Predicting sediment connectivity in a mountain basin: A quantitative analysis of the index of connectivity. Issue 6 (9th February 2022)

• Record Type: Journal Article
• Authors: Martini, Lorenzo; Cavalli, Marco; Picco, Lorenzo
• Is Part Of: Earth surface processes and landforms. Volume 47:Issue 6(2022)
• Page Start: 1500
• Page End: 1513
• Publication Date: 2022-02-09
• Subjects: index of connectivity -- logistic regression -- mountain basin -- sediment connectivity -- sediment source areas; Geomorphology -- Periodicals; 551.4
• DOI: 10.1002/esp.5331
• Languages: English
• ISSNs: 0197-9337

Abstract

Abstract: Sediment connectivity underlies the relationships between sediment source areas and stream network and the use of topography‐based indices, such as the index of connectivity (IC), has become a common approach to investigate these relationships. However, few studies have tested the potential of the IC as an independent variable for predicting observable processes. In this study, the aim is the validation of the IC as a semi‐quantitative tool for depicting structural connectivity and predicting sediment dynamics linking sediment sources to the channel network after a large infrequent disturbance in the Rio Cordon catchment (Italy). First, the assessment of lateral connectivity was carried out using a combination of remote sensing data and field observations. In this way, it was possible to classify the sediment sources into disconnected, connected or functionally connected. Second, logistic regression analyses were performed using different IC variants, with different weighting factors and spatial resolutions as independent variables and connectivity status as dependent variable. Hence, the predictive capacity of the IC was tested and a threshold was derived to distinguish between low and high sediment connectivity. The results showed that only 15% of sediment sources are connected to the stream network. Moreover, the IC proved to be a reliable tool for depicting structural connectivity when using surface roughness as weighting factor and high‐resolution digital terrain models. On the contrary, it failed at predicting sediment dynamics as it did not classify correctly the functionally connected areas, so it cannot infer functional sediment connectivity in this case study. As a consequence, it was possible to obtain an IC threshold of −2.32, capable of differentiating between low and high structural sediment connectivity and useful for future management decisions. The threshold, in fact, represents an objective boundary between disconnected and connected sources in the Rio Cordon catchment. Abstract : This study validated the index of connectivity (IC) as a semi‐quantitative tool to depict structural connectivity between sediment source areas and stream network in a mountain basin. As result, it was possible to derive an IC threshold to distinguish high and low sediment connectivity areas in a more objective way. On the contrary, the IC is unable to predict event‐based sediment dynamics.