Companies damaged by natural disasters can receive the insurance payout if they have contract in advance. Then, they can start recovery work in the early stage with budget and can minimize the losses due to interruption of business activities. On the other hand, number of examples in coastal disasters especially storm surge disaster is limited, and a few studies on probabilistic risk assessment have been done. Therefore, it is currently difficult for property and casualty insurance companies to estimate the amount of insurance payout to contracted companies. Settlement of accounts in the business year and insurance contracts are basically every year, it is also important to estimate annual expected damage. This study assesses annual aggregate risk of storm surge by typhoons which attack Japanese major bays by employing synthetic typhoon datasets made by the stochastic typhoon model. Storm surges are calculated by an empirical formula and a nonlinear shallow water equation model. This study estimates loss function by using the results of inundation simulation, and calculates damage using asset map. Risk curves from 1 area to 5 areas are estimated by the relationship of annual exceedance probability and annual aggregate loss. Annual expected loss are calculated by risk curves. It was shown that proposed risk curves enable us to perform more appropriate assessment close to the actual situation by conducting an annual aggregate risk assessment in an arbitrary region.

 Pools of liquid water, called melt ponds, form on the ice during the Arctic summer melt season. A better understanding of sea ice conditions during the Arctic melt season facilitates an investigation of the role of melt ponds in predicting the ice extent of sea ice. Our previous study developed an image analysis method to identify the ice surface conditions into five types (type 1: water only; type 2: ice only; type 3: water and ice; type 4: pond and ice; type 5: water, pond, and ice). However, the method did not used an orthorectified image but rather an oblique-view image and it is difficult to separate the type 5 condition from types 1–4. To resolve this, we have improved our method of image analysis to identify ice surface conditions (particularly type 5) using an orthorectified image. Moreover, we discussed the versatility and future applicability of the improved method.

 A structural performance evaluation method for wave-dissipating concrete blocks has not yet been established. In this study, rocking collision of wave-dissipating concrete block under wave action was examined through model experiments with various wave conditions in order to clarify the characteristics of impact velocity and number of impacts. Based on the test results, the characteristics of impact velocity and number of impacts were clarified as follows. The impact velocity was approximately according to the normal distribution and affected by the wave celerity, the relative water depth and the wave height. The number of impacts was affected by the horizontal distance from the center of rotation to the gravity center of the block and the wave height. The formulae for estimating impact velocity and number of impacts were proposed.

 The present study was undertaken to estimate the method for the determination of corrosion rate of steel covered with sand and masonry. The diffusion-limited current density of dissolved oxygen in the environment is one the most predominant factors influencing the determination and rate of microcell corrosion of steel in seawater. The rate of electrochemical corrosion of steel under sand deposit and masonry is similarly determined using diffusion-limited current density of dissolved oxygen in the environment. Parameters like particle size, thickness of the barriers, diffusion coefficient, and concentration of dissolved oxygen (DO) were employed in the estimation of diffusion-limited current density of DO. It is pertinent to note that, corrosion behavior of steel in an the environment is not only shaped by microcell corrosion effect, but also by macrocell corrosion formed at the barrier due to environmental conditions, and other factors. Therefore, to achieve effective corrosion protection of steel, the total value of microcell and macrocell corrosion rates should be evaluated to determine the area of application. Hence, the estimation method described above was used for the microcell corrosion estimation, and finite element analysis (FEM) was used for the macrocell corrosion estimation. Finally, the application area of corrosion protection was considered from the balance of inflow and outflow of the current density caused by both the corrosions.

 This report summarizes our reconnaissance survey after Typhoon No. 15 (Faxai), which struck Tokyo Bay on September 9, 2019. In Kanagawa, there was no major damage on the Sagami Bay side, but on the Tokyo Bay side, overtopping over an upright revetment with a height of 3.3 m above the sea occurred. In Chiba, there was no conspicuous high wave damage, except a building in Kujukurihama Beach that was obviously struck by wave run-up and splash. On the other hand, wind disasters were severe, and damage occurred in various places, such as the scattering of building roofs and the collapse of power poles. Wave-damage in Ibaraki was also minor. In Ibaraki, the breakwaters should have been constructed against severe winter storms, and the embankments have been substantially upgraded after the 2011 Earthquake and Tsunami. These structural resilience may have contributed to limiting typhoon impacts. Based on our wave model verified by the observations at three stations inside/outside the bay, the peak wave height during the typhoon was estimated to be 3.4 m off the coast of Yokohama. Compared with other 16 major typhoons that landed in the Kanto region, this typhoon was characterized as a strong small typhoon that slowly moved through Tokyo Bay. The result of the wave hindcast suggests that wind waves were rapidly intensified within the bay, resulting in significant damage in particular coasts, exacerbated by a storm surge of up to 1 m.