Spatio-Temporal Variability of Phytoplankton Primary Production in Baltic Lakes Using Sentinel-3 OLCI Data
Phytoplankton primary production (PP) in lakes play an important role in the global carbon cycle. However, monitoring the PP in lakes with traditional complicated and costly in situ sampling methods are impossible due to the large number of lakes worldwide (estimated to be 117 million lakes). In thi...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-07-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/15/2415 |
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| author | Tuuli Soomets Kristi Uudeberg Kersti Kangro Dainis Jakovels Agris Brauns Kaire Toming Matiss Zagars Tiit Kutser |
| author_facet | Tuuli Soomets Kristi Uudeberg Kersti Kangro Dainis Jakovels Agris Brauns Kaire Toming Matiss Zagars Tiit Kutser |
| author_sort | Tuuli Soomets |
| collection | DOAJ |
| description | Phytoplankton primary production (PP) in lakes play an important role in the global carbon cycle. However, monitoring the PP in lakes with traditional complicated and costly in situ sampling methods are impossible due to the large number of lakes worldwide (estimated to be 117 million lakes). In this study, bio-optical modelling and remote sensing data (Sentinel-3 Ocean and Land Colour Instrument) was combined to investigate the spatial and temporal variation of PP in four Baltic lakes during 2018. The model used has three input parameters: concentration of chlorophyll-<i>a</i>, the diffuse attenuation coefficient, and incident downwelling irradiance. The largest of our studied lakes, Võrtsjärv (270 km<sup>2</sup>), had the highest total yearly estimated production (61 Gg C y<sup>−1</sup>) compared to the smaller lakes Lubans (18 Gg C y<sup>−1</sup>) and Razna (7 Gg C y<sup>−1</sup>). However, the most productive was the smallest studied, Lake Burtnieks (40.2 km<sup>2</sup>); although the total yearly production was 13 Gg C y<sup>−1</sup>, the daily average areal production was 910 mg C m<sup>−2</sup> d<sup>−1</sup> in 2018. Even if lake size plays a significant role in the total PP of the lake, the abundance of small and medium-sized lakes would sum up to a significant contribution of carbon fixation. Our method is applicable to larger regions to monitor the spatial and temporal variability of lake PP. |
| first_indexed | 2024-03-10T18:10:16Z |
| format | Article |
| id | doaj.art-97cddf31c54048879b707ffdaa0fc8be |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T18:10:16Z |
| publishDate | 2020-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-97cddf31c54048879b707ffdaa0fc8be2023-11-20T08:11:03ZengMDPI AGRemote Sensing2072-42922020-07-011215241510.3390/rs12152415Spatio-Temporal Variability of Phytoplankton Primary Production in Baltic Lakes Using Sentinel-3 OLCI DataTuuli Soomets0Kristi Uudeberg1Kersti Kangro2Dainis Jakovels3Agris Brauns4Kaire Toming5Matiss Zagars6Tiit Kutser7Institute for Environmental Solutions, Lidlauks, LV-4101 Priekuļu parish, LatviaTartu Observatory, University of Tartu, Observatooriumi 1, 61602 Toravere, EstoniaTartu Observatory, University of Tartu, Observatooriumi 1, 61602 Toravere, EstoniaInstitute for Environmental Solutions, Lidlauks, LV-4101 Priekuļu parish, LatviaInstitute for Environmental Solutions, Lidlauks, LV-4101 Priekuļu parish, LatviaEstonian Marine Institute, University of Tartu, Mäealuse 14, 12618 Tallinn, EstoniaInstitute for Environmental Solutions, Lidlauks, LV-4101 Priekuļu parish, LatviaEstonian Marine Institute, University of Tartu, Mäealuse 14, 12618 Tallinn, EstoniaPhytoplankton primary production (PP) in lakes play an important role in the global carbon cycle. However, monitoring the PP in lakes with traditional complicated and costly in situ sampling methods are impossible due to the large number of lakes worldwide (estimated to be 117 million lakes). In this study, bio-optical modelling and remote sensing data (Sentinel-3 Ocean and Land Colour Instrument) was combined to investigate the spatial and temporal variation of PP in four Baltic lakes during 2018. The model used has three input parameters: concentration of chlorophyll-<i>a</i>, the diffuse attenuation coefficient, and incident downwelling irradiance. The largest of our studied lakes, Võrtsjärv (270 km<sup>2</sup>), had the highest total yearly estimated production (61 Gg C y<sup>−1</sup>) compared to the smaller lakes Lubans (18 Gg C y<sup>−1</sup>) and Razna (7 Gg C y<sup>−1</sup>). However, the most productive was the smallest studied, Lake Burtnieks (40.2 km<sup>2</sup>); although the total yearly production was 13 Gg C y<sup>−1</sup>, the daily average areal production was 910 mg C m<sup>−2</sup> d<sup>−1</sup> in 2018. Even if lake size plays a significant role in the total PP of the lake, the abundance of small and medium-sized lakes would sum up to a significant contribution of carbon fixation. Our method is applicable to larger regions to monitor the spatial and temporal variability of lake PP.https://www.mdpi.com/2072-4292/12/15/2415primary productionproductivitybio-optical modelinglakesoptically complex watersremote sensing |
| spellingShingle | Tuuli Soomets Kristi Uudeberg Kersti Kangro Dainis Jakovels Agris Brauns Kaire Toming Matiss Zagars Tiit Kutser Spatio-Temporal Variability of Phytoplankton Primary Production in Baltic Lakes Using Sentinel-3 OLCI Data Remote Sensing primary production productivity bio-optical modeling lakes optically complex waters remote sensing |
| title | Spatio-Temporal Variability of Phytoplankton Primary Production in Baltic Lakes Using Sentinel-3 OLCI Data |
| title_full | Spatio-Temporal Variability of Phytoplankton Primary Production in Baltic Lakes Using Sentinel-3 OLCI Data |
| title_fullStr | Spatio-Temporal Variability of Phytoplankton Primary Production in Baltic Lakes Using Sentinel-3 OLCI Data |
| title_full_unstemmed | Spatio-Temporal Variability of Phytoplankton Primary Production in Baltic Lakes Using Sentinel-3 OLCI Data |
| title_short | Spatio-Temporal Variability of Phytoplankton Primary Production in Baltic Lakes Using Sentinel-3 OLCI Data |
| title_sort | spatio temporal variability of phytoplankton primary production in baltic lakes using sentinel 3 olci data |
| topic | primary production productivity bio-optical modeling lakes optically complex waters remote sensing |
| url | https://www.mdpi.com/2072-4292/12/15/2415 |
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