Characterizing the space-time evolution of wet channels in a non-perennial Mediterranean catchment exploiting a network of camera traps

Non-perennial streams are those streams that periodically cease to flow in at least one point along their network. The research community well recognizes the importance of such watercourses for they have a global prevalence and provide diverse hydrological functions and ecosystem services. The spatiotemporal pattern of the active drainage network is anything but simple, sometimes showing a very complex pattern. Non-perennial streams, in fact, are often located in heterogeneous environments, in which the combination of climate, morphology, land cover, soil, substrate, and anthropic factors could play a role in the observed drying and wetting patterns. This work combined two techniques, with different spatiotemporal resolutions, to characterize the spatiotemporal extent of the stream network in a 3.7 km2 Mediterranean catchment of central Italy. The hydrological status of a set of nodes of the network was derived for the period 2020-2022 from sporadic visual surveys and, most importantly, through the analysis of sub-hourly images collected by 21 cameras distributed along a set of strategic nodes of the network. The latter technique is particularly promising to reconstruct the hydrological dynamics taking place in the target cross-section, as the temporal evolution of the underlying hydrological conditions (wet vs. dry), the water stage, and the corresponding discharge can be inferred from the automatic or manual analysis of the acquired images. The available experimental data was combined exploiting the hierarchical principle, that postulates the existence of a Bayesian chain based on the local persistency of the nodes that dictates their drying/wetting order during stream retraction/contraction cycles. The results highlighted the complexity of the network dynamics in the study area: while the number of wet nodes decreased during the dry season and increased during the wet season, the local persistency of the nodes showed a highly heterogeneous and non-monotonic pattern, resulting in a dynamically disconnected network. The approach allowed the reconstruction of the entire river network and represented a useful tool to estimate the extent of its wet portion, even in case part of the network could not be inspected. This work represents a novel approach to reconstruct the extension of the wet portion of the stream network in difficult-to-access environments, where traditional techniques might be inadequate.