Seismic hazard maps play an important role in earthquake disaster risk reduction. The availability of spatial data is crucial to generate these maps that plot the spatial distribution of hazard potentials to emphasize spatial differences. The past few decades have seen an exponential increase in the availability of geospatial data. However, we cannot ascertain whether the amount of available data is sufficient, and we have no guidelines to draw the maps based on the available data consistent with the data accumulation. In this study, we address these issues in terms of data visualization techniques. Using information theory, we propose a parameter that measures the incremental information gain as maps are updated with new data over time. Data saturation occurs as the proposed parameter approaches zero. The concept is applied to a case study area in the Furukawa district of Japan where earthquake data has been collected over 7 years from 31 seismometers in a dense seismic array. Convergence in site amplification maps generated over different observation periods conclude that the mapping in Furukawa district is approaching data saturation and from the viewpoint of information theory, the current operation may be terminated.
Threats of potential natural disasters have necessitated the urgency to construct and sustain a highly reliable network for promotion of national resilience. However, improving all the links simultaneously is difficult due to budget constraints. Therefore, network reliability can be improved effectively by improving the most important key link. Our previous research revealed that improved criticality importance(CIW) is better than reliability importance (RI). However, as link reliability increases, the difference between the values of both indicators shrinks in terms of fairness of link improvement. In this study, we compared four importance indices. The newly added indices are Fussell-Vesely (FV) and the risk achievement worth (RAW), which are used in highly reliable systems (e.g., nuclear power plants). CIW, RI, FV, and RAW are compared by terminal reliability, difference between maximum and minimum values of link reliability (DBMM), and number of improved links. First, RI and RAW improve terminal reliability better compared with CIW and FV; however, the difference is small. RI and RAW give a larger DBMM than CIW, which indicates that using RI implies more gaps between parallel routes than using CIW and FV. Moreover, CIW is the best in terms of fairness of link improvement, as it has the largest number of improved links. Therefore, CIWis a recommended importance index.
Typhoon Jebi (T1821) was a high-speed typhoon with a moving speed exceeding 60 km/h at landfall, and with a further acceleration of the moving speed just before 14:00 on September 4, 2018, formed an extremely strong wind field, causing a storm surge and high wave disasters along the northern coast of Osaka Bay.
This study conducted a numerical simulation of storm surges and waves using the wave-surge combined numerical model taking the effects of moving speed acceleration into consideration by enhancing the JMA GPV wind data. The computation successfully reproduced the disaster external forces in Kobe and Osaka Ports, Yodo River mouth, and Kansai International Airport. The major findings of the study are summarized as follows:
(1) Numerical analysis considering the rapid increase of surface wind due to acceleration of the typhoon moving speed reproduced the storm surge anomaly exceeding 2.77 m observed at the northern end of Osaka Bay.
(2) The storm surge water level in Yodo River exceeding O.P.+5.2 m was also reproduced.
(3) The computed total water level was CDL+4.16 m (storm surge + wave run-up height + margin height) on the southeast side of Kansai International Airport Island that exceeded the current crown height of CDL+3.9 m.