徒骇河流域灰水足迹时空演变及其影响因素

Spatio-temporal Evolution of Grey Water Footprint and Its Influencing Factors in the Tuhai River Basin

为了有效控制徒骇河流域水环境污染,采用流域内聊城、济南、德州和滨州市的统计数据、数字高程模型数据,以16个县(区)为单元测算了2021年徒骇河流域的灰水足迹及强度,利用ArcGIS 10.7等软件对2011—2021年流域内灰水足迹进行时空变化和空间差异分析,并结合基尼系数评价聊城、济南、德州和滨州市灰水足迹强度的区域差异,利用基于人口、财富、技术的可拓展的随机性的环境影响评估(STIRPAT)模型分析灰水足迹的影响因素。结果表明:在时间上,徒骇河流域四市灰水足迹以年均1.7%的速度减小;农业、生活和工业灰水足迹的贡献率分别为80.14%、15.51%和4.35%;在空间上,阳信县的灰水足迹最大,为7.56×10^(8)m^(3),东阿县的灰水足迹最小,为2.46×10^(8)m^(3);徒骇河流域灰水足迹强度的基尼系数为0.398,空间差距处于相对合理的水平;对徒骇河流域灰水足迹影响最大的是有效灌溉面积,影响最小的是灰水足迹强度。

To effectively control the water environment pollution in the Tuhai River Basin,the gray water footprint and intensity of the Tuhai River Basin in 2021 were measured using the statistical data and digital elevation models of cities of Liaocheng,Jinan,Dezhou,and Binzhou in the basin with 16 counties or districts as the units.The spatio-temporal changes and spatial differences of the gray water footprint of the basin from 2011 to 2021 were analyzed using ArcGIS 10.7 and other softwares.Combined with Gini coefficient,the regional differences in gray water footprint intensity in cities of Liaocheng,Jinan,Dezhou,and Binzhou were evaluated and the influencing factors on gray water footprints were analyzed by using stochastic impacts by regression on population,affluence,and technology(STIRPAT)model.The results show that,on the time scale,the gray water footprint of the Tuhai River Basin decrease at an average annual rate of 1.7%,and the contributions of agricultural,domestic and industrial gray water footprints are 80.14%,15.51%and 4.35%,respectively.On the space scale,the gray water footprint of Yangxin County is the largest(7.56×10^(8)m^(3)),while that of Dong’e County is the smallest(2.46×10^(8)m^(3)).Gini coefficient of grey water footprint intensity in the Tuhai River Basin is 0.398,and the spatial gap is at a relatively reasonable level.Effective irrigation area has the greatest impact on the grey water footprint of the Tuhai River Basin,while the gray water footprint strength has the least impact.