Estimating internal phosphorus loading for a water quality model using chemical characterisation of sediment phosphorus and contrasting oxygen conditions.

The Finnish Archipelago Sea (AS) has long been subject to intensive anthropogenic phosphorus (P) loading. The area suffers from seasonal hypoxia and cyanobacterial blooms despite reductions in nutrient discharge from the catchment and point sources. Internal loading may even dominate the P budget. Previous estimates of internal P loading have limitations (e.g., in spatial coverage and infrequent measurements). We present the first area-wide estimates of the magnitude of internal P loading based on the long-term release of P stored in the sediments. Modelling the internal P loading in the AS is challenging due to the complexity of biogeochemical processes in the sediment-water interface, as well as the heterogenic topography of the seafloor. Instead, we calculated estimates of internal P loading based on data from previous studies on sequential chemical extraction of sediment P, sediment physical characteristics (e.g., organic content, location of muddy seabed substrates), and near-bottom oxygen (O) conditions. The estimates in three scenarios of contrasting O conditions were based on potentially mobile P pools in the sediments, recycled from sediment to water (i.e., loosely-bound or exchangeable P, P bound to reducible iron oxy(hydr)oxides, and labile organic P). The potentially mobile P pools were determined by chemical extraction methods (modified from Psenner et al., 1984 and Ruttenberg, 1992). The internal P loading under presumable O conditions was estimated to be fivefold that of waterborne P input to the AS; comparable to previous estimates for hypoxic areas in the Baltic Sea. Our estimates revealed wide spatial variability in the internal P loading, depending on O conditions and seabed sediment substrate. The site-specific P release estimates are included in a water quality model used by regional authorities, which increases the model's reliability for estimating the impact of human activities on the water quality across the AS.