农业气象灾害主要指标研究进展与展望

Advances and Prospects in Research on Agrometeorological Disaster Indices for Major Crops

摘要:

气候变化加剧极端天气事件发生的频率与强度,导致农业气象灾害对我国粮食安全构成严重威胁。灾害指标作为连接气象胁迫与农业响应的量化工具,在风险管理中居核心地位。本文围绕我国主要作物农业气象灾害指标的发展与应用,系统梳理了干旱、渍涝、高温热害、低温冷害与霜冻害,以及高温干旱、干热风、连阴雨和低温寡照等典型单一与复合灾害指标演进特征,并总结人工控制试验、统计模型和作物生长模型等主要指标构建方法及其适用性。结果表明,农业气象灾害指标总体经历了由单一气象阈值向多要素综合指数、由灾害环境表征向作物响应刻画、由单一灾害识别向复合灾害评估发展的过程。当前指标体系仍存在监测、预警与风险评估功能配置不均衡,动态演变过程表征能力不足,以及灾害指标与作物生理生态响应、产量和品质损失之间衔接不足等问题。未来需明确区分监测—预警—风险评估功能,构建基于作物敏感期的动态指标,并推动“遥感—作物模型—AI”多源融合,对提升农业气象服务水平和维护国家粮食供给稳定具有重要意义。

Abstract:

Climate change is increasing the frequency and intensity of extreme weather events, posing serious threats to food security in China through increasingly severe agrometeorological disasters. Disaster indicators, as quantitative tools linking meteorological stresses with agricultural responses, play a central role in disaster risk management. It focused on the development and application of agrometeorological disaster indicators for major crops in China, systematically summarized the evolution of indicators for typical single and compound disasters, including drought, waterlogging, heat stress, chilling injury and frost damage, as well as compound heat-drought events, dry-hot wind, persistent cloudy and rainy weather, and combined low-temperature and low-light stress. The major approaches for constructing disaster indicators, including controlled experiments, statistical models, and crop growth models, were also reviewed in terms of their applicability. The results showed that agrometeorological disaster indicators had generally evolved from single meteorological thresholds to multi-factor integrated indices, from characterization of hazardous environmental conditions to representation of crop responses, and from identification of individual hazards to assessment of compound disasters. However, current indicator systems still suffer from imbalanced functional development among monitoring, early warning, and risk assessment, insufficient capacity to characterize the dynamic evolution of disaster processes, and inadequate linkages between disaster indicators and crop physiological and ecological responses, yield losses, and quality deterioration. Future research should clearly distinguish the functions of monitoring, early warning, and risk assessment, develop dynamic indicators based on crop-sensitive growth stages, and promote multi-source integration of remote sensing, crop models, and artificial intelligence. These advances were of great significance for improving agrometeorological services and maintaining the stability of the national food supply.