Surface solar radiation and lake productivity: Investigating a global relationship

Abstract

In recent decades, the intensity and frequency of lake algal blooms have been increasing worldwide. In addition to potentially toxic effects for humans and wildlife, intense algal blooms negatively impact recreation and economy. Therefore, it is crucial to understand the underlying mechanisms controlling the blooms. Most algal bloom management programs focus on limiting nutrient input; however, other controlling factors such as solar radiation are often not considered in practice. This study examined time series of surface solar radiation (SSR), chlorophyll-a, temperature and other factors controlling algal growth since the 1990’s, using a combination of in situ and satellite data. A random forest regression model was used to qualitatively investigate the importance of different controlling factors on chlorophyll-a rates of increase during algal blooms. Results of the modelling support that temperature and SSR – both during and immediately before periods of rapid growth – were important predictive factors in seasonal chlorophyll-a rates overall. This study joins recent literature in successfully demonstrating the feasibility of using satellite data for global scale lake monitoring, using a widely applicable supervised machine learning tool. The results of this study, and further research taking advantage of satellite data for lake monitoring, will increase our understanding of factors controlling algal bloom intensification and improve our ability to evaluate best management practices.