The effect of energy–water nexus on single resource system in urban agglomerations: Analysis based on a multiregional network approach

Interaction between energy and water exists widely within a city and among different cities in an urban agglomeration (UA). However, certain issues regarding such interactions (i.e., the energy–water nexus; EWN) remain unclear, e.g., whether and how the EWN affects traditional understanding and management of a regional single-source system. Here, we present a multiregional network approach to analyze a UA from the EWN perspective to assess the impact of the complex interactions within the UA on regional energy and water systems. A nexus network was constructed by modeling EWN flows between the cities and sectors of the Pearl River Delta (PRD) UA. The key sectors and flows within the region were identified based on multidimension ecological network analysis, which synthesized the nature of the system circulation rate, system sustainability, ecological structure, and network dynamics. Results revealed notable changes in the Finn's cycling index and the control/dependency relationships among cities and sectors following inclusion of the nexus, together with marked changes in the system robustness and network structure of the UA. The cycling rates of 21.04 % and 21.42 % for the hybrid energy and water networks, respectively, were higher than those of the single energy (20.71 %) and water (18.29 %) networks. The average system robustness of PRD in the hybrid networks were higher than that of both the energy network (0.346) and water network (0.351). This implies that the EWN contributed to improvement in both the cycling rate and the system robustness of the UA, but the sectoral level also reflected the insufficient interaction of energy and water, especially in relation to the Manufacturing, Electricity and gas supply, and Other services. The nexus effect on the control relationship was mainly concentrated in the internal sectors of the city, but that on the dependence relationship was mainly concentrated between cities. Our findings provide a reference for UAs to improve the efficiency of using water for energy and using energy for water and suggest energy–water collaborative management by considering EWN.