Lawrence V. Stanislawski

USGS2026

Estimating baseline flow resistance parameters for remote sensing river discharge (RSQ) from river morphology characteristics

This study demonstrates that flow resistance in rivers, quantified via calibration of a modified Manning equation, can be estimated from channel hydrometric information available from globally derived data sets for a subset of river reaches in Alaska and with less certainty in a subset of river reaches in the contiguous United States. The channel morphometry data sets tested include the National Aeronautics and Space Administration (NASA) Surface Water Ocean Topography (SWOT) river database (SWORD) and U.S. Geological Survey (USGS) Scale Specific Sinuosity (S3) river channel morphometry metrics. It is found that for the subset of rivers considered, the meander length, number of active channels, maximum width, width variance, and slope of the channel are strongly correlated with the flow resistance term in the Manning equation. Analytical machine learned models were derived, and a statistical multiple regression model developed to map the flow resistance in rivers across Alaska that are contained in the SWORD data base. The study points to the possibility of global a priori estimation of flow resistance in rivers for application in remote sensing of river discharge from river water surface-width, slope and height measurements made by SWOT and other satellites.

Journal of the American Water Resources Associatio↗

USGS2026

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↗