Department of Soil and Water Conservation, National Chung Hsing University, Taichung, Taiwan.
Department of Agronomy, National Chung Hsing University, Taichung, Taiwan.
Environ Monit Assess. 2024 Aug 13;196(9):809. doi: 10.1007/s10661-024-12970-y.
Tea is a vital agricultural product in Taiwan. Due to global warming, the increasing extreme weather events have disrupted tea garden conditions and caused economic losses in agriculture. To address these challenges, a comprehensive tea garden risk assessment model, a Bayesian network (BN), was developed by considering various factors, including meteorological data, disaster events, tea garden environment (location, altitude, tea tree age, and soil characteristics), farming practices, and farmer interviews, and constructed risk assessment indicators for tea gardens based on the climate change risk analysis concept from the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5). The results demonstrated an accuracy of over 92% in both validating and testing the model for tea tree damage and yield reduction. Sensitivity analysis revealed that tea tree damage and yield reduction were mutually influential, with weather, fertilization, and irrigation also impacting tea garden risk. Risk analysis under climate change scenarios from various global climate models (GCMs) indicated that droughts may pose the highest risk with up to 41% and 40% of serious tea tree growth damage and tea yield reduction, respectively, followed by cold events that most tea gardens may have less than 20% chances of serious impacts on tea tree growth and tea yield reduction. The impacts of heavy rains get the least concern because all five tea gardens may not be affected in terms of tea tree growth and tea yield with large chances of 67 to 85%. Comparing farming methods, natural farming showed lower disaster risk than conventional and organic approaches. The tea plantation risk assessment model can serve as a valuable resource for analyzing and offering recommendations for tea garden disaster management and is used to assess the impact of meteorological disasters on tea plantations in the future.
茶是台湾重要的农产品。由于全球暖化，极端气候事件增加，打乱茶园环境条件，造成农业经济损失。为因应此一挑战，本研究以贝氏网络（Bayesian network, BN）建构茶园风险评估模式，整合气象资料、灾害事件、茶园环境（位置、海拔、茶树龄、土壤特性）、农事操作及茶农访谈等各项因子，依据政府间气候变化专门委员会第五次评估报告（Intergovernmental Panel on Climate Change Fifth Assessment Report, IPCC AR5）之气候变迁风险分析概念，建构茶园风险评估指标。茶树受害及减产评估模式验证与测试结果，茶树受害准确率达 92%以上，减产准确率达 85%以上。敏感度分析结果显示，茶树受害与减产相互影响，且天气、施肥、灌溉等农事操作亦会影响茶园风险。不同全球气候模式（global climate model, GCM）之气候变迁情境风险分析显示，干旱可能是最大风险，茶树严重受害及减产风险分别高达 41%及 40%，其次为寒害，各茶园茶树严重受害及减产风险均低于 20%。暴雨冲击风险最小，各茶园茶树生长及减产风险均无严重冲击的机率高达 67-85%。比较不同农事操作方式，自然农法茶园的灾害风险较低于传统及有机农法茶园。本茶园风险评估模式可作为茶园灾害管理之分析与建议的参考依据，以评估未来气象灾害对茶园之冲击。
