GM3.4

Floodplain wetlands are an important and integrated component of riverine environment as they perform various ecological and hydrological functions. However, these wetlands are under acute pressure because of changing climate and land-use and require urgent attention. Stakeholders (e.g., wetland management authorities) need a science-based information about wetlands at basin scale for prioritising them for restoration and monitoring. To facilitate the prioritisation of wetlands, we used geomorphic connectivity concept and hypothesise that the best possible connectivity scenario for the existence of a wetland is (a) if that wetland has a high connectivity with its upslope area, and (b) if that wetland has a low connectivity with its downslope region. The first condition ensures flow of water into the wetland and second condition allows longer residence time of water in the wetland. Accordingly, we defined 4 categories of connectivity-based restoration scenarios – good, no impact, bad, worst. We applied the proposed method to 3226 wetlands of Ramganga Basin in north India which were mapped in our previous work (Singh and Sinha, 2022, Remote Sensing Letters, 13:1, 1-13). The results show that 676 wetlands are in good category, 1155 show no impact, 831 are in bad category, and 564 in worst category. Further selection criteria such as distance from nearest stream and stream density can be applied to filter the wetlands from different connectivity scenario categories. For example, in present case, there are 112 wetlands within 100 m of any stream and require restoration. Therefore, using connectivity concept, it is possible to identify the wetlands which are easiest to restore and to identify those which are under threat. The proposed method can be applied to any basin for wetland management applications.

How to cite: Singh, M. and Sinha, R.: Geomorphic connectivity analysis for prioritising floodplain wetlands for restoration and monitoring in the Ramganga basin, India, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-298, https://doi.org/10.5194/egusphere-egu22-298, 2022.

The channel patterns in rivers and estuaries range from meandering single-thread channels to complex channel networks comprising looping, branching, and offshoot structures through which water, resediment, and nutrients are transported. Representing channelized systems as networks provides a mathematical framework for analyzing transport and has become increasingly common in hydrology and geomorphology. However, several challenges remain: 1) the automatic extraction of multi-channel networks from topography has historically been a major challenge; 2) the relative importance of individual channels in the identified network; and 3) the issue of transport direction in channel networks, especially where bi-directional flows dominate in estuarine environments. This presentation discusses recent work addressing these three challenges with the introduction of a novel algorithm for extracting topology and geometry from digital elevation models of braided rivers and estuaries and by quantifying structural and dynamical connectivity in two flow directions for estuaries around the world. In both efforts, networks are constructed with network links representing channels and networks nodes representing channel confluences, bifurcations, inlets, and outlets. Across estuaries and braided rivers, scale asymmetry iis detected n links downstream of bifurcations, indicating geometric asymmetry which point to bifurcation stability. Estuaries tend to organize around a deep main channel whereas the channel networks of braided rivers are more evenly distributed across channel size. Analyses of flow direction in estuaries reveal that flood direction fluxes are more broadly distributed across the channel network, while ebb direction fluxes are more localized to the individual channels. The estuaries studied contain signatures of mutually evasive flood and ebb channels that are typical of alluvial estuaries, but also exhibit characteristics of branching or converging patterns typical of deltas and tidal networks, respectively. Finally, this presentation will offer perspectives on the state of the science for network analyses of channelized environments and present challenges for future research.

How to cite: Hiatt, M., Kleinhans, M., Addink, E., van Dijk, W., Sonke, W., and Speckmann, B.: Identification and analysis of channel connectivity in rivers and estuaries, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5678, https://doi.org/10.5194/egusphere-egu22-5678, 2022.

The boundary between a river and its floodplain is often viewed as a static feature which demarcates where the river ends and where the floodplain begins. This boundary, however, is a geomorphic transition whose spatial and temporal evolution controls the interaction of rivers and their floodplains. The transport of water, solutes, and solids across this geomorphic transition affects the functioning of rivers, floodplain sedimentation, carbon storage, and ecosystem functioning. Using examples from studies that combine remotely sensed observations, modeling, and field observations, I will discuss the exchange of fluxes across geomorphic transitions in the context of connectivity and its variability in space and time. We will analyze the role of various climate forcings as well as topography and vegetation patterns, and their effect on water connectivity and the connectivity of sediment and other materials. These connectivity patterns can be quite different from each other, suggesting that water exchanges are not always accurate proxies for sediment exchanges in river systems and their floodplains.

How to cite: Passalacqua, P., Wright, K., Tull, N., Hassenruck-Gudipati, H., and Mohrig, D.: Connected or disconnected? Spatial and temporal patterns of river-floodplain connectivity, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2072, https://doi.org/10.5194/egusphere-egu22-2072, 2022.

In mountain catchments connectivity regulates the capability of sediment to be transferred from sediment source areas to the stream network. Raster-based indices, such as the Index of Connectivity (IC), have become a widely used tool for analysing the relationships facilitating or inhibiting the coupling among different compartments of the catchment. However, despite the numerous applications in literature, few studies have tested the capability of IC to quantitatively represent the linkages between sediment sources and channels and to predict potential new linkages. In this study, the aim is the semi-quantitative validation of IC as a tool for depicting structural connectivity and for predicting sediment dynamics in a mountain basin. Moreover, a specific objective is to derive a crisp threshold between high and low connectivity that could enhance the communication of IC maps. To this end, a benchmark was set regarding the actual connectivity status of 420 sediment source areas present in a mountain headwater catchment in the Dolomites (Italy). The assessment of connectivity status was carried out through remote sensing analysis and field observations. Then, multiple IC variants were computed changing the weighting factor and the pixel resolution of the input DTM. Finally, logistic regression analyses were performed using the different IC variants as independent variables and connectivity status as dependent variable. Therefore, the predictive capacity of IC was tested and a crisp IC threshold was obtained to discriminate connected and disconnected sources. The results showed that only 64 out of 420 sediment sources are connected to the channel network. Moreover, IC as a structural index proved to be suited to depict structural connectivity whereas fails to fully represent process-induced sediment linkages, i.e. functional connectivity. Finally, it was possible to derive an IC threshold of -2.32, useful to differentiate between high and low IC and useful to improve IC maps. The threshold functions as a clear boundary between disconnected and connected sources but only applicable to the catchment under investigation. Nevertheless, the overall approach can be transferred to other mountain areas.

How to cite: Martini, L., Cavalli, M., and Picco, L.: The Index of Connectivity on trial. How reliable is IC to quantitatively assess sediment connectivity in mountain basins?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5049, https://doi.org/10.5194/egusphere-egu22-5049, 2022.

Debris flow processes are known to contribute substantial amounts of sediment to the fluvial system in mountainous areas, such as the Alps. In fact, debris flow release areas represent relevant sediment sources that should be taken into account when mitigating flood hazards for lower order streams. However, terrain that frequently produces debris flows is not necessarily connected to the channel network while structurally connected areas may often not produce debris flows. Therefore, the relevance of an area to contribute debris flow material to a channel mainly depends on the co-occurrence of two aspects: a high debris flow susceptibility which coincides with a high structural sediment connectivity.

In this work, we present a novel data-driven approach that allows to identify areas that are both, susceptible to debris flow initiation and structurally connected to the main channel network. The methodology was developed for a debris flow prone basin located in the Dolomites (Italy) and further tested for other catchments that exhibit different geomorphological settings.

The methodical approach was based on the manual mapping of event-specific connected and disconnected debris flows areas that allowed to (i) calibrate a statistically based debris flow release susceptibility model and (ii) to derive quantitative thresholds for the previously derived connectivity index map (IC). The joined results reflect debris flow connectivity-susceptibility maps that were evaluated from numerous perspectives, including the evaluation of the spatial transferability of the approach.

We present (i) quantitative IC index thresholds that allow to discriminate connected from disconnected debris flow release areas, (ii) well-performing debris flow release susceptibility models and (iii) joint debris flow connectivity-susceptibility maps that allow identifying zones that are differently relevant in terms of debris flow connectivity. Issues related to the geomorphic plausibility of the results and the spatial transferability of the approach are discussed. The proposed approach requires few basic input data sets and therefore will be applied over vast areas with similar geomorphological settings.

How to cite: Scorpio, V., Steger, S., Pitscheider, F., Comiti, F., and Marco, C.: A statistically driven spatial model to delineate (dis)connected debris flow release areas, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5386, https://doi.org/10.5194/egusphere-egu22-5386, 2022.

In agricultural catchments, the landscape structure elements (ditches, hedges, pounds etc.) are recognized to play a major role in hydro-sedimentary transfers. It determines not only sediments availability, but also sediment pathways, water and sediments (de)coupling and connectivity patterns from source to sinks. However, linear drainage infrastructures remain often poorly represented in hydro-sedimentary modelling. Therefore, understanding the link between the catchment landscape structure and the transfer processes at its outlet is still a major challenge. Graph theory has been proved to be a significant tool to investigate sediment connectivity among agricultural catchments as it allows an explicit representation of linear and punctual elements of the landscape.

Based on a detailed inventory of linear landscape elements and a continuous monitoring of sediment fluxes, we built a new graph theory framework to comprehend sediments transfers in a dense agricultural drainage network in the Beaujolais vineyard (France). It integrates all types of linear infrastructures that might canalize water and sediment fluxes (tracks, ditches and soil bunds) and sediment traps used by winegrowers. From the intersection of the drainage network and a topographic graph, we went for spatial analysis to take indices out (IC and RF indices), to extract effects of (dis)connectivity and to compare with a null model (i.e. topographic graph excluding linear infrastructures). Drainage network outlets were extracted to distinguish direct connections to the river in comparison to sediment sinks. The network structure emphasizes a reduction of sediment connectivity on the upper slope unlike on the lower slope where it is increased. Describing sediment structural connectivity through landscape structure analysis allows to identify the drainage infrastructures efficiency and might be of interest in a management perspective.

How to cite: Pic, J., Fressard, M., and Cossart, É.: Assessment of sediment connectivity in a densely drained vineyard catchment: contributions from graph theory, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6960, https://doi.org/10.5194/egusphere-egu22-6960, 2022.

Large wood (LW) has earned increased attention as a component of fluvial systems as its ecological and physical benefits, as well as its contributions to damages during flood events, have been realized. As LW found in river networks had originated from outside of the channel corridor, significant efforts have been made to identify recruitment processes that supply LW to channels. Evidence has proved treefall, landslides, bank erosion, debris flows, and fluvial entrainment contribute to LW recruitment. Prediction and identification of the areas prone to these processes are very challenging but could serve to better understand wood dynamics. Therefore, identifying areas prone to recruitment processes, estimating available LW, and determining LW connections in a watershed will help design management strategies aimed at mitigating LW’s impacts as well as provide insight on the movement and recruitment of LW in fluvial systems. Analogous challenges exist when dealing with sediment dynamics.

We applied the graph theory (GT) to instream LW supply and transfer. A GT is a set of nodes representing different entities (i.e., wood sources) with edges connecting nodes based on determined relationships (i.e., wood recruitment processes). The GT proves useful in exploring landscape connectivity with the capability of identifying critical nodes or regions, measuring properties of connectivity, identifying process coupling based on spatial patterns, and defining related geomorphological processes such as that of sediment cascades in which landscape components are coupled based on properties effecting sediment transfer.

GT proves capable of defining connections between LW recruitment from hillslopes to the channel and from channel segment to channel segment. Currently, the fuzzy logic toolbox presented by Ruiz-Villanueva and Stoffel (2018) has been utilized to delineate the connected, recruitment process prone areas for landslides, debris flows, and bank erosion in the study area of Vallon de Nant, Canton of Vaud, Switzerland. The delineated areas have been used in ArcPro in coalition with vegetation data to extract hillslope-to-channel connections and channel-to-channel connections. The channel or fluvial network has been segmented based on the presence of features which reduce downstream transfer of LW such as channel widening and presence of obstructions. The determined connections will be applied in the R package, igraph, to extract network properties of the constructed, instream LW GT model.

GT aids complex network analyses by providing a technique which retains only the critical information. Therefore, following the rigorous work of determining the system components, connections, and constructing the graph model, additional analysis can be performed with streamlined performance. Through our graph representation of instream LW supply and transfer, we plan to use the mathematical framework and algorithms from graph theory to further our understanding of instream LW such as the likely origins based on cost analysis.

“This work is supported by the SNSF Eccellenza project PCEFP2-186963 and the University of Lausanne.”

Ruiz-Villanueva, V., Stoffel, M. (2018). Application of fuzzy logic to large organic matter recruitment in forested river basins. Proceedings of the 5th IAHR Europe Congress New Challenges in Hydraulic Research and Engineering, 467-468. doi:10.3850/978-981-11-2731-1_047-cd

How to cite: Finch, B. and Ruiz-Villanueva, V.: Exploring the potential of the Graph Theory to large wood supply and transfer in river networks, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8232, https://doi.org/10.5194/egusphere-egu22-8232, 2022.

The present study deals with the hydrology of two adjoining watersheds, located in an area where average annual rainfall is ~280 mm. One watershed is located in a loess covered area, and the second in a rocky area. Hydrological data collected in the loess area point to a very high frequency of channel flow. However, even in extreme rain events, peak discharges are extremely low, pointing to a limited contributing area. The explanation proposed is that runoff generation is limited to the channel area, where a quasi-permanent seal, very rich in dispersive clays, responds quickly to low rain intensities. The contribution of the adjoining hillslopes is negligible. The hydrological regime in the rocky area is opposite. The frequency of overland flow is very high. 
However, channel flow did not develop, even in an extreme rain event of 105 mm with peak rain intensities of 90 mm/h1 in 2 min. The hydrological dis-connectivity at the-hillslope-channel interface is explained by the local rainfall characteristics. Rainstorms are highly intermittent, and the concentration time required for a continuous flow, along a whole slope, is much longer than the duration of most effective intermittent rain showers. Data obtained limit the possibility of extrapolation hydrological data from one area to another, under the same rainfall regime.

How to cite: Yair, A.: Contrasting hydrological regimes in two adjoining semi-arid areas, with low rain intensities, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11085, https://doi.org/10.5194/egusphere-egu22-11085, 2022.

The active portion of river networks varies in time thanks to event-based and seasonal cycles of expansion-retraction, mimicking the unsteadyness of the underlying climatic conditions. These rivers constitute a major fraction of the global river network, and are usually referred to as temporary streams.
Channel network dynamics have significant implications in catchment hydrology an beyond, including ecological dispersion, stream metabolism and greenhouse gas emissions. Moreover, temporary streams provide a unique contribution to riverine ecosystems, as they host unique habitats that are capable of promoting biodiversity. Nonetheless, to date the complex ways in which the temporal dynamics of the active portion of a stream network affect ecological processes and ecosystem services are not fully understood. In this contribution, we present a stochastic framework for the coupled simulation temporary stream dynamics and the related occupancy of a metapopulation. The framework combines a stochastic model for the generation of synthetic streamflow time series with the hierarchical structuring of river network dynamics, to enable the simulation of the full spatio-temporal dynamics of the active portion of the stream network under a wide range of climatic settings on the basis of a limited number of physically meaningful parameters. The hierarchical nature of stream dynamics - which postulates that during wetting nodes are activated sequentially  from the most to the least persistent, and deactivated in reverse order during drying - represents a key feature of the approach, as it enables a clear separation between the spatial and temporal dimensions of the problem. The framework is complemented with a stochastic dynamic metapopulation model that simulates the occupancy of a metapopulation on the simulated stream. Our results show that stream intermittency negatively impacts the average occupancy and the probability of extinction of the focus metapopulation. Likewise, the spatial correlation of flow persistency along the network also bears a significant impact on the mean network connectivity and occupancy. This effect is particularly important in drier climates, where most of the network undergoes sporadic and flashy activations, and species dispersal is therefore inhibited by river fragmentation most of the time. The approach offers a robust but parsimonious mathematical framework for the synthetic simulation of the spatio-temporal dynamics of the active stream network under a broad range of climatic and morphological conditions, providing useful insights on  stream expansion and retraction and its ecological significance.

How to cite: Durighetto, N., Bertassello, L. E., and Botter, G.: A Bayesian hierarchical model of channel network dynamics reveals the impact of stream dynamics and connectivity on metapopulation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12014, https://doi.org/10.5194/egusphere-egu22-12014, 2022.

Runoff generation and the consequent overland flow result from the interactions between gravity-driven flow over complex topography, Earth’s roughness, and infiltration. These processes mostly occur at small spatio-temporal scales, but aggregate throughout the landscape to produce a hydrodynamic response at catchment and stream scales during a rainfall event. While this response is highly transient and spatially heterogeneous, it is mostly studied through aggregated signatures, such as hydrographs. It is therefore of importance to understand how the hydrodynamic response builds up across scales in the landscape into such signatures. Arguably, hydrological (dis)connectivity, which describes how different parts of a hydro-system (dis)connect through fluxes, is a useful concept to describe this multiscale behaviour. In this contribution, we explore the dynamic connectivity behaviour of surface runoff in first order catchments (ranging between 0.06 and 15 km²) in response to singular rainfall events. We further analyse the connectivity response, mainly in terms of the number of disconnected clusters and the flooded areas, together with hydrological signatures. To do this, we use the GPU-enabled shallow water solver SERGHEI-SWE, which allows us to solve the shallow water equations at below-metre resolution (with tens of millions of grid cells per catchment). The extremely high spatial resolution of the model accurately captures spatial heterogeneity of topography and surface properties and thus, correctly represents the structural connectivity of the system. In the same manner, the hydrodynamics obtained on these high-resolution grids accurately capture the dynamic connectivity. Based on the simulated water depths, we assess dynamic connectivity at different spatial scales, and at different stages of runoff development, and study how the connectivity properties vary in different catchments. Furthermore, we perform a first analysis of how connectivity changes with scale and its relation to hydrological signatures and catchment features. Additionally, we explore the effects of coarser resolution simulations on dynamic connectivity on the same catchments.

How to cite: Özgen-Xian, I., Morales-Hernández, M., and Caviedes-Voullième, D.: Exploring dynamic (dis)connectivity of surface runoff on multiple catchments through a shallow water model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12905, https://doi.org/10.5194/egusphere-egu22-12905, 2022.