Large scale connectivity of river networks during rainfall events

River connectivity is essential for maintaining fertile floodplains, healthy ecosystems, and human activities, particularly in semi-arid regions, where water flow is often intermittent. Despite its importance, very few studies have attempted to quantify connectivity at the scale of individual rainfall-runoff events. In this study, we present a novel framework for exploring synchronous and sequential connectivity to capture the hydrological response of a system. We distinguish between structural (SC) and functional (FC) connectivity by constructing structural networks utilizing topographic data from the Walnut Gulch Experimental Watershed in Arizona, USA, and correlation-based functional networks using high-resolution runoff data. We examine how SC-FC relations vary across events and how they relate to the hydrological responses of the system. We classify rainfall events via unsupervised clustering and identify the corresponding dominant runoff connectivity patterns within each cluster. The results of our analysis showed that short, intense storms tend to produce localized runoff connectivity, characterized by dominant synchronous SC-FC relations, whereas larger rainfall events tend to exhibit higher sequential SC-FC correlation values, indicating widespread system connectivity. Furthermore, our analysis revealed that there is a minimum threshold in the synchronous connectivity value (0.13), before positive sequential activity appears in the system. Comparable synchronous and sequential connectivity values typically indicate that water flow reached the watershed outlet; however, maximum SC-FC value is not necessarily associated with peak discharge at the watershed outlet. Due to its flexibility, our approach suggests a general framework for analyzing connectivity in any river network with an ephemeral flow regime.