Evaluating Canola Yield under Arid and Climate Change Conditions

پژوهشهای زراعی ایران

Article 5, Volume 15, Issue 2 - Serial Number 46, July 2017, Pages 355-367   

Document Type: Research Article

DOI: 10.22067/gsc.v15i2.50856

Authors

S Farhangfar; M Bannayan Aval^* ; H. R Khazaei; M Mousavi Baygi

Ferdowsi University of Mashhad

Abstract

Introduction Climate change has a profound influence on crop production sustainability in arid and semi-arid environments. A more arid climate is usually accompanied by a higher frequency and severity of droughts. Drought prevention and mitigation has become important content of promoting economic and social sustainable development. Assessing vulnerability of agricultural crops is an effective approach in understanding the impacts of climate change and extreme climatic events on agricultural systems. In recent years vulnerability was generally considered as a function of exposure, sensitivity and adaptive capacity. Sensitivity reflects the degree to which a given system responds to the fluctuations in stress. Adaptive capacity has been defined as the capacity of a system to adjust to the change and take advantage from it. Exposure is the possibility of the system being exposed to the concerned change in the stress. This study aims to achieve an understanding of the vulnerability of wheat and maize production, to various severities of drought conditions in the past and coming future years.
Materials and Methods This study was performed in Mashhad, Sabzevar and Torbat Heydarieh. Daily historical weather data including maximum and minimum air temperature (°C), precipitation (mm) and solar radiation (MJ m-2 d-1) for the period of 1961-2008 were collected for each study location from their established climatologic stations. Two general circulation models including IPCM4 and HadCM3 were used under A1B, A2 and B1 emission scenarios using LARS-WG. Historical crop yields of canola were collected for study locations from the established Ministry of Agricultural. The potential canola yield was simulated by the crop growth model WOFOST version 7.1.7. For quantifying drought, Aridity Index (UNEP 1992) was calculated for canola growing season March-October. In this study vulnerability was considered as a function of sensitivity, well-being state relative to its damage threshold and exposure. Sensitivity was calculated as the slope value of the simulated trend line of yield and aridity index during the growing season of canola. The crop production well-being to its damage threshold was calculated as the proportion of the yield of a specific year to the average yield over the selected years. Exposure was calculated as the proportion of years having an AIU value under the specified level within the concerned period.
Results and Discussion The estimated agricultural sensitivity showed that in all the study locations canola was extremely sensitive to drought in the baseline; the same trend was obtained in the projected years by both HadCM3 and IPCM4 models (SEN > 200). For all the study locations the estimated values of VEXPL, VEXPS and EVEXP in the baseline were extremely high (> 20), while EEXP was low. It seems that canola production in the baseline have suffered from severe drought. The results of both GCM models showed the same trend under all scenarios as the estimated values of SEN, VEXPL, VEXPS and EVEXP during the coming future years were extremely high, while EEXP was low. It seems that in all study locations drought is going to affect canola production in the coming future years. These negative effects can be related to photosynthesis reduction and decline in the speed and amount of transportation assimilation under drought conditions that causes crop yield and dry matter reduction. Drought also affects plants pollination and causes pollen sterility, which affects crop production. It was reported by Daneshmand et al., 2006 that drought usually affects the grains of canola by reducing the number of seeds in siliqua. It was stated by Ma et al., 2006 that the number of seeds in the siliqua declines under drought conditions. According to the results of Mishra and Cherkauer, 2010 during 1980-2007 the yield of crops showed a strong correlation with drought during the seed filling and reproductive periods in western part of the center United States. It was also reported that drought reduces the morphological traits of canola (bush height, number of sub-branches and the length of siliqua), grain yield and its components (the number of siliqua in a bush, number of seeds in a siliqua and the weight of 1000 seeds) and the oil yield significantly.
Conclusions Overall, this study results showed that canola production has affected from severe droughts during the baseline years. The results of both GCM models showed the same trend as the baseline. Canola production was extremely sensitive and vulnerable to drought during the baseline and projected years.

Keywords

Sensitivity; Vulnerability; WOFOST model

References

1. Adamenko, T., and Prokopenko, T. 2011. Monitoring Droughts and Impacts on Crop Yield in Ukraine from Weather and Satellite Data. Use of Satellite and In-Situ Data to Improve Sustainability NATO Science for Peace and Security Series C: Environmental Security 3-9.

2. Adger, W. N. 2006. Vulnerability. Global Environmental Change 16: 268-281.

3. Alberini, A., Chiabai, A., and Muehlenbachs, L. 2006. Using expert judgment to assess adaptive capacity to climate change: Evidence from a conjoint choice survey. Global Environmental Change 16(2): 123-144.

4. Antwi Agyei, P., Fraser, E. D. G., Dougill, A. J., Stringer, L. C., and Simelton, E. 2012. Mapping the vulnerability of crop production to drought in Ghana using rainfall, yield and socioeconomic data. Applied Geography 32 (2): 324–334.

5. Boogaard, H., Van Diepen, C., Roetter, R., Cabrera, J., and Van Laar, H. 1998. WOFOST 7.1 User’s guide for the WOFOST 7.1 crop growth simulation model and WOFOST control center 1.5. SC-DLO. Wageningen.

6. Boruff, B. J., Emrich, C., and Cutter, S. L. 2005. Erosion hazard vulnerability of US coastal countries. Journal of Coastal Research 21(5): 932-942.

7. Brooks, N., Adger, W. N., and Kelly, P. M. 2005. The determinants of vulnerability and adaptive capacity at the national level and the implications for adaptation. Global Environmental Change 15(2): 151-163.

8. Burke, E., and Brown, S. J. 2010. Regional drought over the UK and changes in the future. Journal of Hydrology 394(3-4): 471-485.

9. Chipanshi, A. C., Chanda, R., and Totolo, O. 2003. Vulnerability Assessment of the Maize and Sorghum Crops to Climate Change in Botswana. Climatic Change 61(3): 339-360.

10. Craft, K. E., Mahmood, R., King, S. A., Goodrich, G., and Yan, J. 2015. Twentieth century droughts and agriculture: Examples from impacts on soybean production in Kentucky, USA. AMBIO: A Journal of the Human Environment.

11. Daneshmand, A. R., Shirani Rad, A. H., and Ardakani, M. R. 2006. Evaluation of water deficit stress on tolerance of spring rapeseed (Brassica napus L.) genotypes. Agronomy Research 1(1): 48-60. (in Persian).

12. Dixon, B. 2005. Applicability of neuro-fuzzy techniques in predicting ground water vulnerability: a GIS based sensitivity analysis. Journal of Hydrology 309(1-4): 17-38.

13. Emam, Y., Ranjbari, A., and Behrani, M. J. 2007. Evaluation of drought stress effects on yield and yield components of wheat genotypes after flowering. Journal of Science and Technology of Agriculture and Natural Resources, Water and Soil Sceinces 11(1): 317-328. (in Persian).

14. FAO statistics. 2015. http://faostat.fao.org. 6 May 2015.

15. Gallopin, GC. 2006. Linkage between vulnerability, resilience, and adaptive capacity. Global Environmental Change 16(3): 293-303.

16. Gove P. B. Ed. 1981. Webster’s third new international dictionary of the English language.

17. Hargreaves, G. H., and Samani, A. Z. 1985. Reference crop evapotranspiration from temperature. Applied Engineering in Agriculture 1(2): 96-99.

18. Hasanzadeh, M., Naderi Darbaghshahi, M., and Shirani Rad, A. H. 2005. Evaluation of drought stress effects on yield and yield components of autumn rapeseed varieties in Isfahan region. Research in Agricultural Sciences 2(1): 51-62. (in Peraisn).

19. Humphreys, M. W., Yadav, R. S., Cairns, A. J., Turner, L. B., Humphreys, J., and Skot, L. 2006. A changing climate for grassland research. New Phytologist 169(1): 9-26.

20. IPCC. 2001. Impacts, adaptation, and vulnerability climate change 2001. Third Assessment Report of the IPCC. Cambridge University Press. UK.

21. Jamshidi, N., Shirani Rad, A. M., Takht Chin, F. Nazeri, P., and Ghaffari, M. 2012. Evaluation of canola varieties under drought stress. Crop Ecophysiology 6(3): 323-338. (in Peraisn).

22. Kenny, G. J., Ye, W., Flux, T., and Warrick, R. A. 2001. Climate variations and New Zealand agriculture: the CLIMPACTS system and issues of spatial and temporal scale. Environment International 27:189-194.

23. Lashkari, A., Alizadeh, A., and Bannayan, M. 2011. Investigation of mitigation of climate change impacts on maize production in Northeast of Iran. Journal of water and soil 25(4): 926-939.

24. Li, Y., Huang, H., Ju, H., Lin, E., Xiong, W., Han, X., Wang, H., Peng, Z., Wang, Y., Xu, J., Cao, Y., and Hu, W. 2015. Assessing vulnerability and adaptive capacity to potential drought for winter-wheat under the RCP 8.5 scenario in the Huang-Huai-Hai Plain. Agriculture, Ecosystems & Environment 209: 125-131.

25. Luers, A. L., Lobell, D. B., Sklar, L. S., Addams, C. L., and Matson, P. A. 2003. A method for quantifying vulnerability, applied to the agricultural system of the Yaqui Valley, Mexico. Global Environmental Change 13(4): 255-267.

26. Ma, Q., Niknam, S. R., and Turner, D. W. 2006. Responses of osmotic adjustment and seed yield of Brassica napus and B. juncea to soil water deficit at different growth stages. Australian Journal of Agricultural Research 57(2): 221-226.

27. McCarl, B. A., Musumba, M., Smith, J. B., Kirshen, P., Jones, R., El-Ganzori, A., Ali M. A., Kotb M., El-Shinnawy I., El-Agizy, M. Bayoumi, M., and Hynninen, R. 2013. Climate change vulnerability and adaptation strategies in Egypt’s agricultural sector. Mitigation and Adaptation Strategies for Global Change.

28. Mirhashemi, S. M., and Bannayan, M. 2012. Model for simulating canola yield under water stress conditions. Journal of Water and Soil 26(2): 392-403. (in Persian with English abstract).

29. Mishra, V., and Cherkauer, K. A. 2010. Retrospective droughts in the crop growing season: Implications to corn and soybean yield in the Midwestern United States. Agricultural and Forest Meteorology 150(7-8): 1030-1045.

30. Nash, J. E., and Sutcliffe, J. V. 1970. River flow forecasting through conceptual models. Part I: a discussion of principles. Journal of Hydrology 1970; 10:282-290.

31. Ren, X. 2007. Agricultural vulnerability to drought in Southern Alberta: a quantitative assessment. MSc Thesis. University of Lethbridge. Canada.

32. Royo, C., Alvaro, F., Martos, V., Ramdani, A., Isidro, J., Villegas, D., Luis, F., and Garcı´a del, M. 2006. Genetic changes in durum wheat yield components and associated traits in Italian and Spanish varieties during the 20th century. Euphytica 155: 259-270.

33. Schilling, J., Freier, K. P., Hertig, E., and Scheffran, J. 2012. Climate change, vulnerability and adaptation in North Africa with focus on Morocco. Agriculture, Ecosystems & Environment 156: 12-26.

34. Semenov, M. A., and Brooks, R. J. 1999. Spatial interpolation of the LARS-WG stochastic weather generator in Great Britain. Climatic Research 11:137-148.

35. Smit, B., and Wandel, J. 2006. Adaptation, adaptive capacity and vulnerability. Global Environmental Change 16(3): 282-292.

36. Sultana, H., Ali, N., Iqbal, M. M., Khan, A. M. 2009. Vulnerability and adaptability of wheat production in different climatic zones of Pakistan under climate change scenarios. Climatic Change 94(1-2): 123-142.

37. Supit, I., Hooijer, A. A., and Van Diepen, C. A. 1994. System description of WOFOST 6.0 crop simulation model implemented in GCMs. European Commission Joint Research Center. Luxembourg.

38. Tao, F. L., Hayashi, Y., and Lin, E. D. 2002. Soil vulnerability and sensitivity to acid deposition in China. Water Air and Soil Pollution 140(1-4): 247-260.

39. Turner, B. L., Kasperson, R. E., Matson, P. A., McCarthy, J. J., Corell, R. W., Christensen, L., Eckleyg, N., Kaspersonb, J. X., Luerse, A., Martellog, M. L., Polskya, C., Pulsiphera, A., and Schillerb, A. 2003. A framework for vulnerability analysis in sustainability science. Proceedings of the National Academy of Sciences of the United States of America 100(14): 8074-8079.

40. United Nations Environment Programme (UNEP). (1992). World atlas of desertification.

41. Zeleke, K. T., Luckett, D. J., and Cowley, R. B. 2014. The influence of soil water conditions on canola yields and production in Southern Australia. Agricultural Water Management 144: 20-32.

42. Zomorodian, A., Kavoosi, Z., and Momenzadeh, L. 2010. Determination of EMC isotherms and appropriate Mathematical models for canola. Food and Bioproducts Processing 89(4):407-413.