Effects of Bias Correction of Daily Satellite-Based Rainfall Estimates on Real-Time Monitoring and Hydrological Forecasting at the Rimac River Watershed, Peru.

Abstract. Due to technological advances there are available satellite precipitation products (SPP) which have acceptable spatial coverage and are accessible in real-time. However, the usefulness of SPP in hydrological applications have not yet been evaluated over the Andean and Pacific watersheds of Peru. This paper evaluates the performance of two SPP (TRMM-3B42RT and PERSIANN-CCS) with bias correction (BC) in real-time monitoring and hydrological forecasting of Rimac River (RR) watershed (~2364 Km²). To correct the bias of daily SPP, it has been used Quantile-Mapping method. For reference hydro-meteorological data, 22 rain gauges and one streamflow gauge was used for the period 2007-2015 when all SPP are available. The impacts of SPP on model parameterization and outputs were evaluated in two optimization experiments. In the first one, observed precipitation dataset were used as forcing in the optimization of hydrological models. In the other experiment, bias-corrected SPP were used as forcing in the optimization of hydrological models. The results show that there is a very weak linear relationship between SPP and observed precipitation dataset. Based on the statistical analysis of temporal patterns and magnitude, applying BC method has been possible to improve the performance of SPP in real-time monitoring and hydrologic forecasting of RR watershed. Specifically, it has been possible to obtain better results using the Quantile-Mapping method applied to the TRMM-3B42RT than PERSIANN-CCS product when using both HBV and HYMOD models.

Keywords: Bias correction, satellite-based precipitation products, real-time monitoring, streamflow simulation, Rimac river watershed.