Adaptation Strategies of Wheat to Climate Change (Case Study: Ahvaz Region)

Document Type : Research Article

Authors

• M. Delghandi ¹
• S. Broomandnasab ²
• B. Andarzian ³
• A.R. Massah-Bovani ⁴

¹ Shahrood University

² ShahidChamran University of Ahwaz

³ Assistant Professor and Lecuture

⁴ Tehran University

https://doi.org/10.22067/jsw.v30i1.38854

Abstract

Introduction In recent years human activities induced increases in atmospheric carbon dioxide (CO2). Increases in [CO2] caused global warming and Climate change. Climate change is anticipated to cause negative and adverse impacts on agricultural systems throughout the world. Higher temperatures are expected to lead to a host of problems. On the other hand, increasing of [CO2] anticipated causing positive impacts on crop yield. Considering the socio-economic importance of agriculture for food security, it is essential to undertake assessments of how future climate change could affect crop yields, so as to provide necessary information to implement appropriate adaptation strategies. In this perspective, the aim of this study was to assess potential climate change impacts and on production for one of the most important varieties of wheat (chamran) in Khouzestan plain and provide directions for possible adaptation strategies.
Materials and Methods: For this study, The Ahvaz region located in the Khuzestan province of Iran was selected.
Ahvaz has a desert climate with long, very hot summers and mild, short winters. At first, thirteen GCM models and two greenhouse gases emission (GHG) scenarios (A2 and B1) was selected for determination of climate change scenarios. ∆P and ∆T parameters at monthly scale were calculated for each GCM model under each GHG emissions scenario by following equation:


Where ∆P, ∆T are long term (thirty years) precipitation and temperature differences between baseline and future period, respectively. average future GCM temperature (2015-2044) for each month, , average baseline period GCM temperature (1971-2000) for each month, , average future GCM precipitation for each month, , average baseline period GCM temperature (1971-2000) for each month and i is index of month. Using calculated ∆Ps for each month via AOGCM models and Beta distribution, Cumulative probability distribution function (CDF) determined for generated ∆Ps. ∆P was derived for risk level 0.10 from CDF. Using the measured precipitation for the 30 years baseline period (1971-2000) and LARS-WG model, daily precipitation time series under risk level 0.10 were generated for future periods (2015-2045 and 2070-2100). Mentioned process in above was performed for temperature. Afterwards, wheat growth was simulated during future and baseline periods using DSSAT, CERES-Wheat model. DSSAT, CERES4.5 is a model based on the crop growth module in which crop growth and development are controlled by phenological development processes. The DSSAT model contains the soil water, soil dynamic, soil temperature, soil nitrogen and carbon, individual plant growth module and crop management module (including planting, harvesting, irrigation, fertilizer and residue modules). This model is not only used to simulate the crop yield, but also to explore the effects of climate change on agricultural productivity and irrigated water. For model validation, field data from different years of observations were used in this study. Experimental data for the simulation were collected at the experimental farm of the Khuzestan Agriculture and Natural Resources Research Center (KANRC), located at Ahwaz in south western Iran.
Results and Discussion: Results showed that wheat growth season was shortened under climate change, especially during 2070-2100 periods. Daily evapotranspiration increased and cumulative evapotranspiration decreased due to increasing daily temperatures and shortening of growth season, respectively. Comparing the wheat yield under climate change with base period based on the considered risk value (0.10) showed that wheat yield in 2015-2045 and 2070-2100 was decreased about 4 and 15 percent, respectively. Four adaptation strategies were assessed (shifting in the planting date, changing the amount of nitrogenous fertilizer, irrigation regime and breeding strategies) in response to climate change. Results indicated that Nov, 21 and Dec, 11 are the best planting dates for 2015-2045 and 2070-2100, respectively. The late season varieties with heat-tolerant characteristic had higher yield in comparison with short and normal season varieties. It indicated that breeding strategy was an appropriate adaptation under climate change. It was also found that the amount of nitrogen application will be reduced by 20 percent in future periods. The increase and decease of one irrigation application (40mm) to irrigation regime of base period resulted in maximum yield for 2015-2045 and 2070-2100, respectively. But, reduction of two irrigation application (80mm) resulted in maximum water productivity (WPI).
Conclusions In the present study, four adaptation strategies of wheat (shifting in the planting date, changing the amount of nitrogenous fertilizer, irrigation regime and breeding strategies) under climate change in Ahvaz region were investigated. Result showed that Nov, 21 and Dec, 11 were the best planting dates for 2015-2045 and 2070-2100, respectively. The late season varieties with heat-tolerant characteristic had higher yield in comparison with short and normal season varieties. It indicated that breeding strategy was an appropriate adaptation strategy under climate change. It was also found that the amount of nitrogen application will be reduced by 20 percent in future periods. The increase and decease of one irrigation application (40mm) to irrigation regime of base period resulted in maximum yield for 2015-2045 and 2070-2100, respectively.

Keywords

• Climate change
• wheat
• Adaptation Strategies
• Crop Model
• scenario

20.1001.1.20084757.1395.30.1.25.5

References

1- Aggarwal P.K. 1991. Simulation growth, development and yield of wheat in warm area. PP 429-435. In (eds) Sanders, D.A., and G.H. Hettle. Wheat in heat stressed environments. Irrigated, dry areas and rice-wheat farming system, CIMMYT, Thailand, 549 p.

2- Geerts S., Raes D., and Garcia M. 2010. Using AquaCrop to derive deficit irrigation schedules. Agricultural Water Management, 98: 213-216.

3- Anonymous. 2009. How to feed the world in 2050. High-level Experts Form, FAO, Rome. P.35.

4- Delghandi M. 2012. Risk assessment of climate change impacts on wheat production and adaptation strategies (case study: South of Khuzestan Plain). Department of Irrigation and Drainage, Chamranuniversity, Iran.Ph.D Dissertation. (in Persian with English abstract).

5- Delghandi M., Andarzian B., Broomand-Nasab S., MassahBovani A., and Javaheri E. 2014. Evaluation of DSSAT 4.5-CSM-CERES-Wheat to Simulate Growth and Development, Yield and Phenology Stages of Wheat under Water Deficit Condition (Case Study: Ahvaz Region).Journal of Water and Soil, 28(1):82-91. (In Persian with English abstract).

6- Delghandi M., MassahBovani A., Ajorlou M.J., Broomand-Nasab S., and Andarzian B. 2014. Risk assessment of climate change impacts on production and phenology of wheat (case study: Ahvaz Region). Journal of Water and Irrigation Management, 4(2): 161-175. (in Persian with English abstract).

7- Easterling W.E., Aggarwal P.K., Batima P., Brander K.M and others. 2007. Food, fibre and forest products. In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds) Climate change 2007: impacts, adaptation and vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the IPCC. Cambridge University Press, Cambridge, p 273–313.

8- Gouache CH., Bris, X.L., Bogard M., Deudon O., Page C.H., and Philippe P.H. 2012. Evaluating agronomic adaptation options to increasing heat stress under climate change during wheat grain filling in France. European Journal of Agronomy, 39: 62-70.

9- Harmsen E.W., Miller N.L., Schlegel N.J., and Gonzalez J.E. 2009. Seasonal climate change impacts on evapotranspiration, precipitation deficit and crop yield in Puerto Rico. Agricultural Water Management, 96: 1085-1095.

10- Holden N.M., and Brereton A.J. 2006. Adaptation of water and nitrogen management of spring barley and potato as a response to possible climate change in Ireland. Agricultural Water Management, 82: 297–317.

11- IPCC. 2001. Climate change. The science of climate change. Contribution of working group I to the second assessment report of the intergovernmental panel on climate change. Eds. Houghton, J.T., Filho, L.G.M., Callander, B.A., Harris, N., Attenberg, A. and Maskell K., 572 pp. Cambridge University Press, Cambridge.

12- IPCC. 2001. Summary for Policymakers, in McCarthy, J.J., Canziani, O.F., Leary, N.A., Dokken, D.J.and White, K.S. (eds.) (2001) Climate Change 2001: Impacts, Adaptation, and Vulnerability,Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panelon Climate Change, Cambridge University Press, Cambridge, 1-17.

13- IPCC-TGICA. 2007. General guidelines on the use of scenario data for climate impact and adaptation assessment. eds. Carter, T.R., Version 2, 71p. Intergovernmental Panel on Climate Change, Task Group on Data and Scenario Support for Impact and Climate Assessment.

14- Ishagh H.M. 1994. Genotype, differences in heat stress in wheat in the irrigated Gazira scheme. pp 170-174. in(eds) Sanders, D.A and G.H. Hettle. Wheat in heat stressed environments. Irrigated, dry areas and rice-wheat farming system, CIMMYT, Thailand, 549 p.

15- KoochekiA., and Nassiri M. 2008. Impacts of climate change and CO2 concentration on wheat yield in Iran and adaptation strategies. Journal of Iranian Field Crop Research, 6(1):139-153. (In Persian with English abstract).

16- Lobell D.B and Ortiz-Manasterio I. 2006. Evaluating strategies for improved water use in spring wheat with CERES. Agricultural Water Management, 84: 249-258.

17- Lobell B.D., Sibley A., and Ortiz-Monasterio J.I. 2012. Extreme heat effects on wheat senescence in India. Nature Climate Change, 2: 186-189.

18- Lobell D.B., Hammer G.L., McLean G., Messina C., Roberts M.J., and Schlenker W. 2013. The critical role of extreme heat for maize production in the United States. Nature Climate Change, 3: 497-501.

19- Luo Q., Bellotti W., Williams M. and Wang E. 2009. Adaptation to climate change of wheat growing in South Australia: Analysis of management and breeding strategies Agriculture. Ecosystems and Environment, 129: 261–267.

20- Mereu V. 2009. Climate change impact on durum wheat in Sardinia. Agrometeorology and Ecophysiology of agricultural Systems and Forestry. XXII ciclo – UniversitadegliStudi di Sassari. Ph.D Dissertation.

21- Parry M.L., Rosenzweig C., and Iglesias A., Livermore M and Fischer G. 2004. Effects of climate change on global food production under SRES emissions and socio-economic scenarios. Global Environmental Change, 14: 53-67.

22- Parry M.A.J., Reynolds M., Salvucci M.E., Raines C., Andralojc P.J., Zhu X.G., and Price G.D., Condon A.G., andFurbank R.T. 2011. Raising yield potential of wheat. II.Increasing photosynthetic capacity and efficiency. Journal of Experimental Botany, 62, 453-467.

23- Ruiz-Ramos M and Minguez M.I. 2010. Evaluating uncertainty in climate change impacts on crop productivity in the Iberian Peninsula. Climate Research, 44: 69-82.

24- Semenov M.A and Stratonovitch P. 2010. Use of multi-model ensembles from global climate models for assessment of climate change impacts. Climate Research, 41: 1-14.

25- Semenov M.A., Stratonovitch P., Alghabari F., and Gooding M.J. 2014. Adapting wheat in Europe for climate change. Journal of Cereal Science, 59: 245-256.

26- White J.W., Hoogenboom G., Kimball B.A and Wall G.W. 2011. Methodologies for simulating impacts of climate change on crop production. Field Crops Research, 124: 357–368.