Unraveling the Impacts of River Network Connectivity on Ecological Quality Dynamics at a Basin Scale

作者：Xia Li, Xiaobiao Mo, Cheng Zhang, Qing Wang, Lili Xu, Ze Ren, Gregory W. McCarty, Baoshan Cui · 发表于：Remote Sensing · 年份：2024 · DOI：10.3390/rs16132370 · 被引用次数：8 · 研究领域：Hydrology and Watershed Management Studies、Land Use and Ecosystem Services、Hydrology and Sediment Transport Processes

The ecological quality of river basins is significantly influenced by the complex network of river structures and their connectivity. This study measured the temporal and spatial variability of ecological quality, as reflected by remote sensing ecological indices (RSEI), and examined their responses to river network connectivity (RNC). In total, 8 RNC indices, including river structure of river density (Dr), water surface ratio (Wr), edge-node ratio (β), and network connectivity (γ), and node importance indices of betweenness centrality (BC), PageRank (PG_R), out_degree centrality (Out_D), and in_closeness centrality (In_C), were generated at the subbasin scale. Our results highlighted the significance of RNC in influencing both the values and variability of RSEI, and the extent of this influence varied across different time periods. Specifically, three distinct clusters can be extracted from the temporal variability of RSEI, representing wet, near-normal, and dry years. The river structure index of γ significantly influenced the spatial patterns of subbasin RSEIs, particularly in wet years (R2 = 0.554), whereas β displayed a pronounced U-shape correlation with subbasin RSEIs in dry years (R2 = 0.512). Although node importance indices did not correlate directly with subbasin RSEI levels, as the river structure indices did, they significantly positively affected temporal variability of subbasin RSEIs (EI_SD_t). Higher values of PG_R, Out_D, and In_C were associated with increa...