Integrating spatially-and temporally-heterogeneous data on river network dynamics using graph theory

: The study of non-perennial streams requires extensive experimental data on the temporal evolution of surface flow presence across different nodes of channel networks. However, the consistency and homogeneity of available datasets is threatened by the empirical burden required to map stream network expansions and contractions. Here, we developed a data-driven, graph-theory framework aimed at representing the hierarchical structuring of channel network dynamics (i.e., the order of node activation/deactivation during network expansion/retraction) through a directed acyclic graph. The method enables the estimation of the configuration of the active portion of the network based on a limited number of observed nodes, and can be utilized to combine datasets with different temporal resolutions and spatial coverage. A proof-of-concept application to a seasonally-dry catchment in central Italy demonstrated the ability of the approach to reduce the empirical effort required for monitoring network dynamics and efficiently extrapolate experimental observations in space and time

Evaluating stream CO2 outgassing via drifting and anchored flux chambers in a controlled flume experiment

Carbon dioxide (CO2) emissions from running waters represent a key component of the global carbon cycle. However, quantifying CO2 fluxes across air-water boundaries remains challenging due to practical difficulties in the estimation of reach-scale standardized gas exchange velocities (k(600)) and water equilibrium concentrations. Whereas craft-made floating chambers supplied by internal CO2 sensors represent a promising technique to estimate CO2 fluxes from rivers, the existing literature lacks rigorous comparisons among differently designed chambers and deployment techniques. Moreover, as of now the uncertainty of k(600) estimates from chamber data has not been evaluated. Here, these issues were addressed by analysing the results of a flume experiment carried out in the Summer of 2019 in the Lunzer:::Rinnen - Experimental Facility (Austria). During the experiment, 100 runs were performed using two different chamber designs (namely, a standard chamber and a flexible foil chamber with an external floating system and a flexible sealing) and two different deployment modes (drifting and anchored). The runs were performed using various combinations of discharge and channel slope, leading to variable turbulent kinetic energy dissipation rates (1.5 x 10(-3) epsilon < 1 x 10(-1) m(2) s(-3)). Estimates of gas exchange velocities were in line with the existing literature (4 < k(600) < 32 m(2) s(-3)), with a general increase in k(600) for larger turbulent kinetic energy dissipation rates. The flexible foil chamber gave consistent k600 patterns in response to changes in the slope and/or the flow rate. Moreover, acoustic Doppler velocimeter measurements indicated a limited increase in the turbulence induced by the flexible foil chamber on the flow field (22 % increase in 8, leading to a theoretical 5 % increase in k(600)). The uncertainty in the estimate of gas exchange velocities was then estimated using a generalized likelihood uncertainty estimation (GLUE) procedure. Overall, uncertainty in k(600) was moderate to high, with enhanced uncertainty in high-energy set-ups. For the anchored mode, the standard deviations of k 6 00 were between 1.6 and 8.2 m d(-1), whereas significantly higher values were obtained in drifting mode. Interestingly, for the standard chamber the uncertainty was larger (+ 20 %) as compared to the flexible foil chamber. Our study suggests that a flexible foil design and the anchored deployment might be useful techniques to enhance the robustness and the accuracy of CO2 measurements in low-order streams. Furthermore, the study demonstrates the value of analytical and numerical tools in the identification of accurate estimations for gas exchange velocities. These findings have important implications for improving estimates of greenhouse gas emissions and reaeration rates in running waters

Esplorazione delle reti fluviali dinamiche con strumenti empirici e teorici

Empirical evidence has shown that the flowing portion of many river networks does vary in time, owing to seasonal and/or event-based expansion-retraction cycles that mimic the unsteady nature of the underlying climatic forcing. Such rivers, commonly referred to as temporary streams, are believed to represent more than half of the global river network, and are observed in most climatic regions worldwide, from arid, to humid areas. The goal of this thesis is to provide a comprehensive hydrological analysis of temporary streams, by combining empirical data from 18 study catchments spread all over the world with theoretical analyses and stochastic models. A Bayesian framework is developed for the statistical description of the dynamics of the active network, linking the behaviour of the stream network to the underlying local properties of the constituting nodes. The local persistency of the nodes is found to be a key statistical index to quantify the probability of activation of each node, and dictates the interaction between different nodes and defines the spatial pattern of active network at any given time. The activation of the nodes during network expansion is found to follow a fixed order of decreasing persistency, while the deactivation of nodes during network contraction occurs in reverse order. This general behaviour, called hierarchical, is defined in a mathematically rigorous way within the Bayesian framework, and used to derive analytical expressions for the main statistics of the active length as function of the mean network persistency. The latter is then linked to the mean effective precipitation, thus providing a direct connection between climate and network dynamics. The Stream Length Duration Curve links each possible length of the active network to the duration for which that length is exceeded, and allows a quantitative description of the dynamics of a temporary stream. Under the hierarchical hypothesis, this curve is proven to be solely determined by the spatial distribution of the local persistency, providing a crucial link between the spatial and temporal dimensions of the problem. Temporary streams can be also characterized via their length regimes, providing an objective classification system based on the dynamic behaviour of the networks. A stochastic model for streamflow generation is also exploited in conjunction with the hierarchical activation scheme, to enable the spatio-temporal simulation of a temporary stream under a wide variety of climatic scenarios. This type of simulations require a small number of parameters and a limited computational effort, and allows a deeper understanding of the influence of climate on the origins and implications of channel network dynamics. A set of synthetic temporary streams are used as input for a dynamic metapopulation model simulating the occupancy of a target aquatic species within the network. This application reveals the fundamental role that network dynamics have in degrading the ability of a riverine ecosystem to support a metapopulation, particularly in drier climates, by significantly reducing the average occupancy and increasing the probability of extinction of the target species. Taking into account the dynamic nature of the active network represents a fundamental prerequisite for a correct assessment of many ecological and biochemical functions that are mediated by riverine systems. The work presented in this thesis offers a comprehensive analysis of dynamical river networks, providing a new theoretical framework and novel analytical tools and numerical models for the reconstruction and simulation of the dynamics of the active extent of a stream. Given the rising awareness of the impacts of human activities on the environment, and the sensitivity of temporary streams to a changing climate, the tools provided in this study will hopefully foster the development of better strategies for the management and protection of such systems.Empirical evidence has shown that the flowing portion of many river networks does vary in time, owing to seasonal and/or event-based expansion-retraction cycles that mimic the unsteady nature of the underlying climatic forcing. Such rivers, commonly referred to as temporary streams, are believed to represent more than half of the global river network, and are observed in most climatic regions worldwide, from arid, to humid areas. The goal of this thesis is to provide a comprehensive hydrological analysis of temporary streams, by combining empirical data from 18 study catchments spread all over the world with theoretical analyses and stochastic models. A Bayesian framework is developed for the statistical description of the dynamics of the active network, linking the behaviour of the stream network to the underlying local properties of the constituting nodes. The local persistency of the nodes is found to be a key statistical index to quantify the probability of activation of each node, and dictates the interaction between different nodes and defines the spatial pattern of active network at any given time. The activation of the nodes during network expansion is found to follow a fixed order of decreasing persistency, while the deactivation of nodes during network contraction occurs in reverse order. This general behaviour, called hierarchical, is defined in a mathematically rigorous way within the Bayesian framework, and used to derive analytical expressions for the main statistics of the active length as function of the mean network persistency. The latter is then linked to the mean effective precipitation, thus providing a direct connection between climate and network dynamics. The Stream Length Duration Curve links each possible length of the active network to the duration for which that length is exceeded, and allows a quantitative description of the dynamics of a temporary stream. Under the hierarchical hypothesis, this curve is proven to be solely determined by the spatial distribution of the local persistency, providing a crucial link between the spatial and temporal dimensions of the problem. Temporary streams can be also characterized via their length regimes, providing an objective classification system based on the dynamic behaviour of the networks. A stochastic model for streamflow generation is also exploited in conjunction with the hierarchical activation scheme, to enable the spatio-temporal simulation of a temporary stream under a wide variety of climatic scenarios. This type of simulations require a small number of parameters and a limited computational effort, and allows a deeper understanding of the influence of climate on the origins and implications of channel network dynamics. A set of synthetic temporary streams are used as input for a dynamic metapopulation model simulating the occupancy of a target aquatic species within the network. This application reveals the fundamental role that network dynamics have in degrading the ability of a riverine ecosystem to support a metapopulation, particularly in drier climates, by significantly reducing the average occupancy and increasing the probability of extinction of the target species. Taking into account the dynamic nature of the active network represents a fundamental prerequisite for a correct assessment of many ecological and biochemical functions that are mediated by riverine systems. The work presented in this thesis offers a comprehensive analysis of dynamical river networks, providing a new theoretical framework and novel analytical tools and numerical models for the reconstruction and simulation of the dynamics of the active extent of a stream. Given the rising awareness of the impacts of human activities on the environment, and the sensitivity of temporary streams to a changing climate, the tools provided in this study will hopefully foster the development of better strategies for the management and protection of such systems

The stream length duration curve: a tool for characterizing the time variability of the flowing stream length

In spite of the importance of stream network dynamics for hydrology, ecology, and biogeochemistry, there is limited availability of analytical tools suitable for characterizing the temporal variability of the active fraction of river networks. To fill this gap, we introduce the concept of Stream Length Duration Curve (SLDC), the inverse of the exceedance probability of the total length of active streams. SLDCs summarize efficiently the effect of hydrological variability on the length of the flowing streams under a variety of settings. A set of stochastic network models is developed to link the features of the local hydrological status of the network nodes with the shape of the SLDC. We show that the mean network length is dictated by the mean persistency of the nodes, whereas the shape of the SLDC is driven by the spatial distribution of the local persistencies and their network‐scale spatial correlation. Ten field surveys performed in 2018 were used to estimate the empirical SLDC of the Valfredda river (Italy), which was found to be steep and regular—indicating a pronounced sensitivity of the active stream length to the underlying hydrological conditions. Available observations also suggest that the activation of temporary reaches during network expansion is hierarchical, from the most to the least persistent stretches. Under these circumstances, the SLDC corresponds to the spatial Cumulative Distribution Function of the nodes persistencies. The study provides a sound theoretical basis for the analyses of network dynamics in temporary rivers

Technical note: Analyzing river network dynamics and the active length–discharge relationship using water presence sensors

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 2 months in the late fall of 2019. The setup of the ER sensors was customized to make them more flexible for the deployment in the field and more accurate under low flow conditions. Available ER data were compared to field-based estimates of the nodes' persistency (i.e., a proxy for the probability to observe water flowing over a given node) 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 highlighted the diversity of the hydrological behavior of distinct zones of the study catchment, which was attributed to the heterogeneity in catchment geology and stream-bed composition. Our work emphasizes the potential of ER sensors for analyzing 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

On the relationship between active network length and catchment discharge

Dataset about flowing network length and discharge in the Valfredda catchment, as analyzed in the manuscript "On the relationship between active network length and catchment discharge"

Dataset: Extending active network length vs. catchment discharge relations to temporarily-dry outlets

Dataset about flowing network length and discharge in the Burnaby, Turbolo and Poverty catchments, as analyzed in the manuscript "Extending active network length vs. catchment discharge relations to temporarily-dry outlets"

Heterogeneity Matters: Aggregation Bias of Gas Transfer Velocity Versus Energy Dissipation Rate Relations in Streams

The gas transfer velocity, k, modulates gas fluxes across air-water interfaces in rivers. While the theory postulates a local scaling law between k and the turbulent kinetic energy dissipation rate e, empirical studies usually interpret this relation at the reach-scale. Here, we investigate how local k(e) laws can be integrated along heterogeneous reaches exploiting a simple hydrodynamic model, which links stage and velocity to the local slope. The model is used to quantify the relative difference between the gas transfer velocity of a heterogeneous stream and that of an equivalent homogeneous system. We show that this aggregation bias depends on the exponent of the local scaling law, b, and internal slope variations. In high-energy streams, where b>1, spatial heterogeneity of e significantly enhances reach-scale values of k as compared to homogeneous settings. We conclude that small-scale hydro-morphological traits bear a profound impact on gas evasion from inland waters