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The ocean is considered nutrient-barren, but lakes are in constant exchange with their environment and therefore prone to higher nutrient loads. Increases in their nutrient loading is referred to as eutrophication, and associated with cascading effects in biogeochemical processes. Through artificially increased nutrient levels phytoplankton can grow excessively. The consequences are manifold: a decrease in levels of dissolved oxygen, increased turbidity and the formation of algal blooms that may become harmful.

Re-oligotrophication is the process to reverse the effects of eutrophication. In order to facilitate the recovery of lakes, a measure of primary production (PP) is essential to identify and monitor the sources that cause phytoplankton growth. Commonly, the concentration of the phytoplankton pigment chlorophyll-a (Chla) is used to estimate PP indirectly. However, the relation of Chla to PP is prone to large uncertainty. Bio-optical models that use inherent optical properties (IOPs) to estimate PP are thus favoured but require an accurate characterisation of the target water conditions. An IOP-based approach to estimate PP was successfully demonstrated using Envisat-MERIS data of Lake Geneva (Switzerland), and it is currently adopted for Sentinel-3 OLCI data over the entirety of Switzerland. The PACE-OCI sensor marks an unprecedented opportunity in terms of its spectro-radiometric sampling properties, and it unlocks a huge potential for improved PP monitoring in large lakes.

Our PACE contribution is to develop and provide a hyperspectral PP model for lakes based on pigment absorption, diffuse attenuation and photosynthetically available radiation. For the model development we investigate the detailed optical-biogeochemical conditions driving model performance. PP model development sites are Lake Geneva on the border of France and Switzerland, the largest lake in Western Europe, and Lake Greifensee close to Zurich. Lake Geneva and Greifensee are characterised by meso-eutrophic states and thus strongly benefit from active re-oligotrophication programmes. Visibility in Lake Geneva varies between 5 and 20 meters and is often larger than the stratification depth. It therefore constitutes an appropriate target for investigating vertical variations as seen by optical satellite sensors like OCI.

In order to develop a novel retrieval method in time for the launch of PACE, we use several data sources:

• OCI-simulated data distributed by NASA
• OCI-analog data acquired through own airborne campaigns using the imaging spectrometer AVIRIS NG
• Automated in situ measurements taken on the LéXPLORE (https://lexplore.info/) research platform using a SeaBird Thetis profiler
• An underwater flow-through system installed on LéXPLORE
• Field campaigns in both Lake Geneva and Greifensee in conjuncture with laboratory analyses

Using the the physical properties obtained from the above data sources we will evaluate and test different physical-based approaches for the inversion of PACE reflectance data. The best performing approach will be implemented, validated and made accessible through the Swiss Datalakes portal (https://www.datalakes-eawag.ch/).