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Title:Rice production and water requirement under climate change conditions - developing management strategies for a sustainable system for an agriculturally predominant region
Author(s):Jha, Ranjeet Kumar
Director of Research:Kalita, Prasanta K.
Doctoral Committee Chair(s):Kalita, Prasanta K.
Doctoral Committee Member(s):Czapar, George; Cooke, Richard A.; Kumar, Praveen; Davidson, Paul
Department / Program:Engineering Administration
Discipline:Agricultural & Biological Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Rice production, Climate Change, Water requirement
Abstract:Increasing crop production is an inevitable demand of current growing population all over the world. Implementation of field crop practices potentially enables farmers to achieve that desired increase in crop production estimated to be a 60% increase compared to current condition. The CERES-Rice model in DSSAT was used for this study in order to provide the water stress impact on crop production, and best management strategies to improve the rice yield, followed by the calibration and validation with collected field experimental data. Ten-years (2006-2015) of field experimental data were collected from the CIMMYT (International Maize and Wheat Improvement Centre)-BISA (Borlaug Institute for South Asia), Pusa, Bihar, India, research farm for calibration and validation of the CERES-Rice model. Predicted change in climate has significant impact on rice production in Bihar, and thus, will affect food security issues in India and other developing countries. Since rice is the primary food for the majority of Indian people, the focus of this study was to predict the changes in the (a) rice yield and phenological growth, and (b) irrigation water requirement for current yield level as well as 60% increase in rice yield by 2050s (2050-2059) as affected by climate change in the state of Bihar. The genetic coefficients were developed for the rice variety, Rajendra Mahsuri (predominantly used by more than 90% rice farmers in Bihar), and used for validation of the model. The normalized root means square error (RMSEn) and d-index values were obtained to be 2.73% and 0.62, respectively, for prediction of yield with a model performance efficiency of 75%. The crop model simulation for water stress during vegetative and maturity phase showed to decrease in rice yield by 24% and 33%, respectively, from measured data. However, the water stress during reproductive stage showed the highest reduction in the yield by 43%. Considering the management strategies, where farmers do not need to invest a large amount of resources to increase the rice production, some factors were assessed by sensitivity analysis of the CERES-Rice model. The optimum transplanting date was found to be during the month of June to achieve the highest yield of Rajendra Mahsuri rice. Incorporation of crop residue up to 2500 kg/ha would increase the yield by 22%, compared to the management practices where no residue is applied in the field. Additionally, row spacing of 20 cm increased rice yield by 16-18%, compared to the yield obtained at spacing of 5 cm, and for maximum yield, optimum planting depth was found to be 2 to 4 cm. Keeping a ponding depth of 4-6 cm during crop duration would aid in maximizing the rice yield by 10-15%. To study the climate change impact on rice yield and water requirement, four GCMs were used for all four climate change scenarios (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5). The projected changes in climatic variables showed the change in future climate during 2020-2059 from baseline period (1980-2004). A Taylor diagram was constructed to analyze the relationship between the historical observed and simulated climate data; Mann-Kendall trend test for climate data of each GCM revealed the trend in climate from 2020-2059 for the climate change scenarios (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5). Further, in order to increase the rice production by 60% during the 2050s, the irrigation requirement for all four climate change scenarios was computed based on the percentage of yield productivity from irrigation water. The results showed that the precipitation amount increased from 2020 to 2059, and hence, the irrigation requirement was predicted not to be as much higher as one would expect for a 60% increase in crop yield. Yield increase by the year of 2059 also partly accounted by an increase in CO2 concentration as predicted by all climate change scenarios. We investigated several strategies, such as conservation agriculture (direct-seeded rice with residue application) and reduction of post-harvest loss, to reduce the water requirement to produce 60% more rice by 2059. Moreover, if we combine both conservation agriculture and removal of 30% of postharvest losses, the irrigation requirement would be reduced by 26% (45 to 19%), 20% (44 to 24%), 21% (43 to 22%), 22% (39 to 17%), and 20% (41 to 21%) with current, RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 conditions, respectively. The assessment on rice production with default value of CO2 concentration (400 ppm) during 2020-2059 demonstrated a decrease in rice yield and phenological days, but increase in water demand. The increase in water demand was found due to reduction in CO2 concentration, which increases the water use efficiency. Larger the differences between default and changed CO2 concentration (as predicted by the climate change scenarios), larger were the deviations between all the outputs. During 2050s, the maximum reduction in yield was 23% with RCP 8.5 and the lowest reduction of 15% was observed with RCP 2.6. Similarly, water demand increased due to decrease in CO2 concentration. The maximum decrease in phenological days was estimated to be 14 days with worst-case scenario (RCP 8.5). Since most farmers in the state of Bihar only produce Rajendra Mahsuri rice variety, this information can help in planning for maximizing production of this rice variety and decreasing water requirement strategies in the state of Bihar, India and similar other locations, where water availability would be severely impacted by climate change.
Issue Date:2019-04-17
Type:Text
URI:http://hdl.handle.net/2142/105199
Rights Information:Copyright 2019 Ranjeet Kumar Jha
Date Available in IDEALS:2019-08-23
Date Deposited:2019-05


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