Riccardo Bonanomi, Ph.D. Candidate 37th cycle, University of Trento, DICAM

Meandering rivers are single-channel rivers that are usually found in the latter fractions of river basins due to milder slopes and higher bank cohesion caused, as an example, by denser vegetation and finer sediments. They are found all over the world, from the deep Amazon to the Siberian steppe, but even in these remote areas, they start to feel the impact of climate change and anthropogenic stressors.

The goal of my research is to develop a new modelling framework to better represent the changes caused by these external stressors. Combining the ability to represent the planimetric migration with the bankfull geometry adaptation to changes in the sediment and water supply is key to modelling the evolution under varying input conditions, such as changing water and sediment supply due to climate or land use alterations.
While using numerical and analytical models we will also need data from real rivers to validate the model and to understand which processes are actually worth modelling. Since we focus on the river in remote locations, the easiest available information come from remote sensing data, in particular satellite images, that can be processed with the PyRIS software developed by Monegaglia et al. (2018) specifically for meandering rivers. 
In this first year of Ph.D., I focused on the study of pre-existing models to better understand how they work and started to implement simplified cases for the new approach, in order to test the feasibility of the framework. Moreover, I converted PyRIS for use with the more recent Python3 and I started, working with another colleague, to introduce Google Earth Engine for river extraction, to enhance the software capabilities. 
We plan on starting to use soon the first simplified approach on test cases, to check if it is working properly conceptually and then we will implement the new complete model. Alongside this, we will begin to extract data from satellite images with the updated PyRIS and analyze the centreline as a signal, to be able to compare the model output with the real river. 

Furthermore, we started looking into permafrost rivers using and adapting PyRIS to understand how this substrate changes the evolution patterns. This is interesting for the fragility of the environment that will be heavily affected by climate change, but also because it has not been widely studied yet. According to a preliminary study by a colleague, the permafrost presence should change some of the planform characteristics, but this has not been tested against patterns shown by real rivers. Firstly then, we will compare this preliminary result and sub-tropical rivers with the satellite data extracted with PyRIS to verify the theory and the differences with non-artic rivers. Secondly, in order to look into the changes that external stressors will produce in this complex environment, we will introduce the erosion law developed by our colleague into our model, to combine both the effects of permafrost and of the changing bankfull geometry.