Modeling total particulate organic carbon (POC) flows in the Baltic Sea catchment

The largest input source of carbon to the Baltic Sea catchment is river discharge. A tool for modeling riverine particulate organic carbon (POC) loads on a catchment scale is currently lacking. The present study describes a novel dynamic model for simulating flows of POC in all major rivers draining...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Biogeochemistry 2016-03, Vol.128 (1-2), p.51-65
Hauptverfasser: Strååt, Kim Dahlgren, Mörth, Carl-Magnus, Sobek, Anna, Smedberg, Erik, Undeman, Emma
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The largest input source of carbon to the Baltic Sea catchment is river discharge. A tool for modeling riverine particulate organic carbon (POC) loads on a catchment scale is currently lacking. The present study describes a novel dynamic model for simulating flows of POC in all major rivers draining the Baltic Sea catchment. The processes governing POC input and transport in rivers described in the model are soil erosion, in-stream primary production and litter input. The Baltic Sea drainage basin is divided into 82 sub-basins, each comprising several land classes (e.g. forest, cultivated land, urban areas) and parameterized using GIS data on soil characteristics and topography. Driving forces are temperature, precipitation, and total phosphorous concentrations. The model evaluation shows that the model can predict annual average POC concentrations within a factor of about 2, but generally fails to capture the timing of monthly peak loads. The total annual POC load to the Baltic Sea is estimated to be 0.34 Tg POC, which constitutes circa 7–10 % of the annual total organic carbon (TOC) load. The current lack of field measurements of POC in rivers hampers more accurate predictions of seasonality in POC loads to the Baltic Sea. This study, however, identifies important knowledge gaps and provides a starting point for further explorations of large scale POC mass flows.
ISSN:0168-2563
1573-515X
1573-515X
DOI:10.1007/s10533-016-0194-8