ABSTRACT Accurate estimates of precipitation amounts are necessary to evaluate river flows, assess water-related risks (floods and drought) and quantify water availability for a broad range of water uses, such as water supply, agriculture, navigation and energy production. Especially in the context of operations in the Brazilian electricity sector, where the electrical system is essentially hydrothermal and more than 65% of its production comes from hydroelectric generation, real-time observed precipitation plays a key role as a primary input for hydrological models and river flow forecasting. It is thus crucial to build knowledge on and quantify river basin precipitation and its uncertainties. In this paper, we evaluate two sources of real-time (or near real-time) precipitation data, the TRMM-MERGE dataset from the CPETC and the CPC dataset, distributed by NOAA. Our assessment is based on 41 river basins in South America and covers the period 1997-2017. We investigated differences for different time resolutions (daily, monthly and annual precipitation) and their impact on the simulation of streamflows. Substantial differences were found between the two data sources, which seem to be amplified in the second decade. A spatial trend was found towards higher TRMM-MERGE precipitation values than CPC values when moving from north and west in the study area. We also found evidence that differences in precipitation propagate to simulated flows, with large percent differences in precipitation resulting in even larger percent differences in streamflow.
Development of Real-Time River Flow Forecasting Model with Data Assimilation Technique
