Abstract
Rainfall runoff modelling in a river basin is vital for number of hydrologic application including water resources assessment. However, rainfall data from sparse gauging stations are usually inadequate for modelling which is a major concern in Tanzania. This study presents the results of comparison of Tropical Rainfall Measuring Mission (TRMM) satellite rainfall products at daily and monthly time-steps with ground stations rainfall data; and explores the possibility of using satellite rainfall data for rainfall runoff modelling in Pangani River Basin, Tanzania. Statistical analysis was carried out to find the correlation between the ground stations data and TRMM estimates. It was found that TRMM estimates at monthly scale compare reasonably well with ground stations data. Time series comparison was also done at daily and annual time scales. Monthly and annual time series compared well with coefficient of determination of 0.68 and 0.70, respectively. It was also found that areal rainfall comparison in the northern parts of the study area had poor results compared to the rest of areas. On the other hand, rainfall runoff modelling with ground stations data alone and TRMM data set alone was carried out using five Real Time River Flow Forecasting System models and then outputs combined by Models Outputs Combination Techniques. The results showed that ground stations data performed better during calibration period with coefficient of efficiency of 76.7%, 81.7% and 89.1% for Simple Average Method, Weight Average Method and Neural Network Method respectively. Simulation results using TRMM data were 59.8%, 73.5% and 76.8%. It can therefore be concluded that TRMM data are adequate and promising in hydrological modelling.
Recommended Citation
Nobert, J. (2014). APPLICATION OF REMOTELY SENSED RAINFALL DATA IN RAINFALL-RUNOFF MODELLING. A CASE OF PANGANI RIVER BASIN, TANZANIA. Tanzania Journal of Engineering and Technology (TJET), 35(1), 1-14. https://doi.org/https://doi.org/10.52339/tjet.v35i1.465
Publisher Name
University of Dar es Salaam