Droughts are a recurrent phenomenon in water abundant tropical countries worldwide and are expected to become more frequent in the future. However, drought risk in tropical catchments is poorly understood and usually not adequately incorporated in water management strategies. Thus, methodologies to evaluate spatial and seasonal drought risk in data scarce tropical catchments are urgently needed. We combined hazard and vulnerability related information to assess drought risk in the test basin, the rural Muriaé basin in southeast tropical Brazil. Hazard indicates the cumulative frequency of drought anomalies, while vulnerability represents the potential of a drought to cause damages in the socioeconomic system. We simulated subcatchment discharges with a hydrological model (SWAT) to evaluate spatially distributed hydrological drought hazard and combined this information with precipitation and vegetation based indices to define the cumulative frequency of drought occurrence for each grid cell (0.1°). We tested the sensitivity of different climate and catchment related model input variables against low flow events and simulated artificial drought risk scenarios. To assess vulnerability, we reclassified and weighted globally and regionally available gridded socioeconomic data. Vulnerability in the downstream area was found to be stronger which coincided with a higher hydrological and vegetation based hazard. The drought risk map clearly identified the downstream area of the Muriaé basin as being exposed to a stronger drought risk compared to the upstream areas. Only limited hydrological drought sensitivity of the system against changes in land cover type and temperature was shown in the model results while geology and soils turned out to play a larger role for low flows. The drought scenarios showed that low flows were more severely affected than high flows by climatic changes such as decreased precipitation. In can be concluded that our risk assessment methodology offers a holistic, science based and innovative solution to inform regional planning and water management institutions dealing with the control of drought disasters in tropical rural areas. Such drought risk evaluation frameworks and spatial information are urgently needed in tropical regions worldwide.