Evaluation of future climate using SDSM and secondary data (TRMM and NCEP) for poorly gauged catchments of Uganda: the case of Aswa catchment

Abstract

Forecast rise in global temperature is expected to have variable spatial and temporal impacts on rainfall patterns and crop productivity. In Aswa catchment, with a population of over two million, of which 70% are peasant farmers, there are concerns about increasing frequency of droughts, food shortage, and famine. However, hydro-climate data over the catchment are insufficient and often inconsistent to be used for spatial hydrological modeling and water resource management. This study explores the use of secondary data, such as the Tropical Rainfall Measuring Mission (TRMM) and the National Centers for Environmental Prediction (NCEP) reanalysis data, to generate future climatic information over Aswa catchment. This is achieved by interrogating the relationships between these secondary datasets and the available station data and using the secondary data to downscale two General Circulation Models (GCMs): Hadley Centre Coupled Model 3 and Canadian Earth System Model with Statistical Downscaling Model (SDSM). Correlation coefficients between secondary and station data lie between 0.75 and 0.85. Calibration and validation of the SDSM are satisfactory. For instance, Agago location gave correlation coefficient value of 0.64–0.96, standard error for temperature of 0.37–1.30 °C, and monthly rainfall of 23–45 mm. By 2099, minimum temperature is expected to rise by 3.25 °C and maximum temperature by 1.95 °C above the 2015 value. The annual rainfall coefficient of variability lies between 14 and 56%. These results suggest that the future temperature and rainfall patterns over Aswa catchment are likely to depart from the present and produce extreme events and challenges.