Articles | Volume 15, issue 7
Hydrol. Earth Syst. Sci., 15, 2179–2193, 2011

Special issue: Climate, weather and hydrology of East African Highlands

Hydrol. Earth Syst. Sci., 15, 2179–2193, 2011

Research article 13 Jul 2011

Research article | 13 Jul 2011

Water balance modeling of Upper Blue Nile catchments using a top-down approach

S. Tekleab1,2,3,4, S. Uhlenbrook1,4, Y. Mohamed1,4, H. H. G. Savenije4, M. Temesgen1,5, and J. Wenninger1,4 S. Tekleab et al.
  • 1UNESCO-IHE Institute for Water Education, P.O. Box 3015, 2601 DA Delft, The Netherlands
  • 2Addis Ababa University, Institute for Environment, Water and Development, Addis Ababa University, P.O. Box 1176, Addis Ababa, Ethiopia
  • 3Hawassa University, Department of Irrigation and Water Resources Engineering, P.O. Box 5, Hawassa, Ethiopia
  • 4Delft University of Technology, Faculty of Civil Engineering and Applied Geosciences, Water Resources section, Stevinweg 1, P.O. Box 5048, 2600 GA Delft, The Netherlands
  • 5Addis Ababa University, Department of Civil Engineering, P.O. Box 385, Addis Ababa, Ethiopia

Abstract. The water balances of twenty catchments in the Upper Blue Nile basin have been analyzed using a top-down modeling approach based on Budyko's hypotheses. The objective of this study is to obtain better understanding of water balance dynamics of upper Blue Nile catchments on annual and monthly time scales and on a spatial scale of meso scale to large scale. The water balance analysis using a Budyko-type curve at annual scale reveals that the aridity index does not exert a first order control in most of the catchments. This implies the need to increase model complexity to monthly time scale to include the effects of seasonal soil moisture dynamics. The dynamic water balance model used in this study predicts the direct runoff and other processes based on the limit concept; i.e. for dry environments since rainfall amount is small, the aridity index approaches to infinity or equivalently evaporation approaches rainfall and for wet environments where the rainfall amount is large, the aridity index approaches to zero and actual evaporation approaches the potential evaporation. The uncertainty of model parameters has been assessed using the GLUE (Generalized Likelihood Uncertainty Estimation) methodology. The results show that the majority of the parameters are reasonably well identifiable. However, the baseflow recession constant was poorly identifiable. Parameter uncertainty and model structural errors could be the reason for the poorly identifiable parameter. Moreover, a multi-objective model calibration strategy has been employed to emphasize the different aspects of the hydrographs on low and high flows.

The model has been calibrated and validated against observed streamflow time series and it shows good performance for the twenty study catchments in the upper Blue Nile. During the calibration period (1995–2000) the Nash and Sutcliffe efficiency (E NS) for monthly flow prediction varied between 0.52 to 0.93 (dominated by high flows), while it varied between 0.32 to 0.90 using logarithms of flow series (indicating the goodness of low flow simulations). The model is parsimonious and it is suggested that the calibrated parameters could be used after some more regionalization efforts to predict monthly stream flows in ungauged catchments of the Upper Blue Nile basin, which is the vast majority of catchments in that region.