Using historical source data to understand urban flood risk: a socio-hydrological modelling application at Gregorio Creek, Brazil

This is an Accepted Manuscript of an article published by Taylor & Francis in Hydrological Sciences Journal on [date of publication], available online: https://doi.org/10.1080/02626667.2020.1740705.The city of São Carlos, state of São Paulo, Brazil, has a historical coexistence between society and floods. Unplanned urbanization in this area is a representative feature of how Brazilian cities have developed, undermining the impact of natural hazards. The Gregório Creek catchment is an enigma of complex dynamics concerning the relationship between humans and water in Brazilian cities. Our hypothesis is that social memory of floods can improve future resilience. In this paper we analyse flood risk dynamics in a small urban catchment, identify the impacts of social memory on building resilience and propose measures to reduce the risk of floods. We applied a socio-hydrological model using data collected from newspapers from 1940 to 2018. The model was able to elucidate human–water processes in the catchment and the historical source data proved to be a useful tool to fill gaps in the data in small urban basins

Observatório Socio-Hidrológico para Segurança Hídrica sob cenários de mudanças climáticas: utilizando soluções locais de memórias sociais para desafios globais

Today, society is in a state of frequent change, and this is not different in the disaster risk management field. Responses to social disasters, which were previously treated isolated, are increasingly demanding planning and decision in face of great complexity. In the case of flood events, climate projections combined with urbanization trends show an increase in their intensity. Social aspects, such as the social memory of past events, can play an important role in reducing flood damage through the voluntary displacement of people outside risk areas or the resilience improvement. Such factors demonstrate that the risk analysis must be carried out dynamically, considering that the human-water system co-evolves, to reduce flood risk. The first hypothesis in this study is explored in the second chapter and is that the flood risk can be reduced by keeping the memory of past events alive for longer periods in flood-prone areas. The second hypothesis, explored in the third chapter, is that climate change scenarios and social aspects can be incorporated in long-term risk analysis, improving the risk reduction measures planning. Thus, this study conceptually developed a Socio-Hydrological Observatory for Water Security (SHOWS) that aggregates climatic, social, and hydrological information for flood risk analysis. To this end, a socio-hydrological model was applied using historical data and climate projections for the years between 1940 and 2099 to estimate flood risk in a Brazilian catchment. These results served as a basis for identifying strategies to reduce risk through social and environmental measures and for the elaboration of the observatory model.Atualmente, a sociedade se encontra num estado de frequente mudança e isso não é diferente no campo de gestão de risco de desastres. Respostas a desastres sociais, que antes eram tratadas de maneira isolada, exigem cada vez mais planejamento e tomada de decisão diante da grande complexidade. No caso de eventos de inundação, as projeções climáticas combinadas com as tendências de urbanização, mostram um aumento em sua intensidade. Aspectos sociais, como a memória social de eventos passados, podem desempenhar um papel importante na redução dos danos gerados por inundações através do deslocamento voluntário de pessoas para fora de áreas de risco ou de um aumento na resiliência. Tais fatores demonstram que a análise de risco deve ser executada de maneira dinâmica, considerando que sistema sociedade-água evolui de maneira integrada, para reduzir o risco de inundações. A primeira hipótese desse estudo é explorada no segundo capítulo e é de que o risco de inundações pode ser reduzido através da manutenção da memória de eventos passados viva por mais tempo em áreas suscetíveis a inundação. A segunda hipótese, explorada no terceiro capítulo, é de que cenários de mudanças climáticas e aspectos sociais podem ser incorporados na análise de risco a longo prazo, aprimorando o planejamento de medidas de redução de risco. Com isso, esse estudo desenvolveu conceitualmente um Observatório Socio-Hidrológico para Segurança Hídrica (SHOWS) que agrega informações climáticas, sociais e hidrológicas para análise de risco de inundações. Para tanto, foi aplicado um modelo socio-hidrológico utilizando dados históricos e projeções climáticas para os anos entre 1940 e 2099 para estimar o risco de inundações em uma bacia hidrográfica brasileira. Esses resultados serviram como base para identificação de estratégias para redução de risco através de medidas ambientais e sociais e para a elaboração do modelo de observatório

Linking Urban Floods to Citizen Science and Low Impact Development in Poorly Gauged Basins under Climate Changes for Dynamic Resilience Evaluation

Cities must develop actions that reduce flood risk in the face of extreme rainfall events. In this study, the dynamic resilience of the Gregorio catchment (São Carlos, Brazil) was assessed. The catchment lacks environmental monitoring and suffers from recurrent floods. The resilience curves were made considering the water depth in the drainage system as the performance index, obtained by simulations with SWMM and HEC-RAS. The calibration of the flood extension was performed using citizen science data. The contribution to increasing the dynamic resilience by implementing decentralized low impact development (LID) practices was also evaluated. For this purpose, bioretention cells were added to the SWMM simulations. The resilience curves were then calculated for the current and future climate scenario, with and without LID, for return periods of 5, 10, 50, and 100 years and duration of 30, 60, and 120 min. Intensity–duration–frequency curves (IDFs) updated by the regional climate model MIROC5 for 2050 and 2100 were used. The results showed a significant improvement in the system’s resilience for light storms and the current period due to LID practice interventions. Efficiencies were reduced for moderate and heavy storms with no significant drops in floodwater depth and resilience regardless of the scenario