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Analysis of crop water requirements and irrigation demands for rice: Implications for increasing effective rainfall

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  • Luo, Wanqi
  • Chen, Mengting
  • Kang, Yinhong
  • Li, Wenping
  • Li, Dan
  • Cui, Yuanlai
  • Khan, Shahbaz
  • Luo, Yufeng

Abstract

Determining the irrigation demands of rice in a humid region is essential for water conservation through improving rainfall utilization in southern China. In this paper, six representative rice areas in southern China were selected, and the daily reference evapotranspiration (ETo) of the representative stations during 1953–2017 was calculated using the Penman-Monteith method. The daily crop evapotranspiration (ETc) was computed using the single crop coefficient method, and the irrigation scheduling under flood irrigation (FI) was obtained by establishing a field water balance model. The characteristics and trends of the irrigation demand of early, middle and late rice, as well as the irrigation changes under a “double-to-single” cropping pattern, were also analyzed with advanced statistical tests. The results indicated that most of the abundant rainfall was concentrated in the growth period of early rice in southern China. Early rice required less water (135.0 mm) and even no irrigation in some wet years, while middle and late rice required more irrigation water (288.1 mm and 265.2 mm, respectively). The key reasons for the differences in irrigation demand among the three rice types are the amount and distribution characteristics of rainfall during the rice growth period. In addition, the irrigation demands of rice showed a downward trend as a response to a decrease in ETc and the increase in rainfall in the past 60 years, where rainfall was the dominant factor. With this increasing trend of rainfall and its better and efficient utilization in the future, rice irrigation demands may be further reduced or completely stopped. Under the “double-to-single” cropping pattern, irrigation demand decreased by 16% on average, and the irrigation frequency, as well as the drainage volume burden, were simultaneously reduced.

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  • Luo, Wanqi & Chen, Mengting & Kang, Yinhong & Li, Wenping & Li, Dan & Cui, Yuanlai & Khan, Shahbaz & Luo, Yufeng, 2022. "Analysis of crop water requirements and irrigation demands for rice: Implications for increasing effective rainfall," Agricultural Water Management, Elsevier, vol. 260(C).
    • Handle: RePEc:eee:agiwat:v:260:y:2022:i:c:s037837742100562x
    DOI: 10.1016/j.agwat.2021.107285
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    7. Liu, Yanqi & Lin, Yifan & Huo, Zailin & Zhang, Chenglong & Wang, Chaozi & Xue, Jingyuan & Huang, Guanhua, 2022. "Spatio-temporal variation of irrigation water requirements for wheat and maize in the Yellow River Basin, China, 1974–2017," Agricultural Water Management, Elsevier, vol. 262(C).
    8. Jiaxin Sun & Liwen Chen & Peng Qi & Guangxin Zhang, 2024. "Agricultural Irrigation Water Requirement and Its Response to Climatic Factors Based on Remote Sensing and Single Crop Coefficient Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(13), pages 5215-5233, October.
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    10. Yin, Jieling & Wu, Nan & Engel, Bernie A. & Hua, En & Zhang, Fuyao & Li, Xin & Wang, Yubao, 2022. "Multi-dimensional evaluation of water footprint and implication for crop production: A case study in Hetao Irrigation District, China," Agricultural Water Management, Elsevier, vol. 267(C).
    11. Phon Sheng Hou & Lokman Mohd Fadzil & Selvakumar Manickam & Mahmood A. Al-Shareeda, 2023. "Vector Autoregression Model-Based Forecasting of Reference Evapotranspiration in Malaysia," Sustainability, MDPI, vol. 15(4), pages 1-18, February.
    12. Wu, Yinshan & Jiang, Jie & Zhang, Xiufeng & Zhang, Jiayi & Cao, Qiang & Tian, Yongchao & Zhu, Yan & Cao, Weixing & Liu, Xiaojun, 2023. "Combining machine learning algorithm and multi-temporal temperature indices to estimate the water status of rice," Agricultural Water Management, Elsevier, vol. 289(C).

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