World Aquaculture Singapore 2022

November 29 - December 2, 2022

Singapore

LONG TERM MODELLING OF BENTHIC EFFECTS OF THE SEABREAM CAGE CULTURE FARM IN QURIYAT, OMAN, USING AQUAMODEL

Dawood Al-Yahyai*, Wenresti Gallardo, Gerd Bruss, Dale Kiefer and Zach Siegrist

 

Ministry of Agriculture Wealth, Fisheries and Water Resources

Muscat, Sultanate of Oman

dawoodalyahyai@gmail.com

 



Accumulation of uneaten feed and fecal matter is the main impact on marine sediments beneath the cages. Their continuous accumulation will lead to enrichment of sediment with organic carbon which can affect benthic life and may lead to an anoxic bottom environment. Different simulation models have been established and developed to examine these effects from aquaculture cages. Therefore, the main objective of this study was to use the modelling approach in quantifying the possible impacts of gilthead seabream (Sparus aurata) marine cage farm at Quriyat, Oman, on benthic sediment.

A modelling tool (AquaModel) was used for simulations in this study. The simulation period was for the period from 25 May 2017 to 31 December 2020. The operational farm data for this period along with the environmental water quality variables were incorporated in the model for purpose of simulation. Many sediment variables were selected for simulation with main ones including total Organic carbon (TOC), total Organic carbon rate (TOC rate), sediment sulfide and sediment oxygen.

The average monthly TOC levels of the farm were below 1.6% which was the threshold set during the simulations (Table 1). For sediment sulfide, the monthly average levels were below the threshold level of 1500 µM. For sediment oxygen, the monthly average levels were above the threshold level of 2 g_ox m-3. The average TOC rate from the cage farm was 1.15 g_C m-2 d-1 (Figure 1). Modeling results showed low to moderate effects of cage farms on the sediments based on current activities of the farm. However, there is a need for continuous monitoring to determine potential changes in sediment variables with the expected increase in production capacity of the farm in the future.