Spectral wave energy period and peak period statistics concomitant with maximum significant wave heights

Yang

Water Resources Research

et al. 2023

Wave and water depth were measured with an instrumented tripod in the Yellow River Delta from 9 December 2014 to 29 April 2015. Concurrent wind data were also collected from a nearby wind station. A high‐precision model for predicting local significant wave height (Hs) with wind speed (vw) is constructed using an improved data‐driven approach. The proposed model realized high accuracy as it solves the problem that the Hs falls too fast during the wind‐decreasing periods. It was tackled by considering the remaining influence of historical vw on the present Hs via incorporating a memory curve of the past wind effect. This innovative approach significantly improves the prediction (R2 from 0.60 to 0.83). The winds in the past 24 hr still left an influence on the waves at the observation site although the influence decreases with time. Physically, it is an implicit but simpler consideration of wind fetch/duration. Further data modeling experiments indicated that the decisive factor for the Hs at the site is the wind speed. Wind directions slightly improve the prediction, indicating that waves are slightly affected by the underwater seabed slope along different wind directions, and northwest winds cause the strongest waves at the site. Adding atmospheric pressure or water depth even reduces the accuracy, which indicated that storm surges and wave deformations under different tide levels have a weak impact on Hs. The proposed local wave model can be easily constructed with available wind and wave data, making it expandable to other regions dominated by wind waves.

mentioning

confidence: 99%

Improved Prediction of Local Significant Wave Height by Considering the Memory of Past Winds

Yang

Water Resources Research

et al. 2023

Uncertainty of Wave Spectral Shape and Parameters Associated with the Spectral Estimation

Clarindo,

Campos,

Guedes Soares

2024

JMSE

The uncertainty in estimating the wave spectrum from the records of wave elevation by heave–pitch–roll buoys is studied, considering the effects of the estimation method and the spectral resolution adopted in the process. This investigation utilizes measurements from a wave buoy moored in deep water in the South Atlantic Ocean. First, the spectra are computed using the autocorrelation function and the direct Fourier method. Second, the spectral resolution is tested in terms of degrees of freedom. The degrees of freedom are varied, and the resulting spectra and integrated parameters are computed, showing significant variability. A simple and robust methodology for determining the wave spectrum is suggested, which involves calculating the average energy density in each frequency band. The results of this methodology reduce the variability of the estimated parameters, improving overall accuracy while preserving frequency resolution, which is crucial in complex sea states. Additionally, to demonstrate the feasibility of the implemented approach, the final spectrum is fitted using an empirical model ideal for that type of spectrum. Finally, the performance and the goodness of the fit process for the final averaged curve are checked by widely used statistical metrics, such as R2 = 0.97 and root mean square error = 0.49.

Are Beaches Losing Their Capacity to Receive Holidaymakers? The Case of Ofir, Portugal

Silva,

Novais,

Vieira

et al. 2024

Sustainability

Coastlines are suffering from the effects of erosive processes, the decrease in sediment supply, the rise in mean sea level, and the construction of coastal infrastructure and drainage works, which are further exacerbated by global climate change. The area of the Parque Natural do Litoral Norte (North Coast Natural Park) reveals worsening erosion rates and the transformations directly affect the natural resources that support tourism activities, particularly beach and nature tourism. As part of the CLICTOUR project, we have selected the coastline from Restinga de Ofir to Bonança Beach as a case study. The ESRI ArcGIS software and the Digital Shoreline Analysis System (DSAS) were used to quantify coastline migration and identify the impacts on beach morphology between 2010 and 2023. Based on this information, we calculated changes in carrying capacity and scenarios for visitor usage availability to ensure the protection of fauna and flora, as well as the safety of beachgoers. The results of the linear regression rate confirm the coastline has retreated during the period analyzed (2010–2023). The outcome of these dynamics is noticeable in the beach area, promoting its reduction in area and leisure quality. Considering climate change, this study shows the importance of developing resilience strategies for coastal territories that serve as traditional summer destinations.