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2021•IOP Conference Series Earth and Environmental ScienceOpen access

Construction of a model of nutrient export from the catchment using GIS-technologies for a transboundary river in Russia and Finland

Ksenia Korobchenkova, Alexandra Ershova

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Abstract

Abstract GIS model SWAT to assess the nutrient load on the catchment area of the Gulf of Finland from the transboundary Seleznevka River (Rakkolanjoki) was applied. All stages of the model setup are considered: preparation of initial data, building the SWAT-model, its calibration and scenario calculations. We consider the possibility of using the SWAT-model for managing the quality of water bodies in Russia and the difficulties that arise while building a model for this catchment area.

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Abstract GIS model SWAT to assess the nutrient load on the catchment area of the Gulf of Finland from the transboundary Seleznevka River (Rakkolanjoki) was applied. All stages of the model setup are considered: preparation of initial data, building the SWAT-model, its calibration and scenario calculations. We consider the possibility of using the SWAT-model for managing the quality of water bodies in Russia and the difficulties that arise while building a model for this catchment area.

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Available abstract

Abstract GIS model SWAT to assess the nutrient load on the catchment area of the Gulf of Finland from the transboundary Seleznevka River (Rakkolanjoki) was applied. All stages of the model setup are considered: preparation of initial data, building the SWAT-model, its calibration and scenario calculations. We consider the possibility of using the SWAT-model for managing the quality of water bodies in Russia and the difficulties that arise while building a model for this catchment area.

Key concepts: Drainage basin, SWAT model, Catchment area, Environmental science, Nutrient, Water quality, Hydrology (agriculture), Water resource management

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Construction of a model of nutrient export from the catchment using GIS-technologies for a transboundary river in Russia and Finland — Research Paper | ScholarLens