Modelling seasonal nutrient inputs from non-point sources across large catchments of importance to aquaculture

Abstract

Accumulation of nutrients in aquatic systems can have negative impacts on water quality, which can then affect the performance and impact of an aquaculture system. Non-point sources (NPS) and runoff from different land use practices are a major contributor of nutrients to the aquatic environment. However, NPS loading is difficult to identify, and monitoring schemes are often insufficient, particularly across large areas. Aquaculture production areas often extend across large catchments, basins and deltas and knowledge of where there could potentially be higher nutrient loads in the environment would be advantageous to inform strategic site selection and management decisions. This study developed seasonal models within a Geographic Information system (GIS) that can be applied to large catchments of importance to aquaculture to identify areas at risk of nutrient loading from NPS which should be prioritized by monitoring schemes. The models were applied to case study areas in Bangladesh, China, Thailand and Vietnam. The results of the individual models reveal changes in the spatial distribution of priority areas depending on the nutrient (nitrogen or phosphorus) and season. The modelling approach presented here has the advantage that it can be applied to large areas without the need for complex data sets. The model and outputs can also be used to assess impacts of land use and land use change on aquaculture, determine site suitability, establish zones, inform carrying capacity studies and identify potential production and disease risks.