Spatiotemporal optimization of irrigation practices for winter wheat in China: Rationale, implications, and solutions
In recent years, the increasing frequency and intensity of drought events have posed significant challenges to wheat production in China, making irrigation a crucial measure to mitigate associated yield losses. However, the escalating issues of water scarcity and groundwater depletion necessitate th...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | Agricultural Water Management |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0378377425000113 |
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| author | Luchen Zhang Yuan Cao Weihao Qian Junning Tian Shengshi Huang Xiaolei Qiu Bing Liu Liang Tang Liujun Xiao Weixing Cao Yan Zhu Leilei Liu |
| author_facet | Luchen Zhang Yuan Cao Weihao Qian Junning Tian Shengshi Huang Xiaolei Qiu Bing Liu Liang Tang Liujun Xiao Weixing Cao Yan Zhu Leilei Liu |
| author_sort | Luchen Zhang |
| collection | DOAJ |
| description | In recent years, the increasing frequency and intensity of drought events have posed significant challenges to wheat production in China, making irrigation a crucial measure to mitigate associated yield losses. However, the escalating issues of water scarcity and groundwater depletion necessitate the development of strategies to reduce water use while sustaining crop production. In this study, the Crop Water Deficit Index (CWDI) and Moisture Index (MI) were employed to assess the drought stress and its impact on yield within the main winter wheat production region of China. Subsequently, a multi-model ensemble approach integrated with a multi-objective optimization algorithm was utilized to propose the optimized irrigation strategies, which could enhance water use efficiency while attaining high yields. The results showed a continuous increase in drought stress over the past four decades, with the North Subregion (NS) and Huang-Huai Subregion (HHS) experienced more severe drought stress, while drought stress in the Middle-Lower Reaches of Yangzi River Subregion (MYS) increased the most. Drought stress was most severe during the jointing to heading period; furthermore, the greatest increase in drought stress was also observed during this period. Over the past four decades, due to the intensification of drought stress, winter wheat yield in China has been declining at a rate of 0.36 % per year. Compared to the irrigation practices of farmers, the optimal irrigation practices not only increased the wheat yield, water use efficiency (WUE), and irrigation water use efficiency (IWUE) by 468–5034 kg·ha−1, 1–13 kg·ha−1·mm−1, and 1–30 kg·ha−1·mm−1, respectively, but also reduced the irrigation amount and frequency by 4–118 mm and 0–2 times, respectively. The findings offer a method for quantitatively predicting and warning of the impacts of drought stress, and meanwhile support the formulation of irrigation strategies that maximize crop yield and water use efficiency and reducing water consumption in China. |
| format | Article |
| id | doaj-art-2102f486878346c0a3ad8f0c32891f51 |
| institution | Kabale University |
| issn | 1873-2283 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Agricultural Water Management |
| spelling | doaj-art-2102f486878346c0a3ad8f0c32891f512025-01-25T04:10:51ZengElsevierAgricultural Water Management1873-22832025-03-01308109297Spatiotemporal optimization of irrigation practices for winter wheat in China: Rationale, implications, and solutionsLuchen Zhang0Yuan Cao1Weihao Qian2Junning Tian3Shengshi Huang4Xiaolei Qiu5Bing Liu6Liang Tang7Liujun Xiao8Weixing Cao9Yan Zhu10Leilei Liu11National Engineering and Technology Center for Information Agriculture, Engineering Research Center of Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, ChinaNational Engineering and Technology Center for Information Agriculture, Engineering Research Center of Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, ChinaNational Engineering and Technology Center for Information Agriculture, Engineering Research Center of Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, ChinaNational Engineering and Technology Center for Information Agriculture, Engineering Research Center of Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, ChinaNational Engineering and Technology Center for Information Agriculture, Engineering Research Center of Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, ChinaNational Engineering and Technology Center for Information Agriculture, Engineering Research Center of Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, ChinaNational Engineering and Technology Center for Information Agriculture, Engineering Research Center of Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, ChinaNational Engineering and Technology Center for Information Agriculture, Engineering Research Center of Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, ChinaNational Engineering and Technology Center for Information Agriculture, Engineering Research Center of Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, ChinaNational Engineering and Technology Center for Information Agriculture, Engineering Research Center of Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, ChinaCorresponding authors.; National Engineering and Technology Center for Information Agriculture, Engineering Research Center of Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, ChinaCorresponding authors.; National Engineering and Technology Center for Information Agriculture, Engineering Research Center of Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, ChinaIn recent years, the increasing frequency and intensity of drought events have posed significant challenges to wheat production in China, making irrigation a crucial measure to mitigate associated yield losses. However, the escalating issues of water scarcity and groundwater depletion necessitate the development of strategies to reduce water use while sustaining crop production. In this study, the Crop Water Deficit Index (CWDI) and Moisture Index (MI) were employed to assess the drought stress and its impact on yield within the main winter wheat production region of China. Subsequently, a multi-model ensemble approach integrated with a multi-objective optimization algorithm was utilized to propose the optimized irrigation strategies, which could enhance water use efficiency while attaining high yields. The results showed a continuous increase in drought stress over the past four decades, with the North Subregion (NS) and Huang-Huai Subregion (HHS) experienced more severe drought stress, while drought stress in the Middle-Lower Reaches of Yangzi River Subregion (MYS) increased the most. Drought stress was most severe during the jointing to heading period; furthermore, the greatest increase in drought stress was also observed during this period. Over the past four decades, due to the intensification of drought stress, winter wheat yield in China has been declining at a rate of 0.36 % per year. Compared to the irrigation practices of farmers, the optimal irrigation practices not only increased the wheat yield, water use efficiency (WUE), and irrigation water use efficiency (IWUE) by 468–5034 kg·ha−1, 1–13 kg·ha−1·mm−1, and 1–30 kg·ha−1·mm−1, respectively, but also reduced the irrigation amount and frequency by 4–118 mm and 0–2 times, respectively. The findings offer a method for quantitatively predicting and warning of the impacts of drought stress, and meanwhile support the formulation of irrigation strategies that maximize crop yield and water use efficiency and reducing water consumption in China.http://www.sciencedirect.com/science/article/pii/S0378377425000113Drought stressIrrigationYieldWater use efficiencyMulti-modelWheat |
| spellingShingle | Luchen Zhang Yuan Cao Weihao Qian Junning Tian Shengshi Huang Xiaolei Qiu Bing Liu Liang Tang Liujun Xiao Weixing Cao Yan Zhu Leilei Liu Spatiotemporal optimization of irrigation practices for winter wheat in China: Rationale, implications, and solutions Agricultural Water Management Drought stress Irrigation Yield Water use efficiency Multi-model Wheat |
| title | Spatiotemporal optimization of irrigation practices for winter wheat in China: Rationale, implications, and solutions |
| title_full | Spatiotemporal optimization of irrigation practices for winter wheat in China: Rationale, implications, and solutions |
| title_fullStr | Spatiotemporal optimization of irrigation practices for winter wheat in China: Rationale, implications, and solutions |
| title_full_unstemmed | Spatiotemporal optimization of irrigation practices for winter wheat in China: Rationale, implications, and solutions |
| title_short | Spatiotemporal optimization of irrigation practices for winter wheat in China: Rationale, implications, and solutions |
| title_sort | spatiotemporal optimization of irrigation practices for winter wheat in china rationale implications and solutions |
| topic | Drought stress Irrigation Yield Water use efficiency Multi-model Wheat |
| url | http://www.sciencedirect.com/science/article/pii/S0378377425000113 |
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