10:45 AM - 12:15 PM
[HTT17-P04] Elucidation of mechanism of macrophytes overgrowth in lakes using satellite images
Keywords:macrophytes, lakes, eutrophication, COD, organic substance
1 Introduction
Macrophytes are an important biome for freshwater ecosystems, playing a role related to carbon and nutrient cycling (Villa et al., 2015). However, the overgrowth of macrophytes has recently become a problem in several lakes in Japan (Yamamuro, 2014). This problem is related to eutrophication of lakes due to human activities (Kiage and Walker, 2009). Therefore, it is necessary to elucidate the mechanism of macrophyte merging in lakes. However, previous studies use satellite data with low spatial resolution, such as MODIS and LANDSAT, and often have a short study period. In addition, the focus is on mapping the distribution area of macrophytes, and there is no study of the relationship with meteorological or water quality indicators that affect the growth of macrophytes. So, it is necessary to combine data from multiple types of satellites to explore the relationship between climate or water quality indicators and macrophyte growth over a longer period with greater precision. In this study, specific indicators of macrophyte growth (time series of vegetation index and macrophyte area) are extracted from Lake Suwa, Lake Inbauma, and Lake Biwa, where macrophyte growth is a particular problem in Japan, to clarify the relationship with climate and water quality indicators.
2 Research Methodology
Form Planet labs satellite images (2019-2022), NDVI, NDAVI, and WAVI were calculated for the target area, and the area was extracted as the area of thriving floating leaf plants in the range of water depth shallower than 3 m with NDAVI of 0.2 or more. Using the same method, the area of thriving floating leaf plants was extracted from Sentinel2, LANDSAT8, 7, and 5 data. Areas other than the areas extracted as floating-leaf plant coverage in the satellite images were classified into water areas and submerged plant coverage areas using Random Forest, and the areas were extracted. Time series data on the area of floating and submerged vegetation obtained from this process were generated. In addition, time series data of vegetation indices obtained from the analysis of satellite images were generated. Using the time-series data of vegetation area and vegetation index obtained in this way and the time-series data of weather and water quality data for the same period, we calculated the correlation coefficient between each indicator and conducted a causal analysis (Granger causality test) to examine the variables that influence the growth of macrophytes.
3 Results and Discussion
In Lake Suwa, the area of floating leafy vegetation is on an upward trend between 1984 and 2020. This trend has been particularly strong after 2000. This may be due to the decrease of algae and improvement of water quality. Among the meteorological data, the highest correlation with the area of floating vegetation was the annual mean wind speed. The water quality index that showed the highest correlation with it was COD at the R5 that flows into the lake from the north side of Lake Suwa. Among the water quality of Lake Suwa, transparency and coliform group counts tended to be highly correlated with it. The results of causal analysis showed that COD was the water quality indicator that tended to have the highest Granger causality with the area of floating plants in Lake Suwa. COD is an indicator of organic substance, and when there is a lot of organic substance, it decomposes and changes into nitrate, which may positively affect the growth of water plants in the lake.
4 Conclusion
In summary, wind speed and the behavior of organic substance in river water and lake water influence the area where macrophytes grow in Lake Suwa. In the future, a more quantitative evaluation of the influence of climatic and water quality factors, as well as a comprehensive interpretation that considers the status of land cover and human activities in the watershed, which affect water quality, will be required.
Macrophytes are an important biome for freshwater ecosystems, playing a role related to carbon and nutrient cycling (Villa et al., 2015). However, the overgrowth of macrophytes has recently become a problem in several lakes in Japan (Yamamuro, 2014). This problem is related to eutrophication of lakes due to human activities (Kiage and Walker, 2009). Therefore, it is necessary to elucidate the mechanism of macrophyte merging in lakes. However, previous studies use satellite data with low spatial resolution, such as MODIS and LANDSAT, and often have a short study period. In addition, the focus is on mapping the distribution area of macrophytes, and there is no study of the relationship with meteorological or water quality indicators that affect the growth of macrophytes. So, it is necessary to combine data from multiple types of satellites to explore the relationship between climate or water quality indicators and macrophyte growth over a longer period with greater precision. In this study, specific indicators of macrophyte growth (time series of vegetation index and macrophyte area) are extracted from Lake Suwa, Lake Inbauma, and Lake Biwa, where macrophyte growth is a particular problem in Japan, to clarify the relationship with climate and water quality indicators.
2 Research Methodology
Form Planet labs satellite images (2019-2022), NDVI, NDAVI, and WAVI were calculated for the target area, and the area was extracted as the area of thriving floating leaf plants in the range of water depth shallower than 3 m with NDAVI of 0.2 or more. Using the same method, the area of thriving floating leaf plants was extracted from Sentinel2, LANDSAT8, 7, and 5 data. Areas other than the areas extracted as floating-leaf plant coverage in the satellite images were classified into water areas and submerged plant coverage areas using Random Forest, and the areas were extracted. Time series data on the area of floating and submerged vegetation obtained from this process were generated. In addition, time series data of vegetation indices obtained from the analysis of satellite images were generated. Using the time-series data of vegetation area and vegetation index obtained in this way and the time-series data of weather and water quality data for the same period, we calculated the correlation coefficient between each indicator and conducted a causal analysis (Granger causality test) to examine the variables that influence the growth of macrophytes.
3 Results and Discussion
In Lake Suwa, the area of floating leafy vegetation is on an upward trend between 1984 and 2020. This trend has been particularly strong after 2000. This may be due to the decrease of algae and improvement of water quality. Among the meteorological data, the highest correlation with the area of floating vegetation was the annual mean wind speed. The water quality index that showed the highest correlation with it was COD at the R5 that flows into the lake from the north side of Lake Suwa. Among the water quality of Lake Suwa, transparency and coliform group counts tended to be highly correlated with it. The results of causal analysis showed that COD was the water quality indicator that tended to have the highest Granger causality with the area of floating plants in Lake Suwa. COD is an indicator of organic substance, and when there is a lot of organic substance, it decomposes and changes into nitrate, which may positively affect the growth of water plants in the lake.
4 Conclusion
In summary, wind speed and the behavior of organic substance in river water and lake water influence the area where macrophytes grow in Lake Suwa. In the future, a more quantitative evaluation of the influence of climatic and water quality factors, as well as a comprehensive interpretation that considers the status of land cover and human activities in the watershed, which affect water quality, will be required.