Global Observations of Riverbank Erosion and Accretion From Landsat Imagery

Riverbank migration has historically been seen as a risk to infrastructure that can be combated through channelization, bank stabilization, and sediment trapping. The physical processes involved with riverbank erosion and deposition are well defined, yet the solutions to equations that describe these processes are computationally and data intensive over large domains. While current understanding of large‐scale river channel mobility largely comes from reach‐ and watershed‐scale observations, we need global observations of riverbank erosion and accretion to broaden our understanding of sediment processes within and across river basins. In this work, we create the first global data set of riverbank erosion for >370,000 km of large rivers using up to 20 years of water classifications from Landsat imagery. We estimate uncertainty by propagating water classification errors through our methods. Globally, we find riverbank erosion for rivers wider than 150 m to have an approximately log‐normal distribution with a median value of 1.52 m/yr. Comparing our data set to 25 similar estimates of riverbank migration, we found a normalized mean absolute error of 42% and a bias of 5.8%. We show that river width is the best first‐order predictor of riverbank erosion, in agreement with existing literature. We also show that the relationship between width and bank erosion is substantially different among a sample of global river basins and suggest that this is due to second‐order influences of geology, hydrology, and human influence. These data will help improve models of sediment transport, support models of bank erosion, and improve our understanding of human modification of rivers.