Design and practice of a platform for monitoring, early-warning and simulation of algal blooms in Lake Chaohu

Abstract

近20年来，巢湖蓝藻水华频繁暴发，对流域内居民生活和社会生产产生了严重影响.由于缺乏蓝藻水华全方位监测、高精度模拟和智能化分析手段，传统方法难以实现现状掌握、异常识别、原因追溯、未来模拟的目标，无法满足巢湖蓝藻水华科学防控与应急处置的要求，蓝藻水华引起的突发事件随时可能发生.本文针对巢湖蓝藻水华的全面监测和应急决策问题，整合了卫星遥感、无人机监测、视频监控、浮标监测和人工巡测手段，构建了巢湖水质和水华全方位监测网络；结合巢湖水动力-水质-藻类耦合模拟模型，研制了蓝藻水华预测预警和蓝藻水华暴发应急处置模块，实现了蓝藻水华短期（未来2日逐时）和长期（未来7日逐日）模拟，并实现了未来5日蓝藻水华沿岸堆积模拟.最终，通过集成巢湖水质和水华监测、预测预警、应急处置等模块，研发了巢湖蓝藻水华监测预警与模拟分析平台，实现了全湖水质和水华现状迅速掌握、超标信息自动识别与高精度预测预警、沿岸重点区域水华堆积风险评估等功能，为巢湖蓝藻水华的科学防控和应急处置提供了科学依据和数据支撑.;Algal blooms occur frequently in Lake Chaohu in recent 20 years, producing a serious impact on the resident life and social production in Lake Chaohu watershed. Due to the lack of effective means in terms of comprehensive monitoring, high-precision simulation, and intelligent analysis, it is quite difficult for traditional methods to achieve the goal of status mastering, anomalies identifying, causes tracing, and trend simulating of water quality and algal blooms. Accordingly, the requirements of scientific prevention and emergency disposal of algal blooms in Lake Chaohu cannot be satisfied currently, and emergencies caused by algal blooms may occur at any time. Aiming at the requirements of comprehensive monitoring and emergency decision-making of algal blooms, a comprehensive monitoring network of water quality and algal blooms has been established in Lake Chaohu, by integrating several monitoring means, i.e., satellite remote sensing, UAV (unmanned aerial vehicle) monitoring, video monitoring, buoy and field monitoring. And modules of prediction, early-warning and emergency response of algal blooms are developed by combining the coupled hydrodynamic-water quality-algal blooms model. And both short-term (hourly in the next 2 days) and long-term (daily in the next 7 days) simulations of algal blooms are realized, as well as the simulation of algal blooms accumulation along the coast in the next 5 days. Finally, a platform for monitoring, early-warning and simulation of algal blooms in Lake Chaohu has been developed by integrating several function modules, e.g., monitoring of water quality and algal blooms, prediction and early-warning, emergency response, etc. By running this platform, the present situation, exceding standard limits information, and high-precision simulation and prediction of water quality and algae bloom in the whole lake can be grasped quickly and automatically, and risk assessment of algae bloom accumulation in key areas along the coast can also be realized. It shows that the implemented platform can provide scientific basis and data support for scientific prevention and emergency disposal of algal blooms in Lake Chaohu.