An Integrated Web-Based System for the Monitoring and Forecasting of Coastal Harmful Algae Blooms: Application to Shenzhen City, China

Huang Huang,Tian Tian

doi:10.3390/jmse7090314

Abstract

Harmful algal blooms (HABs) cause environmental problems worldwide. Continuous monitoring and forecasting of harmful algal blooms are necessary for marine resources managers to detect the intensity and spatial extent of HABs and provide early warnings to the public. In this study, we introduce an integrated web-based system for the monitoring and forecasting of coastal HABs. The system is named the Harmful Algal Blooms Monitoring and Forecasting System (HMFS). HMFS integrates in situ observations, a remote-sensing-based model, hydrodynamic and water quality model and Web-Based Geographic Information System (GIS) techniques into one environment. The in situ sensors and remote sensing model provide automatic and continuous monitoring of the coastal water conditions. The numerical models provide short-term prediction and early warning of HAB of up to 5 days. The overall forecast accuracy is more than or equal to 50% for the major coastal areas of Shenzhen in 2018. By leveraging a web-based GIS technique and Service-Oriented Architecture (SOA), the web portal of HMFS provides a graphic interface for users and mangers to view real-time in situ measurements and remote sensing maps, explore numerical model forecasts and get early warning information. HMFS was applied to Shenzhen, which is a rising megacity in Southern China. The application study demonstrated the applicability and effectiveness of HMFS for monitoring and predicting HABs.

Highlights

The coastal and marine environment provides valuable natural resources for food, transportation, and recreation
In China, harmful algal blooms (HABs) are a national concern because they have occurred in every coastal province and their occurrences are on the rise [2]
Despite the significant progress that has been made in monitoring techniques, numerical ocean modeling, remote sensing methods of ocean color and Geographic Information System (GIS), integrated systems that are capable of integrating these techniques and models into a single platform for HABs detection and forecasting are limited

Summary

Introduction

The coastal and marine environment provides valuable natural resources for food, transportation, and recreation. Despite the significant progress that has been made in monitoring techniques, numerical ocean modeling, remote sensing methods of ocean color and GIS, integrated systems that are capable of integrating these techniques and models into a single platform for HABs detection and forecasting are limited. This study introduces the design and development of a Web-Based GIS system named HABs Monitoring and Forecasting System (HMFS). HMFS integrates in situ observations, a remote-sensing-based model, hydrodynamic and water quality model and Web-Based GIS technique into one environment. The geodatabase is a central data repository to store and manage all kinds of data, including time series at in situ stations, remote sensing maps and numerical model outputs. The web portal can be accessed through a common browser such as Internet Explorer

In Situ Observation

Remote Sensing Based Estimation of Chlorophyll-a

Numerical Models for HAB Forecasting

Data Post-Processing and Publication

Findings

Overview of the Web Portal