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Data acquisition. Cost-effective methods for obtaining data on water quality

TitleData acquisition. Cost-effective methods for obtaining data on water quality
Publication TypeJournal Article
Year of Publication1987
AuthorsMar BW, Horner R.R., Richey J.S., Palmer RN, Lettenmaier DP
JournalEnvironmental Science and Technology
Volume20
Issue6
Start Page545
Pagination545-551
Date Published06/1986
Abstract

Environmental monitoring is becoming a larger and more important part of environmental impact assessment, the de velopment and management of ~tural resources, and the regulation of environmental qnality (I). Despite this, until recently little work has been done on the design of cost-effective monitoring methcdology. We recently concluded a threeyear study, for the Electric Power Research htitute, on aquatic ecosystem monitoring programs in the electric utility industry. The study included an extensive survey of sampling program design concepts and data acquisition practices (2-4). We developed a forW13-9SWW~2M)545$01.~ 0 1986 American Chemical Society mal, systematic procedure based on extensive interviews and consultation with industry experts and information published in the literature. The procedure involves four general tasks, which accomplish the following: identification of environmental changes of interest and the effects that would most likely manifest these changes, formulation of potential changes into conventional scientific hypotheses; definition of variables to be sampled, the technique to be used, and any Environ. Sci. Technol., Vol. 20, No. 6, is86 545 alternative hypotheses that may cause the same type of change; and determination of whether complementary hypotheses provide the same information for decision making at lower cost, design of a cost-effective monitoring program to test each hypothesis by considering trade-offs between the improvement in statistical power (that is, the pmbabdity of discriminating between the various hypotheses) and the added cost of data acquisition, and integration of the individual monitoring programs by multiobjective ranking of all monitoring designs with respect to overall program goals. The general ideas underlying this procedure have been suggested by Platt 0, Mm (a, HoKhz (a, and Rag0 et al. (8), but none of these authors implemented the concepts in a comprehensive operational framework. In this paper we explore certain aspects of the third task described above in greater detail. Specifically, we focus on three sampling program design issues that are essential to cost-effective hypothesis testing and hence to the successful implementation of environmental monitoring programs. The three issues are determining the best strategy to sample the quantity of interest, determining the statistical basis for the experimental design, and estimating the costs of such observations.

DOI10.1021/es00148a002