Modelo de alerta hidrológico com base participativa usando sistema de informações voluntárias para previsão de enchentes [thesis]

Maria Clara Fava
parte dos requisitos para obtenção do título de Mestre em Ciências: Engenharia Hidráulica e Saneamento. VERSÃO CORRIGIDA São Carlos, SP Março, 2015 DEDICATÓRIA Aos meus pais, Maria Evaneide de Jesus Fava e Sidnei da Silva Fava por todo o amor, apoio e incentivo. Sendo eles minha eterna motivação para buscar ser alguém melhor. de enchente recentes foram utilizados dados de nível medidos por sensores para simular dados voluntários. Foram levantadas diversas hipóteses para que a inserção de dados
more » ... inserção de dados voluntários no modelo MAHP tenham maior influência na redução da incerteza na previsão de enchentes. Palavras-chave: Enchentes, Previsão Hidrometeorológica, Informações Geográficas Voluntárias, SWMM. ABSTRACT FAVA, M. C. (2015). Participative-Based Early Warning Model using Volunteer Geographic Information Systems for Flood Forecasting. São Carlos, 100p. M. Sc. Dissertation. School of Engineering at São Carlos, University of São Paulo, São Carlos, Brazil. This work presents a new approach for flood forecasting: Hydrological Alert Model with Participatory Base (HAMPB). The HAMPB consists of a flood forecasting model applied to urban basins integrating Volunteered Geographic Information (VGI) and Wireless Sensor Networks (WSN). The main contribution of this model is the use of heterogeneous data sources (convencional sensors and volunteered data) aiming to reduce the uncertainty in the flood forecasting. The HAMPB model was divided in modules, which are responsible for the forecasting process activities. The Although the model has multiple auxiliary modules, we can summarize the HAMPB model in three modules: data acquisition; rainfall forecasting and, finally, the module responsible for flood forecasting. Telemetric water level sensors were installed at strategic points in river channels of the city to create the WSN. In order to use the volunteered information, a methodology was proposed to develop the acquisition module. The rainfall forecasting module consists of two forecasting models: an empirical model and a conceptual model. The conceptual prediction model presented closest predictions of observed rainfall compared to the forecast of the empirical model. In order to apply the flood forecasting methodology, we modelled the urban basin of São Carlos using SWMM model. The rainfall-runoff simulations performed with the basin model showed satisfactory adjustments compared with actual flood events. Since the use of voluntary information on flood forecasting is a fairly new concept, another important contribution of this work was the proposition of spatiotemporal parameters that influence on the forecast caused by the use of VGI data. There are many scenarios and combinations which using volunteered information can be helpful in the flood forecasting. In this work we consider only one combination. Due to absence of real volunteered data, we use sensor data to simulate VGI data. Several hypotheses have been raised to the inclusion of volunteers in HAMPB data model to produce more relevant results than using traditional methods of forecasting.
doi:10.11606/d.18.2015.tde-22062015-144238 fatcat:6mfds4k7ojec3bycmxcyvng7sy