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Probabilistic flood forecasting system attributed to different estimates of precipitation, hydrologic and hydraulic model and uncertainty analysis

Grant number: 12/17854-0
Support type:Scholarships abroad - Research Internship - Doctorate (Direct)
Effective date (Start): February 01, 2013
Effective date (End): January 31, 2014
Field of knowledge:Engineering - Sanitary Engineering - Water Resources
Principal Investigator:Eduardo Mario Mendiondo
Grantee:Danielle de Almeida Bressiani
Supervisor abroad: Raghavan Srinivasan
Home Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Local de pesquisa : Texas A&M University, United States  
Associated to the scholarship:11/10929-1 - Integrated web-mapping decision support system of hydrologic risks in urban basins, BP.DD

Abstract

The global economic losses associated with environmental disasters increased, as did the frequency of hydro-meteorological disasters. Floods induced by extreme precipitation events are a concern in many locations around the world, making it urgent and necessary to take preventive actions in an integrated manner. Adaptation strategies, such as early warning systems for floods and environmental insurance must be used. It is necessary to combine weather forecasts with hydrological forecasts for the short-term, using hydro-meteorological monitoring data, precipitation estimates from radar and/or meteorological models, which are used as input to hydrologic models to estimate flows with different times in advance, precision and uncertainty. Deterministic forecasts provide an illusion of certainty that does not exist. In this manner an important research challenge is to include quantification of uncertainty of the prediction process, promoting probabilistic forecasts. The flood modeling will be done through distributed hydrologic model Soil & Water Assessment Tool (SWAT) and through the hydraulic model Hydrologic Engineering Center's River Analysis System-: HEC-RAS. The sensitivity analysis, calibration and uncertainty analysis will be conducted using global optimization methods available in SWAT-CUP software such as: ParaSol and GLUE. The performance of the models to evaluate the calibration and validation will be achieved through measures such as: efficiency coefficient of Nash-Sutcliffe, coefficient of determination, root mean square error and percentage bias. To calculate the uncertainty of the models will be used as methods: GLUE and ParaSol, and to perform a global analysis in situations with multiple models will be used Bayesian Model Averaging (BMA). (AU)

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
BRESSIANI, DANIELLE DE ALMEIDA; GASSMAN, PHILIP W.; FERNANDES, JOSIMAR GURGEL; POSPISSIL GARBOSSA, LUIS HAMILTON; SRINIVASAN, RAGHAVAN; BONUMA, NADIA BERNARDI; MENDIONDO, EDUARDO MARIO. Review of Soil and Water Assessment Tool (SWAT) applications in Brazil: Challenges and prospects. INTERNATIONAL JOURNAL OF AGRICULTURAL AND BIOLOGICAL ENGINEERING, v. 8, n. 3, SI, p. 9-35, JUN 2015. Web of Science Citations: 48.
BRESSIANI, DANIELLE DE ALMEIDA; SRINIVASAN, RAGHAVAN; JONES, CHARLES ALLAN; MENDIONDO, EDUARDO MARIO. Effects of spatial and temporal weather data resolutions on streamflow modeling of a semi-arid basin, Northeast Brazil. INTERNATIONAL JOURNAL OF AGRICULTURAL AND BIOLOGICAL ENGINEERING, v. 8, n. 3, SI, p. 125-139, JUN 2015. Web of Science Citations: 32.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.