Sea level prediction is essential for the design of coastal structures and harbor operations. This study presents a methodology to predict sea level changes using sea level height and meteorological factor observations at a tide gauge in Antalya Harbor, Turkey. To this end, two different scenarios were established to explore the most feasible input combinations for sea level prediction. These scenarios use lagged sea level observations (SC1), and both lagged sea level and meteorological factor observations (SC2) as the input for predictive modeling. Cross-correlation analysis was conducted to determine the optimum input combination for each scenario. Then, several predictive models were developed using linear regressions (MLR) and adaptive neuro-fuzzy inference system (ANFIS) techniques. The performance of the developed models was evaluated in terms of root mean squared error (RMSE), mean absolute error (MAE), scatter index (SI), and Nash Sutcliffe Efficiency (NSE) indices. The results showed that adding meteorological factors as input parameters increases the performance accuracy of the MLR models up to 33% for short-term sea level predictions. Moreover, the results contributed a more precise understanding that ANFIS is superior to MLR for sea level prediction using SC1- and SC2-based input combinations.

Many power plants use fossil fuels to produce electrical energy. A safe fuel supply is an important issue in power plant operation. Although traditional use of pipeline systems is a common economical method, serious environmental problems are inevitable in case of a leak, a puncture, a rupture, or any other mechanical damages in the pipeline system. Therefore, the fuel supply pipeline system (FSPS) of power plant projects needs a comprehensive risk assessment study. In this study, a risk assessment framework was presented to analyze the potential risks and their occurrence probability for the FSPS of the Kalecik Power Plant, located in North Cyprus. To this end, the FSPS was divided into four manageable segments and then four major and 20 minor affecting criteria were identified. The scoring method was used to determine risk weights for each criterion. To distill quantitative risk scores, the risk frequency and potential fuel release into the Mediterranean Sea were calculated. The results showed that the potential risks of all the segments are in the acceptable range.