Article Sidebar
Published:
Jun 30, 2014Keywords:
Article Details
Tanzania Journal of Engineering and Technology (Tanz. J. Engrg. Technol.) publications are written as a basis for academic discussions. Whereas effort is made by the Editorial Board to screen out inaccurate or misleading statements, data or opinions, Tanz. J. Engrg. Technol. wishes to make it clear that the contents of the articles are the sole responsibility of the authors. Accordingly, the Editorial Board and editors, publisher, College of Engineering and Technology and the University of Dar es Salaam accept no responsibility or liability whatsoever for the opinions, inaccurate or misleading data or statement and views expressed by the authors.
However, the College of Engineering and Technology, the publisher of the Journal, reserve all rights of the articles published in the Journal. Whereas the contents of the articles are available electronically without cost, no part of the publication may be transmitted in any form or reproduced electronically or mechanically, except for short extract in critical scholarly review, research or discourse with an acknowledgement.
Main Article Content
Application of Remotely Sensed Rainfall Data in Rainfall-Runoff Modelling. A Case of Pangani River Basin, Tanzania
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.
