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The six rainfall-runoff models can be configured based on: (i) a delineation of the catchment into smaller sub-catchments; or (ii) a lumped catchment scale. Inputs are spatially explicit, allowing representation of the heterogeneity in sub-catchments for land use, rainfall, evapotranspiration, etc; the generated runoff is lumped at the catchment scale. The models can be calibrated using observed climate and streamflow data in gauged catchments using a combination of objective functions and optimisation methods (the framework includes four optimisation methods and four pre-defined objective functions - more information is available via Enhanced analysis - SRG). The calibrated models can be used to simulate runoff from ungauged catchments using a suitable regionalisation method; alternatively, it may be possible to estimate parameter values from other studies or from the literature. Model inputs and outputs can be displayed as time series or spatial and temporal plots to assist with quality assurance. The framework also provides a number of test statistics that can be used to determine the quality of model calibration and simulation results. (After Abridged from Welsh, et al, 2013.)
The general approach in these models is to use rainfall and evaporation data as inputs. Stream flow is produced as a model output, often as the sum of quick flow and slow flow components (Figure 1). If evaporation data is not available, temperature may be used as an input in some models (e.g. IHACRES Classic). The complexity of the models varies considerably from four parameter models (e.g. GR4J) to models with a large number of conceptual stores and parameters (e.g. the Sacramento model).
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