Abstract:
Majority of watersheds associated with civil engineering infrastructure projects are
ungauged and most commonly used method to determine streamflow in ungauged basins is
mathematical modelling with the use of Synthetic Unit Hydrograph (SUH) technique. Mathematical
models require watershed characteristics to be spatially and temporally averaged. The SUH is an
event based model which estimates direct runoff. Hence model calibration and verification requires
event based evaluations with a baseflow separation effort or a method incorporating a baseflow model
to combine with the SUH model and generate total runoff. In this study, a rainfall runoff model was
developed using SUH and a linear baseflow concept while selecting the watershed of Attanagalu Oya
at Karasnagala as the study area. Other than the SUH parameters to be identified, the conceptual
model used for this work consisted of 5 model parameters to be optimised. The main objective of this
research was to identify the issues during calibration and verification of this five parameter model.
Model calibration was carried out for 30 datasets, selecting the Mean Ration of Absolute Error
(MRAE) as the objective function. Optimum model parameters for each event were determined and
the most probable range of values for each parameter was computed. Using 30 datasets, model
verification was carried out by assuming that the average of each range would lead to a representative
watershed model. A successful calibration produced a good match of observed and calculated
streamflows with a MRAE of 0.34. Parameter optimisation revealed the inability to obtain an average
initial moisture level for the entire watershed while catering both wet and dry conditions. The runoff
coefficients and rainfall thresholds also indicated the need of further investigations. Event based
modelling approach in this work provides an insight to the watershed behaviour and to the
appropriateness of model parameters, however in order to identify the spatially and temporally
averaged parameters it is necessary to carryout optimisations using a lengthy data series together with
an appropriate model.
