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Margherita Lombardo

Publications and source records attributed to Margherita Lombardo.

2 recordsLinked to original sources

Linking scale-specific sinuosity to hydrogeomorphic domains in Alaska watersheds

River meander patterns arise from geomorphological processes influenced by climate, geology, terrain, and hydrology. These processes produce a wide spectrum of sinuous channel and meander forms, and understanding them is essential for land management practices, such as natural channel restoration (Dominguez et al., 2018), flood and erosion control, bank stabilization (U.S. Department of Interior, 2015), and riparian corridor and agricultural land management (Ran, et al., 2022; Yu, et al., 2023; Zhu et al., 2022). Studies of meander migration provide insight into sediment dynamics and river ecosystem health (Ielpi et al. 2023, Constantine et al., 2014). A river’s natural ability to clean itself, or reduce pollutants, through physical, chemical, and biological processes, also termed self-purification capacity, has been linked to river sinuosity (Xiao et al, 2019, 2025). Scale-specific sinuosity (S3) is an easily computed metric for characterizing planform meander bend geometry across a range of measurement scales (Stanislawski et al., 2023). Unlike the traditional single summary value of sinuosity for a stream section, S3 estimates the relative distribution of meander‑bend sizes, such as peak‑to‑trough lengths, within a planform linear representation of a stream section, along with the relative contributions of these bend sizes to its overall sinuosity. The aim of this study is to assess the potential of S3 as a diagnostic geomorphic metric with applications to process-based river and fluvial domain classification. Rivers vary widely in their sensitivity to change depending on sediment and bedload materials, landscape position, and hydroclimatic variability, including flooding or drought. River classification systems were developed to organize the diversity of river forms and processes in ways that support both scientific understanding and management needs. Classification provides a framework for geomorphological analyses related to resource assessment, habitat evaluation, and mitigation of natural or human-driven disturbances. Process-based classification systems help predict how channels respond to changes in flow or sediment regimes (Buffington and Montgomery, 2022), and also support resource exploration because ecological habitats, mineral deposits, and other natural resources often correspond to sediment characteristics that vary systematically across channel types (Rosgen, 1994; Wheaton et al., 2013; Wheaton et al., 2015). Planform-based metrics such as channel sinuosity have long been components of river classification systems (Rosgen, 1994; Wheaton et al., 2015; Buffington and Montgomery, 2022), where sinuosity is measured as a simple ratio of path length over end-to-end distance.

Alaska↗

Unravelling spatial heterogeneity of inundation pattern domains for 2D analysis of fluvial landscapes and drainage networks

Fluvial landscape analysis is an essential part of geomorphology, hydrology, ecology, and cartography. It is traditionally focused on the transition between hillslopes and channel domain, in which the network drainage is represented by static flow lines. However, the natural fluctuations of the processes occurring in the watershed induce lateral and longitudinal expansions and contractions in the drainage patterns and variations of stream surface area. These dynamics can be better understood by introducing a two-dimensional (2D) view of catchment hydrography, in which river width and floodplain are included in the analysis. The novelty introduced in this work is the development of a hydrodynamic hierarchical framework (HHF) to analyse the transitions among geomorphic and hydrographic features of the fluvial landscape, distinguishing hillslope, unchanneled valleys, floodplains, and single/multithreads channels. HHF is based on the estimation of nested inundation pattern domains (IPDs) from digital elevation models and 2D hydrodynamic modeling. IPDs are defined by scaling laws that characterize log–log relations between watershed drainage density and unit discharge thresholds extracted from a 2D direct rainfall method (DRM) under steady state solutions. The physical significance of the IPDs is analysed within the context of both the physiographic features of the fluvial landscape and the rainfall rates employed as input for the modeling approach. Initially, the spatial heterogeneity of the IPDs is used to derive stream width metrics as a function of the rainfall rate. Then, a spatial index, representative of the IPDs' heterogeneity, is introduced as a measure of the susceptibility of the drainage network surface area to expansion and contraction. Finally, the consistency of the results is assessed in comparison to another hydrodynamic-based method for fluvial landscape analysis recently proposed in the literature. The proposed approach is analysed using challenging mountain and low-relief environments, characterized by multithread channels, meander cut-offs, oxbow lakes, and extreme landscapes that feature glacial outwash, permafrost, and peatlands.

Alaska↗