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

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.

Automated summary

This study developed a novel framework that can timely and accurately grasp both present conditions and accumulation risks of harmful algal blooms (HABs) in nearshore areas of lakes. By using quantitative monitoring and simulation modeling, the framework showed high value in monitoring and emergency prevention of HABs.