This is not a comprehensive explanation of any methods used to prepare data for use in Source. Although it refers specifically to calibration, it is suggested that these methods are used for data in general.
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This section introduces some interpolation methods and indicates how those methods can result in unexpected distortions to data. Care and experience is required to undertake effective interpolation, and the resulting data should be tested to avoid surprises.The simplest spatial interpolation methods are usually based on deterministic concepts. These assume that one true, but unknown, spatial pattern exists which is estimated by either some ad-hoc assumptions or some optimality criterion. The simplest spatial interpolation methods are usually based on deterministic concepts. These assume that one true, but unknown, spatial pattern exists which is estimated by either some ad-hoc assumptions or some optimality criterion.
Deterministic interpolation methods include:
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Although slope, land use, soil profile, soil depth and hydraulic conductivity may not be used by a model this information is also worth considering. The type of land use will influence surface runoff characteristics, evapotranspiration rates and interception losses. The soil characteristics will influence the size of soil stores and seepage rates. This sort of information is invaluable for setting realistic bounds on model parameters as well as sanity checking the fluxes out of the model. This information may be used in the grouping of models and parameter sets in the calibration process. Generally the only catchment characteristic required by lumped rainfall runoff models is the catchment area. However, some models (eg. SWAT) need to know slope, land use, soil profile, soil depth, and hydraulic conductivity. The models operate in mm and to convert the model output from runoff depth to runoff volume, catchment area is required. The catchment area is usually an easy parameter to obtain but should be used with caution.The area is dependent on the scale of maps or the DEMs from which it was derived and in flatter areas there can be large uncertainty with regard to where catchment boundaries are. A small error in catchment area can cause a large error in the estimated volume that runs off the catchment.
Rainfall Data
The calibration of most Source models will be most sensitive to the rainfall data that are provided. If the volume of rainfall is incorrect or the rain days are not representative of the peaks in flow then good calibration may be difficult.
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Infilling water quality records
The techniques for infilling continuous water quality records are similar to those mentioned for flow. There is also an additional method that can be applied when there is reasonable correlation between flow and concentration. For example in salinity records high flows are associated with lower salinities and low flows with higher salinities, the opposite occurs with sediment and often particulate nutrient concentrations. There may also be correlations with other constituents for example water temperature may correlate with solar radiation or air temperature, and total suspended solids may correlate with particulate nutrients or turbidity (which can be measured continuously).
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