Eventos extremos de precipitação pluvial na cidade de Itacoatiara - AM

Abstract

This research aimed to understand the extreme events of rainfall integrated with socio-spatial vulnerability in the city of Itacoatiara. The theoretical contribution of the research was based on Geographic Climatology and Climate Geography. First, rainfall variability analysis was performed between 1971-2020, using daily, monthly and annual precipitation data from the city of Itacoatiara made available by the National Institute of Meteorology (INMET) and the analysis of extreme rainfall events using the percentile technique (90/95/99) and the nonparametric tests of Mann-Kendall and Petitt. By using climate geography and Geographic Climatology as a way of approach, we sought to tie an analysis of atmospheric elements in their dynamics (through rhythmic analysis). For this, historical studies were used on the production of urban space, its dynamics. Subsequently, a detailed analysis of the sand-time variability of rainfall at different scales was made in order to identify the main atmospheric systems that generate extreme rainfall events, and we tried to verify the places of occurrence through newspaper news, thus analyzing the episodes. In addition, the socio-spatial vulnerability index (SoVI®) applied to the city of Itacoatiara-AM was performed and identified the most socially vulnerable sites and hydroclimatic events. The results showed that the extreme precipitation events analyzed by decade showed an increase in total days in all thresholds, 90th percentiles, 95, 99 mainly in the last decade of 2010-2020.extreme events have been more frequent in recent decades, with a positive and significant trend. The episodes triggered were related to the occurrence of flooding in streets, difficulty in the movement of vehicles and people, landslides and landslides, difficulty in trafficability. The main atmospheric systems at work were: Intertropical Convergence Zone, South Atlantic Convergence Zone, Lines of Instabilities and Continental Equatorial Mass. It was found that in the neighborhoods (San Francisco; From Iracy, Santa luzia, Mamoud Amed, Prainha, Jauary) reside the population most vulnerable to episodes of extreme events