Abstract
Monthly CHL-a and Secchi Depth (SD) data derived from the full mission data of the Medium Resolution Imaging Spectrometer (MERIS; 2002–2012) 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 (R2: 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.
Highlights
Eutrophication is a process of increased production of organic matter in the waterbody, which is stimulated by increased availability of inorganic nitrogen (N) and phosphorus (P) [1]
The monthly mean values of the calibrated CHL-a derived for the in situ monitoring stations GB11, GB20, GB22 and GB16 showed 41% MNB, 96% RMS and 63% APD when compared to the SHARKweb in situ point measurements (Figure 1, all available monitoring station throughout Bråviken)
It indicates that the calibration regression model developed for Swedish lakes improved CHL-a derived from Medium Resolution Imaging Spectrometer (MERIS) substantially (Figure 2) in coastal waters
Summary
Eutrophication is a process of increased production of organic matter in the waterbody, which is stimulated by increased availability of inorganic nitrogen (N) and phosphorus (P) [1]. Sea eutrophication is recognized as a major large-scale environmental pressure, partially attributed to an excess loading of anthropogenically-derived nutrients [2,3,4]. 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 blooms [7,8,9,10,11]
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