Spatio-temporal evolution of grey water footprint and its influencing factors in Shandong’s coastal cities

To investigate the spatiotemporal variation characteristics and influencing mechanism of grey water footprint ( Q ) in coastal areas of Shandong province from 2002 to 2021, this paper takes seven coastal cities as the study area, calculates and analyzes the temporal change and spatial differentiation pattern of Q ． The random forest model is adopted to identify the key influencing factors through relative importance analysis and partial dependence analysis． Furthermore, the structural equation model is used to quantitatively analyze the direct and indirect transmission paths among different factors． The results indicate that the regional Q decreases at an average annual rate of 3.4%, showing a three-stage characteristic of "initial increase, subsequent stability, and final decrease"． Q_\textagr contributes the largest proportion on average, which is the primary source of the total Q． In terms of spatial distribution, both the total Q and Q_\textagr present a pattern of "high in the central region and low in the surrounding areas"． Meanwhile, the distribution of Q_\textdom and Q_\textind is highly correlated with population size and industrial structure, respectively． Fertilizer application rate per unit cultivated land (U_n-irr), aquaculture yield per unit area (Y_aqp), pollutant emission per standard livestock equivalent (U_pol−liv), and industrial wastewater discharge intensity (U_ind) were the core influencing factors of the regional Q． The partial dependence relationship revealed the marginal effect of each factor on the Q． The structural equation model further confirmed that agricultural non-point source pollution was the main driving factor for the increase of Q, while agricultural pollution control and industrial pollution control were the main driving forces for the reduction of Q．