The driving force of water resource stress change based on the STIRPAT model: take Zhangye City as a case study |
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| Institution: | Key Laboratory of Ecohydrology of Inland River Basin,Chinese Academy of Sciences,Lanzhou,Gansu 730000,China;Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou,Gansu 730000,China;Ecological Environmental Supervision and Administration Bureau of Gansu Province,Lanzhou,Gansu 730020,China;Gansu Computing Center,Lanzhou,Gansu 730030,China |
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| Abstract: | A prominent contradiction between supply and demand of water resources has restricted local development in social and economic aspects of Zhangye City, located in a typical arid region of China. Our study quantified the Water Resource Stress Index(WRSI) from 2003 to 2017 and examined the factors of population, urbanization level, GDP per capita, Engel coefficient, and water consumption per unit of GDP by using the extended stochastic impact by regression on population,affluence and technology(STIRPAT) model to find the key factors that impact WRSI of Zhangye City to relieve the pressure on water resources. The ridge regression method is applied to improve this model to eliminate multicollinearity problems. The WRSI system was developed from the following three aspects: water resources utilization(WR), regional economic development water use(WU), and water environment stress(WE). Results show that the WRSI index has fallen from 0.81(2003) to 0.17(2017), with an average annual decreased rate of 9.8%. Moreover, the absolute values of normalized coefficients demonstrate that the Engel coefficient has the largest positive contribution to increase WRSI with an elastic coefficient of 0.2709, followed by water consumption per unit of GDP and population with elastic coefficients of 0.0971 and 0.0387, respectively. In contrast, the urbanization level and GDP per capita can decrease WRSI by-0.2449 and-0.089, respectively. The decline of WRSI was attributed to water-saving society construction which included the improvement of water saving technology and the adjustment of agricultural planting structures. Furthermore, this study demonstrated the feasibility of evaluating the driving forces affecting WRSI by using the STIRPAT model and ridge regression analysis. |
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