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Data-Based Mechanistic modelling of rainfall to riverflow of large nested tropical rainforest catchments in Ghana.

Research output: Contribution to journalJournal article


<mark>Journal publication date</mark>06/2013
<mark>Journal</mark>Canadian Journal of Pure and Applied Sciences
Issue number2
Number of pages20
Pages (from-to)2405-2424
<mark>Original language</mark>English


Within the Data Based Mechanistic (DBM) Transfer Function rainfall to riverflow modelling approach a mathematical model in the form of a transfer function rainfall to riverflow is obtained by extracting information from the available
time series data. The DBM methodology is able to use the data to identify the model structure in an objective statistical manner using the simplified recursive instrumental variable algorithm (SRIV). The approach requires few spatially distributed data for the estimation of the models and is, therefore, suitable for data limited regions like West Africa. Within this paper we present a review of the application of the model in hydrological studies in different climatic conditions. The application of the approach to large nested catchments in the humid rainforest zone in Ghana have also been presented. The approach revealed an exponential form of non-linear behaviour for the catchments. The estimated
model parameters and the associated dynamic response characteristics (DRCs) of time constant (TC) and steady state gain (SSG) indicates that riverflow generation within the catchments are not flashy. The model identified mathematical
relationships which could be used to simulate flows in the catchments.