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Article • GEOUSP 28 (1) • 2024 • https://doi.org/10.11606/issn.2179-0892.geousp.2024.196088.en linkcopy

Open-access Evaluation of the Main Variables that Influence the Sediment Connectivity Based on Applied Models

Evaluación de las principales variables que influyen en la conectividad de sedimentos basados en modelos aplicados

AuthorshipSCIMAGO INSTITUTIONS RANKINGS

    Abstract

    The hydro-sedimentological connectivity index determines the degree of possibility that sediments from a given area reach a control point. To understand the dynamics that occur with sediments, the use of variables that represent the morphology and environmental conditions involved in space and time is necessary. This research proposed the analysis of models, identifying the main variables that explain the connectivity of sediments and observing their influences and frequency of use. Based on 35 specific articles that addressed sediment connectivity models, an important representativeness of the use of digital elevation models was found in 85% of the studies, emphasizing slope variables, drainage area, and land use and cover. Roughness was used only with tabulated data, despite being extremely important, thus being able to be an element to be detailed in new models.

    Keywords: Hydro-sedimentology; Connectivity Index; Hydro-sedimentological parameters; Hydro-sedimentological methods

    Resumen

    El índice de conectividad hidrosedimentológica determina el grado de posibilidad de que los sedimentos de una zona determinada lleguen a un punto de control. Comprender la dinámica que ocurre con los sedimentos requiere el uso de variables que representen la morfología y las condiciones ambientales involucradas en el espacio y el tiempo. Esta investigación propuso el análisis de modelos, identificando las principales variables que explican la conectividad de los sedimentos y observando sus influencias y frecuencia de uso. A partir de 35 artículos específicos que abordaron modelos de conectividad de sedimentos, se encontró una representatividad importante del uso de modelos digitales de elevación en el 85% de los trabajos, con énfasis en variables de pendiente, área de drenaje, además del uso del suelo. La rugosidad, a pesar de ser sumamente importante, se utilizó únicamente con datos tabulados, pudiendo así ser un elemento a detallar en nuevos modelos.

    Palabras Clave: hidrosedimentología; índice de conectividad; parámetros hidrosedimentológicos; métodos hidrosedimentológicos

    Resumo

    O índice de conectividade hidrossedimentológica determina o grau de possibilidade que os sedimentos de uma determinada área chegue a um ponto de controle. Compreender a dinâmica que ocorre com os sedimentos requer o uso de variáveis que representam a morfologia e as condições ambientais envolvidas no espaço e no tempo. Esta pesquisa propõe a análise de modelos, identificando as principais variáveis que explicam a conectividade de sedimentos e observando as influências e frequências de uso delas. Com base em 35 artigos específicos que trataram de modelos de conectividade de sedimentos, foi constatada uma representatividade importante do uso de modelos digitais de elevação em 85% dos trabalhos, com destaque para variáveis de declividade, área de drenagem, além do uso da terra. A rugosidade, apesar de extrema importância, foi usada apenas com dados tabelados, podendo assim ser um elemento a ser detalhado em novos modelos.

    Palavras-chave: hidrossedimentologia; índice de conectividade; parâmetros hidrossedimentológico; métodos hidrossedimentológicos

    Introduction

    Sedimentology addresses all the processes of production, transport, and deposition of sediments from their origin to the outlet of a basin or at a given reference point for analysis. This dynamic can occur through water, wind, the dragging movement of animals, or anthropic actions (Perry; Taylor, 2007; Oliveira, 2023; Mahoney; Fox, 2024). To understand sedimentological processes (also studied by Rodrigues, 2015), recent studies have employed computational models and/or developed indices that can represent the dynamics of sediments along the watershed. These examples are presented in this article. These models were built with available data input depending on the objective and the study area. These are addressed as variables in this article and considered input parameters for some authors.

    As part of Sedimentology studies, connectivity has been gaining ground, as reported in a literature review addressing sediment dynamics (Najafi et al., 2021). According to the authors, most studies focused on static characteristics and not on dynamic aspects of connectivity, developing methods and indices based especially on structures and placing functional connectivity-basically related to sediment transport processes-at the margin of the studies. With the evolution of these, the concepts to define sediment connectivity emerged, such as water transfer mediated by matter, energy, and/or organisms within or between the elements of the hydrological cycle (Pringle, 2001); passage of water between compartments of the landscape from runoff in the basin, affecting biological processes and sediment movement (Bracken et al., 2013); estimation of the potential connection between the eroded sediment on the slopes and the stream system (Borselli; Cassi; Torri, 2008); integrated transfer of sediment throughout the basin, from any possible source to a given control point in a system, where the transport vector is solely and exclusively water, with links along the sediment cascade (Zanandrea; Kobiyama; Michel, 2017).

    Sediment connectivity works with both structural and functional components. Structural connectivity is related to physical characteristics, such as slope, land use and cover, drainage area, surface roughness, and sediment characteristics. Functional components, in turn, are related to characteristics such as soil erosion, transport, sediment deposition, surface runoff, and precipitation (NAJAFI et al., 2021). One of the first models to calculate sediment connectivity by an index was proposed by Borselli, Cassi, and Torri (2008), using topographic characteristics and land use and cover and with the support of Geographic Information Systems (GIS). The LAPSUS model (Research, 2018), which applies kinematic wave theory to simulate erosion and deposition by surface flow, was used with six digital elevation models with different characteristics to evaluate the relationship of different landforms with sediment connectivity. The results confirmed that the relationship is not linear and that rainfalls may have different importance depending on the complexity of the landscape (Baartman et al., 2013).

    Sediment production, connectivity, and delivery ratio are strongly related, but some significant differences can be identified. Sediment production quantifies mass in space and time by mathematical models using equations consolidated in the literature (Carvalho, 2008). The sediment delivery ratio (SDR) determines the fraction of all eroded sediment in the watershed outlet (Minella; Merten; Clarke, 2009). Sediment connectivity only depends on morphology for its determination. However, other variables can be used to calculate connectivity (Zanandrea et al., 2020).

    By several articles reviewed within the topic of sediment connectivity, Najafi et al. (2021) organized the studies into five different categories: (1) development of conceptual structures; (2) representation of spatial and temporal distribution of sediment source and sink areas; (3) development of sediment connectivity indices; (4) use and development of models; or (5) investigation of the probability of sediment delivery by a network analysis approach.

    Studies have been developed using geomorphological and morphometric data, such as the length of the sediment transport path, terrain slope, drainage area, and surface roughness, derived from digital terrain model (DTM). This high number of research using these DTM data can be explained by the evolution of Geographic Information System (GIS) applications, which facilitate and streamline the processes of using these data. These applications can be observed in older articles such as Fryirs et al. (2007) and Borselli, Cassi, and Torri (2008).

    Among the diverse variables applied in the models, some had greater frequency, and others were specific to the sediments, which were the targets of analysis and observations in this study. Based on the search for studies that applied models related to sediment connectivity, the proposal of this article is a literature review aiming at analyzing and discussing the main variables applied, based on a grouping of hydrological, geomorphological, and sedimentological variables, to identify possible gaps for future research.

    Materials and methods

    This study reviews the analytical scientific literature regarding the models applied for sediment connectivity analysis. The search and selection of reference information for this study was done using the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) database, Google Scholar, and Science Direct. We selected only articles published from 2000 to 2023 as a search criterion. Among the articles found on Sedimentology, those that used sediment connectivity models to analyze the parameters applied in the methodology were identified, which served as the basis for the discussion of this study. After identifying the articles, the main variables used in the models were selected to observe the frequency of application by the studies.

    At first, we grouped the variables of interest into hydrological (precipitation, erosivity, antecedent precipitation, infiltration rate, surface runoff), geomorphological (drainage length, slope, drainage area, topographic factor, terrain roughness), sedimentological (sediment density, soil erodibility, sediment granulometry, sediment cohesion, suspended solids, and soil loss), and land use and cover. We created a spreadsheet to organize and identify the variables applied in the articles and thus calculate the appropriate proportions.

    The identification of the data used as input in the models to meet the objectives of each study is understood as variables. Notably, other variables are applied in the models and not previously reported because they are not common to all articles analyzed. Once the articles were selected, the following aspects were identified and tabulated: the model used, an objective definition of the study, the resolution of the digital elevation model (DEM) applied, the variables used, and the group that the variables belong to.

    Regarding the database search, 831 articles containing the term “sediments” were identified at CAPES, 105 at Google Scholar, and 835 at Science Direct, all in the past 24 years. When we restricted the search to “sedimentological models,” the number of articles was considerably reduced, totaling 70 articles at CAPES, 371 at Google Scholar, and 645 at Science Direct. Finally, with one more keyword, “hydro-sedimentology,” the search found 40 articles at CAPES, 1,650 at Google Scholar, and none at Science Direct. In the end, 35 articles addressed the application of sedimentological connectivity models to analyze and discuss the parameters applied in the connectivity models.

    Results and discussions

    During the analyses, studies applied more than one model, and some adaptations were observed (Table 1).

    Thumbnail
    Table 1 -
    Relationship of sediment connectivity assessment models.

    The first sedimentology study recorded in Brazil was carried out by the Companhia Estadual de Energia Elétrica (CEEE) on the Camaquã River in the state of Rio Grande do Sul, aiming to predict siltation and calculate the useful life of the reservoir of the Paredão powerplant (Carvalho, 2008). However, regarding specificity with the sediment connectivity process, research is more recent (Zanandrea, 2017). The chronological evolution of scientific production related to sediment connectivity was reported by 142 studies and shown in Figure 1, highlighting 2017 as the apex (Najafi et al., 2021).

    Figure 1 -
    Evolution of scientific production for sediment connectivity.

    Among the articles evaluated, 43% applied the basis of the model proposed by Borselli, Cassi, and Torri (2008) or adapted by Cavalli et al. (2013), and 69% cited Borselli, Cassi, and Torri (2008). This shows the importance of the proposal initiated by Borselli, which has been evolving and bringing new indices and elements to sediment connectivity modeling.

    By the groups in Table 2, 31% of the articles used hydrological data, 46% geomorphological data, 12% sedimentological data, and 11% land use and cover data. This reinforces the importance of geomorphological data. Also, 28% of the articles used at least one variable from each class, thus demonstrating a diversity in the use of variables.

    Thumbnail
    Table 2 -
    Proportion of applications of the variables in the evaluated studies

    Even with an extensive application of the variable drainage area (Table 2), this does not mean that the area value was used in the analyses as a possible influence on sediment dynamics. Although it is not considered a variable in the analyses, DEM is crucial information, and only one article did not use it as input data for the model. However, it is important to emphasize that some variables are derived from DEM, such as slope, ramp length, and drainage area, which justifies the wide use of this variable.

    Due to the great use of DEM in the applications, we highlighted the resolutions of the images used in the modeling. The use of images with spatial resolution above 5m was observed in most articles, as shown in Figure 2.

    Figure 2 -
    Range of image resolutions applied in the articles.

    Among the articles that used surface roughness, 60% applied tabulated values, either by Manning’s coefficient, C factor, or slope variation. The remainder (40%) used calculations based on residual topography with satellite imagery. Among the studies that applied a table of values for roughness, 73% used Manning’s coefficient. Only 10% of the studies employed roughness based on land use and cover with tabulated data. Considering the high proportion of roughness variables employed (91%), this variable draws attention to the value and different forms of use (tabulated or calculated). Although Manning’s coefficient is well-consolidated data in the articles, it is noteworthy that tabulated values may not reflect the reality of the areas, which may suggest studies to compare the use of roughness in its two forms of application (tabulated or calculated). Only one article employed the SWAT model application's integration with land use and cover, slope, and soil type data; however, it was used with secondary data (Mishra et al., 2019). Furthermore, the authors analyzed the influence of slope variation only related to watercourses and not the basin. Based on the articles evaluated, Figure 3 presents the distribution of the methods applied to use roughness.

    Figure 3 -
    Methods applied for roughness.

    Conclusions

    Given the observations in the analyzed references, the authors converge to a consensus that sedimentological connectivity is a complex term where diversity, correlations between parameters, and the dynamics of sediments in a region can be the main obstacles in developing sedimentological connectivity models. Thus, the literature agrees that the evidence in the processes of sedimentological connectivity is limited and that there are still several gaps to be filled, such as using more parameters of functional elements or improving the representation of surface roughness. In addition to these limiting points, research tends to focus more on the structural component than on the functional component. Thus, it opens opportunities for future research to employ the variables of this component.

    Despite the great potential of employing sedimentological connectivity associated with slope - which holds significant importance in connectivity processes - a more careful analysis of the relation between the variation of slopes and its influence over connectivity was not observed.

    The use of geomorphological data, especially based on digital elevation models, is well consolidated in the literature, with the quality of the results standing out due to the spatial resolutions of the images. Therefore, these data can be better used and enhanced with drone imaging and more accurate photogrammetric processes, especially with those presenting smaller pixel sizes, reaching up to 0.05 m. Nevertheless, evaluating the current computational capacity limitations and feasibility in terms of processing time is important.

    Only 12% of the articles studied applied these parameters when sedimentological parameters were observed. Notably, the parameters corresponding to density and cohesion were little used in the models, which does not eliminate their significance. Thus, searching for new models focusing on sedimentological parameters will open paths for future observations and a better understanding of sediment dynamics.

    With a significant amount of parameters applied in the models, none of the studies discussed the relative importance of each one in the proper models. Important information that can direct future research better to understand the processes of the most sensitive variables.

    Acknowledgements

    This research was supported by Fundação de Amparo à Pesquisa de Minas Gerais (FAPEMIG, doctoral scholarship to WLO), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, research productivity grant to DRM), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES, Finance Code 001).

    REFERENCES

    • ASADI, H.; DASTORANI, M. T.; SIDLE, R. C. Estimating index of sediment connectivity using a smart data-driven model. Journal of Hydrology, v. 620, Parte A, p. 129467, 2023.
    • BAARTMAN, J. E. M. et al Linking landscape morphological complexity and sediment connectivity. Earth Surface Processes and Landforms, v. 38, n. 12, p. 1457-1471, 2013.
    • BORSELLI, L.; CASSI, P.; TORRI, D. Prolegomena to sediment and flow connectivity in the landscape: A GIS and field numerical assessment. Catena, v. 75, n. 3, p. 268-277, 2008.
    • BRACKEN, L. J. et al Concepts of hydrological connectivity: Research approaches, Pathways and future agendas. Earth-Science Reviews, v. 119, p. 17-34, 2013.
    • BYWATER-REYES, S.; SEGURA, C.; BLADON, K. D. Geology and geomorphology control suspended sediment yield and modulate increases following timber harvest in temperate headwater streams. Journal of Hydrology, v. 548, p. 74-83, 2017.
    • CALSAMIGLIA, A. et al Changes in soil quality and hydrological connectivity caused by the abandonment of terraces in a Mediterranean burned catchment. Forests, v. 8, n. 9, p. 1-20, 2017.
    • CARVALHO, N. de O. Hidrossedimentologia Prática. 2. ed. Rio de Janeiro: Editora Interciência, 2008.
    • CAVALLI, M. et al Geomorphometric assessment of spatial sediment connectivity in small Alpine catchments. Geomorphology, v. 188, p. 31-41, 2013.
    • CISLAGHI, A.; BISCHETTI, G. B. Source areas, connectivity, and delivery rate of sediments in mountainous-forested hillslopes: A probabilistic approach. Science of the Total Environment, v. 652, p. 1168-1186, 2019.
    • COULTHARD, T. J.; VAN DE WIEL, M. J. Modelling long term basin scale sediment connectivity, driven by spatial land use changes. Geomorphology, v. 277, p. 265-281, 2017.
    • CROKE, J.; FRYIRS, K.; THOMPSON, C. Channel-floodplain connectivity during an extreme flood event: Implications for sediment erosion, deposition, and delivery. Earth Surface Processes and Landforms, v. 38, n. 12, p. 1444-1456, 2013.
    • DE WALQUE, B. et al Artificial surfaces characteristics and sediment connectivity explain muddy flood hazard in Wallonia. Catena, v. 158, p. 89-101, Nov. 2017.
    • DI STEFANO, C.; FERRO, V. Assessing sediment connectivity in dendritic and parallel calanchi systems. Catena, v. 172, p. 647-654, Jan. 2019.
    • DUVERT, C. et al Baseflow control on sediment flux connectivity: Insights from a nested catchment study in Central Mexico. Elsevier, v. 87, p. 129-140, 2011.
    • FRESSARD, M.; COSSART, E. A graph theory tool for assessing structural sediment connectivity: Development and application in the Mercurey vineyards (France). Science of the Total Environment, v. 651, p. 2566-2584, 2019.
    • FRYIRS, K. A. et al Buffers, barriers and blankets: The (dis)connectivity of catchment-scale sediment cascades. Catena, v. 70, n. 1, p. 49-67, 2007.
    • GRAN, K. B.; CZUBA, J. A. Sediment pulse evolution and the role of network structure. Geomorphology, v. 277, p. 17-30, 2015.
    • GRAUSO, S.; PASANISI, F.; TEBANO, C. Assessment of a simplified connectivity index and specific sediment potential in river basins by means of geomorphometric tools. Geosciences (Switzerland), v. 8, n. 2, 2018.
    • KALANTARI, Z. et al Flood probability quantification for road infrastructure: Data-driven spatial-statistical approach and case study applications. Science of the Total Environment, v. 581-582, p. 386-398, 2017.
    • LISENBY, P. E.; FRYIRS, K. A. Sedimentologically significant tributaries: catchment-scale controls on sediment (dis)connectivity in the Lockyer Valley, SEQ, Australia. Earth Surface Processes and Landforms, v. 42, n. 10, p. 1493-1504, 2017.
    • LIU, W. et al Evaluating sediment connectivity and its effects on sediment reduction in a catchment on the Loess Plateau, China. Geoderma, v. 408, p. 115566, 2022.
    • LIU, Y.; FU, B. Assessing sedimentological connectivity using WATEM/SEDEM model in a hilly and gully watershed of the Loess Plateau, China. Ecological Indicators, v. 66, p. 259-268, 2016.
    • LLENA, M. et al The effects of land use and topographic changes on sediment connectivity in mountain catchments. Science of the Total Environment, v. 660, p. 899-912, 2019.
    • LÓPEZ-VICENTE, M.; BEN-SALEM, N. Computing structural and functional flow and sediment connectivity with a new aggregated index: A case study in a large Mediterranean catchment. Science of the Total Environment, v. 651, p. 179-191, 2019.
    • MAHONEY, D. T.; FOX, J. F.; AL AAMERY, N. Watershed erosion modeling using the probability of sediment connectivity in a gently rolling system. Journal of Hydrology, v. 561, p. 862-883, 2018.
    • MAHONEY, D. T.; FOX, J. F. Quantification of bedrock structural controls of longitudinal sediment connectivity using the probability of connectivity and sediment continuity model. Geomorphology, v. 448, p. 109027, 2024.
    • MASSELINK, R. et al Assessing hillslope-channel connectivity in an agricultural catchment using rare-earth oxide tracers and random forests models. Cuadernos de Investigación Geográfica, v. 43, n. 1, p. 17, 2017.
    • MESSENZEHL, K.; HOFFMANN, T.; DIKAU, R. Sediment connectivity in the high-alpine valley of Val Müschauns, Swiss National Park - linking geomorphic field mapping with geomorphometric modelling. Geomorphology, v. 221, p. 215-229, 2014.
    • MINELLA, J. P. G.; MERTEN, G. H.; CLARKE, R. T. Método “ fingerprinting ” para identificação de fontes de sedimentos em bacia hidrográfica rural Fingerprinting method for identification of sediment sources in a rural watershed. Revista Brasileira de Engenharia Agrícola e Ambiental, v. 13, n. 5, p. 633-638, 2009.
    • MISHRA, K. et al Towards the assessment of sediment connectivity in a large Himalayan river basin. Science of the Total Environment, v. 661, p. 251-265, 2019.
    • NAJAFI, S. et al Sediment connectivity concepts and approaches. Catena, v. 196, p. 104880, 2021.
    • OLIVEIRA, Leon Dias. Análise estratigráfica das formações Serra do Catuni e Chapada Acauã inferior, grupo macaúbas, ao longo do paralelo 17°30’S, região Centro-Oeste de Minas Gerais. Dissertação (Mestrado em Evolução Crustal e Recursos Naturais) - Escola de Minas, Universidade Federal de Ouro Preto, Ouro Preto, 2023.
    • ORTÍZ-RODRÍGUEZ, A. J.; BORSELLI, L.; SAROCCHI, D. Flow connectivity in active volcanic areas: Use of index of connectivity in the assessment of lateral flow contribution to main streams. Catena, v. 157, p. 90-111, Oct. 2017.
    • PECHENICK, A. M. et al A multi-scale statistical approach to assess the effects of connectivity of road and stream networks on geomorphic channel condition. Earth surface processes and landforms, v. 39, p. 1538-1549, 2014.
    • PERRY, C.; TAYLOR, K. Environmental Sedimentology. Journal of Soils and Sediments, v. 7, n. 6, p. 460, 2007.
    • PERSICHILLO, M. G. et al The role of human activities on sediment connectivity of shallow landslides. Catena, v. 160, p. 261-274, Jan. 2018.
    • PRINGLE, C. M. Hydrologic Connectivity and the Management of Biological Reserves: A Global Perspective. Ecological Applications, v. 11, n. 4, p. 981, 2001.
    • RATHBURN, S. L.; SHAHVERDIAN, S. M.; RYAN, S. E. Post-disturbance sediment recovery: Implications for watershed resilience. Geomorphology, v. 305, p. 61-75, 2018.
    • RESEARCH, W. U. Software LAPSUS, 2018. Disponível em: https://www.wur.nl/en/Research-Results/Chair-groups/Environmental-Sciences/Soil-Geography-and-Landscape-Group/Research/LAPSUS/Downloads-and-Updates.htm Acesso em: 10 maio 2022.
      » https://www.wur.nl/en/Research-Results/Chair-groups/Environmental-Sciences/Soil-Geography-and-Landscape-Group/Research/LAPSUS/Downloads-and-Updates.htm
    • RODRIGUES, C. Atributos ambientais no ordenamento territorial urbano. O exemplo das planícies fluviais na Metrópole de São Paulo. GEOUSP Espaço e Tempo (Online), v. 19, n. 2, p. 324-347, 2015.
    • TOBIAS, H.; WOLFGANG, S. Geomorphic coupling and sediment connectivity in an alpine catchment - Exploring sediment cascades using graph theory. Elsevier, v. 182, p. 89-103, 2013.
    • TURNBULL, L.; WAINWRIGHT, J. From structure to function: Understanding shrub encroachment in drylands using hydrological and sediment connectivity. Ecological Indicators, v. 98, p. 608-618, Mar. 2019.
    • ZANANDREA, F. et al Conectividade dos Sedimentos: Conceitos, Princípios e Aplicações. Revista Brasileira de Geomorfologia, v. 21, n. 2, p. 0-3, 2020.
    • ZANANDREA, F.; KOBIYAMA, M.; MICHEL, G. P. Conectividade Hidrossedimentológica: Uma Abordagem Conceitual. In: SIMPÓSIO BRASILEIRO DE RECURSOS HÍDRICOS, 22., 2017, Florianópolis, 2017. Anais [...]. Porto Alegre : ABRH, 2017. p. 1-8.
    • ZINGARO, M. et al Sediment mobility and connectivity in a catchment: A new mapping approach. Science of the Total Environment, v. 672, p. 763-775, 2019
    • Financial Disclosure
      This research was supported by Fundação de Amparo à Pesquisa de Minas Gerais (FAPEMIG, doctoral scholarship to WLO), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, research productivity grant to DRM), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES, Finance Code 001).

    Edited by

    • Section editor:
      Fernando Villela

    Publication Dates

    • Publication in this collection
      01 July 2024
    • Date of issue
      2024

    History

    • Received
      01 Nov 2022
    • Accepted
      22 Nov 2023
    Creative Common - by 4.0
    This is an open-access article distributed under the terms of the Creative Commons Attribution License
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