Personal Water Footprint in Taiwan: A Case Study of Yunlin County

Abstract

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.

Water–Energy Nexus for Multi-Criteria Decision Making in Water Resource Management: A Case Study of Choshui River Basin in Taiwan

“…Industrial development in the township had little influence on the individual use of water. Therefore, attention on water conservation in the region was suggested to be paid to the reuse and recycling of industrial wastewater [17].…”

“…The high water demand in this area resulted in water-related difficulties such as water shortage and land subsidence from improper use of groundwater. Lee et al examined personal water footprint in Yunlin County and revealed that the footprint was the highest in coastal areas, mainly due to the location quotients of industries (primary, secondary, or tertiary industry) [17]. In fact, the industries also suffered from serious water shortage, especially in the dry seasons when the water rights of public and agricultural uses were prioritized over industrial uses [9].…”

Soft Drink Supply Chain Sustainability: A Case Based Approach to Identify and Explain Best Practices and Key Performance Indicators

“…Beverage industry's standards specify that water treated with intent for reuse must be at least the same quality as mains water [18,53]. The principle recurring activities in water treatment are shown in Table 4 [54][55][56][57][58]. Table 4.…”

Integrating Ecosystem Services and Eco-Security to Assess Sustainable Development in Liuqiu Island

“…Due to the fact that it is relatively easy to both understand and calculate, EF has become a quantitative indicator that is now widely utilized in the field of ecological economics. A number of studies conducted in Taiwan have investigated the EF model in terms of its basic concepts, theoretical hypotheses, assessment methods, deficiencies, and empirical applications [48][49][50], in addition to developing a number of EF-related theories and estimation methods. Relatedly, Lee and Peng conducted a study in 2014 [51] in which they expanded upon earlier research in order to analyze Taiwan's EF from 2008 to 2011.…”