Abstract Water storage dynamics modulate fluxes within catchments, control the rainfall-runoff response and regulate the velocity of water particles through mixing associated processes. Tracer-aided models are useful tools for tracking the interactions between catchment storage and fluxes, as they can capture both the celerity of the runoff response and the velocity of water particles revealed by tracer dynamics. The phase-space reconstruction of modelled systems can help in this regard; it traces the evolution of a dynamic system from a known initial state as phase trajectories in response to inputs. In this study, we compared the modelled storage-flux dynamics obtained from the application of a spatially distributed tracer-aided hydrological model (STARR) in five contrasting long-term research catchments with varying degrees of snow influence. The models were calibrated using a consistent multivariate methodology based on discharge, isotope composition and snowpack water equivalent. Analysis of extracted modelled storage dynamics gave insights into the system functioning. Large volumes of total stored water needed to be invoked at most sites to reconcile celerity and travel times to match observe discharge and isotope responses. This is because changes in dynamic storage from water balance considerations are small when compared to volume of storage necessary for observed tracer dampening. In the phase-space diagrams, the rates of storage change gave insights into the relative storage volume and seasonal catchment functioning. The storage increase was dominated by hydroclimatic inputs; thus, it presented a stochastic response. Furthermore, depending on the dominance of snow or rainfall inputs, catchments had different seasonal responses in storage dynamics. Decreases in storage were more predictable and reflected the efficiency of catchment drainage, yet at lower storages the influence of ET was also evident. Activation of flow paths due to overland and near-surface flows resulted in non-linearity of catchment functioning largely at high storage states. The storage-discharge relationships generally showed a non-linear distribution, with more scattered states during wettest condition. In turn, all the catchments exhibited an inverse storage effect, with modelled water ages decreasing with increasing storage as lateral flow paths were activated. Insights from this inter-comparison of storage-flux-age dynamics show the benefits of tracer-aided hydrological models in exploring their interactions at well-instrumented sites to better understand hydrological functioning of contrasting catchments.

Abstract. Permafrost strongly controls hydrological processes in cold regions, and our understanding of how changes in seasonal and perennial frozen ground disposition and linked storage dynamics affects runoff generation processes remains limited. Storage dynamics and water redistribution are influenced by the seasonal variability and spatial heterogeneity of frozen ground, snow accumulation and melt. Stable isotopes provide a potentially useful technique to quantify the dynamics of water sources, flow paths and ages; yet few studies have employed isotope data in permafrost-influenced catchments. Here, we applied the conceptual model STARR (Spatially distributed Tracer-Aided Rainfall-Runoff model), which facilitates fully distributed simulations of hydrological storage dynamics and runoff processes, isotopic composition and water ages. We adapted this model to a subarctic catchment in Yukon Territory, Canada, with a time-variable implementation of field capacity to include the influence of thaw dynamics. A multi-criteria calibration based on stream flow, snow water equivalent and isotopes was applied to three years of data. The integration of isotope data in the spatially distributed model provided the basis to quantify spatio-temporal dynamics of water storage and ages, emphasizing the importance of thaw layer dynamics in mixing and damping the melt signal. By using the model conceptualisation of spatially and temporally variant storage, this study demonstrates the ability of tracer-aided modelling to capture thaw layer dynamics that cause mixing and damping of the isotopic melt signal.

Abstract. Permafrost strongly controls hydrological processes in cold regions. Our understanding of how changes in seasonal and perennial frozen ground disposition and linked storage dynamics affect runoff generation processes remains limited. Storage dynamics and water redistribution are influenced by the seasonal variability and spatial heterogeneity of frozen ground, snow accumulation and melt. Stable isotopes are potentially useful for quantifying the dynamics of water sources, flow paths and ages, yet few studies have employed isotope data in permafrost-influenced catchments. Here, we applied the conceptual model STARR (the Spatially distributed Tracer-Aided Rainfall–Runoff model), which facilitates fully distributed simulations of hydrological storage dynamics and runoff processes, isotopic composition and water ages. We adapted this model for a subarctic catchment in Yukon Territory, Canada, with a time-variable implementation of field capacity to include the influence of thaw dynamics. A multi-criteria calibration based on stream flow, snow water equivalent and isotopes was applied to 3 years of data. The integration of isotope data in the spatially distributed model provided the basis for quantifying spatio-temporal dynamics of water storage and ages, emphasizing the importance of thaw layer dynamics in mixing and damping the melt signal. By using the model conceptualization of spatially and temporally variable storage, this study demonstrates the ability of tracer-aided modelling to capture thaw layer dynamics that cause mixing and damping of the isotopic melt signal.

Use of isotopes to quantify the temporal dynamics of the transformation of precipitation into run-off has revealed fundamental new insights into catchment flow paths and mixing processes that influence biogeochemical transport. However, catchments underlain by permafrost have received little attention in isotope-based studies, despite their global importance in terms of rapid environmental change. These high-latitude regions offer limited access for data collection during critical periods (e.g., early phases of snowmelt). Additionally, spatio-temporal variable freeze-thaw cycles, together with the development of an active layer, have a time variant influence on catchment hydrology. All of these characteristics make the application of traditional transit time estimation approaches challenging. We describe an isotope-based study undertaken to provide a preliminary assessment of travel times at Siksik Creek in the western Canadian Arctic. We adopted a model-data fusion approach to estimate the volumes and isotopic characteristics of snowpack and meltwater. Using samples collected in the spring/summer, we characterize the isotopic composition of summer rainfall, melt from snow, soil water, and stream water. In addition, soil moisture dynamics and the temporal evolution of the active layer profile were monitored. First approximations of transit times were estimated for soil and streamwater compositions using lumped convolution integral models and temporally variable inputs including snowmelt, ice thaw, and summer rainfall. Comparing transit time estimates using a variety of inputs revealed that transit time was best estimated using all available inflows (i.e., snowmelt, soil ice thaw, and rainfall). Early spring transit times were short, dominated by snowmelt and soil ice thaw and limited catchment storage when soils are predominantly frozen. However, significant and increasing mixing with water in the active layer during the summer resulted in more damped steam water variation and longer mean travel times (~1.5 years). The study has also highlighted key data needs to better constrain travel time estimates in permafrost catchments.