Keywords
monitoring design, water quality, effectiveness, constrained optimization
Start Date
1-7-2010 12:00 AM
Abstract
The issues of possible improvements, increased efficiency and/or optimizationof a monitoring system in general, and a monitoring design in particular, are urgent. Sincemonitoring activities are always limited by financial and logistics constraints, algorithms ofconstrained optimization are deemed more suitable for this purpose. Monitoring designs aredeveloped as solutions of an operation research model. In order to formulate such modelthe effectiveness function has been introduced. The effectiveness reflects the extent towhich a monitoring design meets the objectives of the monitoring program and can be usedfor comparison of different monitoring designs. The effectiveness function depends on theinvestigated water quality parameters, selected indicators of water quality and theirestimators. The function properties suggest the selection of an optimization algorithm. Theproposed approach has been applied to a case study in order to develop temporalmonitoring designs. It has been shown that the designs differ significantly only when thelevels of the effectiveness are high. With the effectiveness of 80% or less the designs fordifferent water quality parameters and the same indicator can be compromised. Sincemonitoring data are usually used for various purposes, the preference should be given tosimple monitoring designs or to the designs which support efficient reconstruction ofchemographs of investigated water quality parameters
Efficiency Criteria for Water Quality Monitoring
The issues of possible improvements, increased efficiency and/or optimizationof a monitoring system in general, and a monitoring design in particular, are urgent. Sincemonitoring activities are always limited by financial and logistics constraints, algorithms ofconstrained optimization are deemed more suitable for this purpose. Monitoring designs aredeveloped as solutions of an operation research model. In order to formulate such modelthe effectiveness function has been introduced. The effectiveness reflects the extent towhich a monitoring design meets the objectives of the monitoring program and can be usedfor comparison of different monitoring designs. The effectiveness function depends on theinvestigated water quality parameters, selected indicators of water quality and theirestimators. The function properties suggest the selection of an optimization algorithm. Theproposed approach has been applied to a case study in order to develop temporalmonitoring designs. It has been shown that the designs differ significantly only when thelevels of the effectiveness are high. With the effectiveness of 80% or less the designs fordifferent water quality parameters and the same indicator can be compromised. Sincemonitoring data are usually used for various purposes, the preference should be given tosimple monitoring designs or to the designs which support efficient reconstruction ofchemographs of investigated water quality parameters
