A framework to determine the locations of the environmental monitoring in an estuary of the Yellow Sea. (October 2018)

• Record Type: Journal Article
• Authors: Kim, Nam-Hoon; Hwang, Jin Hwan; Cho, Jaegab; Kim, Jae Seong
• Is Part Of: Environmental pollution. Volume 241(2018)
• Page Start: 576
• Page End: 585
• Publication Date: 2018-10
• Subjects: Pollution -- Periodicals; Pollution -- Environmental aspects -- Periodicals; Environmental Pollution -- Periodicals; Pollution -- Périodiques; Pollution -- Aspect de l'environnement -- Périodiques; Pollution -- Effets physiologiques -- Périodiques; Pollution; Pollution -- Environmental aspects; Periodicals; Electronic journals; 363.73
• DOI: 10.1016/j.envpol.2018.05.097
• Languages: English
• ISSNs: 0269-7491

Abstract

Abstract: The characteristics of an estuary are determined by various factors as like as tide, wave, river discharge, etc. which also control the water quality of the estuary. Therefore, detecting the changes of characteristics is critical in managing the environmental qualities and pollution and so the locations of monitoring should be selected carefully. The present study proposes a framework to deploy the monitoring systems based on a graphical method of the spatial and temporal optimizations. With the well-validated numerical simulation results, the monitoring locations are determined to capture the changes of water qualities and pollutants depending on the variations of tide, current and freshwater discharge. The deployment strategy to find the appropriate monitoring locations is designed with the constrained optimization method, which finds solutions by constraining the objective function into the feasible regions. The objective and constrained functions are constructed with the interpolation technique such as objective analysis. Even with the smaller number of the monitoring locations, the present method performs well equivalently to the arbitrarily and evenly deployed monitoring system. Graphical abstract: Highlights: A framework designing the systems to monitor pollution in the coastal region with a graphical optimization method. Constrained optimization method can locate monitoring positions appropriately. Objective analysis efficiently interpolates discretized data constructing the objective and constrained functions. The present method successfully determines the minimum number of the monitoring locations to detect the pollution.