Amazonian Juruá river meander migration impact on riverine communities: a case of study using remote sensing time series and cloud computing

• Ano de defesa: 2021
• Autor(a) principal: Gustavo Willy Nagel
• Orientador(a): Evlyn Márcia Leão de Moraes Novo, Vitor Souza Martins
• Banca de defesa: João Vitor Campos e Silva, Marie Paule Bonnet
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Instituto Nacional de Pesquisas Espaciais (INPE)
• Programa de Pós-Graduação: Programa de Pós-Graduação do INPE em Sensoriamento Remoto
• País: BR
• Link de acesso: http://urlib.net/sid.inpe.br/mtc-m21c/2021/02.24.17.54

River meander migration promotes the formation of exceedingly sinuous rivers resulting in oxbow floodplain lakes. These riparian environments support communities that live along the river banks by providing reliable fishery and thus economic and food security. Meander migration results from erosion, sedimentation, and cutoffs that naturally change the floodplain geomorphology affects the dynamic of local communities and ultimately forces them to move to other banks or nearby cities. The erosion process, for example, might promote the loss of land on community shores and increase the risk of inundation frequency and severity. Sedimentation might gradually increase the distance between the river channel and communities settlements, reducing their access to the river. Moreover, cutoff events, when the river favors a shorter path, might reduce the community access to the main river, and with time, totally isolate the population. In this context, communities that live along the Amazonian Juruá River banks, one of the most sinuous rivers on Earth, are vulnerable to the negative effects of the meander migration. Giving the size of the Amazon Basin rivers, it is not easy to monitor this process to prevent damages to the riverine population. Although not properly explored, remote sensing and cloud computing are promising for the study of the floodplains dynamics and their relationship with residents. In this research, we investigated the river meander impacts on local communities along the main Juruá Basin river channels. For that, the study consisted in (i) the development of an automatic algorithm to measure the river meander migration using cloud computing and Landsat time series, (ii) the identification of the number of communities affected by erosion and sedimentation along the Juruá River, (iii) the development of an easy-to-use methodology to predict the year of neck cutoff occurrence using remote sensing time series. (i) The Water Surface Change Detection Algorithm (WSCDA) identified meander migration areas along the Juruá River, with omission and commission errors lower than 13.44% and 7.08%, respectively. (ii) There are 369 rural communities without road access along the Juruá banks, the majority of which located in stable regions (58.8%). Those located on unstable reaches represent almost 40 %, divided into communities living in sedimentation (26.02%), and erosion areas (15.18%). This result suggests that the riverine population can make decisions based on their empirical knowledge and develop successful adaptations to the environment. Furthermore, larger communities (more than 20 houses), tend to live in more stable locations (70% of the total large communities), when compared to middle size (11-20 houses = 63.2%) and small communities (1-10 houses = 55.6%). (iii) The methodology for predicting the year of neck cutoff occurrence was accurate (R² =0.79 and MAPE = 13%) within 20 years. We identified migration rates previous to cutoffs ranging from 3 to 29 m/year along the Juruá Basin. The cutoff prediction methodology was then applied in river sections with potential community impact. The results in all sections promote essential knowledge about the relationship between local communities and the river meander migration and aim to support local planning to improve communities resilience. Furthermore, the proposed WSCDA might be used to measure river morphology dynamics of water resources in different regions, with the potential to assess the impact on different riverine communities worldwide.