Abstract:
Prediction stream flow of ungauged catchment is important for water resources design,
planning and management system. Stream flow estimation in catchment is probably one of the
most basic and oldest tasks of hydrologists. In developing countries like Ethiopia most of the
rivers are ungauged. Therefore, applying regionalization techniques on an ungauged or poorly
gauged river basin is crucial. The study area of Zamra catchment have the scarcity of record
data, but the Zamra River have the capability of feeding the society nearby as source of small scale irrigation. Therefore, this thesis deals with stream flow prediction in an ungauged Zamra
catchment using GR4J hydrological model. Physical similarity regionalization techniques were
applied to identify physically similar catchments which would be the best donors for streamflow
prediction in ungauged catchments. For this study, seven gauged catchments located in gheba
sub basin of Tekeze river basin were used. The physical similarity among catchments was
determined by a weighted Euclidean distance based on catchment descriptors including
catchment topography, land cover, and soil type. The results of physical similarity index
indicate that all of the Watersheds are similar to each other. Gheba Nr Adikumsi Watershed
with S value of 0.99 are used as donor Watershed to calibrate GR4J model. The Time period of
2004-2013 is used for model Calibration, and the 2014-2018 period for validation. The result
shows that the calibrated gauging river have good agreement since Nash Sutcliff efficiency and
R
2
greater than 0.75. Discharge for the ungauged watershed simulates on a daily basis in the
period of 2004-2018 and with input data such as precipitation and potential evapotranspiration.
The importance of the study is in that the output data from the Model can be used in water
resource planning and management for its irrigation potential and any water harvesting
structures.
