IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v12y2022i10p1648-d937085.html
   My bibliography  Save this article

Climate Change Affects the Utilization of Light and Heat Resources in Paddy Field on the Songnen Plain, China

Author

Listed:
  • Ennan Zheng

    (School of Hydraulic and Electric Power, Heilongjiang University, Harbin 150080, China
    These authors contributed equally to this work.)

  • Mengting Qin

    (School of Hydraulic and Electric Power, Heilongjiang University, Harbin 150080, China
    These authors contributed equally to this work.)

  • Peng Chen

    (College of Agricultural Science and Engineering, Hohai University, Nanjing 210098, China)

  • Tianyu Xu

    (School of Hydraulic and Electric Power, Heilongjiang University, Harbin 150080, China)

  • Zhongxue Zhang

    (School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin 150030, China)

Abstract

Efficient utilization of light and heat resources is an important part of cleaner production. However, exploring the changes in light and heat resources utilization potential in paddy under future climate change is essential to make full use of the potential of rice varieties and ensure high-efficient, high-yield, and high-quality rice production, which has been seldom conducted. In our study, a process-based crop model (CERES-Rice) was calibrated and validated based on experiment data from the Songnen Plain of China, and then driven by multiple global climate models (GCMs) from the coupled model inter-comparison project (CMIP6) to predict rice growth period, yield, and light and heat resources utilization efficiency under future climate change conditions. The results indicated that the rice growth period would be shortened, especially in the high emission scenario (SSP585), while rice yield would increase slightly under the low and medium emission scenarios (SSP126 and SSP245), it decreased significantly under the high emission scenario (SSP585) in the long term (the 2080s) relative to the baseline of 2000–2019. The light and temperature resources utilization (E RT ), light utilization efficiency (E R ), and heat utilization efficiency (HUE) were selected as the light and heat resources utilization evaluation indexes. Compared with the base period, the mean E RT in the 2040s, 2060s, and 2080s were −6.46%, −6.01%, and −6.03% under SSP126, respectively. Under SSP245, the mean E RT were −7.89%, −8.41%, and −8.27%, respectively. Under SSP585, the mean E RT were −6.88%, −13.69%, and −28.84%, respectively. The E R would increase slightly, except for the 2080s under the high emission scenario. Moreover, the HUE would reduce as compared with the base period. The results of the analysis showed that the most significant meteorological factor affecting rice growth was temperature. Furthermore, under future climate conditions, optimizing the sowing date could make full use of climate resources to improve rice yield and light and heat resource utilization indexes, which is of great significance for agricultural cleaner production in the future.

Suggested Citation

  • Ennan Zheng & Mengting Qin & Peng Chen & Tianyu Xu & Zhongxue Zhang, 2022. "Climate Change Affects the Utilization of Light and Heat Resources in Paddy Field on the Songnen Plain, China," Agriculture, MDPI, vol. 12(10), pages 1-19, October.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:10:p:1648-:d:937085
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/12/10/1648/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/12/10/1648/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kadiyala, M.D.M. & Jones, J.W. & Mylavarapu, R.S. & Li, Y.C. & Reddy, M.D., 2015. "Identifying irrigation and nitrogen best management practices for aerobic rice–maize cropping system for semi-arid tropics using CERES-rice and maize models," Agricultural Water Management, Elsevier, vol. 149(C), pages 23-32.
    2. Zhenling Cui & Hongyan Zhang & Xinping Chen & Chaochun Zhang & Wenqi Ma & Chengdong Huang & Weifeng Zhang & Guohua Mi & Yuxin Miao & Xiaolin Li & Qiang Gao & Jianchang Yang & Zhaohui Wang & Youliang Y, 2018. "Pursuing sustainable productivity with millions of smallholder farmers," Nature, Nature, vol. 555(7696), pages 363-366, March.
    3. Kang, Xiaoyu & Qi, Junyu & Li, Sheng & Meng, Fan-Rui, 2022. "A watershed-scale assessment of climate change impacts on crop yields in Atlantic Canada," Agricultural Water Management, Elsevier, vol. 269(C).
    4. Gao, Mingyun & Yang, Honglin & Xiao, Qinzi & Goh, Mark, 2022. "A novel method for carbon emission forecasting based on Gompertz's law and fractional grey model: Evidence from American industrial sector," Renewable Energy, Elsevier, vol. 181(C), pages 803-819.
    5. Huang, Mingxia & Wang, Jing & Wang, Bin & Liu, De Li & Feng, Puyu & Yu, Qiang & Pan, Xuebiao & Li, Siyi & Jiang, Tengcong, 2022. "Dominant sources of uncertainty in simulating maize adaptation under future climate scenarios in China," Agricultural Systems, Elsevier, vol. 199(C).
    6. Bin Wang & De Li Liu & Ian Macadam & Lisa V. Alexander & Gab Abramowitz & Qiang Yu, 2016. "Multi-model ensemble projections of future extreme temperature change using a statistical downscaling method in south eastern Australia," Climatic Change, Springer, vol. 138(1), pages 85-98, September.
    7. Barrios, Salvador & Ouattara, Bazoumana & Strobl, Eric, 2008. "The impact of climatic change on agricultural production: Is it different for Africa?," Food Policy, Elsevier, vol. 33(4), pages 287-298, August.
    8. Tan, Lili & Feng, Puyu & Li, Baoguo & Huang, Feng & Liu, De Li & Ren, Pinpin & Liu, Haipeng & Srinivasan, Raghavan & Chen, Yong, 2022. "Climate change impacts on crop water productivity and net groundwater use under a double-cropping system with intensive irrigation in the Haihe River Basin, China," Agricultural Water Management, Elsevier, vol. 266(C).
    9. Funes, I. & Savé, R. & de Herralde, F. & Biel, C. & Pla, E. & Pascual, D. & Zabalza, J. & Cantos, G. & Borràs, G. & Vayreda, J. & Aranda, X., 2021. "Modeling impacts of climate change on the water needs and growing cycle of crops in three Mediterranean basins," Agricultural Water Management, Elsevier, vol. 249(C).
    10. De Liu & Heping Zuo, 2012. "Statistical downscaling of daily climate variables for climate change impact assessment over New South Wales, Australia," Climatic Change, Springer, vol. 115(3), pages 629-666, December.
    11. Ding, Yimin & Wang, Weiguang & Zhuang, Qianlai & Luo, Yufeng, 2020. "Adaptation of paddy rice in China to climate change: The effects of shifting sowing date on yield and irrigation water requirement," Agricultural Water Management, Elsevier, vol. 228(C).
    12. Wang, Weiguang & Yu, Zhongbo & Zhang, Wei & Shao, Quanxi & Zhang, Yiwei & Luo, Yufeng & Jiao, Xiyun & Xu, Junzeng, 2014. "Responses of rice yield, irrigation water requirement and water use efficiency to climate change in China: Historical simulation and future projections," Agricultural Water Management, Elsevier, vol. 146(C), pages 249-261.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dengpan Xiao & Wenjiao Shi, 2023. "Modeling the Adaptation of Agricultural Production to Climate Change," Agriculture, MDPI, vol. 13(2), pages 1-4, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kaiwen Chen & Shuang’en Yu & Tao Ma & Jihui Ding & Pingru He & Yao Li & Yan Dai & Guangquan Zeng, 2022. "Modeling the Water and Nitrogen Management Practices in Paddy Fields with HYDRUS-1D," Agriculture, MDPI, vol. 12(7), pages 1-18, June.
    2. Pengtao Wang & Xupu Li & Liwei Zhang & Zhuangzhuang Wang & Jiangtao Bai & Yongyong Song & Hongzhu Han & Ting Zhao & Guan Huang & Junping Yan, 2023. "Spatiotemporal Variations of Production–Living–Ecological Space under Various, Changing Climate and Land Use Scenarios in the Upper Reaches of Hanjiang River Basin, China," Land, MDPI, vol. 12(9), pages 1-21, September.
    3. Zhang, Qingsong & Sun, Jiahao & Zhang, Guangxin & Liu, Xuemei & Wu, Yanfeng & Sun, Jingxuan & Hu, Boting, 2023. "Spatiotemporal dynamics of water supply–demand patterns under large-scale paddy expansion: Implications for regional sustainable water resource management," Agricultural Water Management, Elsevier, vol. 285(C).
    4. Zhang, Ziya & Li, Yi & Chen, Xinguo & Wang, Yanzi & Niu, Ben & Liu, De Li & He, Jianqiang & Pulatov, Bakhtiyor & Hassan, Ishtiaq & Meng, Qingtao, 2023. "Impact of climate change and planting date shifts on growth and yields of double cropping rice in southeastern China in future," Agricultural Systems, Elsevier, vol. 205(C).
    5. Kim, Dong-Hyeon & Jang, Taeil & Hwang, Syewoon & Jeong, Hanseok, 2021. "Paddy rice adaptation strategies to climate change: Transplanting date shift and BMP applications," Agricultural Water Management, Elsevier, vol. 252(C).
    6. Zhang, He & Tao, Fulu & Zhou, Guangsheng, 2019. "Potential yields, yield gaps, and optimal agronomic management practices for rice production systems in different regions of China," Agricultural Systems, Elsevier, vol. 171(C), pages 100-112.
    7. Wang, Bin & Feng, Puyu & Chen, Chao & Liu, De Li & Waters, Cathy & Yu, Qiang, 2019. "Designing wheat ideotypes to cope with future changing climate in South-Eastern Australia," Agricultural Systems, Elsevier, vol. 170(C), pages 9-18.
    8. Dengpan Xiao & Huizi Bai & De Li Liu, 2018. "Impact of Future Climate Change on Wheat Production: A Simulated Case for China’s Wheat System," Sustainability, MDPI, vol. 10(4), pages 1-15, April.
    9. Bin Wang & De Li Liu & Cathy Waters & Qiang Yu, 2018. "Quantifying sources of uncertainty in projected wheat yield changes under climate change in eastern Australia," Climatic Change, Springer, vol. 151(2), pages 259-273, November.
    10. Ding, Yimin & Wang, Weiguang & Song, Ruiming & Shao, Quanxi & Jiao, Xiyun & Xing, Wanqiu, 2017. "Modeling spatial and temporal variability of the impact of climate change on rice irrigation water requirements in the middle and lower reaches of the Yangtze River, China," Agricultural Water Management, Elsevier, vol. 193(C), pages 89-101.
    11. Wang, Haidong & Cheng, Minghui & Liao, Zhenqi & Guo, Jinjin & Zhang, Fucang & Fan, Junliang & Feng, Hao & Yang, Qiliang & Wu, Lifeng & Wang, Xiukang, 2023. "Performance evaluation of AquaCrop and DSSAT-SUBSTOR-Potato models in simulating potato growth, yield and water productivity under various drip fertigation regimes," Agricultural Water Management, Elsevier, vol. 276(C).
    12. Wen-Ze Wu & Chong Liu & Wanli Xie & Mark Goh & Tao Zhang, 2023. "Predictive analysis of the industrial water-waste-energy system using an optimised grey approach: A case study in China," Energy & Environment, , vol. 34(5), pages 1639-1656, August.
    13. De Li Liu & Garry J. O’Leary & Brendan Christy & Ian Macadam & Bin Wang & Muhuddin R. Anwar & Anna Weeks, 2017. "Effects of different climate downscaling methods on the assessment of climate change impacts on wheat cropping systems," Climatic Change, Springer, vol. 144(4), pages 687-701, October.
    14. Lu, Jie & Bai, Zhaohai & Velthof, Gerard L. & Wu, Zhiguo & Chadwick, David & Ma, Lin, 2019. "Accumulation and leaching of nitrate in soils in wheat-maize production in China," Agricultural Water Management, Elsevier, vol. 212(C), pages 407-415.
    15. Yu, Yanan & He, Yong & Zhao, Xuan, 2021. "Impact of demand information sharing on organic farming adoption: An evolutionary game approach," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    16. Ahmed, Moiz Uddin & Hussain, Iqbal, 2022. "Prediction of Wheat Production Using Machine Learning Algorithms in northern areas of Pakistan," Telecommunications Policy, Elsevier, vol. 46(6).
    17. Feng Huang & Baoguo Li, 2020. "What is the Redline Water Withdrawal for Crop Production in China?—Projection to 2030 Derived from the Past Twenty-Year Trajectory," Sustainability, MDPI, vol. 12(10), pages 1-14, May.
    18. Laura Barasa & Bethuel K. Kinuthia & Abdelkrim Araar & Stephene Maende & Faith Mariera, 2023. "Nonfarm entrepreneurship, crop output, and household welfare in Tanzania: An exploration of transmission channels," Agribusiness, John Wiley & Sons, Ltd., vol. 39(3), pages 762-792, July.
    19. Xuejia Sang & Xiaopeng Leng & Linfu Xue & Xiangjin Ran, 2022. "Based on the Time-Spatial Power-Based Cryptocurrency Miner Driving Force Model, Establish a Global CO 2 Emission Prediction Framework after China Bans Cryptocurrency," Sustainability, MDPI, vol. 14(9), pages 1-18, April.
    20. Fan, Yubing & McCann, Laura M., 2017. "Farmers’ Adoption of Pressure Irrigation Systems and Scientific Scheduling Practices: An Application of Multilevel Models," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258458, Agricultural and Applied Economics Association.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:12:y:2022:i:10:p:1648-:d:937085. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.