ABSTRACT System for hydrological forecasting and alert running in an operational way are important tools for floods impacts reduction. The present study describes the development and results evaluation of an operational discharge forecasting system of the upper Uruguay River basin, sited in Southern Brazil. Developed system was operated every day to provide experimental forecasts with special interest for Barra Grande and Campos Novos hydroelectric power plants reservoirs inflow, with 10 days in advance. We present results of inflow forecasted for floods occurred between July 2013 to July 2016, the period which the system was operated. Forecasts results by visual and performance metrics analysis showed a good fit with observations in most cases, with possibility of floods occurrence being well predicted with antecedence of 2 to 3 days. Comparing the locations, it was noted that the sub-basin of Campos Novos, being slower in rainfall-runoff transformation, is easier forecasted. The difference in predictability between the two basins can be observed by the coefficient of persistence, which is positive from 12h in Barra Grande and from 24h to Campos Novos. These coefficient values also show the value of the rainfall-runoff modeling for forecast horizons of more than one day in the basins.
ANNUAL RAINFALL-RUNOFF MODELING OF HARNAV WATERSHED OF A SABARMATI RIVER BASIN, INDIA USING ARTIFICIAL NEURAL NETWORK
