Development of a collaborative framework for quantitative monitoring and accumulation prediction of harmful algal blooms in nearshore areas of lakes

水华 环境科学 索引(排版) 海岸 环境资源管理 海洋学 生态学 浮游植物 计算机科学 地质学 生物 万维网 营养物
作者
Yinguo Qiu,Hao Liu,Fuzhang Liu,Dexin Li,Chengzhao Liu,Weixin Liu,Jiacong Huang,Qitao Xiao,Juhua Luo,Hongtao Duan
出处
期刊:Ecological Indicators [Elsevier]
卷期号:156: 111154-111154 被引量:7
标识
DOI:10.1016/j.ecolind.2023.111154
摘要

Harmful algal blooms (HABs) in lakes have been a salient problem of global water environment due to their harmful impacts. Present situation and future tendency of HABs in nearshore areas are more important than those in other areas of lakes, but traditional researches generally ignored this point. This study developed a novel framework aiming to timely and accurately grasp both present conditions and accumulation risks of HABs in nearshore areas of lakes. By designing a quantitative monitoring method, land-based video monitoring devices around lakes were used to obtain present situation of HABs in nearshore areas rapidly, periodically and automatically. On this basis, a coupled simulation model was established to predict accumulation risks of HABs in nearshore areas using five indexes, i.e., shoreline index, chlorophyll-a index, algal bloom index, wind direction index and dynamic index. Experimental results indicated that the accuracy of HAB monitoring in nearshore areas is quite satisfying (85.20%) and the prediction results of HABs accumulation in nearshore areas is reasonable and credible. This study demonstrated a high value of the developed collaborative framework in emergency prevention and control of HABs in lakes.

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