Center of Excellence for Infrastructure Engineering and Management, Faculty of Civil Engineering, University of Tehran, Tehran, Iran.
Environ Monit Assess. 2010 Feb;161(1-4):247-57. doi: 10.1007/s10661-008-0742-3. Epub 2009 Feb 6.
Assessment and redesign of water quality monitoring networks is an important task in water quality management. This paper presents a new methodology for optimal redesign of groundwater quality monitoring networks. The measure of transinformation in discrete entropy theory and the transinformation-distance (T-D) curves are used to quantify the efficiency of sampling locations and sampling frequencies in a monitoring network. The existing uncertainties in the T-D curves are taken in to account using the fuzzy set theory. The C-means clustering method is also used to classify the study area to some homogenous zones. The fuzzy T-D curve of the zones is then used in a multi-objective hybrid genetic algorithm-based optimization model. The proposed methodology is utilized for optimal redesign of monitoring network of the Tehran aquifer in the Tehran metropolitan area, Iran.
水质监测网络的评估和重新设计是水质管理中的一项重要任务。本文提出了一种用于地下水质量监测网络优化重新设计的新方法。离散熵理论中的互信息测度和互信息距离（T-D）曲线用于量化监测网络中采样位置和采样频率的效率。使用模糊集理论考虑 T-D 曲线中的现有不确定性。C-均值聚类方法也用于将研究区域划分为一些同质区域。然后，在基于多目标混合遗传算法的优化模型中使用该区域的模糊 T-D 曲线。该方法用于优化伊朗德黑兰大都市区德黑兰含水层的监测网络重新设计。
