Identification of potential sites for deep-ocean waste isolation with a geographic site-selection model

Abstract

Identification of optimal sites for the isolation of waste on the abyssal seafloor was performed with two approaches: by the traditional method of map overlays of relevant attributes, and by a specially developed, automated Site-Selection Model (SSM). Five initial, Surrogate Sites, identified with the map-overlay approach, were then compared with the more rigorously produced scores from the SSM. The SSM, a process for optimization of site locations, accepts subjective, expert-based judgments and transforms them into a quantitative, reproducible, and documented product. The SSM is adaptable to any siting scenario. Forty-one factors relevant to the isolation scenario, including 21 weightable factors having a total of 123 scorable categories, have been entered into the SSM. Factors are grouped under project definition, unique environments, anthropogenic, geologic, biologic, weather, oceanographic and distance criteria. The factor scores are linked to a georeferenced database array of all factors, corresponding to 1°×1° latitude–longitude squares. The SSM includes a total of 2241 one-degree squares within 1000 n.m. of the U.S. coasts, including the western North Atlantic, the Gulf of Mexico, and the eastern North Pacific. Under a carefully weighted and scored scenario of isolation, the most favorable sites identified with the SSM are on the Hatteras and Nares Abyssal Plains in the Atlantic. High-scoring sites are also located in the Pacific abyssal hills province between the Murray and Molokai Fracture Zones. Acceptable 1° squares in the Gulf of Mexico are few and of lower quality, with the optimum location on the northern Sigsbee Abyssal Plain. Two of the five Surrogate Site locations, on the Hatteras and Sigsbee Abyssal Plains, correspond to the best SSM sites in each ocean area. Two Pacific and a second Atlantic Surrogate Site are located in low-scoring regions or excluded by the SSM. Site-selection results from the SSM, although robust, are an initial attempt to quantify the site-selection process. The SSM database exposes a significant lack of high-quality information for many areally mappable attributes on the abyssal seafloor, particularly bottom-current speed and measures of biologic productivity and flux. Terminologies and classifications of some measures, such as sediment types, suffer from parochialism and vary by ocean. Considerable research is needed even for a broad understanding of the environmental measures required to make sound societal decisions about use of the abyssal seafloor for disposal or other purposes.