Analysis of Statistical Monitoring Network Design
- 1 September 1987
- journal article
- Published by American Society of Civil Engineers (ASCE) in Journal of Water Resources Planning and Management
- Vol. 113 (5), 599-615
- https://doi.org/10.1061/(asce)0733-9496(1987)113:5(599)
Abstract
The need to detect anthropogenic impacts in the natural environment has increased interest in the design of cost‐effective environmental monitoring networks. A variety of statistical models have been proposed for this purpose. This paper examines four statistical models, with varying degrees of complexity, used to represent the underlying characteristics of potential impacts. The models are incorporated into an optimization procedure used to select cost‐effective designs. Aquatic monitoring data from a nuclear power plant are used to test the robustness of the statistical models, analyze their sensitivity to input parameters, and determine the circumstances that require the use of more complex statistical models to design effective monitoring programs.Keywords
This publication has 9 references indexed in Scilit:
- Optimal design of biological sampling programs using the analysis of varianceEstuarine, Coastal and Shelf Science, 1986
- Optimization of Water Quality Monitoring NetworksJournal of Water Resources Planning and Management, 1985
- Space–Time Correlation and Its Effects on Methods for Detecting Aquatic Ecological ChangeCanadian Journal of Fisheries and Aquatic Sciences, 1985
- Water quality monitoring—Some practical sampling frequency considerationsEnvironmental Management, 1980
- Sampling frequency for river quality monitoringWater Resources Research, 1978
- DESIGN CONSIDERATIONS FOR AMBIENT STREAM QUALITY MONITORING1Jawra Journal of the American Water Resources Association, 1978
- Evaluation of environmental data relating to selected nuclear power plant sites. The Zion Nuclear Power Station sitePublished by Office of Scientific and Technical Information (OSTI) ,1976
- QUANTITATIVE METHODS FOR PRELIMINARY DESIGN OF WATER QUALITY SURVEILLANCE SYSTEMS1Jawra Journal of the American Water Resources Association, 1974
- Cost‐effectiveness methodologies for data acquisition in water quality managementWater Resources Research, 1973