Estudo de impactos das mudanças climáticas no sistema de drenagem da bacia do córrego Samambaia, Goiânia - GO

Abstract

The development of studies on the effects of global climate change on the hydrological response dynamics of watersheds is an essential aspect of adaptation and integrated management of urban infrastructure in resilient cities. This study focuses on river basins as the unit of analysis for drainage systems in metropolitan regions, which are crucial for addressing the challenges posed by extreme weather events. Although there is evidence on the magnitude of global climate change, predicting its effects at regional and local scales remains a challenge. However, the responsibility of local governments to prepare for these changes is increasing through urban planning focused on climate adaptation. In Brazil, the 2022 census indicated that inland cities and regions have experienced the most growth in the current century. Moreover, since the 1970s, the rural population has declined, with all growth occurring in urban areas. Among the consequences associated with climate change, the country has already recorded a significant increase in extreme events, with cities like São Paulo, Rio de Janeiro, and Porto Alegre facing recurring floods that cause billions of reais in damages annually. In this scenario, more modern drainage systems are essential for mitigating flood events, especially in densely urbanized metropolitan areas. However, the performance of these drainage systems has generated growing concerns as climate change contributes to more intense rainfall and a higher frequency of extreme precipitation events. Thus, alongside changes in hydrological response patterns, there is a need to increase climate resilience in large cities by adapting urban infrastructure to face the challenges posed by these increasingly severe events. In particular, this study adopts the Córrego Samambaia watershed as its study area, located in the municipality of Goiânia, GO. Located in the heart of the Cerrado biome, studies carried out for the Goiânia Metropolitan Region point to the need to analyze the environmental impacts of climate change on the region and its population, incorporating climate projection scenarios into the analysis. This study aims to analyze the impacts of climate change associated with the effects of long-term hydrological projections (the year 2025 to 2040) in the Córrego Samambaia basin, with a focus on the process of generating surface runoff and potential impacts on the planning of urban drainage infrastructure. In view of the above, changes in the patterns of hydrological responses, with regard to the surface runoff component, were obtained by integrating climate projections of precipitation into the SCS (Soil Conservation Service) hydrological model. This study aims to analyze the impacts of climate change associated with the effects of long-term hydrological projections (the year2025 to 2040) in the Córrego Samambaia basin, with a focus on the process of generating surface runoff and potential impacts on the planning of urban drainage infrastructure. In view of the above, changes in the patterns of hydrological responses, with regard to the surface runoff component, were obtained by integrating climate projections of precipitation into the SCS (Soil Conservation Service) hydrological model. The results obtained from the long-term hydrological projections indicate a reduction in the pattern of maximum daily precipitation over the period analyzed, which reflects changes in the pattern of the I-D-F (Intensity - Duration - Frequency) relationships of precipitation. On the other hand, when simulating scenarios with increased sealing in the basin, it was observed that approximately 44% of rainfall could contribute to the generation of surface runoff. In this sense, the study made it possible to assess potential climate impacts in the Córrego Samambaia basin, offering subsidies for future research aimed at adapting and planning drainage systems in strategic regions of the basin, with updates based on new climate projections.