Residence time dynamics in fragmented river networks, a mechanistic modelling approach using optimal channel networks

Abstract. Hydrological models often lack the capacity to explicitly connect river network topology with dynamic water balance processes and localised flow disturbances. Here, we present a novel modelling framework that integrates Optimal Channel Network (OCN) theory with time evolving precipitation–runoff dynamics and physically grounded representations of in-channel barriers (e.g. dams and weirs). Unlike traditional OCN implementations that remain hydrologically static, our approach simulates discharge, storage, and residence time dynamically across synthetic yet realistic river geometries. This coupling enables controlled numerical experiments to isolate the effects of network structure, hydroclimatic forcing, and flow fragmentation, effects that are otherwise difficult to disentangle in real-world systems.

As a proof of concept, we investigate how flow disturbance structures alter channel network residence times under both steady and periodic flow regimes. We show that while outlet discharge remains virtually unchanged, local residence time at dammed nodes can increase by over 25 %, revealing strong spatial decoupling between upstream disturbance and downstream flow signals. By exploiting the self-affine scaling of OCN geometry, we further derive an analytical scaling law that links residence-time amplification around local flow disturbances to commonly available river-network metrics (slope–length and discharge–length exponents). This provides a transferable theory for residence-time impacts in fragmented networks that can be evaluated directly from network geometry, without requiring full numerical simulations. These findings have broad implications for modelling contaminant decay, microbial transport, and ecological connectivity, all of which depend critically on local hydrologic conditions. Our framework offers a generalisable, disturbance-aware platform for advancing the mechanistic understanding of river network behaviour under changing climate and anthropogenic impacts.