Experimental Application of Sediment Flow Connectivity Index (SCI) in Flood Monitoring

Abstract

<jats:p>Sediment connectivity is considered a powerful geomorphic indicator for defining the most sensitive areas to geomorphological modifications in a fluvial catchment (hotspots). This encourages the development of methods and models for its assessment, to investigate the interrelation of the various phenomena that occur in a river basin (landslides, floods, etc.). This work explores the potential connection of the processes in flood dynamics, by focusing on induced flood hazard, in order to evaluate the applicability of sediment connectivity to flood monitoring. By applying the recently developed sediment flow connectivity index (SCI) computation method to the Severn River basin, in UK, recurrently affected by floods, we investigate the agreement between the hotspot areas (described by the index) and the areas recurrently flooded (as mapped by aerial photography, satellite imagery and hydrodynamic modelling). Qualitative and quantitative approaches are used for the analysis of past (March 2007 and January 2010) as well as predicted (with return periods of 200 and 500 years) flood events. The results show a good correspondence of areas of high sediment connectivity with flood occurrence. Moreover, the detection performance of the SCI is slightly better than that of a simple flow accumulation map, confirming the importance of the initial mapping of sediment availability and mobility. This experiment extends the direct applicability of the SCI from fluvial analysis to flood monitoring, thus opening interesting future scenarios.</jats:p>

Improving Flood Detection and Monitoring through Remote Sensing

“…The results demonstrate, among other things, how sediment deposition plays an important part in flood propagation. This is in line with other studies in this direction [3].…”

Suitability assessment of global, continental and national digital elevation models for geomorphological analyses in Italy

“…Thus, surface and terrain modeling became an advantageous ancillary method for visualizing and analyzing the spatial variability of surface processes, as proved by many studies (Dipanwita, Seghal, Kumar, & Sundara Sarma, 2011; Domeneghetti, 2016; Hani, Sathyamoorthy, & Asirvadam, 2011; Tarolli, Arrowsmith, & Vivoni, 2009; Zingaro et al., 2019). In fact, DEMs are widely applied in the various disciplines involved in the investigation of surface‐occurring phenomena such as geomorphology, geomatics, hydrology, archaeology, environmental and civil engineering, climatology, and others (Brancato, 2020; Durand et al., 2016; Fernández‐Lozano & Gutiérrez‐Alonso, 2016; Hou, Sun, Yang, & Sun, 2011; Kawabata & Bandibas, 2009; Ninyerola, Pons, & Roure, 2000; Zingaro et al., 2020).…”

Erosion Rate of the Aliano Biancana Badlands Based on a 3D Multi-Temporal High-Resolution Survey and Implications for Wind-Driven Rain

“…Even if the evolution of biancane is quite well known, their spatial continuous erosion rates are not easy to assess [17]. These rates are very important in terms of sediment (dis)connectivity on hillslopes and carbon dynamics [18,19]. In several studies, direct erosion measurements were made with pins placed in slightly accessible areas where piping was usually absent [8,[20][21][22][23].…”