Drought is a natural feature of the climate usually associated with dry and warm weather over an extended period of time causing less than normal water available at the land surface. The development of a drought is a slow process and it is often hard to detect early. Malawi represents a country that is highly dependent on agriculture and where data scarcity is a common problem. This study examines the applicability of modelled monthly precipitation data in drought assessment by comparing observed and modelled precipitation series in Malawi. The study reveals a high average correlation (~0.86) between modelled and observed data, suggesting that the modelled data provides a valuable tool in drought studies. A simple but novel method, Regional Drought Index, combining SPI and modelled data is introduced to examine drought on a regional scale. The method recognizes the severe droughts of the region documented in the literature. Standardized Precipitation Index and Standardized Runoff Index series are compared to investigate whether meteorological anomalies can be expected to characterize streamflow in rivers with different catchment sizes. The comparison of meteorological and hydrological monthly data suggests that the response time of the catchments increases with increasing catchment area. The ability to recognize runoff variability was highest for catchment sizes larger than 2000 km2, whereas for the smaller catchments the agreement between the two was low.