Development of a Decision Support System for Suitability Assessment of Mariculture Site Selection
As the world’s population increases, demand on fish products as a strong source of protein is increasing as well. To avoid the depletion of natural living resources in the ocean, the request cannot be supplied from capture fisheries alone, but must also be supported by aquaculture products. Due to regional limitation inland, aquaculture in the seas, or mariculture, had been introduced as an alternative to inland aquaculture by utilization of coastal and offshore areas. Over the last two-decades, mariculture has been intensified and has created essential employment opportunities. This development has also augmented environmental concerns and questions about possible environmental impacts. Intensive fish farming releases considerable amounts of nutrient waste in dissolved and particulate form into the environment through feed excess, soluble fish excretion and faeces production. It is important before the implementation of fish farming mariculture activities, appropriate site conditions for culturing the species should be selected in order to minimize environmental impacts arising from the farming activities (sustainability) as well as to guarantee adequate conditions from the operational point of view (suitability). This study focuses on the development of a Decision Support System (DSS) as a tool for the decision maker in coastal zone management and mariculture for the appropriate selection of mariculture site location. Extensive use of GIS as part of the Decision Support System was deployed in this study. The DSS is based on physical, chemical and sediment criteria as well as on data of conflicting coastal use. The GIS analysis results in a map indicating the suitable areas for the improved method of offshore cage mariculture. In this study, emphasis was placed on finfish species, however the methods and results may be employed for other species as well following some modifications. The DSS was applied for the Seribu Islands area in the Java Sea and the Riau Archipelago, Indonesia. The data were acquired from direct field measurement, numerical modelling and existing information from particular agencies. Numerical modelling was used to obtain spatial and temporal distributions of hydrodynamic parameters (i.e. current velocities and water levels). The Delft3D modelling system (Delft Hydraulics, The Netherlands) was employed for this purpose. The DSS was developed under GIS application of ESRI® ArcGIS™ v8.3 using weighted overlay method. Due to lack of data, some parameters were excluded from the analysis. The results showed the adequacy of the system for supporting governmental authorities in the implementation, environmental controlling, and estimation of overall carrying capacity for environmental sustainable marine fish farming.