Data limitations on groundwater (GW) recharge over large areas are still a challenge for efficient water resource management, especially in semi-arid regions. Thus, this study seeks to integrate hydrological cycle variables from satellite imagery to estimate the spatial distribution of GW recharge in the Ipanema river basin (IRB), which is located in the State of Pernambuco in Northeast Brazil. Remote sensing data, including monthly maps (2011–2012) of rainfall, runoff and evapotranspiration, are used as input for the water balance method within Geographic Information Systems (GIS). Rainfall data are derived from the TRMM Multi-satellite Precipitation Analysis (TMPA) Version 7 (3B43V7) product and present the same monthly average temporal distributions from 15 rain gauges that are distributed over the study area (r=0.93 and MAE=12.7mm), with annual average estimates of 894.3 (2011) and 300.7mm (2012). The runoff from the Natural Resources Conservation Service (NRCS) method, which is based on regional soil information and Thematic Mapper (TM) sensor image, represents 29% of the TMPA rainfall that was observed across two years of study. Actual evapotranspiration data, which were provided by the SEBAL application of MODIS images, present annual averages of 1213 (2011) and 1067 (2012)mm. The water balance results reveal a large inter-annual difference in the IRB GW recharge, which is characterized by different rainfall regimes, with averages of 30.4 (2011) and 4.7 (2012)mmyear−1. These recharges were mainly observed between January and July in regions with alluvial sediments and highly permeable soils. The GW recharge approach with remote sensing is compared to the WTF (Water Table Fluctuation) method, which is used in an area of alluvium in the IRB. The estimates from these two methods exhibit reliable annual agreement, with average values of 154.6 (WTF) and 124.6 (water balance) mm in 2011. These values correspond to 14.89 and 13.53% of the rainfall that was recorded at the rain gauges and the TMPA, respectively. Only the WTF method indicates a very low recharge of 15.9mm for the second year. The values in this paper provide reliable insight regarding the use of remotely sensed data to evaluate the rates of alluvial GW recharge in regions where the potential runoff cannot be disregarded from WB equation and must be calculated spatially.