作者：LUYan,WANGJinxin,LIUJianzhong,QINFen,WANGJiayao, 单位：SchoolofGeoscienceandTechnology,ZhengzhouUniversity；LaboratoryofGeospatialTechnologyfortheMiddleandLowerYellowRiverRegions,MinistryofEducation,HenanUniversity；HenanIndustrialTechnologyAcademyofSpatio-TemporalBigData,HenanUniversity；CollegeofGeographyandEn 本文刊于： 《Chinese Geographical Science》 2022年第03期
关键词:
waterwithdrawal data-drivenframework spaKeywords
water withdrawal, data-driven framework, spatial data analysis, water coefficient, Huaihe River watershed,China,
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摘要
With an increase in population and economic development, water withdrawals are close to or even exceed the amount of water available in many regions of the world. Modelling water withdrawals could help water planners improve the efficiency of water use,water resources allocation, and management in order to alleviate water crises. However, minimal information has been obtained on how water withdrawals have changed over space and time, especially on a regional or local scale. This research proposes a data-driven framework to help estimate county-level distribution of water withdrawals. Using this framework, spatial statistical methods are used to estimate water withdrawals for agricultural, industrial, and domestic purposes in the Huaihe River watershed in China for the period 1978–2018. Total water withdrawals were found to have more than doubled, from 292.55×10~8 m~3 in 1978 to 642.93×10~8 m~3 in 2009,and decreased to 602.63×10~8 m~3 in 2018. Agricultural water increased from 208.17×10~8 m~3 in 1978 to 435.80×10~8 m~3 in 2009 and decreased to 360.84×10~8 m~3 in 2018. Industrial and domestic water usage constantly increased throughout the 1978–2018 period.In 1978, industrial and domestic demands were 20.35×10~8 m~3 and 60.04×10~8 m~3, respectively, and up until 2018, the figures were105.58×10~8 m~3 and 136.20×10~8 m~3. From a spatial distribution perspective, Moran’s I statistical results show that the total water withdrawal has significant spatial autocorrelation during 1978–2018. The overall trend was a gradual increase in 1978–2010 with withdrawal beginning to decline in 2010–2018. The results of Getis-Ord G_i~* statistical calculations showed spatially contiguous clusters of total water withdrawal in the Huaihe River watershed during1978–2010, and the spatial agglomeration weakened from 2010 to 2018. This study provides a data-driven framework for assessing water withdrawals to enable a deeper understanding of competing water use among economic sectors as well as water withdrawal modelled with proper data resource and method.
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