摘要
为识别和量化导致用水量变化的主要影响因素及其驱动作用,准确把握用水变化趋势,将全国总用水量分为生活、工业和农业用水量,通过构建多层次对数均值迪氏指数(logarithmic mean Divisia index,LMDI)分解模型,在生活、工业及农业用水量变化的驱动因素分解的基础上,对全国总用水量驱动效应进行测度,并进一步量化研究用水驱动效应在时间和空间尺度上的分异特征。结果表明:2020年用水总量几乎与20年前持平,但各驱动要素的相对作用发生了显著变化,与此同时,用水量变化驱动效应存在较强的空间分异性,并且在“十三五”时期表现出了新的变化态势。结果可为我国水资源的高效利用和水资源管理政策的科学制定提供技术支撑与决策依据。
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 13 th 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 57.42%.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.
作者
何凡
顾冰
何国华
路培艺
尹婧
赵勇
李海红
HE Fan;GU Bing;HE Guohua;LU Peiyi;YIN Jing;ZHAO Yong;LI Haihong(State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin,China Institute of Water Resources and Hydropower Research,Beijing 100038,China)
出处
《南水北调与水利科技(中英文)》
CAS
北大核心
2022年第3期417-428,共12页
South-to-North Water Transfers and Water Science & Technology
基金
国家重点研发计划项目(2021YFC3200204)
国家杰出青年科学基金项目(52025093)
国家自然科学基金项目(52061125101,52109042)。
关键词
用水量
驱动效应
空间分异
指数分解
LMDI
water consumption
driving effect
spatial differentiation
index decomposition
LMDI