Identifying Atlantic salmon spawning areas based on multispectral airborne laser scanning, and hydraulic modeling

Modern fishery management and fish stock conservation are often based on estimated biological reference points or conservation limits. For Atlantic salmon, the reference points, defined as spawning targets, are based on the definition of spawning areas. Based on previous studies water depth, flow velocity and substrate type (particle size) are considered the most important instream habitat variables in determining the spawning habitat selection of salmon. The large subarctic Tana River, located in northern Fennoscandia, is one of the most biologically diverse salmon rivers in the world. The importance of salmon fishing to the local community is significant. The catchment area of the Tana River system is c. 16.400 km², the main stem is approximately 200 km long and has several tributaries. More than 90 % of the catchment area is subarctic tundra, forest, swamp and wetlands, practically remote wilderness.

The location and size of spawning areas in the Tana River system relies on coarse resolution maps and subjective habitat evaluation (local knowledge and expert judgement). Remote sensing and hydraulic modeling offer a quantitative, objective, spatially continuous and high-resolution approach for identifying the spawning areas. Water depths and flow velocities have been studied by hydraulic modeling for decades. The hydraulic model offers the opportunity to simulate different flow conditions and make predictions. Remote sensing is increasingly used for mapping fluvial habitats, and by utilizing the novel multispectral (including green wavelength) airborne laser scanning (ALS), it is possible to collect high detailed spatial data simultaneously from the riparian zone and underwater environment characteristics.

The aim of this study is to use quantitative and data-based approach to identify potential salmon spawning areas in the Tana River, and to examine how multispectral ALS, aerial photogrammetry and hydraulic modeling can be used to characterize hydromorphological variables important to salmon spawning areas. By integrating high-resolution digital elevation model (DEM) obtained from multispectral ALS and hydraulic data, the hydraulic model will be generated to identify the ideal depth and velocity areas for spawning, and simulate different water levels and discharge scenarios. The substrate type is defined based on ALS data and aerial photographs. The model is also used for studying the effects of extremes, such as floods and droughts, on the spawning areas. The validation will be done by comparing modeling results with habitat and hydraulic data collected from the river system with conventional means and results of long-term electrofishing surveys. The research is carried out as part of the Digital Waters (DIWA) flagship and the DIWA PhD pilot.