Framework Construction and Dynamic Characteristics of Spring Low-Temperature Disasters Affecting Winter Wheat in the Huang-Huai-Hai Region, China
The accurate and sub-daily identification of agricultural low-temperature disasters (LTDs) facilitates the understanding of their dynamic evolution, the evaluation of the characteristics of disaster events, and informs effective strategies aimed at disaster prevention and mitigation. In order to ens...
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MDPI AG
2024-12-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/14/12/2898 |
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| author | Meixuan Li Zhiguo Huo Qianchuan Mi Lei Zhang Yi Wang Rui Kong Mengyuan Jiang Fengyin Zhang |
| author_facet | Meixuan Li Zhiguo Huo Qianchuan Mi Lei Zhang Yi Wang Rui Kong Mengyuan Jiang Fengyin Zhang |
| author_sort | Meixuan Li |
| collection | DOAJ |
| description | The accurate and sub-daily identification of agricultural low-temperature disasters (LTDs) facilitates the understanding of their dynamic evolution, the evaluation of the characteristics of disaster events, and informs effective strategies aimed at disaster prevention and mitigation. In order to ensure the timely, precise, and comprehensive capture of disaster processes, we have developed a dynamic evaluation framework for winter wheat spring LTD in the Huang-Huai-Hai (HHH) region, driven by meteorological data. This framework consists of two primary components: a disaster classification module and a dynamic simulation-assessment module. Through disaster mechanisms and comprehensive statistical analysis, we have established the input features and structural framework of the classification module using a decision tree algorithm. The dynamic simulation evaluation module is based on our newly developed index for the cumulative hourly intensity of low-temperature stress (CHI) and its grade indicators. This index integrates the interaction between cold stress (low-temperature intensity, cooling amplitude, and duration) and mitigating conditions (air humidity) during the evolution process of LTD. Based on CHI, we found that as the intensity of low temperatures and the amplitude of cooling rise, along with an extended duration of stress and a reduction in relative humidity, the severity of spring LTDs in winter wheat get worse. The overall validation accuracy of the evaluation framework is 92.6%. High validation accuracy indicates that our newly established framework demonstrates significant efficacy in identifying LTDs and assessing grade. Through the analysis of the characteristics of the disaster process, spring LTDs affecting winter wheat are mainly mild, with frost identified as the primary category of LTD. The duration of freeze injury typically exceeds 24 h, while the duration of frost damage and cold damage is less than 24 h. From 1980 to 2022 in the HHH region, the frequency of spring freeze injury and frost damage on winter wheat showed an overall decreasing trend, with a particularly significant decrease in frost damage occurrences. Conversely, cold damage occurrences are on the rise. In addition, the duration of individual disaster events for the three categories of spring LTDs is decreasing, while both the average intensity and extremity of these events show increasing trends. This study has important practical value for the sub-daily scale evaluation of the spring LTD affecting winter wheat in the HHH region and serves as an effective guide for agricultural disaster prevention and mitigation, as well as for the formulation of planting strategies. |
| format | Article |
| id | doaj-art-7be5950861b64667bcf0cf55b65f6eca |
| institution | DOAJ |
| issn | 2073-4395 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
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| series | Agronomy |
| spelling | doaj-art-7be5950861b64667bcf0cf55b65f6eca2025-08-20T02:56:05ZengMDPI AGAgronomy2073-43952024-12-011412289810.3390/agronomy14122898Framework Construction and Dynamic Characteristics of Spring Low-Temperature Disasters Affecting Winter Wheat in the Huang-Huai-Hai Region, ChinaMeixuan Li0Zhiguo Huo1Qianchuan Mi2Lei Zhang3Yi Wang4Rui Kong5Mengyuan Jiang6Fengyin Zhang7State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, ChinaState Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, ChinaState Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, ChinaNational Meteorological Center, Beijing 100081, ChinaState Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, ChinaState Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, ChinaState Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, ChinaState Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, ChinaThe accurate and sub-daily identification of agricultural low-temperature disasters (LTDs) facilitates the understanding of their dynamic evolution, the evaluation of the characteristics of disaster events, and informs effective strategies aimed at disaster prevention and mitigation. In order to ensure the timely, precise, and comprehensive capture of disaster processes, we have developed a dynamic evaluation framework for winter wheat spring LTD in the Huang-Huai-Hai (HHH) region, driven by meteorological data. This framework consists of two primary components: a disaster classification module and a dynamic simulation-assessment module. Through disaster mechanisms and comprehensive statistical analysis, we have established the input features and structural framework of the classification module using a decision tree algorithm. The dynamic simulation evaluation module is based on our newly developed index for the cumulative hourly intensity of low-temperature stress (CHI) and its grade indicators. This index integrates the interaction between cold stress (low-temperature intensity, cooling amplitude, and duration) and mitigating conditions (air humidity) during the evolution process of LTD. Based on CHI, we found that as the intensity of low temperatures and the amplitude of cooling rise, along with an extended duration of stress and a reduction in relative humidity, the severity of spring LTDs in winter wheat get worse. The overall validation accuracy of the evaluation framework is 92.6%. High validation accuracy indicates that our newly established framework demonstrates significant efficacy in identifying LTDs and assessing grade. Through the analysis of the characteristics of the disaster process, spring LTDs affecting winter wheat are mainly mild, with frost identified as the primary category of LTD. The duration of freeze injury typically exceeds 24 h, while the duration of frost damage and cold damage is less than 24 h. From 1980 to 2022 in the HHH region, the frequency of spring freeze injury and frost damage on winter wheat showed an overall decreasing trend, with a particularly significant decrease in frost damage occurrences. Conversely, cold damage occurrences are on the rise. In addition, the duration of individual disaster events for the three categories of spring LTDs is decreasing, while both the average intensity and extremity of these events show increasing trends. This study has important practical value for the sub-daily scale evaluation of the spring LTD affecting winter wheat in the HHH region and serves as an effective guide for agricultural disaster prevention and mitigation, as well as for the formulation of planting strategies.https://www.mdpi.com/2073-4395/14/12/2898winter wheatlow-temperature disasterevaluation frameworkmachine learningspatial-temporal features |
| spellingShingle | Meixuan Li Zhiguo Huo Qianchuan Mi Lei Zhang Yi Wang Rui Kong Mengyuan Jiang Fengyin Zhang Framework Construction and Dynamic Characteristics of Spring Low-Temperature Disasters Affecting Winter Wheat in the Huang-Huai-Hai Region, China Agronomy winter wheat low-temperature disaster evaluation framework machine learning spatial-temporal features |
| title | Framework Construction and Dynamic Characteristics of Spring Low-Temperature Disasters Affecting Winter Wheat in the Huang-Huai-Hai Region, China |
| title_full | Framework Construction and Dynamic Characteristics of Spring Low-Temperature Disasters Affecting Winter Wheat in the Huang-Huai-Hai Region, China |
| title_fullStr | Framework Construction and Dynamic Characteristics of Spring Low-Temperature Disasters Affecting Winter Wheat in the Huang-Huai-Hai Region, China |
| title_full_unstemmed | Framework Construction and Dynamic Characteristics of Spring Low-Temperature Disasters Affecting Winter Wheat in the Huang-Huai-Hai Region, China |
| title_short | Framework Construction and Dynamic Characteristics of Spring Low-Temperature Disasters Affecting Winter Wheat in the Huang-Huai-Hai Region, China |
| title_sort | framework construction and dynamic characteristics of spring low temperature disasters affecting winter wheat in the huang huai hai region china |
| topic | winter wheat low-temperature disaster evaluation framework machine learning spatial-temporal features |
| url | https://www.mdpi.com/2073-4395/14/12/2898 |
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