Driving effect evolution and spatial differentiation of water use change in China
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Abstract:
Accurately studying and judging changes in national and regional water consumption is prerequisite for rational layout of major water conservancy projects and scientific formulation of water resources management policies.The identification and quantification of the main influencing factors and their driving effects that lead to changes in water consumption is an important basis for accurately grasping the trend of changes in water consumption.At the current stage when the contradiction between water supply and demand is prominent and the economic and social development is undergoing a comprehensive transformation,in-depth research on the main factors affecting water consumption,temporal and spatial changes,and their internal mechanism is undoubtedly of important practical significance and has also received extensive attention from academic circles. The current methods for quantitatively measuring the driving effect of water consumption changes mainly include structural decomposition analysis (SDA) and index decomposition analysis (IDA).However,whether it is the structural decomposition method or the index decomposition method,the existing results are generally based on the total water consumption as a whole to conduct research or only analyze the water consumption of specific industries in specific regions.The study of total water consumption as a whole ignores the differences in the driving forces of water consumption in different industries of life,industry,and agriculture to a certain extent.Research on water consumption of specific industries in specific regions can not fully reflect the evolution of country's water use process.Considering that the logarithmic mean Divisia index (LMDI) in the index decomposition method effectively solves the problem of residual items and zero values in the index decomposition,it is not affected by the input-output table.For the impact of a long release cycle,this study uses the Kaya identity optimization to construct a multi-level LMDI method.Based on the overall analysis of the national water consumption driving effect,it further analyzes the water consumption driving effect of each industry from 2000 to 2010 and 2010 to 2020.Decomposition research is carried out,and an in-depth analysis of the spatial differentiation of driving effects and the latest changes during the 13th Five-Year Plan is carried out. From 2000 to 2020,there is an increase to decrease fluctuation in country's total water consumption.The total water consumption in 2020 is almost the same as 20 years ago,but the water use structure has undergone certain adjustments,taking 2013 as the boundary point,the change in agricultural water use before 2013 dominated the change in total water use,with an average contribution rate of 5742%.After 2013,the change in industrial water consumption has taken up a relatively dominant position,with an average contribution rate of 44.3%.Domestic water consumption before 2012 was mainly due to the increase in water quota,and after 2012,the increase in domestic water consumption was mainly due to the increase in the urbanization rate.Industrial water consumption has always been strongly affected by the two driving forces of industrial-scale expansion and decline in industrial water quotas.Before 2011,the increase in industrial output value was dominant,and after 2011,the decline in industrial water quotas was even greater.Agricultural water use has always been dominated by irrigation area and agricultural water quotas.The effect of reducing agricultural water quota is slightly greater,but the expansion of irrigation area is always an important factor that can not be ignored.During the Thirteenth Five-Year Plan,the leading factor in the provinces to promote the water consumption growth was generally the increase in industrial output value or the expansion of agricultural irrigation area,while the leading factor in restraining the water consumption growth was the decline in the industrial water quota or the decline in the agricultural water quota.
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