., Alam, K., & Gow, J. (2012). Exploring the relationship between climate change and rice yield in Bangladesh: an analysis of time series data. Agricultural Systems, 112, 11–16.

    Article  Google Scholar 

  • Sarker, M. A. R., Alam, K., & Gow, J. (2014). Assessing the effects of climate change on rice yields: an econometric investigation using Bangladeshi panel data. Economic Analysis and Policy, 44(4), 405–416.

    Article  Google Scholar 

  • Sarker, M. A. R., Alam, K., & Gow, J. (2017). Performance of rain-fed Aman rice yield in Bangladesh in the presence of climate change. Renewable Agriculture and Food Systems. https://doi.org/10.1017/S1742170517000473.

    Article  Google Scholar 

  • Schlenker, W., & Roberts, M. J. (2009). Nonlinear temperature effects indicate severe damages to US crop yields under climate change. Proceedings of the National Academy of Sciences, 106(37), 15594–15598.

    Article  CAS  Google Scholar 

  • Selvaraju, R. (2003). Impact of El Niño–southern oscillation on Indian food grain production. International Journal of Climatology: A Journal of the Royal Meteorological Society, 23(2), 187–206.

    Article  Google Scholar 

  • Shahid, S. (2010). Recent trends in the climate of Bangladesh. Clim. Res., 42, 185–193.

    Article  Google Scholar 

  • Shahid, S., & Behrawan, H. (2008). Drought risk assessment in the western part of Bangladesh. Natural Hazards, 46, 391–413. https://doi.org/10.1007/s11069-007-9191-5.

    Article  Google Scholar 

  • Strobl, C., Boulesteix, A. L., Zeileis, A., & Hothorn, T. (2007). Bias in random forest variable importance measures: illustrations, sources and a solution. BMC Bioinformatics, 8(1), 25.

    Article  PubMed  PubMed Central  Google Scholar 

  • Tian, C., Wang, L., Kaseke, K. F., & Bird, B. W. (2018). Stable isotope compositions ( δ2H, δ18O and δ17O) of rainfall and snowfall in the central United States. Scientific Reports, 8(6712), 1–15. https://doi.org/10.1038/s41598-018-25102-7.

    Article  CAS  Google Scholar 

  • Wahiduzaman, M., Islam, A. R. M. T., Luo, J., Shahid, S., Uddin, M. J., Shimul, S. M., & Sattar, M. A. (2020). Trends and variabilities of thunderstorm days over Bangladesh on the ENSO and IOD timescales. Atmosphere, 11(11), 1176. https://doi.org/10.3390/atmos11111176.

    Article  Google Scholar 

  • Wahiduzzaman, M. (2012). ENSO connection with monsoon rainfall over Bangladesh. Int J of Appl Sci Eng Res, 1(1), 26–38.

    Article  Google Scholar 

  • Wang, E., Martre, P., Zhao, Z., Ewert, F., Maiorano, A., Rötter, R. P., et al. (2017). The uncertainty of crop yield projections is reduced by improved temperature response functions. Nature Plants, 3(8), 1–13.

    Google Scholar 

  • WISER, (2018). Water isotope system for data analysis, visualization and electronic retrieval. https://nucleus.iaea.org/wiser

  • Wu, Z., & Huang, N. E. (2004). A study of the characteristics of white noise using the empirical mode decomposition method. Proceedings of the Royal Society of London. Series A Mathematical, Physical and Engineering Sciences, 460(2046), 1597–1611.

    Article  Google Scholar 

  • Wu, Z., & Huang, N. E. (2009). Ensemble empirical mode decomposition: a noise-assisted data analysis method. Advances in Adaptive Data Analysis, 1(1), 1–41.

    Article  Google Scholar 

  • Xu, Y., Li, T., Shen, S., Xu, G., Islam, A. R. M. T., et al. (2020). Effects of cyclic variability in Pacific decadal oscillation on winter wheat production in China. International Journal of Climatology. https://doi.org/10.1002/joc.6956.

    Article  Google Scholar 

  • Yamada, K., Masuma, T., Sakai, S., Seto, K., Ogusa, H., & Irizuki, T. (2016). Centennial-scale East Asian summer monsoon intensity based on δ18 O values in ostracode shells and its relationship to land-ocean air temperature gradients over the past 1700 years. Geology. https://doi.org/10.1130/G37535.1.

    Article  Google Scholar 

  • Yu, W., Alam, M., Hassan, A., Khan, A. S., Ruane, A. C., Rosenzweig, C., et al. (2010). Bangladesh-Climate change risks and food security in Bangladesh. Washington: World Bank.

    Book  Google Scholar 

  • Zannat, F., Islam, A. R. M. T., & Rahman, M. A. (2019). Spatiotemporal variability of rainfall linked to ground water level under changing climate in northwestern region, Bangladesh. European Journal of Geosciences, 1(1), 35–56.

    Article  Google Scholar 

  • Zhang, W., Jin, F. F., & Turner, A. (2014). Increasing autumn drought over southern China associated with ENSO regime shift. Geophysical Research Letters, 41(11), 4020–4026.

    Article  Google Scholar 

  • Zhang, W., Li, H., Stuecker, M. F., Jin, F. F., & Turner, A. G. (2016). A new understanding of El Niño’s impact over East Asia: dominance of the ENSO combination mode. Journal of Climate, 29(12), 4347–4359.

    Article  Google Scholar 

  • Zhao, C., Piao, S., Wang, X., Huang, Y., et al. (2016). Plausible rice yield losses under future climate warming. Nature Plants, 3, 16202. https://doi.org/10.1038/nplants.2016.202.

    Article  PubMed  Google Scholar 

  • Zhao, J., Guo, J., & Mu, J. (2015). Exploring the relationships between climatic variables and climate-induced yield of spring maize in Northeast China. Agriculture, Ecosystems & Environment, 207, 79–90.

    Article  Google Scholar 

  • Ziegler, A., & König, I. R. (2014). Mining data with random forests: current options for real-world applications. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 4(1), 55–63.

    Google Scholar 

  • Zinat, M. R. M., Salam, R., Badhan, M. A., & Islam, A. R. M. T. (2020). Appraising drought hazard during Boro rice growing period in western Bangladesh. International Journal of Biometeorology., 64(10), 1697–1697. https://doi.org/10.1007/s00484-020-01949-2.

    Article  Google Scholar 

  • Zubair, L. (2002). El Nino–southern oscillation influences on rice production in Sri Lanka. International Journal of Climatology, 22(2), 249–260.

    Article  Google Scholar 

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Acknowledgements

This work was supported by Researchers Supporting Project number (RSP-2020/100), King Saud University, Riyadh, Saudi Arabia. We greatly acknowledge the Bangladesh Meteorological Department (BMD) for proving data for this study. We highly acknowledge the NCEP/NCAR and ECMWF ERA5 reanalysis dataset which used in this present study. We also highly thankful to Isotope Hydrology Division, Institute of Nuclear Science & Technology, Atomic Energy Research Establishment, Savar, Dhaka, Bangladesh for shearing Experimental dataset in the study.

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Ghose, B., Islam, A.R.M.T., Islam, H.M.T. et al. Rain-Fed Rice Yield Fluctuation to Climatic Anomalies in Bangladesh. Int. J. Plant Prod. 15, 183–201 (2021). https://doi.org/10.1007/s42106-021-00131-x

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