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GONÇALVES, M.F. (2009). Precipitation forecast aided by weather radar for early warning system of urban floods. 248p. M. Sc. Dissertation Escola de Engenharia de São Carlos, Universidade de São Paulo, São Carlos. To reduce human and material losses during floods it is feasible to concisely study the rainfall forecast as the main part of an early warning system. The use of weather radar information, when linked to physically-based forecast models, can contribute for monitoring and forecasting of intense rainfall episodes. Thus, the rainfall forecast, based on using of radar information along with a conceptual model of hydrometeorological forecast, was outlined in this dissertation. One goal of the study was to improve very short term rainfall forecasts, named as a ‘nowcasting’ process throughout few minutes, coupled with a rainfall-runoff generation model to be used in early warning system. The hydrometeorological model, a hypothetical vertical 1-D cloud, was initially developed by Georgakakos and Bras (1984a) and further developed in this study to profit signals from radar tracking control volumes of moisture storage. Either ‘Echo Top’ radar information was addressed to determinate the cloud height, and the vertically-integrated liquid (‘VIL’) water mass content inside the cloud, estimated by other radar signal, was considered into the model. On the one hand, during rainfall events of hot and convective front genesis monitored with on-field pluviometers, the model results generally anticipated the beginning of the rain process; however the model was capable of not only simulating well the behavior but also the time-step when rainfall monitored peak occurred. On the other hand, and for cold-front events, the simulating peaks depicted a time delay. For simulation episodes with VIL greater than 3 kg m-2, the simulated rainfall accompanied the time behavior of VIL, but with influences from weather variables of pressure, temperature and relative humidity. These rainfall depths became inputs of a simple SCS rainfall-runoff model, partially calibrated with genetic algorithms. At the scale of a small Brazilian urban river basin with experimental gauging station, some preliminary results modeled streamflows a bit lower than, and with some delay of maximum flow forecasts, observed discharges. The advanced lag time period used by model was of about 15 min and, besides its simplicity, it was quite able to anticipate the beginning of the rainfall process that generated the flood formation at the urban creek.

Previsão de chuva com auxílio de radar de tempo visando a um sistema de alerta antecipado de cheias em áreas urbanas