Determination of Optimal Water Quality Monitoring Points in Sewer Systems using Entropy Theory

Abstract

Abstract:To monitor water quality continuously over the entire sewer network is important for efficient management of the system. However, it is practically impossible to implement continuous water quality monitoring of all junctions of a sewer system due to budget constraints. Therefore, water quality monitoring locations must be selected as those points which are the most representative of the dataset throughout a system. However, the optimal selection of water quality monitoring locations in urban sewer networks has rarely been studied. This study proposes a method for the optimal selection of water quality monitoring points in sewer systems based on entropy theory. The proposed model searches for a quantitative assessment of data collected from monitoring points. The points that maximize the total information among the collected data at multiple locations are selected using genetic algorithm (GA) for water quality monitoring. The proposed model is demonstrated for a small urban sewer system.

A Greedy Algorithm for Optimal Sensor Placement to Estimate Salinity in Polder Networks

“…Comprehensive reviews can be found in [16][17][18] for different water systems. Entropy theory developed by [19] is used for water quality monitoring networks optimization in rivers [7,20,21], in a bay [22], in sewer systems [23,24] and groundwater [25][26][27]. PCA is used in [8,9] for river water quality monitoring network analysis.…”

Diagnose Urban Drainage Network Problem Based on Internet of Things and Big Data

“…Drainage pipe network monitoring is of great significance for urban storm water management. Strengthening pipe network monitoring helps to protect drainage facilities, improve drainage system, and urban information management [1], which is the basis for the construction of information platform. The performance of drainage network is evaluated by on-line monitoring technology to guide the operation management and maintenance design of drainage system.…”

A novel SON2‐based similarity index and its application for the rationalization of river water quality monitoring network

“…Memarzadeh, Mahjouri, and Kerachian () proposed a methodology that combines a dynamic FA and discrete entropy theory, which was applied to the River Karoon (Iran). Lee () combined the entropy theory with a genetic algorithm in order to optimize the number of monitoring points in sewer systems. Another integrated technique, which uses a genetic algorithm and geographic information system for the design of effective water quality monitoring network in a large river system was proposed (Park et al, ).…”