In inland and coastal waters, organic carbon undergoes seasonal and spatial variations in relation to river run-off and biological processes. Particulate organic carbon, while being a smaller fraction of the total organic carbon with respect to dissolved organic carbon, plays an important role in the local and regional carbon dynamics. In fact, it is the variation of POC that can be used to examine carbon sequestration and well as carbon sink. Particulate matter strong influences the optical, chemical and biological conditions of most inland and coastal aquatic ecosystems. There are numerous challenges to identifying particulate carbon, and most importantly specifying particulate carbon classes. These latter are dominated largely by productive particulate carbon from phytoplankton and detrital particulate organic carbon. These two pools play very different roles in the aquatic carbon dynamics, with high temporal and spatial variability within a single waterbody in relation to local sources and seasonal changes. However, many studies examine particulate carbon dynamics with a single algorithm, which leads to poor estimation where multiple numerous sources and sinks are present, typical for inland and coastal water environments. The BioGeoLakes team has been working on an absorption-based approach was used to determine surface particulate organic carbon based on the specification of local POC absorption characteristics of dominant POC sources; phytoplankton or detritus based. This specification was made using a new particulate organic matter index, which was tested across a range of modelled and real lake/coastal conditions. Based on remote sensing reflectance in four wavebands, the model provided a good separation of organic particulate types and a good estimate of organic particulate concentrations in shallow lakes in the Yangtze River valley and estuary. These study lakes include Taihu, Chaohu and Poyang while work in the coming year will include a large number of smaller lakes in the Valley using the OLCI/Sentinel-3 satellite data. The approach shows a good potential to quantify particulate carbon dynamics in ecosystems where multiple organic carbon sources are present

Source Specific Approaches to Identifying Spatial and Temporal Dynamics of Organic Particulate Matter in Complex Inland and Coastal Waters by Remote Sensing: Developments from the BioGeoLakes Project

Paolo Villa;
2019

Abstract

In inland and coastal waters, organic carbon undergoes seasonal and spatial variations in relation to river run-off and biological processes. Particulate organic carbon, while being a smaller fraction of the total organic carbon with respect to dissolved organic carbon, plays an important role in the local and regional carbon dynamics. In fact, it is the variation of POC that can be used to examine carbon sequestration and well as carbon sink. Particulate matter strong influences the optical, chemical and biological conditions of most inland and coastal aquatic ecosystems. There are numerous challenges to identifying particulate carbon, and most importantly specifying particulate carbon classes. These latter are dominated largely by productive particulate carbon from phytoplankton and detrital particulate organic carbon. These two pools play very different roles in the aquatic carbon dynamics, with high temporal and spatial variability within a single waterbody in relation to local sources and seasonal changes. However, many studies examine particulate carbon dynamics with a single algorithm, which leads to poor estimation where multiple numerous sources and sinks are present, typical for inland and coastal water environments. The BioGeoLakes team has been working on an absorption-based approach was used to determine surface particulate organic carbon based on the specification of local POC absorption characteristics of dominant POC sources; phytoplankton or detritus based. This specification was made using a new particulate organic matter index, which was tested across a range of modelled and real lake/coastal conditions. Based on remote sensing reflectance in four wavebands, the model provided a good separation of organic particulate types and a good estimate of organic particulate concentrations in shallow lakes in the Yangtze River valley and estuary. These study lakes include Taihu, Chaohu and Poyang while work in the coming year will include a large number of smaller lakes in the Valley using the OLCI/Sentinel-3 satellite data. The approach shows a good potential to quantify particulate carbon dynamics in ecosystems where multiple organic carbon sources are present
2019
Istituto per il Rilevamento Elettromagnetico dell'Ambiente - IREA
POC
remote sensing
water quality
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/360794
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