Estimation of the primary productivity and particulate organic carbon in inland waters using shipborne polarimetric lidar.

Estimation of primary productivity (PP) and particulate organic carbon (POC) in inland waters is of significant importance in understanding the global climate change and carbon cycle. In this study, we developed an enhanced PP inversion model based on a large number of lidar (light detection and ranging) profiles, in-situ observations, and satellite remote sensing data, which enabled us to obtain the vertical profile distribution of PP in water bodies along the lidar tracks of 400 km. Concurrently, we established a novel model for retrieving the POC applicable to inland waters based on a considerable number of lidar profiles, in-situ observations, and organic element analyzer measurements, which allowed us to obtain the vertical profile distribution of POC along the lidar tracks of 400 km. Subsequently, the results obtained through lidar inversion were validated by comparison with in-situ measurements. Finally, we discussed the effects of temperature and nutrients on the chlorophyll-a concentration and PP in the Xinanjiang Reservoir. The results from this study indicate that the lidar remote sensing technology is a highly effective and feasible method for the future implementation of all-weather, large-scale, and high-precision evaluations of PP and POC using spaceborne ocean profiling lidar.