Deriving the storage function model parameters by using runoff data only

Rainfall-runoff models require rainfall and runoff data for determining the model parameters. Problem usually emerges in finding the optimal model parameters due to lack of rainfall data in terms of quantity and quality. In a lumped model such as the storage function model, good quality and quantity of input (rainfall) data that represent the catchment behavior is needed in order to get the optimum model parameters. However, it is difficult to get the rainfall data that fulfill the requirement as results of high spatial variability of rainfall data and lack of automatic rainfall recorder that are commonly found in tropical regions. To overcome the above problem, the filter separation autoregressive model might be used to estimate the rainfall time series based on runoff data only. The resulted rainfall together with the runoff data are then used to find the storage function model parameters. The results show that the inversely estimated rainfall was useful for estimating the rainfall-runoff model parameters in topical regions.