Long-Term Changes and Influencing Factors of Water Quality in Aquaculture Dominated Lakes Unveiled by Sediment Records and Time Series Remote Sensing Images

Hydraulic connectivity has great effects on water quality. Enclosure aquaculture can largely alter lake flow regime and thus deteriorate water quality. Understanding the dynamics and influencing factors of water quality in enclosure aquaculture lakes is of great significance to ecosystem restoration of degraded lakes. However, it remains challenging due to the lack of long time series data. In this study, the dynamics of water quality in aquaculture dominated lakes were captured through Pb-210 and Cs-137 dating based on sediment records. Meanwhile, the effects of landscape pattern within aquaculture lakes on water quality were revealed by long time series of remote sensing images. Results showed the Pb-210 and Cs-137 sediment dating could provide an effective way to obtain long-term series of lake water quality data in the unmonitored area. The contents of lake sediment nutrients showed an upward trend from 1960 to 2018. The transformation of lakes from agriculture dominated to aquaculture dominated had increased sediment nutrients level. The long-term changes of lake sediment nutrients could be well explained by the landscape pattern metrics within aquaculture lakes, with an average explain power of 87.6%. The configuration metrics at class level had the most contribution (73.6%) to the changes of lake sediment nutrients, followed by the composition metrics (48.8%) and the configuration metrics at landscape level (33.4%). This study can provide a promising method to understand water quality changes in lakes with no historical monitoring data available and is of great benefit to water quality management in aquaculture dominated lakes.

Automated summary

Hydraulic connectivity has a significant impact on water quality, and enclosure aquaculture can deteriorate water quality by altering lake flow regime. This study used sediment dating and remote sensing images to capture the dynamics of water quality in aquaculture dominated lakes and reveal the influence of landscape pattern on water quality. The results showed that sediment dating and landscape pattern metrics can effectively provide long-term lake water quality data and contribute to water quality management in aquaculture dominated lakes.