Climate risk analysis of low-altitude tea gardens in central Taiwan using a Bayesian network.

ABSTRACT

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.