Rainfall Variability and Estimation for Hydrologic Modelling
A remote sensing based study at the source basin of the Upper Blue Nile River
Abstract of Alemseged Tamiru Haile's PhD thesis
Rainfall is one of the meteorological forcing terms in hydrologic modelling and therefore its spatial variability in coverage, frequency and intensity affects simulation results. Rainfall variability in particular under the effect of orography adjacent to a large water body is not fully known. Such study is done for the Gilgel Abbay watershed of the Lake Tana basin (Ethiopia). The study area is the source basin of the Upper Blue Nile River which is one of the major contributors to the river flow of the Nile. The livelihood in the Lake Tana basin largely depends on rainfed agriculture and therefore understanding rainfall variability in the basin is required. As part of the study, a set of recording rain gauges have been installed to observe rainfall at high resolution.
First, rainfall variability in the Lake Tana basin is evaluated by statistical analysis of rain gauge observations. Furthermore, a convective index is derived from remote sensing observations to infer the pattern of rainfall variability in the basin. Results suggest that orography and the presence of Lake Tana largely affect the diurnal cycle, frequency and intra- and inter-event properties of the rainfall. The rainfall varies significantly at scales much smaller than inter-station distances suggesting that the existing rain gauge network may be inadequate to fully capture the space-time pattern of the rainfall. Such affects the accuracy of spatial rainfall estimation that serves to specify the input to hydrologic models.
Second, two remote sensing based approaches have been developed to estimate spatial rainfall: (i) a multi-spectral remote sensing approach, and (ii) a conceptual cloud model approach with inputs from remote sensing and typical ground based observations (pressure and temperature). Results show the potential of remote sensing observations for rainfall estimation although the ground based data still provided some limitations at this point.
Third, the effect of the rainfall variability on the accuracy of the simulated stream flows by a physically based rainfall-runoff model is evaluated. The effect of rain gauge density and configuration on rainfall representation and consequently on stream flow simulation is evaluated through a set of performance measures. The large rainfall variability in the study area caused the accuracy of the simulated flow to be significantly affected by both the density and the configuration of the network. The use of rainfall from a single rain gauge resulted in a relative difference of up to 100 % between the simulated and observed stream flows. It is also shown that simulated stream flow largely differs if uniform rainfall input is compared to non-uniform rainfall input. This study is relevant to hydrologic modeling since much research has focused on model development and assessing parameter uncertainty while less attention is given to aspects that relate to effects of rainfall representation.
Alemseged Tamiru Haile
|Alemseged Tamiru Haile was born on 28 February 1978 in Addis Ababa, Ethiopia. After completing high school in 1996, he joined Arba Minch Water Technology institute (AWTI) to pursue his study for B.Sc. degree. In 2001, Alemseged received his B.Sc. degree in Irrigation Engineering with distinction and was offered a lecturer position in AWTI. He has taught several undergraduate courses including principles of hydraulics, irrigation and hydrology.
Alemseged joined the International Institute for Geo-information Science and Earth Observation (ITC), Enschede, The Netherlands in 2003 where he received his MSc degree in ‘Geo-information science and Earth Observation with specialization Watershed management, Conservation and River Basin Planning’ in 2005. His MSc thesis was selected as the best thesis by the scientific jury of ITC and he has received the ‘van de Klaas Jan Beek Award of 2005’. The title of his MSc thesis is: ‘Integrating hydrodynamic models and high resolution DEM (LIDAR) for flood modeling’.
Since March 2006, Alemseged has been a PhD candidate in ITC faculty of the University of Twente. His research interest includes hydrologic modeling, flood modeling, and hydrological change detection and variability using ground based and remote sensing observations.