Estimation of missing hydrological data in monthly rainfall series using meteorological satellite data

Missing data in historical rainfall series are common in Brazilian conditions, making unfeasible several hydrological studies that rely on these data. In this context, orbital sensor products represent a potential tool for estimating rainfall. As a result, this study aims to assess the applicability of data from the Tropical Rainfall Measurement Mission (TRMM) and the Global Precipitation Measurement (GPM) mission to estimate missing hydrological data in monthly rainfall series from surface rain gauges, testing its estimation’s accuracy. Three rain gauges located in the Doce river watershed were selected to simulate and estimate missing hydrological data using linear regression and regional weighting techniques, using historical series of neighboring gauges and TRMM/GPM’s pixels. Although the estimations using TRMM/GPM data were not the most accurate for all the rain gauges, their performance evaluation, done with the Nash–Sutcliffe Efficiency Ratio (NSE) and the Wilmott Concordance Index (d), showed that the estimations obtained are considered good and satisfactory (NSE > 0.75 and 0.36 < NSE < 0.75, respectively), with d higher than 0.9. The results show that the TRMM/GPM missions’ historical series can be used to estimating missing hydrological data in the study area, with great potential for application in Brazilian conditions, characterized by low density of rain gauges without long historical series and missing data.