When scientists know too much – using citizen science to understand delta morphology.

Friday, 19 December 2014
Antoinette Abeyta1, Sarah E Baumgardner1, Danny Im1, Charles Nguyen1 and Chris Paola2, (1)University of Minnesota Twin Cities, Minneapolis, MN, United States, (2)Univ Minnesota, Minneapolis, MN, United States
Deltas are bodies of land created by the deposition of sediment from a river. The deposits formed by these systems are incredibly diverse and complex in shapes, sizes and form. It is believed that the morphology of these systems is controlled by the relative wave, tidal and fluvial forcings on the system, which control the removal and redistribution of the sediment. As a result, we are often trained to classify deltas this way based on qualitative assessments of subaerial features. While this approach has led to many interesting breakthroughs and discoveries, it has also limited our scope of view on what controls delta morphology. As a result, delta scientists are trained to look at the system from a narrow point of view with initial biases. By knowing too much about the system and with strong ideas of what controls the shape of a deltas, we have to ask ourselves if we are overlooking key features by trying to fit a square peg into a round hole. We are proposing a new and novel approach to understand the morphology of the world’s deltas by using citizen science. We have built a delta classification game, which gives participants a random set of images of deltas from satellites, numerical models and experiments. All images are free of location, color, scale and orientation to limit the amount of bias introduced and have participants focus only on features of the morphology, rather than extraneous details. Participants are then asked to group the images however they see fit, with the option to describe why they chose that classification system. By collecting the statistics on which deltas are commonly grouped together, we can then assess what features or details they have in common. The data from this project can help us create a new classification system and shed new light on the controls of delta morphology.