DOI: 10.25349/d90g71
title: Data for: A generalized area-based framework to quantify river mobility from remotely sensed imagery

description: Rivers are the primary conduits of water and sediment across Earth’s
 surface. In recent decades, rivers have been increasingly impacted by
 climate change and human activities. The availability of global-coverage
 satellite imagery provides a powerful avenue to study river mobility and
 quantify the impacts of these perturbations on global river behavior.
 However, we lack remote sensing methods for quantifying river mobility
 that can be generally applied across the diversity of river planforms
 (e.g., meandering, braided) and fluvial processes (e.g., channel
 migration, avulsion). Here, we upscale area-based methods from laboratory
 flume experiments to build a generalized remote sensing framework for
 quantifying river mobility. The framework utilizes binary channel-mask
 time series to determine time- and area-integrated rates and scales of
 river floodplain reworking and channel-thread reorganization. We apply the
 framework to numerical models to demonstrate that these rates and scales
 are sensitive to specific river processes (channel migration, channel-bend
 cut-off, and avulsion). We then apply the framework to natural migrating
 and avulsing rivers with meandering and braided planforms. Results show
 that our area-based framework is an accurate method to quantify river
 mobility at reach- to landscape-scales, and is largely insensitive to
 spatial and temporal biases that can arise in traditional mobility
 metrics. Our work provides a framework for investigating global controls
 on river mobility, testing hypotheses about river response to
 environmental gradients, and quantifying the timescales of terrestrial
 organic carbon cycling.
description: This dataset includes all underlying data included in the
 manuscript. This includes results from numerical model runs, river channel
 masks used to estimate mobility, and measurements of mobility metrics for
 channel mask time series. <br><br>The contents are organized
 in a file structure following:<br>1) AvulsionModel: <br>This
 includes the avulsion model outputs as .mat files (Matlab proprietary
 files) for the model runs with varying avulsion trigger frequencies. We
 also included a Python script we use to generate equivalent binary channel
 masks from the .mat files and calculate mobility. <br><br>2)
 MeanderingModel: <br>This includes the outputs from the meandering
 river model for varying cutoff thresholds (cutoff_runs) as well as varying
 migration constants (migration_runs). We provide numpy objects (.npy),
 which contain the time series of binary raster grids depicting the channel
 changes through time. We also include Python scripts to calculate mobility
 and generate figures.<br><br>3)
 NaturalRiverData: <br>These directories include packages (.gpkg) of
 the study locations for all rivers included in the analysis, annual
 Landsat-derived 7-band images, and DSWE-derived channel masks. We also
 provide the mobility measurements as .csvs. The images and masks can be
 re-pulled using our GEE_watermasks Python software, and the mobility can
 be re-calculated using our CalculateMobility Python software. All .tif
 files are in the GeoTIFF format.
description: We recommend using an open-sourced Python-based workflow. Common
 packages used in the scripts here include Numpy, Scipy, Matplotlib,
 Rasterio, Pillow, and Pandas. For more detailed descriptions on software
 installation, see the related software packages. GeoTiff files can be
 visualized in the open-sourced QGIS software.