A GIS-based software for forecasting pollutant drift on coastal water surfaces using fractional Brownian motion: A case study on red tide drift. (June 2017)

• Record Type: Journal Article
• Authors: Qin, Rufu; Lin, Liangzhao; Kuang, Cuiping; Su, Tsung-Chow; Mao, Xiaodan; Zhou, Yusheng
• Is Part Of: Environmental modelling & software. Volume 92(2017)
• Page Start: 252
• Page End: 260
• Publication Date: 2017-06
• Subjects: Pollutant drift -- Fractional Brownian motion -- GIS -- Particle-tracking -- Visualization -- Red tide; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2017.03.003
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: For ocean pollution emergencies, decision-makers need to quickly know the location of the pollutant for quick assessment and response strategies. In this study, an integrated operational forecasting model coupling a non-Fickian particle-tracking diffusion model based on fractional Brownian motion and geographic information system (GIS) has been developed to implement an operating system for pollutant drift forecasting. The software was developed in C# and C++ language using ArcGIS Engine functions which provides improved visualization and user-friendly and automatic tools for simulation in a geographically referenced environment. The capabilities and effectiveness of the developed software were illustrated by predicting red tide drift through calibration with field observations. This visualized operational forecasting software provides a quick and easy deployable tool for decision-makers in quick response to emergency ocean pollution events. Highlights: A fBm particle-tracking model for forecasting pollutant drift was presented. A GIS-based software coupled with the pollutant dispersion model was developed. The model was well calibrated by field observations. The software provides a quick, visualization and easy deployable tool for drift simulation. The prediction of red tide drift was presented to demonstrate application of software.