A satellite sensor nonspecific operational advanced algorithm is developed to simultaneously retrieve the concentrations of phytoplankton chlorophyll (chl), dissolved organics (doc) and suspended minerals (sm) in turbid and strongly absorbing natural waters (i.e., case II waters). Also, a new interpolation procedure is developed and used jointly with the advanced bio-optical and standard window-split algorithms to generate from SeaWiFS and AVHRR data the time series of spatial and temporal (seasonal and interannual) variations of chl, sm, doc and water surface temperature (TS) for the period 1998-2004 in Lake Ladoga, the largest European fresh water body. Obtained for the first time, the spaceborne fields of the above variables have revealed at an unprecedented time and space resolution some intrinsic features and interdependence of thermal and biogeochemical processes in the lake. Rates of thermobar displacement from the littoral zone to the central deep water area are quantified during periods of lake warming and cooling. From spring to mid-summer, the dynamics of phytoplankton biomass spatial distribution are evidenced to follow the retraction of the cold water zone bordered by the thermobar. Importantly, along with the thermobar dynamics, the zones of the most enhanced phytoplankton concentration are concurrently governed by the lake bathymetry, and thus gradually move from south to north along the eastern coast line. Brought with fluvial input, suspended minerals and allochthonous dissolved organics are not only restricted to the zones of major river deltas but also driven northward by coastal cyclonic currents prevailing in Lake Ladoga. The obtained space data allows the interplay of the above factors to be explicitly revealed and explains the observed interannual variations in the surficial expressions of biogeochemical processes inherent in Lake Ladoga.
Development of water quality retrieval algorithms is discussed in terms of causal dependence of the upwelling spectral radiance upon the water composition. Unlike clean marine/oceanic waters for which linear regression retrieval relationships are valid, inland and coastal zone water masses with high degree of optical complexity necessitate the development of nonparametric retrieval approaches. At the basis of these techniques are models considering the optical competitiveness of several coexisting aquatic components. Such models for Lakes Ladoga and Ontario are described and compared. Monte Carlo simulations have been performed to analyze the spectral and angular variations of the upwelling radiance scattered by the water column out into the atmosphere. Analysis of optical conditions for running remote sounding natural waters of various optical complexity is carried out. Relevant recommendations are formulated.