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Title: Regionalized variable theory and assessment of the consequences of uncertainty in optimal design of water-quality sampling networks

Thesis/Dissertation ·
OSTI ID:5282291

As the task of environmental planning and management becomes increasingly complex and costly, the amount and quality of data it requires grows accordingly. The vast-majority of water-quality sampling networks are designed through a ill-defined, qualitative approach. This dissertation develops the theoretical background for a quantitative approach to the design, testing, and enhancement of water-quality sampling and monitoring networks. The method uses a technique derived from regionalized variable theory known as universal kriging to provide a measure of the uncertainty of estimates at unsampled locations for a particular sampling network. Regionalized variable theory provides a powerful tool for the analysis of spatially auto correlated data. Essentially all aquatic parameters exhibit some degree of autocorrelation due to the nature of hydrodynamic mixing and advection processes. This allows for the adaptation of regionalized variable theory for use in the design of water-quality-sampling networks. By providing a variance for estimates at unsampled locations, kriging gives a measure of uncertainty. A curve depicting the relative severity of water quality in the region of interest is used in conjunction with the kriging variance to develop a function which describes the consequences of the uncertainty of these estimates.

Research Organization:
Wisconsin Univ., Milwaukee (USA)
OSTI ID:
5282291
Resource Relation:
Other Information: Thesis (Ph. D.)
Country of Publication:
United States
Language:
English