CESP Integrated Precipitation Estimation and Forecasting System for its Watersheds

Abstract Flow forecasting is one of the most important information to scheduling hydroelectric power generation and short- to long-term planning. Flow prediction is most relevant in water scarcity scenarios, when there is a reduction in hydroelectric power generation and an increase in production by thermoelectric plants to guarantee other uses of water under such conditions. The prediction and prognostic precipitation through stochastic and deterministic models is essential even with the inherent limitations of atmospheric phenomenological complexity. Establishing guidelines upon such models based on hydrometeorological variables (e.g., precipitation time series) and climate phenomena can reduce errors and improve reservoir operations. The National System Operator (ONS) and generation agencies may decide with fewer operational risks in order to optimize energy resources, minimize consumer costs and supply electricity even in times of water scarcity. Thus, this paper describes a rain monitoring and forecasting system in the CESP watersheds to improve the streamflow estimation of CESP reservoirs. We present an objective statistical analysis scheme (ANOBES) that integrates the meteorological satellite precipitation estimation with CESP, DAEE and ANA telemetric network rainfall measurements. Rain forecasting up to five days in advance is performed with the ARPS system. The estimates, measurements and rainfall simulations obtained were used in tributary flow simulations of CESP watersheds with the SMAP model for verification. Rain forecast up to five days in advance was made with the ARPS system. The estimates, measurements and rainfall simulations obtained were used in tributary flow simulations in CESP basins with the SMAP model for verification. The results suggest performance improvement with data integration and precipitation prediction with the ARPS system.