Aiming at the problem of calculating overtopping of the composite slope breakwater, a prediction model of the overtopping for the composite slope based on the random forest method is proposed. Firstly, by filtering the European CLASH data set, the data consistent with the prediction of overtopping of the composite slope breakwater are selected. Secondly, after dimensionless processing of the data, overtopping prediction model is established based on random forest method, and improved by adjusting the model parameters according to GridSearchCV. Finally, the coefficient of determination R² is used to evaluate the accuracy of the model, and the prediction ability of the model is compared with the ensemble neural network model. The effect of each feature parameter of the random forest model on the prediction accuracy is assessed. The results show that the coefficient of determination of the random forest model is 92.7%, and the coefficient of determination of the ensemble neural network model is 87.7%, indicating the random forest model has a stronger prediction ability for predicting overtopping. Wall height with respect to static water level has the greatest influence on the prediction accuracy of the model, the height of the top of the embankment is the second, and the width of the foot of the embankment least.

Numerous random wave trains are simulated based on the JONSWAP spectrum using the Longuet-Higgins wave model, and then extreme waves are investigated based on the wave trains with stable probabilities of freak waves. The probabilities of freak waves are smaller than those of based on Rayleigh distributions. With the spectra narrower, the probability of freak waves increases. During the fixed times, the frequency of freak waves obeys the Poisson distribution and time intervals satisfy exponential distribution. The most probable occurrence frequency of freak waves decrease and intervals of freak waves are longer with the spectra wider. Wave groups are discriminated based on wavelet spectra and their characteristics are analyzed. There are no more than four freak waves in wave groups. The probability of wave groups containing merely one freak wave is the largest. Numbers of freak waves in wave groups are increasing with the spectral narrower. Furthermore, time lengths of wave groups containing freak waves satisfy Generalized extreme value distribution (GEV distribution), and with spectra narrower, the most probable lengths of the wave groups increase.

Using the 3-D numerical model Ecom-si, saltwater intrusion in the Changjiang Estuary and water take in the Qingcaosha Reservoir under different wind speeds are studied. Model results show that the high saline water in Subei is transported southward to the Changjiang Estuary. Ekman transport drives a surge along the coast and a horizontal circulation in the Changjiang Estuary, which enters the North Channel (NC) and exit through the South Channel. This process increases salinity in the NC. Under the mean river discharge in the dry season (11 900 m³/s), the net water flux across the mouth of the NC is landward when wind speed exceeds 10 m/s, and the saltwater in the NC can spill over into the South Channel when wind speed exceeds 11 m/s. When wind speed is 0, the 15-day averaged salinity in the NC is only 0.97 and the elevation at the mouth of the NC is only 0.13 m. When wind speed increases to 14 m/s, salinity in the NC increases to 27.4 and the elevation at the mouth of the NC increases to 0.42 m. North wind reduces the number of days that the Qingcaosha Reservoir could take water from Changjiang within a month. When wind speed is 0, the number of days is 29.4 and when wind speed exceeds 10 m/s, the number of days is 0. The salinity in the NC increases with the strength of north wind, which is unfavorable to water take in the Qingcaosha Reservoir.

The traditional four-dimensional variational data assimilation method can optimize the parameters of the numerical model while assimilating the observation data. However, the traditional four-dimensional variational method needs to compile special adjoint models for different numerical models, so the portability of the traditional four-dimensional variational method is poor and a lot of resources are consumed in the calculation. In this paper, a new parameter optimization method based on the analytic four-dimensional ensemble variation is proposed, which expands the perturbation and constructs the ensemble based on the model parameters obtained by iterative search, and then explicitly calculates the covariance matrix, and obtains the analytic solution of the minimum value of the cost function, so as to avoid the use of adjoint model. Using Lorenz-63 model, single-parameter and multi-parameter numerical tests and optimization effect tests were carried out on the analytic four-dimensional ensemble variation method, and in the case of different assimilation time window length and observation sampling interval, the traditional four-dimensional variational method was used to compare with the new method, the results show that the new method has the same optimization performance as the traditional four-dimensional variational method, and it can converge to the truth value effectively, and the new method does not need to calculate adjoint mode, so it has good portability. This paper also test the assimilation effect of the new method with different ensemble members and true values of model parameters, and the results show that the new method is insensitive to the number of ensemble members and the true values of model parameters, and the data assimilation can be completed with fewer ensemble members.

Wave breaking is the most prominent feature of the ocean surface and it induces huge loads on structures. In this study, laboratory experiments in a large model scale are carried out to study wave forces on a vertical pile induced by breaking waves and non-breaking extreme waves, and to get insight the magnitude and the distribution of the wave forces, pressure transducers are installed in the face of the tested pile. The results show that in repeated experiments the wave pressures induced by the breaking waves present a wider variance compared with non-breaking waves; as the breaking density at the pile increases and the measuring point gets closer to wave crest, the variance of pressures increases; the maximum measured pressures can reach three times of the maximum hydrostatic pressure and occur at around 1.2 times of the maximum water surface. Based on the continuous wavelet spectrums of the wave pressures, different breaking phases show different characteristics: when the wave breaks far in front of the pile, its spectrum has a high frequency range with a wider vertical distribution, indicting more complicated pressures; when the wave breaks at the front of the pile, the wave force reaches a highest value.

The present study is concerned with the analytical solution for waves propagating over a local permeable seabed and wave reflection and transmission by the local permeable seabed. The computational domain is decomposed into four subdomains of which the middle subdomain is permeable, with the porous seabed beneath it, and the left and right subdomains are impermeable. Applying the linear wave theory, the velocity potential of each fluid subdomain is set up, including the effect of evanescent mode, and the pressure inside the porous seabed is given. The unknowns are solved by the continuous conditions at the interfaces between the neighboring subdomains. The effect of permeability coefficient, water depth and length of permeable seabed on wave transformation is discussed. The results indicate the wave height attenuates increasingly with the increase of permeability coefficient, the length of permeable seabed, and decrease of water depth. Wave reflection and transmission will occur due to the local permeable seabed. The reflection coefficient oscillates, and tends to be constant eventually, while the transmission coefficient reduces exponentially, and tends to be zero with the increase in the length of permeable seabed.

The interface of assimilating radiance on a new satellite sensor GMI (Global Precipitation Measurement (GPM) microwave imager) was constructed in the framework of the mesoscale numerical model WRF (Weather Research and Forecasting Model) and its three-dimensional variational assimilation system (3DVAR). The assimilation of GMI radiance data is applied for the typhoon system based on the case of typhoon Matmo in the Pacific typhoon season in 2014 before its landing. The results show that, after assimilating the GMI radiance data under the clear sky condition, the typhoon position in the background of the model is effectively corrected. The GMI data are able to improve the warm core structure of the typhoon when compared with the control experiment without assimilation and enhanced the typhoon vortex circulation structure at the same time. Data assimilating of GMI data further improves the forecast skills of the typhoon track.

The elevation, current, salinity and suspended sediment concentration (SSC) data were observed during spring and neap tides in the Jiaojiang Estuary. The spatial and temporal characteristics of tides, salinity and SSC in the main tidal channel of the estuary were studied, and the stratification physical mechanism under the action of high turbidity and strong tides was explained, using the field data. SSC and salinity during spring tides were higher than those during neap tides, and SSC during ebb periods was higher than the flood periods along the main channel. Salinity varied with the tidal currents, and the salinity water front appeared around the Station S2. A turbidity maximum zone appeared near the salt water front. SSC decreased and the salinity increased towards the sea. SSC and salinity increased with the water depth. According to the Richardson number and mixing parameters, stratification caused by salinity and SSC changes with tides. Stratification during flood periods was stronger than during ebb periods. Stratification lasted the longest time and was more extensive during neap tides. The mixing parameter varied with the tidal periods, and the value was high/below the critical value of 1.0 during spring/neap tides. The tidal strain term was an important role for the change rate of the potential energy anomaly. The stratified state changed to a mixed state during neap tides, while the opposite change occurred during flood tides.

This paper uses the ADCIRC model to establish a block-scale storm surge inundation model in the Beilun District, Ningbo City, with a land resolution of 5−10 m in the Beilun District. The simulation results show the overall process of inundation flooding urban street buildings, and detail description of the flow of water in the complex distribution of blocks and buildings, as well as changes in water depth near different buildings, which are more refined than previous inundation simulations, reflecting the advantages of block scale grid. Numerical simulation results show that this model can simulate the storm surge process of No. 1211 Typhoon “Haikui” and No. 5612 Typhoon “Wanda” well. Satellite remote sensing images are used to classify features in the Beilun District, and the influence of changes in the friction of different underlying surfaces on inundation simulation is considered. Comparing the results of the simulation experiment without considering the underlying surface friction, the submerged area is reduced by 21.4%, and the water depth in most areas is reduced to 0.1−0.2 m. The block-scale grid shows the degree of water depth reduction and the change of submerged area in different areas.

Particle filter (PF) is a very promising nonlinear data assimilation method. However, due to the particle degeneracy problem, it has not been widely used in large geophysical models. In contrast, the ensemble Kalman filter (EnKF) and its derivative methods have been widely used in operational data assimilation systems in recent years. A newly proposed local particle filter (LPF) which employs the localization technique in particle filter, can effectively avoid the degeneracy problem with low computational costs and has great potential for practical applications. In this paper, data assimilation experiments using LPF and EnKF are conducted in a fully coupled Community earth system model. The sythetic satellite sea surface temperature data are assimilated with each method. Different impact of local parameters on each method is investigated, and the data assimilation performances of LPF and EnKF are compared. The comparison results show that the performance of LPF is more sensitive to localization parameter. With the optimal localization strategy, it is shown that LPF can be better than EnKF, and have a potential to be further improved.