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The six rainfall-runoff models can be configured based on: (i) a delineation of the catchment into smaller lumped sub-catchments; or (ii) a lumped catchment scale. Inputs are spatially explicit for each sub-catchment, allowing representation of the heterogeneity in catchments at the sub-catchments for catchment scale. Variations in land use, rainfall, evapotranspiration, etc; the generated runoff is . are lumped at the sub-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 via /wiki/spaces/SD37/pages/25598103). 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 descriptive statistics that can be used to determine assess the quality of model calibration and simulation results. (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, as illustrated in Figure 1 (Note that quick flow includes may includs lateral subsurface throughflow - also known as interflow - as well as surface runoff). 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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