Orinoco: Retrieving a River Delta Network with the Fast Marching Method and Python

• Published in: ISPRS International Journal of Geo-Information
• Main Authors: Charlie Marshak, Marc Simard, Michael Denbina, Johan Nilsson, Tom Van der Stocken
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2020
• Subjects: SWOT; deltas; geomorphology; Python; geo; anthro-se; Mackenzie Delta
• Online Access: https://doi.org/10.3390/ijgi9110658; https://doaj.org/article/1108fa5a5cd8470ab2ef8d7af1cb5ad2

We present Orinoco, an open-source Python toolkit that applies the fast-marching method to derive a river delta channel network from a water mask and ocean delineation. We are able to estimate flow direction, along-channel distance, channel width, and network-related metrics for deltaic analyses including the steady-state fluxes. To demonstrate the capabilities of the toolkit, we apply our software to the Wax Lake and Atchafalaya River Deltas using water masks derived from Open Street Map (OSM) and Google Maps. We validate our width estimates using the Global River Width from Landsat (GRWL) database over the Mackenzie Delta as well as in situ width measurements from the National Water Information System (NWIS) in the southeastern United States. We also compare the stream flow direction estimates using products from RivGraph, a related Python package with similar functionality. With the exciting opportunities afforded with forthcoming surface water and topography (SWOT) data, we envision Orinoco as a tool to support the characterization of the complex structure of river deltas worldwide and to make such analyses easily accessible within a Python remote sensing workflow. To support that end, all the data, analyses, and figures in this paper can be found within Jupyter notebooks at Orinoco’s GitHub repository.