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MAROFF-2-Maritim virksomhet og offsh-2

A management tool for coastal aquaculture based on knowledge on nearshore ocean circulation dynamics

Alternative title: Et forvaltningsverktøy for lakseoppdrett basert på simuleringer av kystnær havsirkulasjon

Awarded: NOK 12.0 mill.

Sea lice are a significant problem for the aquaculture industry, with implications for animal welfare, profitability, and the potential for growth. The goal of the MATNOC project has been to contribute with knowledge and tools that the aquaculture industry can use to reduce the spread of sea lice. To achieve this, the project has focused on: 1) improving the understanding of circulation and transport processes near the coast and their representation in numerical models, and 2) building a digital risk analysis tool based on enhanced models. Sea lice are typically found near the sea surface, and their spread is largely determined by circulation and transport processes in the upper water layers. More knowledge about this can be used to understand how infection can spread between different aquaculture sites and to improve current numerical models. With good circulation models as a starting point, farmers can plan for a site structure that limits the spread of sea lice. Another issue is lice falling off fish during delousing. These can spread to neighboring facilities, but with good spreading forecasts, this form of lice spread can also be reduced by for example adjusting the timing of the operations. In MATNOC, we have developed a model system specifically designed to simulate coastal transport processes in seawater. The model is equipped with an unstructured computational grid, allowing for high resolution in narrow straits and fjords, while using coarser resolution in areas where the need for fine-scale detail is not as significant. A significant portion of the research in the project's main part 1 has focused on transport through narrow straits with strong tidal currents, and on how waves and currents interact and affect the drift of particles near the sea surface. Dedicated field experiments have been conducted to support the development of the model system. Part of the project studied how particles near the surface (such as sea lice) are affected by currents and waves in a focus area of the coast (Vestfjorden). It emerged from this that waves likely have a significant impact on both how close to the coast the lice reside and in what concentrations they can be found near land. In other words, wave effects appear to be crucial for the spread of lice between aquaculture sites, which are often located in coastal waters. In the project's main part 2, a digital risk assessment tool has been developed for the aquaculture industry. In this mapping tool, statistical spread and a 5-day forecast of lice from all aquaculture sites in Norway can be presented. While the statistical spread is based on high-resolution models for smaller regions of Norway, the 5-day forecast is based on the operational ocean model of the Meteorological Institute (Norkyst800). Norkyst800 covers the entire Norwegian coast with 800 meters resolution. The lice forecast is now run daily and is openly accessible via a dedicated app: https://lus.akvaplan.app. The statistical modeling is a useful tool in aquaculture planning for operations that minimize the risk of infection transmission. The 5-day forecast is intended as a more operational tool, useful when there is an outbreak of lice at a site or if farmers plan a soon delousing and want to assess the risk of re-infection or impact on nearby sites.

Forskningen i prosjektet har ført til en bedre forståelse av fysiske prosesser i havet som påvirker sirkulasjon og transport av partikler, som lus, plastikk og forurensning. Resultatene, som er publisert i fagfelle vurderte journaler, øker kunnskapen i forskningsmiljøet og setter fokus på prosesser som det er behov for å forstå bedre for å forbedre dagens modeller. I tre vitenskapelige artikler er interaksjoner mellom bølger og strøm studert, og resultatene legger et grunnlag for bedre operasjonell varsling av bølger og strøm langs Norskekysten. Gjennom et doktorgradsarbeid er sirkulasjon og transportmønster i fjordsystemer, der tidevannet spiller en særlig stor rolle, undersøkt ved hjelp av både målinger og en numerisk havmodell. Resultatene fra doktorgradsavhandlingen viser blant annet hvordan modelloppløsning kan være viktig for å få modellen til å gi en realistisk representasjon av sirkulasjon i fjorder med sterk tidevannsstrøm. Forskningen har også vist at transport som følge av bølger kan være svært viktig for distribusjon av partikler nær overflaten, som lakselus og plastikk, og særlig hvor nært kysten disse oppholder seg. Gjennom prosjektet er det utviklet et interaktivt kartverktøy som blant annet benyttes til å lage 5-dagers varsel for spredning av lakselus. Varselet oppdateres inntil videre daglig og er åpent tilgjengelig på https://lus.akvaplan.app. Dette verktøyet brukes av ulike oppdretts-aktører til blant annet planlegging av operasjoner som avlusning.

MATNOC’s main aim is to aid the aquaculture industry in reducing the spreading of sea lice, a main problem for the industry with large economic consequences. To achieve this, MATNOC has two distinct foci: 1) to improve the understanding and numerical model representation of near-coast upper-ocean transport processes, and 2) to build an improved digital risk assessment tool based on enhanced model capabilities to be used by the aquaculture industry. The project partners will assemble a numerical model system especially designed for near-shore drift prediction along the complex Norwegian coastline. For this purpose, the model will use unstructured computational grids that allow unprecedented resolution in narrow straits and fjords. It will also account for lice drift by both currents and waves, and major scientific component of the project will be to better understand interactions between currents and waves---and their consequences for net drift. A dedicated field experiment will back up the development of the model system. Finally, the state-of-the art model system and the gained knowledge on current-wave interactions will be fed into a digital decision-making tool to be used by the aquaculture industry. The core novelty of this tool is that ensemble predictions made by the model system will be used to form uncertainty estimates that should improve the knowledge base for decision making.

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Funding scheme:

MAROFF-2-Maritim virksomhet og offsh-2