Sediment residence time and connectivity in non-equilibrium and transient geomorphic systems

Hoffmann, Thomas

doi:10.1016/j.earscirev.2015.07.008

Cited by 121 publications

(93 citation statements)

References 135 publications

(235 reference statements)

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“…Several papers have already addressed the assessment of connectivity (Borselli et al, 2008;Cavalli et al, 2013;Czuba and Foufoula-Georgiu, 2015;Gran and Czuba, 2017;Hoffmann, 2015), so we focus here on the potential improvements offered by graph theory. Following Heckmann and Schwanghart (2013), a graph provides both a geometric and an algebraic description of the sediment cascade network.…”

Section: Discussionmentioning

confidence: 99%

“…In this respect, the SDR has been interpreted as a simple "performance" factor to relate erosion measured at the plot scale to sediment yields observed at the larger scale. Its usefulness has been critically discussed (Hoffmann, 2015). To open such black boxes, the concept of connectivity was subdivided into two distinct parts Tischendorf and Fahrig, 2000;Turnbull et al, 2008).…”

Section: State Of the Artmentioning

confidence: 99%

“…For instance, Ali and Roy (2009) stated that hydrological connectivity can be quantified as a function of the available water volume (calculated from a hydrological balance) and the rate of transfer. More recently, connectivity has appeared as a fruitful conceptual framework in geomorphology (Brierley et al, 2006;Wainwright et al, 2011;Fryirs, 2013;Hoffmann, 2015). It helps in studying the spatiotemporal unsteadiness of sediment transport within catchments and why sediment cascades can be considered a "jerky conveyor belt" (Ferguson,254 É. Cossart and M. Fressard: Assessment of structural sediment connectivity within catchments 1981).…”

Section: Introductionmentioning

confidence: 99%

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Assessment of structural sediment connectivity within catchments: insights from graph theory

Cossart

Fressard

2017

Earth Surf. Dynam.

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Abstract.To describe the sedimentary signal delivered at catchment outlets, many authors now refer to the concept of connectivity. In this framework, the sedimentary signal is seen as an emergent organization of local links and interactions. The challenge is thus to open the black boxes that remain within a sediment cascade, which requires both accurate geomorphic investigations in the field (reconstruction of sequences of geomorphic evolution, description of sediment pathways) and the development of tools dedicated to sediment cascade modeling. More precisely, the development of tools devoted to the study of connectivity in geomorphology is still in progress, although graph theory offers promising perspectives (Heckmann and Schwanghart, 2013). In this paper, graph theory is applied to abstract the network structure of sediment cascades, keeping only the nodes (sediment sources, sediment stores, outlet) and links (linkage by a transportation agent), represented as vertices and edges. From the description of the assemblages of sedimentary flows, we provide three main indices to explore how small-scale processes may result in significant broad-scale geomorphic patterns. The main hypothesis guiding this work is that the network structure dictates how sediment inputs from various sources interact at tributary junctions and finally at the outlet of a cascading system. First, we use the flow index to assess the potential contribution of each node to the sediment delivery at the outlet. Second, we measure the influence of each node regarding how it is accessible from both sediment sources and the outlet (using the Shimbel index). Third, we propose a new connectivity index named "Network Structural Connectivity index" (NSC) revealing whether the potential contribution of a node is lower or higher than expected from its location within the network. These indices are first computed for a conceptual sediment cascade network and then applied to a catchment located in the southern French Alps. We demonstrate that this index may be used to simulate sediment transfer and help in identifying the hotspots of geomorphic change. In the present case, we try to predict how a sediment cascade may be impacted by an edge disruption or a reconnection.

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Section: Discussionmentioning

confidence: 99%

Section: State Of the Artmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Assessment of structural sediment connectivity within catchments: insights from graph theory

Cossart

Fressard

2017

Earth Surf. Dynam.

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“…An increase leads to higher erosion in both cases. However, the results are more sensitive to k r in comparison with k f as indicated by the higher SI 90 . An increase of k r by 90% leads to 10% higher total sediment yield while an increase of K f by 90% results in only 2.8% higher sediment yield.…”

Section: Model Sensitivitymentioning

confidence: 93%

“…where SI 90 is the sensitivity index, O 90 and O -90 the model output resulting from a parameter value increased or decreased by 90%, and O 0 the model output from the base run. A list of parameters to which the model output responds sensitively and the corresponding calibration ranges used in this study are given in Table 5.…”

Section: Model Sensitivity Calibration and Validationmentioning

confidence: 99%

Applying SHETRAN in a Tropical West African Catchment (Dano, Burkina Faso)—Calibration, Validation, Uncertainty Assessment

Hipt

Diekkrüger

Steup

et al. 2017

Water

Self Cite

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This study presents the calibration and validation of the physically based spatially distributed hydrological and soil erosion model SHETRAN for the Dano catchment, Burkina Faso. A sensitivity analysis of six model parameters was performed to assess the model response and to reduce the number of parameters for calibration. The hydrological component was calibrated and validated using observed discharge data of two years. Statistical quality measures (R 2 , NSE, KGE) ranged from 0.79 to 0.66 during calibration and validation. The calibrated hydrological component was used to feed the erosion modeling. The simulated suspended sediment load (SSL) was compared with turbidity-based measurements of SSL of two years. Achieved quality measures are comparable to other SHETRAN studies. Uncertainties of measured discharge and suspended sediment concentration were determined to assess the propagated uncertainty of SSL. The comparison of measurement uncertainties of discharge and SSL with parameter uncertainty of the corresponding model output showed that simulated discharge and SSL were frequently outside the large measured uncertainty bands. A modified NSE was used to incorporate measurement and parameter uncertainty into the efficiency evaluation of the model. The analyses of simulated erosion sources and spatial patterns showed the importance of river erosion contributing more than 60% to the total simulated sediment loss.

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2022

Geomorphology and the Carbon Cycle

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Sediment residence time and connectivity in non-equilibrium and transient geomorphic systems

Cited by 121 publications

References 135 publications

Assessment of structural sediment connectivity within catchments: insights from graph theory

Assessment of structural sediment connectivity within catchments: insights from graph theory

Applying SHETRAN in a Tropical West African Catchment (Dano, Burkina Faso)—Calibration, Validation, Uncertainty Assessment

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