资源环境科技发展态势分析平台

River deltas are lowland systems that can display high hydrological connectivity. This connectivity can be structural (morphological connections), functional (control of fluxes), and process connectivity (information flow from system drivers to sinks). In this work, we quantify hydrological process connectivity in Wax Lake Delta, coastal Louisiana, by analyzing couplings among external drivers (discharge, tides, and wind) and water levels recorded at five islands and one channel over summer 2014. We quantify process connections with information theory, a branch of mathematics concerned with the communication of information. We represent process connections as a network; variables serve as network nodes and couplings as network links describing the strength, direction, and time scale of information flow. Comparing process connections at long (105 days) and short (10 days) time scales, we show that tides exhibit daily synchronization with water level, with decreasing strength from downstream to upstream, and that tides transfer information as tides transition from spring to neap. Discharge synchronizes with water level and the time scale of its information transfer compares well to physical travel times through the system, computed with a hydrodynamic model. Information transfer and physical transport show similar spatial patterns, although information transfer time scales are larger than physical travel times. Wind events associated with water level setup lead to increased process connectivity with highly variable information transfer time scales. We discuss the information theory results in the context of the hydrologic behavior of the delta, the role of vegetation as a connector/disconnector on islands, and the applicability of process networks as tools for delta modeling results.

Plain Language Summary Connectivity is an increasingly important concept in studying the complexity and evolution of landscapes. One aspect of connectivity often overlooked is process connectivity; the interaction between external drivers and system variables such as water level and sediment concentration. A better understanding of deltaic process connectivity would benefit numerical modelers in improving delta simulations. In this work, we apply information theory to directly quantify for the first time the connectivity between discharge, wind, and tides, and water level at five deltaic islands and one channel in Wax Lake Delta (WLD), a prograding delta in coastal Louisiana that is often cast as an analog of a river diversion system. The importance of deltaic islands as areas of increased biogeochemical processing make this analysis particularly relevant to better understand the hydrologic controls on islands. Our results highlight the multi-scale interactions between external drivers and deltaic water level. The role of wind events, tidal regime, and vegetation controls in process connectivity indicate the dynamic nature of deltaic systems. Couplings are characterized in terms of strength, direction, significance, and scale. Process connectivity is visualized as a process network; variables are network nodes and couplings are network links that depict significant information flow.