Research

Refining the concept of hydrological connectivity for large floodplain systems: Framework and implications for eco-environmental assessments

Recent years, the hydrological connectivity has gained popularity in various research fields, however, its definition and threshold effects at a system scale have not received adequate attention. The current research proposes a promising framework to refine the concept of surface hydrological connectivity by combining hydrodynamic modeling experiments, threshold effects and geostatistical connectivity analysis, exemplified by the flood-pulse-influenced Poyang Lake floodplain system (China). To enhance the inherent linkage between hydrological connectivity and eco-environments, total connectivity (TC), general connectivity (GC), and effective connectivity (EC) were proposed to refine the metrics of hydrological connectivity. The results show that substantial differences between the three connectivity metrics are observed for all target directions, demonstrating that the joint role of water depth and flow velocity may produce more dynamic and complex influences on EC than the other two metrics of TC and GC. Topographically, the connectivity objects/areas within the flood pulse system reveal that the floodplain is a more sensitive area than the lake's main flow channels under different connectivity conditions. The modelling experimental studies show that variations in water depth thresholds are more likely to have a strong effect on connectivity for the dry, rising, and falling limbs, rather than the flooding period, while the flow velocity may exert an opposite threshold effect. The lake-floodplain system is characterized by a dynamic threshold behavior, with seasonally varying water depth and velocity thresholds. This study highlights the importance of redefined connectivity concept for facilitating scientific communication by combining hydrodynamic thresholds and offering recommendations for future connectivity assessments using our proposed metrics of TC, GC, and EC.

 

Yunliang Li, Zhiqiang Tan, Qi Zhang et al. Water Research. doi.org/10.1016/j.watres.2021.117005