Development of a geographic information system (GIS) for managing and predicting coastal water quality in the Pearl River estuary (South China)

Abstract

The Pearl River Estuary (PRE), in recent decades, has experienced serious water quality deterioration due to the massive economic and industrial developments in the nearby regions. Mitigation of this situation begins with a good quantitative understanding of the existing hydrodynamic and environmental conditions. Geographic Information System (GIS), with its ability to handle large quantities of geographically-referenced hydrodynamic and water quality information as well as to visualize spatial relationships, has been identified as a plausible tool for this task. However, limited research has been conducted on the development of a GIS for hydrodynamic and water quality applications, particularly for integrations with models which facilitate three-dimensional (3D), dynamic simulations. This has provided the motivation for the development of a tool using GIS technology in 3D hydrodynamic-water quality modelling to assist engineers and decision makers in managing and predicting water quality in the PRE. The GIS-based hydrodynamic-water quality tool for the PRE in this study is developed using the ArcView GIS software package. The developed GIS consists of three main components. The first component involves the compilation of a GIS database of hydrodynamic and water quality data and the development of a set of data retrieval and visualization functions. The compilation of the GIS database has unified hydrodynamic and water quality field-collected data into a single management platform for efficient retrieval and query of information for the PRE. The developed data display tools have resolved the challenge of dealing with 3D, dynamic marine data in a GIS environment by supplementing the time series, profile, as well as dynamic display. In addition, the interpolation functions combining both spatial and one-dimensional (ID) data-fitting techniques adopted in this study have accounted for the typically temporally and spatially scattered field data. The second component involves the integration of the GIS with a 3D finite element hydrodynamic-water quality coupled model based on the interface integration method. A pre-processor component is developed for analyzing and exporting GIS data to model input files, while a post-processor component is for importing the model output and displaying it in the GIS interface. Similar data displaying functionality for field data is extended for visualization of model input and results. In addition, the integrated-GIS is also customized for generating the setup of model mesh grid and for carrying out refinements. Successful integration of the GIS with the hydrodynamic-water quality coupled model has allowed the mutual exchange of field-collected and model data, and thus provides support for various useful applications, such as setting of model initial conditions, calibration and verification of the model, and assessment of quality of the collected data. The third component involves the incorporation of an environmental impact assessment (EIA) module into the system for evaluation of water quality conditions based on either field-collected data or model-predicted results. This module makes use of the GIS Map Algebra functions to combine raster layers of different parameters into a single raster of water quality index. The resulting spatial layer provides an overall picture of the areas potentially at risk. This newly developed integrated-GIS is a comprehensive tool for coastal management, research, and decision-making. This system provides a wide range of applications including retrieval and visualization of 3D, dynamic marine data, viewing and modification of model input, display of model output, estimation of unknown points in space and time, investigation of temporal and spatial trends, assessment of quality of the collected data, and management of wastewater disposal. In the future, the system can be shared with other domains in the field and thus promote better understanding and management of the PRE.