Author:
Robinson N. J.,Benke K. K.,Norng S.
Abstract
In the past, uncertainty analysis in soil research was often reduced to consideration of statistical variation in numerical data relating to model parameters, model inputs or field measurements. The simplified conceptual approach used by modellers in calibration studies can be misleading, because it relates mainly to error minimisation in regression analysis and is reductionist in nature. In this study, a large number of added uncertainties are identified in a more comprehensive attention to the problem. Uncertainties in soil analysis include errors in geometry, position and polygon attributes. The impacts of multiple error sources are described, including covariate error, model error and laboratory analytical error. In particular, the distinction is made between statistical variability (aleatory uncertainty) and lack of information (epistemic uncertainty). Examples of experimental uncertainty analysis are provided and discussed, including reference to error disaggregation and geostatistics, and a systems-based analytic framework is proposed. It is concluded that a more comprehensive and global approach to uncertainty analysis is needed, especially in the context of developing a future soils modelling process for incorporation of all known sources of uncertainty.
Subject
Earth-Surface Processes,Soil Science,Environmental Science (miscellaneous)
Cited by
23 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献