Application of Optimization Algorithms for the Improvement of Water Quality Monitoring Systems

摘要

The number of observations is limited by budgetary and other constraints, but the collected data must be sufficient to meet a wide range of monitoring objectives. The process of determining an efficient temporal water quality monitoring design has been formulated as an optimization problem. In the problem, a target level of acceptable uncertainty for a given indicator is specified, and the resultant solution is the smallest set of observation dates sufficient to achieve this level. Solution robustness can be improved by adding a sliding window - a maximum range in deviations of the observation dates that still provide the acceptable level of uncertainty. Application of the proposed approach to a real-world case study suggested an iterative procedure for the improvement of monitoring designs.