Based on historical wind fields in the Bohai Sea, a sequence of annual extremal wave heights is produced with numerical wave models for deep-water and shallow water. The design wave heights with different return perio...Based on historical wind fields in the Bohai Sea, a sequence of annual extremal wave heights is produced with numerical wave models for deep-water and shallow water. The design wave heights with different return periods for the nearest deep-water point and for the shallow water point are estimated on the basis of P-III type, Weibull distribution, and Gumbel distribution; and the corresponding values for the shallow water point are also estimated based on the HISWA model with the input of design wave heights for the nearest deep-water point. Comparisons between design wave heights for the shallow water point estimated on the basis of both distribution functions are HISWA model show that the results from different distribution functions scatter considerably, and influenced strongly by return periods; however, the results from the HISWA model are convergent, that is, the influence of the design wave heights estimated with different distribution functions for deep water is weakened, and the estimated values decrease for long return periods and increase for short return periods. Therefore, the numerical wave model gives a more stable result in shallow water design wave estimation because of the consideration of the effect of physical processes which occur in shallow water.展开更多
In this paper, we establish a generalized extreme Value-Pareto distribution model and derive an analytical expression of Weibull–Pareto distribution model. Based on a data sample of 26-year wave height, we adopt the ...In this paper, we establish a generalized extreme Value-Pareto distribution model and derive an analytical expression of Weibull–Pareto distribution model. Based on a data sample of 26-year wave height, we adopt the new model to estimate the design wave height for 500, 700 and 1000-year return periods. Results show that the design wave height from Weibull–Pareto distribution is between that of the Weibull distribution and that of the Pearson-Ⅲ distribution.For the 500-year return period design wave height, the results from the new model is 1.601% lower than those from the Weibull distribution and 1.319% higher than those from the Pearson-Ⅲ distribution. The Weibull–Pareto distribution innovatively considers the fractal features, extreme-value statistics and the truncated data in the derivation process. Therefore, it is a more holistic and practical model for estimating the design parameters in marine and coastal environments.展开更多
基金This work was financially supported by the National Natural Science Foundation of China(Grant No.49776282)
文摘Based on historical wind fields in the Bohai Sea, a sequence of annual extremal wave heights is produced with numerical wave models for deep-water and shallow water. The design wave heights with different return periods for the nearest deep-water point and for the shallow water point are estimated on the basis of P-III type, Weibull distribution, and Gumbel distribution; and the corresponding values for the shallow water point are also estimated based on the HISWA model with the input of design wave heights for the nearest deep-water point. Comparisons between design wave heights for the shallow water point estimated on the basis of both distribution functions are HISWA model show that the results from different distribution functions scatter considerably, and influenced strongly by return periods; however, the results from the HISWA model are convergent, that is, the influence of the design wave heights estimated with different distribution functions for deep water is weakened, and the estimated values decrease for long return periods and increase for short return periods. Therefore, the numerical wave model gives a more stable result in shallow water design wave estimation because of the consideration of the effect of physical processes which occur in shallow water.
基金supported by the NSFC-Shandong Joint Fund(Grant No.U1706226)Graduate Education Reform and Research Fund(Grant No.HDJG18007)
文摘In this paper, we establish a generalized extreme Value-Pareto distribution model and derive an analytical expression of Weibull–Pareto distribution model. Based on a data sample of 26-year wave height, we adopt the new model to estimate the design wave height for 500, 700 and 1000-year return periods. Results show that the design wave height from Weibull–Pareto distribution is between that of the Weibull distribution and that of the Pearson-Ⅲ distribution.For the 500-year return period design wave height, the results from the new model is 1.601% lower than those from the Weibull distribution and 1.319% higher than those from the Pearson-Ⅲ distribution. The Weibull–Pareto distribution innovatively considers the fractal features, extreme-value statistics and the truncated data in the derivation process. Therefore, it is a more holistic and practical model for estimating the design parameters in marine and coastal environments.
