Shoreline-position forecasting: Impact of storms, rate-calculation methodologies, and temporal scales
Shoreline-position forecasting: Impact of storms, rate-calculation methodologies, and temporal scales
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海岸线位置预测：风暴的影响、速率计算方法和时间尺度
DOI：
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发表时间：
2001
期刊：
影响因子：
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通讯作者：
B. Douglas
中科院分区：
文献类型：
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作者：
M. Honeycutt;M. Crowell;B. Douglas
尽管有大量的研究试图描述过去和预测未来的海岸线变化，很少有共识的最佳方法来预测未来的海岸线位置。虽然考虑到沿海地貌和沉积物输运过程的可变性，在方法上有一定程度的异质性是有道理的，但没有详细评估与每种方法有关的预测误差。在这项研究中，测量的海岸线位置从特拉华州和纽约被用来计算长期侵蚀率，并作出预测，随后，已知的位置。使用终点和线性回归方法计算发生率，包括和不包括风暴特定的海岸线。与非风暴侵蚀率相比，包括风暴特定海岸线的速率计算结果始终较差（误差平均增加三倍），无论速率计算方法如何。平均而言，线性回归预测比终点率预测更好，对于包括风暴海岸线的数据，纽约和特拉华州的误差分别减少了70%和34%，对于非风暴数据，误差分别减少了4%和31%（DE和NY）。预测（后报）也作出了世纪的海岸线位置使用现代，非风暴数据计算的利率。预测的位置沿着相对不发达的海岸延伸在与预测相关的95%置信区间内。在以大量开发和（或）海滩营养项目为特点的地区，所作的后报很差，鉴于最近自然沉积物供应系统的改变，这是可以预料的。对于所有地点，包括19世纪的数据减少了大约44%的不确定性预测的21世纪的海岸线位置。这些结果表明，使用非风暴，19和20世纪世纪的数据从线性回归率得出的预测产生最低的预测误差和长期趋势的不确定性。
Despite the considerable research that has sought to describe past and predict future shoreline change, little consensus has emerged on the best methodology for forecasting future shoreline positions. While a certain degree of heterogeneity in approach is warranted given the variability in coastal geomorphology and sediment-transport processes, the prediction error associated with each method has not been evaluated in great detail. In this study, measured shoreline positions from Delaware and New York were used to calculate long-term erosion rates and make predictions to subsequent, known positions. Rates were calculated using end-point and linear-regression methods, including and excluding storm-specific shorelines. Those rate computations that included storm-specific shorelines yielded consistently poor predictions (average factor-of-three increase in error) compared with non-storm erosion rates, regardless of rate-calculation method. Linear-regression predictions, on average, performed better than end-point rate predictions, reducing error by over 70% in New York and 34% in Delaware for rates including storm shorelines, and between 4 and 31% for non-storm data (DE and NY, respectively). Predictions (hindcasts) were also made to 19th century shoreline positions using rates computed with modern, non-storm data. The positions predicted along relatively undeveloped stretches of the coast were within the 95% confidence interval associated with the prediction. Hindcasts made in areas characterized by heavy development and/or beach nourishment projects were poor, as would be expected given the recent alteration of the natural sediment-supply system. For all locations, inclusion of 19th century data reduced uncertainty in forecasts of 21st century shoreline positions by roughly 44%. These results show that forecasts derived from linear-regression rates using non-storm, 19th and 20th century data produce the lowest prediction error and uncertainty in the long-term trend.