Reliability of soil data and risk assessment of data applications

Four types of soil data, each with a characteristic reliability, are proposed for point observations and areas of land. Distinctions are based on procedures by which data are obtained: (i) measurement; (ii) estimation by experts; (iii) calculation by pedotransfer-functions, and (iv) same, by simulation models. Data are either static, requiring a single measurement, or dynamic, requiring measurements over a period of time. Three case studies illustrate: (i) interpolation of a static point measurement with multiple indicator kriging allowing an expression of risk of exceeding critical values; (ii) interpolation based on a time series of nitrate fluxes, calculated with a deterministic simulation model. Reliability was difficult to define because input data consisted of measured and estimated parameters with unknown reliability, and (iii) expression of data reliability in an uncertainty analysis by using rotated random scan and Monte Carlo techniques in the context of simulating water fluxes in a clay soil. Results reflect data reliability and use of this procedure is therefore recommended.