BankfullMapper: a semi-automated MATLAB tool on high-resolution digital terrain models for spatio-temporal monitoring of bankfull geometry and discharge

Abstract

ABSTRACT Understanding river channel bankfull geometry is crucial for fluvial monitoring and flood prediction. The bankfull stage marks the point where water spills onto the floodplain, typically occurring every 1-2 years. The corresponding discharge significantly influences channel morphology and characteristics, making it vital for river management and hazard assessment. In our study, we present a novel approach for detecting river channel bankfull levels, utilizing a specialized MATLAB tool we developed, called BankfullMapper. Dividing the river into evenly spaced sections, we extract bankfull geometry by computing a hydraulic depth function for each section. This function plots the elevation above the river thalweg against the area-to-width ratio, highlighting points that correspond to the bankfull stage. It does so by identifying either: (i) the lowest breakpoints from the thalweg or (ii) the most prominent breakpoints. Additionally, by applying Manning’s equation, the function can estimate the bankfull discharge. We applied the method to two Italian rivers - Potenza and Marecchia - which represent contrasting hydrological conditions, from single-channel systems with varying sinuosity (Potenza) to multi-channel braided and wandering systems (Marecchia). These sites were selected also to assess the method's capability to detect spatial and temporal variations in bankfull geometry and discharge. Specifically, Potenza River was used to evaluate the method’s spatial analysis performance, while Marecchia River enabled assessment of its spatio-temporal capabilities. We validated the modeled bankfull extent against expert-mapped active channel polygons using accuracy, precision, sensitivity, and specificity metrics. For the Potenza River, discharge estimates were also compared to gauge data (2010–2023) with a Gumbel distribution to assess model reliability. It consistently estimated bankfull discharges between 33.9 and 52 m 3 s -1 , closely matching discharge measurements. In the Potenza River, the method demonstrated high accuracy (0.92–0.90), sensitivity (0.95–0.94), and specificity (0.92–0.89), with moderate precision (0.61–0.53). For the Marecchia River, analysis of the 2009 and 2022 datasets revealed high to moderate sensitivity (0.92–0.63) and specificity (0.89–0.73), good accuracy (0.83–0.80), and moderate precision (0.65–0.56), confirming the method’s robustness under complex, evolving channel morphologies. Overall, the results demonstrate that the semi-automated approach reliably captures both spatial and spatio-temporal dynamics of bankfull geometry and discharge across diverse river types. The method performed best when using the lowest morphological breakpoints along the thalweg. By focusing on morphological break detection, it provides detailed and accurate delineation of bankfull features, making it a valuable tool for hydrological studies and river management applications.

Topics & Concepts