Assessing the Variability of Extreme Weather Events and Its Influence on Marine Accidents along the Northern Coast of Tanzania

The marine accidents are among the main components of the Zanzibar Disaster Management Policy (2011) and the Zanzibar Blue Economy Policy (2020). These policies aimed to institute legal frame works and procedures for reducing both the frequency of marine accidents and their associated fatalities. These fatalities include deaths, permanent disabilities and loss of properties which may result into increased poverty levels as per the sustainable development goal one (SDG1) which stipulates on ending the poverty in all its forms everywhere. Thus, in the way to support these Government efforts, the influence of climate and weather on marine accidents along Zanzibar and Pemba Channels was investigated. The study used the 10 years (2013-2022) records of daily rainfall and hourly wind speed acquired from Tanzania Meteorological Authority (TMA) (for the observation stations of Zanzibar, Pemba, Dares Salaam and Tanga), and the significant wave heights data, which was freely downloaded from Globally Forecasting System (GFS-World model of 13 km resolution). The marine accident records were collected from TASAC and Zanzibar Maritime Authority (ZMA), and the anecdotal information was collected from heads of quay and boat captains in different areas of Zanzibar. The Mann Kendal test, was used to determine the slopes and trends direction of used weather parameters, while the Pearson correlations analysis and t-tests were used to understand the significance of the underlying relationship between the weather and marine accidents. The paired t-test was used to evaluate the extent to which weather parameters affect the marine accidents. Results revealed that the variability of extreme weather events (rainfall, ocean waves and wind speed) was seen to be among the key factors for most of the recorded marine accidents. For instance, in Pemba high rainfall showed an increasing trend of extreme rainfall events, while Zanzibar has shown a decreasing trend of these events. As for extreme wind events, results show that Dar es Salaam and Tanga had an increasing trend, while Zanzibar and Pemba had shown a decreasing trend. As for the monthly variability of frequencies of extreme rainfall events, March to May (MAM) season was shown to have the highest frequencies over all stations with the peaks at Zanzibar and Pemba. On the other hand, high frequency of extreme wind speed was observed from May to September with peaks in June to July, and the highest strength was observed during 09:00 to 15:00 GMT. Moreover, results revealed an increasing trend of marine accidents caused by bad weather except during November. Also, results showed that bad weather conditions contributed to 48 (32%) of all 150 recorded accidents. Further results revealed significant correlation between the extreme wind and marine accidents, with the highest strong correlation of r = 0.71 (at p ≤ 0.007) and r = 0.75 (at p ≤ 0.009) at Tanga and Pemba, indicating the occurrence of more marine accidents at the Pemba channel. Indeed, strong correlation of r = 0.6 between extreme rainfall events and marine accidents was shown in Pemba, while the correlations between extremely significant wave heights and marine accidents were r = 0.41 (at p ≤ 0.006) and r = 0.34 (p ≤ 0.0006) for Pemba and Zanzibar Channel, respectively. In conclusion, the study has shown high influence between marine accidents and bad weather events with more impacts in Pemba and Zanzibar. Thus, the study calls for more work to be undertaken to raise the awareness on marine accidents as a way to alleviate the poverty and enhance the sustainable blue economy.

The ＂Major Marine Accidents＂ Do Not Occur Randomly

It is estimated that $3.2 billion worth of ships was totally lost （2008-2013）. In addition, 1,788 ships were involved in MMA （major marine accidents） （2004-2008）. However, 70% of those accidents took place in only a quarter of the geographical areas. That is the focus of this study. Hurst＇s generalization of Einstein＇s formula for a random time series requires that MMA should cover a distance proportional to the square root of time. The Hurst exponent is derived from the ＂Rescaled Range Analysis＂ using MATLAB （2009）. The Hurst exponent is 0.50 for a random time series, and this was found to be the case for MMA, in tons of carrying capacity over time. However, considering the time series in relation to the 12 geographical areas, the Hurst exponent for 1,788 MMA was found to be 0.43, which is less than 0.50. This indicates that the time series, related to geographical area, is anti-persistent/non-random. The ships damaged in MMA totaled 27.55 million dwt, and 31% of that tonnage was damaged in the North Sea and Baltic area, 20% in the Mediterranean and Black Sea and 19% in the China Sea. These research findings challenge the assumptions who generally believe that MMA are random in relation to geography.

A Study on the Role of Human Element (Staffs) in Marine Accidents

Ships usually operate in the vibrant and dynamic environment;a majority of crews work and have a rest in a stressful space and have daily job displacements that working in it and moving from port disrupt as soon as reaching to port. Such conditions which require living at work place for a long time raises a unique job life which causes increase in risks of human mistakes. Huge marine accidents occur per year in country in which human element plays a major role. Identification and analysis of the components affect individuals as the staffs in ships, so that such component raises the conditions due to inattention which result in rise of severe and more severe marine accidents. Evaluation of each component has been taken into account in the present research. The present research seeks to examine and identity factors affecting human elements in marine accidents.

Sensitive Resource and Traffic Density Risk Analysis of Marine Spill Accidents Using Automated Identification System Big Data

This study developed a new methodology for analyzing the risk level of marine spill accidents from two perspectives,namely,marine traffic density and sensitive resources.Through a case study conducted in Busan,South Korea,detailed procedures of the methodology were proposed and its scalability was confirmed.To analyze the risk from a more detailed and microscopic viewpoint,vessel routes as hazard sources were delineated on the basis of automated identification system(AIS)big data.The outliers and errors of AIS big data were removed using the density-based spatial clustering of applications with noise algorithm,and a marine traffic density map was evaluated by combining all of the gridded routes.Vulnerability of marine environment was identified on the basis of the sensitive resource map constructed by the Korea Coast Guard in a similar manner to the National Oceanic and Atmospheric Administration environmental sensitivity index approach.In this study,aquaculture sites,water intake facilities of power plants,and beach/resort areas were selected as representative indicators for each category.The vulnerability values of neighboring cells decreased according to the Euclidean distance from the resource cells.Two resulting maps were aggregated to construct a final sensitive resource and traffic density(SRTD)risk analysis map of the Busan–Ulsan sea areas.We confirmed the effectiveness of SRTD risk analysis by comparing it with the actual marine spill accident records.Results show that all of the marine spill accidents in 2018 occurred within 2 km of high-risk cells(level 6 and above).Thus,if accident management and monitoring capabilities are concentrated on high-risk cells,which account for only 6.45%of the total study area,then it is expected that it will be possible to cope with most marine spill accidents effectively.

Marine Accident Analysis with GIS

In this study, marine casualties which are recorded Global Integrated Shipping Information System （GISIS） in 2007-2011, result in death, injury, economic loss and environmental pollution are discussed. The studied types of ships are container, bulk dry, general cargo, roro, ropax, passenger and tankers. The information contained in GISIS system is textual format and it is difficult to systematically analyze this information. For this reason, by creating a new data base, which is Microsoft Excel-based, ship accidents are classified according to name, flag state and type of ship, type, size and coordinates of the accidents that are evaluated by entering the Geographical Information System（GIS）. In the study, all marine areas having been separated into ranges in ArcGIS 10 program, the marine areas with intensive marine accidents have been determined and marine accident chart has been created. As a result of the study, high risk marine areas are Strait of Dover and Hamburg in the North Europe, Belfast Shores in Ireland, the seas surrounding Great Belt, Kattegat and Copenhagen in Baltic Sea, In far east, Kanmon Strait, Urage Channel and Bungo Strait in Japan, Shanghai, Ningbo and Hong Kong in China.

Formal safety assessment and application of the navigation simulators for preventing human error in ship operations

The International Maritime Organization (IMO) has encouraged its member countries to introduce Formal Safety Assessment (FSA) for ship operations since the end of the last century. FSA can be used through certain formal assessing steps to generate effective recommendations and cautions to control marine risks and improve the safety of ships. On the basis of the brief introduction of FSA, this paper describes the ideas of applying FSA to the prevention of human error in ship operations. It especially discusses the investigation and analysis of the information and data using navigation simulators and puts forward some suggestions for the introduction and development of the FSA research work for safer ship operations.