Synergy of Satellite, In Situ and Modelled Data for Addressing the Scarcity of Water Quality Information for Eutrophication Assessment and Monitoring of Swedish Coastal Waters

Abstract

Monthly CHL-a and Secchi Depth (SD) data derived from the full mission data of the Medium Resolution Imaging Spectrometer (MERIS; 2002 were analysed along a horizontal transect from the inner Bråviken bay and out into the open sea. The CHL-a values were calibrated using an algorithm derived from Swedish lakes. Then, calibrated Chl-a and Secchi Depth (SD) estimates were extracted from MERIS data along the transect and compared to conventional monitoring data as well as to data from the Swedish Coastal zone Model (SCM), providing physico-biogeochemical parameters such as temperature, nutrients, Chlorophyll-a (CHL-a) and Secchi depth (SD). A high negative correlation was observed between satellite-derived CHL-a and SD (ρ = −0.91), similar to the in situ relationship established for several coastal gradients in the Baltic proper. We also demonstrate that the validated MERIS-based estimates and data from the SCM showed strong correlations for the variables CHL-a, SD and total nitrogen (TOTN), which improved significantly when analysed on a monthly basis across basins. The relationship between satellite-derived CHL-a and modelled TOTN was also evaluated on a monthly basis using least-square linear regression models. The predictive power of the models was strong for the period May-November (R 2 : 0.58-0.87), and the regression algorithm for summer was almost identical to the algorithm generated from in situ data in Himmerfjärden bay. The strong correlation between SD and modelled TOTN confirms that SD is a robust and reliable indicator to evaluate changes in eutrophication in the Baltic proper which can be assessed using remote sensing data. Amongst all three assessed methods, only MERIS CHL-a was able to correctly depict the pattern of phytoplankton phenology that is typical for the Baltic proper. The approach of combining satellite data and physio-biogeochemical models could serve as a powerful tool and value-adding complement to the scarcely available in situ data from national monitoring programs. In particular, satellite data will help to reduce uncertainties in long-term monitoring data due to its improved measurement frequency.Sea eutrophication is recognized as a major large-scale environmental pressure, partially attributed to an excess loading of anthropogenically-derived nutrients [2][3][4]. In marine systems, eutrophication occurs predominantly in coastal areas and semi-enclosed waterbodies [2,5,6]. Nutrient loads to coastal areas have significantly increased in recent decades due to population growth especially in coastal areas. In the Baltic Sea the problem is exalted due to the relatively large catchment area of the Baltic Sea (i.e., 4.2 times the Baltic Sea), and a relatively low water exchange rate with the North Sea. For the last three decades, it is has been acknowledged that excessive amounts of nutrients such as N, P and organic matter-often represented by organic particular carbon (POC)-result in anoxic bottom waters, the spreading of dead bottom zones and increased frequency and intensity of algal...

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Classification of Geomorphic Units and Their Relevance for Nutrient Retention or Export of a Large Lowland Padma River, Bangladesh: A NDVI Based Approach

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An Improved Eutrophication Assessment Algorithm of Estuaries and Coastal Waters in Liaodong Bay

“…Eutrophication is a process of increased production of organic matter in the water body, which is stimulated by the increased availability of inorganic nitrogen (N) and phosphorus (P) [7]. Excessive amounts of nutrients such as N, P, and organic matter-often represented by organic particular carbon (POC)-result in anoxic bottom waters, the spreading of dead bottom zones, and increased frequency and intensity of algal blooms [8][9][10]. Among the numerous eutrophication assessment indexes, chlorophyll-a (Chl-a), total phosphorus (TP), total nitrogen (TN), chemical oxygen demand (COD), and Secchi depth (SD) are widely used in the eutrophication assessment of lakes and reservoirs.…”

“…Referring to the construction method of TSI, Chinese scholars established a comprehensive Trophic Level Index (TLI) based on Chl-a, TP, TN, COD, and SD with Chl-a as the core, which has widely been used in China [12]. However, this approach is somewhat misleading due to the influence of Colored Dissolved Organic Matter (CDOM) and Suspended Particulate Matter (SPM) on Secchi depth [10,13,14].…”