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) - Qin, Rufu; Lin, Liangzhao; Kuang, Cuiping; Su, Tsung-Chow; Mao, Xiaodan; Zhou, Yusheng
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.