Effects of wind strength and wave height on ship incident risk: Regional trends and seasonality

Abstract

a b s t r a c tOceanographic conditions like wind strength and wave height affect the risk of shipping incidents. Seasonal variations and trends in these effects are studied for weather-related incidents and pollution incidents, for six major ship types and for six regions across the globe. The employed database of more than five million observations combines information from various sources on oceanographic conditions, ship particulars, and incidents. The magnitude of wind and wave effects is found to vary by ship type, region, season, and period, and most of these effects are larger during the autumn and winter season and in recent periods. IntroductionMany maritime administrations and coastal states are nowadays trying to become more proactive in their risk mitigation strategies. Current maritime risk assessments often still ignore various risk dimensions and associated uncertainties (Merrick and Van Dorp, 2006). Van der Hoorn and Knapp (2014) propose a multi-layered approach to incorporate ship-specific risk, vessel traffic densities, and location-specific conditions such as bathymetry, wind, waves, currents, and coastal sensitivities to pollution.For the North Atlantic, it has been reported that oceanographic conditions are changing, with rising sea levels, larger wave height and wind strength, changing wind patterns, and increasing frequency and force of storms (Woolf and Challenor, 2002;Tsimplis et al., 2005;European Parliament, 2007; IPCC, 2007). Meanwhile, new shipping routes are opening up, for example, due to the melting Arctic. Such developments necessitate investigation of the relation between oceanographic conditions and maritime safety, including vessel design aspects like stability and long-term wave stress on the hull structure (IMO, 1995(IMO, , 2005a. Knapp et al. (2011) study the effect of wind strength and wave height on the risk of weather-related incidents for the North Atlantic. The current paper extends this type of risk evaluation to a global level and evaluates risk of weather-related incidents and pollution incidents for six regions across the globe. The focus is on seasonal effects and trends (changes over time) in wind speed and wave height with their impact on incident risk for the following six regions: North Atlantic; East Africa and Indian Ocean; Japan, Korea, and South Chinese Sea; South Atlantic and West Africa; North Pacific; South Pacific and Antarctica. Other relevant physical factors, such as directions of wind and waves and the strength and direction of currents, are not available in the database and are therefore not included in the analysis.

Shipping routes in the South China Sea and northern Indian Ocean and associated monsoonal influences

“…Analyses by Heij and Knapp (2015) showed that international shipping over the Indian Ocean is carried out using three types of ships: general cargo vessels (about 31.4%), containerships (about 22.4%), and oil tankers (about 24%). Containerships and oil tankers normally have a large gross tonnage over 50 K, while general cargo vessels have a small tonnage ranging about 5 -20 K. They also showed that the ratio for weather-related incidents is about 0.3% for general cargo vessels and only 0.02% for containerships sailing across the Indian Oceans.…”

Quantitative Analysis on Risk Influencing Factors in the Jiangsu Segment of the Yangtze River

“…In fact, quantitative maritime risk assessment has been studied and a lot of practices have been performed in many research, as described by Li, Meng, and Qu (2012). These mainly include correlation analysis (Eliopoulou, Papanikolaou, & Voulgarellis, 2016), logistic regression (Jin & Thunberg, 2005; Jin, Kite‐Powell, Thunberg, Solow, & Talley, 2002), zero‐truncated binomial regression (Weng & Yang, 2015), negative binary regression (Heij & Knapp, 2015), data clustering (Kim, Park, & Jung, 2017), Bayesian approach (Hassel, Asbjørnslett, & Hole, 2011), Bayesian Belief Networks (BBN) (Antão, Guedes Soares, Grande, & Trucco, 2009; Yang et al., 2018; Zhang et al., 2016, Wan, Yan, Zhang, Qu, & Yang, 2019, Antão & Guedes Soares, 2019; Zhang, Yan, Yang, Wall, & Wang, 2013), and evidence reasoning (ER) or belief rule base (BRB) (Balmat et al., 2009; Yang, Wang, Bonsall, & Fang, 2010; Zhang et al., 2016; Zhang, Yan, Zhang, Haugen, & Yang, 2014; Zhang, Yan, Zhang, Yang, & Wang, 2016). Moreover, some studies made accident data analysis by combining different approaches (Li, Yin, Bang, Yang, & Wang, 2014; Mullai & Paulsson, 2011; Tirunagari, Hänninen, Ståhlberg, & Kujala, 2012).…”

Contribution of PSC Authorities to Ship Accident Prevention

“…The rating measures both safety and environmental hazards. The process is based on information published by a plethora of sources such as PSC deficiencies, casualties, and vetting inspections [15]. However, the methodology used for rating is not available to the public.…”