Monitoring grey water footprint and associated environmental controls in agricultural watershed

The grey water footprint (GWF) is an advanced index linking pollution load and water resources. However, the existing agriculture-related GWF was developed based on hydrological processes, which limits its role in watershed water pollution level (WPL) measurements. The main scope of this study is to calculate GWF and WPL based on runoff, total nitrogen (TN), and total phosphorus (TP) observations in the Hujiashan Watershed of China's Yangtze River Basin. Partial least squares structural equation modeling (PLS-SEM) was utilized to explore the impact pathways of environmental features on GWF and WPL. On this basis, propose measures for the management of this agricultural watershed. The results showed that the TN concentration had a V-shaped trend in 2008-2015, while the TP gradually decreased. The GWF calculations for the TN and TP were compatible with the temporal trends for the concentrations, which were higher in the wet season (0.45 m³/m² for TN, 0.10 m³/m² for TP) than in the dry season (0.11 m³/m² for TN, 0.02 m³/m² for TP) and increased from upstream to downstream. The WPLs of TN exceeded 2.0 in the midstream and downstream areas, whereas those for TP were inconspicuous. According to PLS-SEM, the GWF is primarily influenced by topographical variables and hydrological features, whereas the WPL is mainly controlled by hydrological features and landscape composition. Fertilizer reduction and efficiency measures should be implemented on farmland and appropriately reducing farming activities on slopes to relieve the GWF and WPL in the watershed.