Oil spill modeling: computational tools, analytical frameworks, and emerging technologies

Abstract

Following the Deepwater Horizon oil spill of 2010, a substantial body of research has focused on the development of computational tools and analytical frameworks for modeling oil spill events. Much of this work is dedicated to deepening our understanding of the interactions between oil, fragile ecosystems, and the environment, as well as the impacts of oil on human settlements which are vulnerable to spill events. These advances in oil spill modeling and associated analytics have not only increased the efficiency of spill interdiction and mitigation efforts, they have also helped to nurture proactive, versus reactive, response strategies and plans for local and regional stakeholders. The purpose of this paper is to provide a progress report on the wide range of computational tools, analytical frameworks, and emerging technologies which are necessary inputs for a complete oil spill modeling package. Specifically, we explore the use of relatively mature tools, such as dedicated spill modeling packages, geographic information systems (GIS), and remote sensing, as well emerging technologies such as aerial and aquatic drones and other in-situ sensing technologies. The integration of these technologies and the advantages associated with using a geographic lens for oil spill modeling are discussed.

Oil spill modeling: Mapping the knowledge domain

“…CiteSpace is powerful bibliometric software package designed to promote a deeper understanding of knowledge domains (Lee et al, 2016; Nelson and Grubesic, 2018; Wei et al, 2015). Scientometric approaches generally view knowledge domains as the corpus of literature surrounding a specific research topic.…”

Pattern recognition analysis of marine oil spills in airborne passive infrared multispectral remote sensing images

“…1,2 Timely and precise mapping of oil spills is important for the management of emergency responses, and remote sensing techniques serve as essential components for oil spill assessment. 1–4 The need for effective detections has led to advances in airborne or satellite oil spill remote sensing, especially those performed through passive optical means. 2 One promising remote sensing technique for oil detection is through a downward-looking passive infrared (IR) sensor mounted on an aircraft platform that captures radiation reflected or emitted from the sea surface.…”

Optimal Model-Based Sensor Placement & Adaptive Monitoring Of An Oil Spill

“…For monitoring oil spills there exists a variety of models (Spaulding, 2017) used to predict the spill trajectory and decision support systems to evaluate potential responses (Nelson and Grubesic, 2019). However, existing models and decision systems are not specific to autonomous sensing and do not support utilisation of measurements to correct externally provided large-scale fluid model outputs.…”