LAUSR

The impacts of human activities on hydrological connectivity disturb the network topology of transport paths, which has gradually evolved from natural terrain features to dual natural-artificial features. In this study, a new framework is proposed to extract information from natural-artificial transport paths and related hydrological connectivity dominated by agricultural practices and ditch networks. Graph theory and connectivity indexes are integrated for the comprehensive classification and the parallel processing of potential flow transport networks and their upstream drainage areas. Based on high-resolution remote sensing data and detailed field investigations, this new framework, which combines graph theory and connectivity indexes, is applied to a typical agriculture-intensive catchment in China. The results show that artificial factors greatly influence the transport paths and the related drainage areas. With the development of ditch construction, the hydrological transport paths become shorter and more fragmented. In addition, key ditch segments are identified by connectivity indexes, and recommendations are given for future planning. This new framework offers an approach for the hydrological connectivity analysis of complex networks and provides effective strategies for agricultural development.