# China's Water Intensity Factor Decomposition and Water Usage Decoupling Analysis
## 1 Introduction  
China is one of the countries with the most serious water shortage pressures in the world [1; 2; 3]. Besides, the weak awareness of water saving, uneven distribution of water resources, rapid population growth, increasing water usage of residents, and climate change have all aggravated the tensions surrounding water resources in China [4; 5]. With the rapid development of modern industry and the accelerating process of urbanization, the demand for water resources in different sectors will change greatly, and access to water will become an important factor restricting China's economic development [6; 7]. In the last 20 years, China's water usage structure has changed significantly in line with economic development. The water usage in China has been divided into three industries. The primary industry category mainly includes agriculture, forestry, and animal husbandry and fisheries. The secondary industry category mainly refers to mining, manufacturing, and construction. The tertiary industries include everything not contained within the primary and secondary industries, including the service industry, transportation, accommodation and catering, finance, real estate, culture and sports, public administration, and social security [8; 9]. The water usage in primary industry showed a downward trend, andthe water usage in secondary industry increased first and then decreased [10; 11; 12]. Water usage in tertiary industry continued to rise at a rapidly increasing rate, which was 15% in 2020 [13; 14]. Therefore, it is of great significance for the sustainable management of water resources to investigate the driving factors behind China's water intensity [15]. A series of publications have calculated the single resource intensity at national level, the city level, and certain industry levels. Some researchers even considered the resource intensity of overall resources in the world or in a certain country. A series of publications regarding driving factors in different resources have been conducted by previous researchers, including structural decomposition analysis (SDA), granger causality test, and the Logarithmic Mean Divisia Index (LMDI) model. Most of the existing studies using SDA were based on the monetary I-O tables, which require a considerable amount of sector data, and the research scope is mainly in a national level [16; 17; 18]. While the Granger causality test is only a statistical estimation, not a real causality, which cannot be used as the basis for affirming or denying causality [19; 20; 21]. Therefore, the LMDI model was adopted in this paper. The LMDI model is a factor decomposition method that does not generate residual error [22]. The application of LMDI is essentially for resources and the environment, such as carbon emissions, energy, land, and water resources [23; 24; 25; 26; 27; 28]. At present, LMDI research on water resources has calculated the driving factors at national level or the city level [29; 30; 31; 32; 33; 34; 35]. The LMDI method in water resources research was mainly broken down into population scale effect, economic development effect, domestic intensity effect, production intensity, and industrial structural effect [36]. However, as the world's most populous country with serious water usage pressure, there is a shortage of research on the drivers of change in China's water intensity at industrial level with provincial data. Based on the data of water usage, GDP, and the added value of various industries in different provinces of China from 2000 to 2020, the LMDI model was used to analyze the potential factors affecting the change of water usage within various industries. Three effects, including the technical effect, industrial structure effect, and regional scale effect will be adopted. Besides, these three effects will be applied in each province and each industry in China.