A comparison of several wave spectra for the random wave diffraction by a semi-infinite breakwater

A comparison of the diffraction of multidirectional random waves using several selected wave spectrum models is presented in this paper. Six wave spectrum models, Bretschneider, Pierson–Moskowitz, ISSC, ITTC, Mitsuyasu, and JONSWAP spectrum, are considered. A discrete form for each of the given spectrum models is used to specify the incident wave conditions. Analytical solutions based on both the Fresnel integrals and polynomial approximations of the Fresnel integrals and numerical solutions of a boundary integral approach have been used to obtain the two-dimensional wave diffraction by a semi-infinite breakwater at uniform water depth. The diffraction of random waves is based on the cumulative superposition of linear diffraction solution. The results of predicted random wave diffraction for each of the given spectrum models are compared with those of the published physical model presented by Briggs et al. [1995. Wave diffraction around breakwater. Journal of Waterway, Port, Coastal and Ocean Engineering—ASCE 121(1), 23–35]. Reasonable agreement is obtained in all cases. The effect of the directional spreading function is also examined from the results of the random wave diffraction. Based on these comparisons, the present model for the analysis of various wave spectra is found to be an accurate and efficient tool for predicting the random wave field around a semi-infinite breakwater or inside a harbor of arbitrary geometry in practical applications.     

Acoustic plane-wave scattering from a rough surface over a random fluid medium

Acoustic plane-wave scattering from a rough surface overlying a fluid half-space with a sound-speed distribution subject to a small random variation is considered. Under the assumption that the surface roughness and medium randomness are statistically independent, the scattered field may be derived by first solving for the mean field in the medium, and then incorporating with boundary-perturbation method to obtain the total mean field and the power spectral density of the scattered field. The employed algorithm is compatible to the analysis available in the existing literature so that the formulations are conveniently integrated. The results for the power spectral density have shown that the effects of medium inhomogeneities on the rough surface scattering are limited in a spectral regime where the scattered components have shallow grazing angles. The distribution of the power spectral density over the space is primarily governed by the power spectrum and correlation lengths of the rough surface.     

Estimating aboveground biomass of the mangrove forests on northeast Hainan Island in China using an upscaling method from field plots,UAV-LiDAR data and Sentinel-2 imagery

The mangrove forests of northeast Hainan Island are the most species diverse forests in China and consist of the Dongzhai National Nature Reserve and the Qinglan Provincial Nature Reserve. The former reserve is the first Chinese national nature reserve for mangroves and the latter has the most abundant mangrove species in China. However, to date the aboveground ground biomass (AGB) of this mangrove region has not been quantified due to the high species diversity and the difficulty of extensive field sampling in mangrove habitat. Although three-dimensional point clouds can capture the forest vertical structure, their application to large areas is hindered by the logistics, costs and data volumes involved. To fill the gap and address this issue, this study proposed a novel upscaling method for mangrove AGB estimation using field plots, UAV-LiDAR strip data and Sentinel-2 imagery (named G∼LiDAR∼S2 model) based on a point-line-polygon framework. In this model, the partial-coverage UAV-LiDAR data were used as a linear bridge to link ground measurements to the wall-to-wall coverage Sentinel-2 data. The results showed that northeast Hainan Island has a total mangrove AGB of 312,806.29 Mg with a mean AGB of 119.26 Mg ha⁻¹. The results also indicated that at the regional scale, the proposed UAV-LiDAR linear bridge method (i.e., G∼LiDAR∼S2 model) performed better than the traditional approach, which directly relates field plots to Sentinel-2 data (named the G∼S2 model) (R² = 0.62 > 0.52, RMSE = 50.36 Mg ha⁻¹<56.63 Mg ha⁻¹). Through a trend extrapolation method, this study inferred that the G∼LiDAR∼S2 model could decrease the number of field samples required by approximately 37% in comparison with those required by the G∼S2 model in the study area. Regarding the UAV-LiDAR sampling intensity, compared with the original number of LiDAR plots, 20% of original linear bridges could produce an acceptable accuracy (R² = 0.62, RMSE = 51.03 Mg ha⁻¹). Consequently, this study presents the first investigation of AGB for the mangrove forests on northeast Hainan Island in China and verifies the feasibility of using this mangrove AGB upscaling method for diverse mangrove forests.     

Generating soil thickness maps by means of geomorphological-empirical approach and random forest algorithm in Wanzhou County,Three Gorges Reservoir

Soil thickness, intended as depth to bedrock, is a key input parameter for many environmental models. Nevertheless, it is often difficult to obtain a reliable spatially exhaustive soil thickness map in wide-area applications, and existing prediction models have been extensively applied only to test sites with shallow soil depths. This study addresses this limitation by showing the results of an application to a section of Wanzhou County (Three Gorges Reservoir Area, China), where soil thickness varies from 0 to ～40 m. Two different approaches were used to derive soil thickness maps: a modified version of the geomorphologically indexed soil thickness (GIST) model, purposely customized to better account for the peculiar setting of the test site, and a regression performed with a machine learning algorithm, i.e., the random forest, combined with the geomorphological parameters of GIST (GIST-RF). Additionally, the errors of the two models were quantified, and validation with geophysical data was carried out. The results showed that the GIST model could not fully contend with the high spatial variability of soil thickness in the study area: the mean absolute error was 10.68 m with the root-mean-square error (RMSE) of 12.61 m, and the frequency distribution residuals showed a tendency toward underestimation. In contrast, GIST-RF returned a better performance with the mean absolute error of 3.52 m and RMSE of 4.56 m. The derived soil thickness map could be considered a critical fundamental input parameter for further analyses.     

Effect of 2D spatial variability on slope reliability: A simplified FORM analysis

To meet the high demand for reliability based design of slopes, we present in this paper a simplified HLRF(Hasofere Linde Rackwitze Fiessler) iterative algorithm for first-order reliability method(FORM). It is simply formulated in x-space and requires neither transformation of correlated random variables nor optimization tools. The solution can be easily improved by iteratively adjusting the step length. The algorithm is particularly useful to practicing engineers for geotechnical reliability analysis where standalone(deterministic) numerical packages are used. Based on the proposed algorithm and through direct perturbation analysis of random variables, we conducted a case study of earth slope reliability with complete consideration of soil uncertainty and spatial variability.     

A rational approach to seepage flow effects on bottom friction beneath random waves

The bottom friction beneath random waves is predicted taking into account the effect of seepage flow. This is achieved by using wave friction factors for rough turbulent, smooth turbulent and laminar flow valid for regular waves together with a modified Shields parameter which includes the effect of seepage flow. Examples using data typical to field conditions are included to illustrate the approach. The analytical results can be used to make assessment of seepage effects on the bottom friction based on available wave statistics. Generally, it is recommended that a stochastic approach should be used rather than using the rms values in an otherwise deterministic approach.     

宁夏及邻区地震活动能量场时空变化特征

运用随机函数理论,将宁夏及邻区地震活动能量场看作时间和空间的随机函数,用自然正交函数展开方法,系统研究宁夏及邻区主要典型能量场的时间权重系数变化曲线以及典型能量场的空间等值线图。结果发现,目标曲线较大幅度的升、降变化预示了可能发生中强地震的时间段,而等值线图的高值变化（危险区）对应了可能发生中强地震的区域。     

Numerical simulation of nearshore circulation on field topography under random wave environment

In order to investigate surf zone hydrodynamics through two-dimensional numerical simulations of nearshore circulation under random wave environment, a nearshore circulation model, SHORECIRC, and a random wave model, SWAN, were combined and utilized. Using this combined model, a numerical simulation of the October 2, 1997 SandyDuck field experiment was performed. For this simulation, field topography and an input offshore spectrum were constructed using observed data sets synchronized with the experiment. The wave-breaking model in SWAN was modified by using breaker parameters varied according to bottom slope. The simulation results were compared with the experimental data, which revealed a well-developed longshore current, as well as with results using other combinations which were SHORECIRC and its original monochromatic wave-driver, and SHORECIRC and the default of SWAN. The results from the novel combined model agreed well with the experimental data. The results of the present simulation also indicate that alongshore field topography influences shear fluctuation of longshore currents.     

Changes in air pollutants during the COVID-19 lockdown in Beijing:Insights from a machine-learning technique and implications for future control policy

基于2015-2020年北京35个环境空气站和20个气象站观测资料,应用机器学习方法(随机森林算法)分离了气象条件和源排放对大气污染物浓度的影响.结果发现,为应对疫情采取的隔离措施使北京2020年春节期间大气污染物浓度降低了35.1％-51.8％;其中,背景站氮氧化物和一氧化碳浓度的降幅最大,超过了以往报道较多的交通站...