Issues that are associated with climate change have global importance. Most related studies take a national or regional perspective on the impact of climate change. Taiwan is constrained by its geographical conditions, which increase its vulnerability to climate change, especially in its western coastal areas. The county that is most affected by climate change is Yunlin. In 2013-2014, projects that were sponsored by Taiwan's government analyzed the relationship among synthesized vulnerability, ecological footprint (EF) and adaptation to climate change and proposed 15 categories of synthesized vulnerability and EF values. This study further examines the relationship between vulnerability and EF values and examines how residents of four townships-Linnei, Sihu, Mailiao, and Huwei-cope with the effects of climate change. This study investigates whether the residents of the four townships vary in their attitudes to climate change, their perceptions of disaster risk, and their behavioral intentions with respect to coping with climate change. The structural equation model (SEM) is used to examine the relationships among attitudes to climate change, perceptions of disaster risk, and the behavioral intentions of residents in townships with various vulnerabilities to climate change. The results that are obtained using the SEM reveal that climate change mitigation/adaptation behavior is affected by attitudes to climate change and perceptions of disaster risk. However, the effects of attitudes and perceptions on mitigation and adaptation that are mediated by place attachment are not statistically significant.
Extreme weather events have affected the environment and water resources in Taiwan for the last two decades. Heavy rainfall, typhoons, and rising sea levels have caused severe flooding along the Southwest Coast in Taiwan. Yunlin County, an important agricultural region, will be significantly affected by climate changes, especially in coastal areas with severe land subsidence. Therefore, using the concept of the water footprint and questionnaire surveys, this study examines personal water footprints in townships in Yunlin County to explore the effectiveness and sustainability of water management. The purpose of the water footprint concept is to quantify environmental burdens imposed by individuals' demand for water. An individual water footprint involves direct and indirect water usage that is associated with personal habits. Analytical results show that the most individual water consumption is highest along coastal areas, such as Kouhu and Taixi, and mountainous areas, such as Gukeng, Douliu, and Linnei. Furthermore, one-way ANOVA of individuals' daily water footprint reveals that individual water footprints vary significantly among Douliu, Gukeng, and Mailiao. The mean daily water footprint per capita in Douliu and Gukeng significantly exceeds that in Mailiao. This study considers the location quotients of industries in these three townships, which indicate that the location quotients of the accommodation and food and beverage industries in Douliu and Gukeng significantly exceed those of Mailiao. The individual virtual water use that is associated with the aforementioned industries is large. Clearly, individual water use habits in townships are related to the industry type. Douliu and Gukeng are major centers of the tertiary industry, which has a higher location quotient than in Mailiao. Mailiao is a major center of manufacturing as a secondary industry. Therefore, flourishing regions with tertiary industries have high virtual water consumption. These findings suggest that personal water use habits can explain why personal water footprints are larger in Yunlin County than in other counties in Taiwan.
The purpose of this study is to develop an integrated model, AgriHydro, and to operate with Climate Adaptation Algorithm (CAA) in order to form the pathway and to support decision-making. Therefore, the targets of this study are: 1. Develop AgriHydro with feedback mechanism (interdisciplinary). 2. Demonstrate how AgriHydro operate as a tool with CAA. 3. Show the potential future development of AgriHydro.
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