Analysing river network dynamics and active length - discharge relationship using water presence sensors
Abstract. Despite the importance of temporary streams for the provision of key ecosystem services, their experimental monitoring remains challenging because of the practical difficulties in performing accurate high-frequency surveys of the flowing portion of river networks. In this study, about 30 electrical resistance (ER) sensors were deployed in a high relief 2.6 km2 catchment of the Italian Alps to monitor the spatio-temporal dynamics of the active river network during the fall of 2019. The set-up of the ER sensors was personalized to make them more flexible for the deployment in the field and more accurate under low flow conditions. Available ER data were analyzed, compared to field based estimates of the nodes' persistency and then used to generate a sequence of maps representing the active reaches of the stream network with a sub-daily temporal resolution. This allowed a proper estimate of the joint variations of active river network length (L) and catchment discharge (Q) during the entire study period. Our analysis revealed a high cross-correlation between the statistics of individual ER signals and the flow persistencies of the cross sections where the sensors were placed. The observed spatial and temporal dynamics of the actively flowing channels also revealed the diversity of the hydrological behaviour of distinct zones of the study catchment, which was attributed to differences in the catchment geology and stream-bed composition. The more pronounced responsiveness of the total active length to small precipitation events as compared to the catchment discharge led to important hysteresis in the L vs. Q relationship, thereby impairing the performances of a power-law model frequently used in the literature to relate these two quantities. Consequently, in our study site the adoption of a unique power-law L-Q relationship to infer flowing length variability from observed discharges would underestimate the actual variations of L by 40%. Our work emphasizes the potential of ER sensors for analysing spatio-temporal dynamics of active channels in temporary streams, discussing the major limitations of this type of technology emerging from the specific application presented herein.