期刊
AGRICULTURAL AND FOREST METEOROLOGY
卷 327, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.agrformet.2022.109205
关键词
Heterogeneous impact; Excessive wetness; Statistical maize yield; Process -based crop models; Climate change adaptation; Agricultural risk management
资金
- National Natural Science Foundation of China [42171075]
- State Key Laboratory of Earth Surface Processes and Resource Ecology of China [2022-ZD-06]
- Program of Introducing Talent to Universities (111 Project) [BP0820003]
Understanding the impacts of excessive wetness on maize yields is crucial for climate change adaptation and agricultural risk management. This study evaluated the effects of excessive wetness on maize yields in China, considering factors such as growing stage, regional climate, and management practices. The results showed that excessive wetness had a negative impact on maize yields, with the flowering-to-maturity stage being the most sensitive. Moreover, crop models tended to overestimate the positive response of maize yields to excessive wetness.
Understanding the impacts of climate extremes on crop yields is critical for climate change adaptation and agricultural risk management. Excessive wetness is known to cause substantial damage to maize yields, but the heterogeneous impacts on yields based on growing stage, regional climate, and management practices are not well researched; additionally, it is uncertain how well state-of-the-art process-based crop models reproduce those responses. This study evaluated the impacts of excessive wetness on statistical and crop-model-simulated maize yields in China, with a special focus on the differences among growing stages, mean climatology, and irrigation, fertilization regimes and soil properties. Statistical maize yields exhibited negative responses to excessive wetness, with yield damage of 6%. Maize yield was most sensitive to excessive wetness in the flowering-tomaturity stage. Maize yields in wetter or colder counties, or places with a greater proportion of irrigation, nitrogen application rates and soil organic carbon, tended to be affected more severely. Multiple crop model ensemble simulations tended to over optimistically report positive maize yield responses to excessive wetness. Research on heterogeneous impacts of excessive wetness on maize yields could benefit agricultural risk management and improve process-based models.
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