South Africa is susceptible to droughts. However, there is little documentation on drought occurrence in South Africa at national level and its various administrative boundaries. The study aimed to profile the hydrological drought in ORTDM from 1998–2018; computing their frequency, severity and intensity so as to show areas of high vulnerability. Data used on this study was obtained from South African Weather Services in Pretoria. Standardized Precipitation Index (SPI) was calculated using the Meteorological Drought Monitor (MDM) software computing drought frequency, severity and intensity using 3 and 6 months SPI. The results showed a wide variation in monthly precipitation throughout the year. Coastal areas receive high rainfall than inland municipalities. When recorded in descending order, the drought intensity Nyandeni shows the highest drought frequency with a percentage of 62%, Mhlontlo (58%), KSDM (57%), Ngquza Hill (55%) and Port St Johns showing the least at (52%). The hydrological drought severity frequency and duration varied between 7 days to 9 weeks. Drought intensity class exposed the annual average intensity for the 5 local municipalities represented as follows; KSDM (-0.71), PSJM (-0.99), Ngquza Hill (-0.81), Nyandeni (-0.71) and Mhlontlo (-0.62). Maximum drought intensity for the 5 local municipalities showed the following results KSDM (-2.4), PSJM (-1.8), Ngquza Hill M (-1.9), Nyandeni M (-2.8) and Mhlontlo M (-3.1). The longest drought duration across OR Tambo was experienced in 2014 and has the following durations: KSDM (3 weeks), PSJM (5 weeks), Ngquza Hill (7 weeks), Nyandeni (8 weeks) and Mhlontlo (11 weeks). ORTDM is susceptible to hydrological droughts and the extent vary across local municipalities. The results could be used as a guide to the allocation of resources for drought relief purpose in a way that seeks to prioritize drought prone areas and vulnerable municipality. The SPI could be a useful when forecasting and estimating the frequency, duration and intensity of droughts. However, emphasis should be placed on improving the quality of data as this is key in improving the quality of its outcome.