Coastal Priority Ranking in Oil Spill Response Decision Support Mechanism

Millions of tons of oil are produced in the world every year and over half of it is transported to the users by means of marine routes. Based on statistics, a best estimate of oil spill is more than 3 million tons per year. Oil spills cause disastrous impacts on the environment, ecology and socio-economic activities. The right decision has to be made in the event of an oil spill to facilitate prompt action, considering the priorities of protection, to prevent environmental damages. Interest in having modern, technological management system in semi-structured fields such as disastrous incidents is increasing rapidly. Response decision support is a mechanism utilizing a knowledge-based plan to choose the most suitable method of response by analyzing the various sensitivity factors, parameters affecting oil spill impacts, environmental concerns in oil spill response, and consequence monitoring and clean-up operations in the shortest time. Environmental sensitivity index (ESI), a traditional scale, is mostly a static scale for evaluation of coastal situation. It requires calibration along with oil nature and impact in each spill case to be able of priority displaying in action. This study aimed to develop a semiautomatic knowledge-based decision support mechanism to retrieve experts’ knowledge for prioritization in responding to oil spill events. A tool was needed to classify information about knowledge and expertise in this field and follow the rational logic of master minds and could be transferable. The knowledge and expertise from knowledgeable participants were obtained through questionnaires and direct interviews as well as information from literatures. Three objectives were covered by the study including ranking of sensitivity-oil-response criteria, development of coastal priority ranking (CPR) scale, and establishment of a validated computer-based mechanism for oil spill response (OSR-DSM). Analyses of questions were conducted using Delphi method, Likert scaling, and repertory grid analysis. The evaluation of knowledge level provided the normalized weights (from 0.09 to 1.0) for respondents’ knowledge and these weights were applied to criteria ranking. Considering two objects of environment and oil, priority ranking matrix was established and CPR scale was calculated based on the fact that various “low/ medium/ high” impacting scenarios of oil can affect the corresponding “low/ medium/ high” sensitive resources. One program was designed to visualize DSM with computation of ESI, coastal sensitivity, oil impact, and CPR values as well as reporting on response alternatives. The advantage of CPR scale method was its ability for a more dynamic quantitative evaluation of priorities in application time rather than only explaining sensitivity indices of area. The scale for CPR was evaluated ranging from 35 to 469 and the values were qualitatively categorized from low priority to medium, high, very high and extremely high priorities. Three major categories were renowned for responses alternatives - on-sea response or preventive activities, shoreline protective activities, and on-coast response or cleanup activities. Results were verified to present the inclusiveness, accuracy, and system algorithm. The verification activity involved exploring the knowledge base, coding of reasoning processes / inference engine, technical performance, ability for development, and interface. A total of 80 percent of users in the verification phase believed that development of such mechanism was a right approach for supporting the right decision in oil spill responses, either by increasing the speed and accuracy in evaluation or reducing the cost. Verification research could attain rates of over 50 percent in all five categories. General rates given to the mechanism by two groups of users were 82 and 85 percent with a + 3.66 percent of uncertainty that was issued a high verification value. This study has resulted in two main products: - coastal priority ranking scale (CPR) and oil spill response decision supporting mechanism (OSR-DSM). It is intended to facilitate the oil spill response process while at the same time improves the decision-making quality by applying the effective knowledge and expertise in oil spill response procedures. Definition of knowledge criteria leading to classification of knowledgeable participants, as well as numerical verification frame for qualitative knowledge-base mechanism were two significant outputs of this study.

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