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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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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