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Article

Prediction of Drought Thresholds Triggering Winter Wheat Yield Losses in the Future Based on the CNN-LSTM Model and Copula Theory: A Case Study of Henan Province

1
School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
2
Henan Key Laboratory of Water Pollution Control and Rehabilitation Technology, Henan University of Urban Construction, Pingdingshan 467036, China
3
Zhengzhou Nongren Irrigation Technology Company Ltd., Zhengzhou 450045, China
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(4), 954; https://doi.org/10.3390/agronomy15040954
Submission received: 9 March 2025 / Revised: 9 April 2025 / Accepted: 11 April 2025 / Published: 14 April 2025
(This article belongs to the Section Water Use and Irrigation)

Abstract

As global warming progresses, quantifying drought thresholds for crop yield losses is crucial for food security and sustainable agriculture. Based on the CNN-LSTM model and Copula function, this study constructs a conditional probability framework for yield losses under future climate change. It analyzes the relationship between the Standardized Precipitation–Evapotranspiration Index (SPEI) and winter wheat yield, assesses the vulnerability of winter wheat in various regions to drought stress, and quantifies the drought thresholds under climate change. The results showed that (1) SPEI in Zhoukou, Sanmenxia, and Nanyang was significantly correlated with yield; (2) the drought vulnerability of southern and eastern was higher than that of center, western, and northern in the past (2000–2023) and future (2024–2047); (3) there were significant differences in drought thresholds. The yield loss of winter wheat below 30, 50, and 70 percentiles in southern and eastern (past/future) were −1.86/−2.47, −0.85/−1.39, and 0.60/0.35 (Xinyang); −1.45/−2.16, −0.75/−1.34, −0.17/−0.43 (Nanyang); −1.47/−2.24, −0.97/−1.61, 0.69/0.28 (Zhoukou); −2.18/−2.86, −1.80/−2.36, −0.75/−1.08 (Kaifeng), indicating that the drought threshold will reduce in the future. This is mainly due to the different climate and soil conditions in different regions of Henan Province. In the context of future climate change, droughts will be more frequent. Hence, the research results provide a valuable reference for the efficient utilization of agricultural water resources and the prevention and control of drought risk under climate change in the future.
Keywords: CNN-LSTM deep learning model; joint distribution; yield loss of winter wheat; conditional probability; future climate change; drought threshold CNN-LSTM deep learning model; joint distribution; yield loss of winter wheat; conditional probability; future climate change; drought threshold

Share and Cite

MDPI and ACS Style

Ma, J.; Zhao, Y.; Cui, B.; Liu, L.; Ding, Y.; Chen, Y.; Zhang, X. Prediction of Drought Thresholds Triggering Winter Wheat Yield Losses in the Future Based on the CNN-LSTM Model and Copula Theory: A Case Study of Henan Province. Agronomy 2025, 15, 954. https://doi.org/10.3390/agronomy15040954

AMA Style

Ma J, Zhao Y, Cui B, Liu L, Ding Y, Chen Y, Zhang X. Prediction of Drought Thresholds Triggering Winter Wheat Yield Losses in the Future Based on the CNN-LSTM Model and Copula Theory: A Case Study of Henan Province. Agronomy. 2025; 15(4):954. https://doi.org/10.3390/agronomy15040954

Chicago/Turabian Style

Ma, Jianqin, Yan Zhao, Bifeng Cui, Lei Liu, Yu Ding, Yijian Chen, and Xinxi Zhang. 2025. "Prediction of Drought Thresholds Triggering Winter Wheat Yield Losses in the Future Based on the CNN-LSTM Model and Copula Theory: A Case Study of Henan Province" Agronomy 15, no. 4: 954. https://doi.org/10.3390/agronomy15040954

APA Style

Ma, J., Zhao, Y., Cui, B., Liu, L., Ding, Y., Chen, Y., & Zhang, X. (2025). Prediction of Drought Thresholds Triggering Winter Wheat Yield Losses in the Future Based on the CNN-LSTM Model and Copula Theory: A Case Study of Henan Province. Agronomy, 15(4), 954. https://doi.org/10.3390/agronomy15040954

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