Monte Carlo Guidance for Better Imaging of Boreal Lakes in the Wavelength Region of 400-800 nm.

Boreal lake depth, one of the most important parameters in numerical weather prediction and climate models through parametrization, helps in identifying notable environmental changes across the globe and in estimating its effect on the ecosystem in remote regions. However, there is no quantitative tool to effectively estimate lake depth from satellite images, leaving scientists to infer lake depth from extrapolation of statistics by relying on certain geological knowledge (such as those used in the Global Lake Database). The bottoms of boreal forest lakes are mainly composed of woody debris, and thus spectral imaging revealing contrast of woody debris can be used to estimate lake depth. Here, we use well-established Monte Carlo software to construct spectral images of boreal lakes that house woody debris, phytoplankton, and chlorophyll. This is accomplished by modeling the dynamic optical properties of selected boreal lakes and simulating the propagation of photons in the wavelength region of 400-800 nm. The results show that the spectral image contrast of boreal lakes is not only determined by the depth level and concentration level of phytoplankton and chlorophyll in water but is also affected by the spectral shape of background absorption, especially the contribution of pure water absorption in the total absorption of lake water.