1. Introduction
Economic development and population increases in recent decades have caused the rapid increase of fresh water consumption, which may hinder societal development. Currently, approximately one-third of the world’s population is threatened by a lack of freshwater for fulfilling daily needs [
1]. Furthermore, increased water scarcity in numerous regions is expected in the future because of various factors such as population growth, pollution of existing resources, climate change, and urbanization. Nearly seven billion people worldwide are predicted to encounter a water crisis by the mid-21st century.
The average annual rainfall in Taiwan is 2467 mm, which is approximately 2.6 times the world average (which is 973 mm). In addition, Taiwanese people have experienced low prices and easy access to tap water; thus, a majority of Taiwanese people consider water an infinite natural resource and lack crisis awareness regarding water resources. However, because Taiwan is a country with limited living space, a dense population, steep mountains, concentrated rainfall, and fast-running rivers, the temporal and spatial distributions of rainfall in Taiwan are extremely uneven. This uneven distribution of rainfall increases the difficulty of preserving and using water resources. The annual rainfall per capita in Taiwan is 4074 m3, which is lower than one-fifth of the world average (21,796 m3). Based on the criteria for the amount of water available worldwide, the United Nations ranked Taiwan 18th among countries with the least water resources per capita.
Since 1960, Taiwan has transformed the labor-intensive light industries into technique-intensive high-technology and high value-added industries. After the occurrence of industrial transformation in Taiwan, the government established the Hsinchu Science Park (HSP) in 1980 to satisfy the development needs of high-technology industries. The HSP is the development base of high-technology industries, including the information, semiconductor, and foundry industries. Subsequently, the government established the Southern Taiwan Science Park (STSP) and Central Taiwan Science Park (CTSP) in 1995 and 2002, respectively. The three science parks occupy a total area of 4610 ha, forming the core area of high-technology industries in Taiwan. According to the statistics obtained by the Water Resources Agency (WRA) [
2]. Executive Yuan, Taiwan, the total revenue generated from the science parks in Taiwan in 2012 was NT$2.004132 trillion, and the HSP, CTSP, and STSP, respectively, accounted for 52.83%, 16.13%, and 31.03%. The total revenue of the science parks accounted for approximately one-seventh of the gross domestic product of Taiwan. The high production value, considerable amounts of investment, and breakthroughs in research and development contributed by the high-technology science parks have elevated the international position of Taiwan. Because of these achievements, advanced countries in Europe and North America dubbed the HSP as the Silicon Valley of Taiwan. However, as various high-technology enterprises in the science parks continue to expand their scales of production, the amount of water resources consumed increases considerably (e.g., water used during the manufacturing process, boiler water, and cooling water), thereby depleting water resources and deteriorating environmental quality, resulting in a substantial social cost [
3].
Under the wave of sustainable development, the international society began to develop tools or indicators that can evaluate sustainable development one by one. They want to reflect ecological environment really and reasonably, meanwhile analyzing resource consumption effectively and exploring the relationship among different kinds of environmental impact [
4]. Generally speaking, the current evaluation indicators or measurement models of sustainable development established or developed internationally or domestically have their own features. Most of them can manage to include various aspects of sustainable development factors of society, economy, ecology and environment [
5]. Among them, water scarcity has been studied by numerous researchers based on various indicators such as the Falkenmark indicator [
6], the physical and economical scarcity indicators [
7], the water poverty index [
8], and the water vulnerability index [
9]. However, collecting and disseminating meaningful water-related information is complex and difficult, because corporate water accounting methods are still under development and require further refinement [
10].
The impact of human consumption on global water resources can be mapped using water footprints. The concept of water footprints was proposed and defined as “…a measure of humans’ appropriation of freshwater resources” [
11]. Water footprints are indicators of water use in which both water consumption and pollution are incorporated; they can also be applied for broadening water resource evaluation systems and providing water utilization information for decision-making [
12,
13,
14,
15]. Several studies have focused on developing the concept of water footprints and quantifying the water footprints of a wide variety of products from a consumption perspective, on either global or national scales [
16,
17,
18,
19,
20].
Recently, several studies have used the input-output (IO) model, a top-down method, to quantify national or regional water footprints. Some of these studies have evaluated the water footprint of China [
21], especially in water deficient regions such as Zhangye City [
22] and the Haihe River basin [
23]. IO models have been used as an effective method for assessing the flow of resources and how environmental burdens are transferred in supply chains [
24]. Thus, the IO model accurately quantifies intersectoral virtual water flows, representing both direct and indirect water inputs during industrial production processes. Extensive research has been conducted on virtual water and water footprints in recent years. Many studies have focused on the microlevel, such as the virtual water content of products or the water footprint of consumers. For example, the virtual water content of products such as coffee, tea, rice, and meat [
16,
25], and the water footprint of industrial production processes [
20] have been explored. Other studies have focused on the macrolevel, such as the national water footprint or virtual water flow, and numerous case studies have been conducted in Spain, the United Kingdom, and China [
21,
26,
27]. Two widely accepted methods for assessing national water footprints are the bottom-up approach, which entails considering the sum of goods and services consumed by inhabitants multiplied by their virtual water content; and the top-down approach, which involves calculating the total use of domestic water resources, plus the imported virtual water flow, minus the exported virtual flow. Furthermore, grey water footprints, which refer to water used to dilute pollutants emitted during industrial production, are often ignored because of a lack of data; therefore, the effects of environmental pollution during industrial production are ignored.
Gerbens-Leenes
et al. [
28] evaluated the water footprint of each unit of bioenergy and compared the water footprints of bioenergy with those of fossil and renewable energies. Their results indicated that the water footprints of bioenergy were 70–400-fold higher than those of other energies. Thus, if bioenergy is used as an alternative energy for reducing the effects of fossil energy on climate change, a substantial influence would be exerted on the water resources. Van Oel and Hoekstra [
29] conducted an empirical study in the Netherlands by investigating the blue and green water footprints of paper products throughout the entire supply chain. The results revealed that according to the current paper recovery rate, the water footprints of printing and writing paper were estimated to be between 300 m
3/ton and 2600 m
3/ton (the specific value depends on the type and source of paper). When paper is recovered for recycling, nearly 40% of the water used in the paper-making process can be conserved, indicating that using recycled paper is extremely beneficial for reducing water footprints.
Mekonnen and Hoekstra [
30] measured the water footprints of various farm animals and animal products globally and showed that the animal products worldwide require 2422 m
3 water annually. The primary factors that influence the water footprints of animal products are the feed conversion efficiency of the animal, feed composition, and origin of the feed. The type of production system used (a grazing, mixed, or industrial system) can influence these three factors.
From an Italian dietary and cultural perspective, Aldaya and Hoekstra [
13] analyzed the influence of pasta and pizza Margherita on water resources based on the concept of water footprints. The results showed that the water footprints of 100 g of pasta and a 725 g pizza were 192.4 L and 1216 L, respectively, which far exceeded the household water use per capita per day in Italy (380 L). Chapagain and Hoekstra [
25] found that the average global water footprint of rice from 2000 to 2004 was 1325 m
3/ton, and that green, blue, and grey water accounted for 48%, 44%, and 8%, respectively.
The water footprint concept, which is closely linked with virtual water or embedded water approaches [
12], was first introduced in 2002 as an analogy to the ecological footprint [
31]. In contrast to the ecological footprint, the water footprint is a volumetric measure of water consumption and pollution. Diverse accounting perspectives have led to different water footprint categories, which may include process, product, consumer, consumer groupings, business, and geographic area, and regional water footprints [
32]. Although differences exist among the various types of water footprints, the water footprint of one process could be considered a building block of all water footprint accounts [
33].
Zhao and Chen [
34] applied a log-mean Divisia index (LMDI) model to evaluate agricultural water footprint in China, The results reveal that the Chinese agricultural water footprint has risen from the 94.1 Gm
3 in 1990 to 141 Gm
3 in 2009. Zhao
et al. [
35] explored the influencing factors of population, affluence, urbanization level, and diet structure on agriculture products-related water footprint change based on an extended STIRPAT model. Empirical results reveal that the all examined factors as positive driving forces have pushed forward Chinese agricultural sector water footprint increases from 549.68 Gm
3 in 1990 to 1016.64 Gm
3 in 2009. Fang
et al. [
36] investigated an embodied socio-economic water system using network analysis developed originally for ecological systems. This study provides a novel perspective and methodology for assessing the structure and efficiency of water utilization system with a whole perspective.
According to Hoekstra and Mekonnen [
20], water resources are subjected to the effects of industrial production and consumption activities through both consumptive use and pollution. Such effects can be local or external to the area of production, as when water-intensive commodities are traded. Several studies in the previous decade have explored alternative methodologies for quantifying virtual water transfers [
37,
38,
39,
40,
41].
Based on the aforementioned concerns and developments regarding water footprints, numerous studies have focused on calculating the water footprints of products, especially those of agricultural products. However, few studies have analyzed the water footprints in specific regions or countries. Moreover, in the regional studies available, the regions of a nation were divided by county, city, or province, and small regions such as a science park were not discussed. Water footprint analysis can determine the extent of water consumption and scarcity and represent the embedded or virtual water in imports and exports. However, the application of such a method in Taiwan is still at its early stage, especially in the science parks where water shortage is severe. Thus, conducting such a study is critical so that appropriate water management policies can be developed by considering local conditions.
Therefore, the primary objective of this study was to apply a water footprint model for evaluating the sustainable development of the HSP in Taiwan. First, an IO method was used to establish the water footprint model for the HSP. Second, we used the model to analyze the historical water footprint of the six major industries in the HSP. Finally, we analyzed the empirical results. The research results are expected to be used as a reference for planning the sustainable development of science parks. For achieving these objectives, the remainder of this paper begins with an overview of previous water footprint-related studies. Details on the research methodology are provided, including an overview of the IO-based analysis framework and data collection process. Subsequently, we present the case study results and provide policy implications. Finally, we draw research conclusions and identify limitations and directions for future research.
The first contribution of this study is the generation of direct water use intensity and total water use intensity indicators for each economic sector. These critical indicators can facilitate evaluating sectoral water use efficiency and identifying sources of pressure in water resources for supporting policy decisions related to water allocation under scarcity conditions. The second contribution is the quantification of both direct and indirect water use in the economies of. This is essential for assessing how commodity supply chains that use water as an input to economic production affect water resources.