The hypocenter and magnitude of the earthquake are determined quite rapidly using available data at stations near the hypocenter, and distribution of strong ground shaking is anticipated quickly, and then the information is delivered immediately to people living far from the hypocenter. The warning is called “Earthquake Early Warning (EEW)”, and is definitely different from earthquake prediction. It is possible to warn people being at a certain distance from the hypocenter before strong ground shaking reaches them.
For the real time decision of the hypocenter, we use the methods such as B-Δ method, territory method (one or two points), the grid search method (3-5 points) by a number of the observation point that we can use and utilize the Not yet arrived data method by NIED.
At P wave stage, we use the P phase magnitude formula to estimate the magnitude of the earthquake. Then after that, we use all phase magnitude formula.
We estimate the maximum velocity at the standard base from hypocenter and magnitude by the experience formula and then estimate the maximum velocity and seismic intensity at the surface by another experience formula.
An Early Earthquake Warning of 1,449 examples was disseminated by April 30, 2007 from February 25, 2004 when experimental use began. Of these, the false report by thunder or the artificial noise had 29 examples, but there was not the false report by the EEW which used more than two stations. About 28 earthquakes that the anticipated maximum seismic intensity is equal to or exceeds “5-lower”, seismic intensity “5-lower” or higher was observed at 15 earthquakes, and seismic intensity “4” was observed at 9 earthquakes, seismic intensity “3” was observed at 3 earthquakes.

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The Real-time Earthquake Information Consortium (REIC) has been contributing to the development of automatic and semi-automatic application systems for utilizing earthquake early warning (EEW) in the Leading Project “Research project for the practical use of Real-time Earthquake Information Network”. The project has been promoted by MEXT (Ministry of Education, Culture, Sports, Science and Technology) during 2003-2007. This system rapidly determines the epicenter location, origin time, magnitude and seismic intensity. Results of estimation are issued within several seconds from P-wave arrivals at the nearby stations. At any place of Japan, users can get this information before the arrival of S-wave in areas of sufficiently far from the epicenter and can take proper actions for reduction of disasters.
This project is executed by the cooperation of governments, universities, governmental research institutions, and companies. This paper describes the current state of development and several problems to be solved in order to utilize the EEW effectively.

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In order to reduce earthquake disaster of railways, we should improve the earthquake-proof performance of facilities. The other way of reducing earthquake disaster is to control the train operation promptly and appropriately in case of an earthquake. The Railway Technical Research Institute (RTRI) had developed an urgent earthquake detection and alarm system (UrEDAS) mainly for Shinkansen and put it into practical use. Valuable knowledge is being accumulated to give an urgent alarm for earthquakes due to the development of the real-time seismology in recent years. The Japan Meteorological Agency (JMA) and other governmental organizations are improving the nationwide earthquake observation network and planning to distribute prompt earthquake information (Earthquake Early Warning information; EEW information). Under the circumstances, RTRI and JMA have developed the data processing system of this information and the application system of this information to an earthquake quick alarm system of railways.
This paper presents new methods to estimate the hypocenter and magnitude in a short time after the detection of P waves, which are called the B-Δ method, territory method and grid search method. This paper also presents a new alarm system using the EEW information developed for a private railway. When this system will receive the EEW information and judge the earthquake to be dangerous for the railway by the M-Δ method, it will give the alarm to the running trains by train radio automatically. In this paper, we express a prospect for the real-time earthquake disaster prevention of railways.

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We have developed an earthquake early warning system (EEWS) by using a spatially dense and high dynamic range seismic network that consists of 800 stations covering the Japanese Islands. The system is able to determine the hypocenter location and magnitude within a few seconds from the P-wave arrivals at the closest stations and then transmits this information before the arrival of S-waves in areas of potentially serious earthquake damage. Since the available waveform data increases with time, our EEWS is designed to update the earthquake parameters every second. An early warning system should be able to reliably determine earthquake parameters as quickly as possible; it is therefore unreasonable to wait until waveform data from numerous stations have been collected for analysis. Assuming that all stations will observe P-wave arrivals from a large earthquake, we have developed a novel method of determining the hypocentral location that uses the arrival times for only a few stations and also the lack of P-wave arrivals at other stations at a given time (T^now). The use of T^now makes it possible not only to reliably determine hypocenter parameters within a few seconds but also to detect spurious arrival times and remove them automatically. By using T^now in our dense seismic network, our EEWS determines hypocenter parameters for 10 to 20 events per day and 99% of them are determined correctly. The receiving unit of earthquake early warning (EEW) is equipped with a CPU and memory and is on-line via the internet. The addition of an inexpensive seismometer and A/D converter would transform this receiver into a real-time seismic observatory, which we are calling a home seismometer. The spread of home seismometers will bring the construction of very dense seismic network available for EEWS.

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Reliable estimation of the expected seismic intensity from the seismic S-waves is the main purpose of an earthquake early warning (EEW) system. To date, empirical regression formulae have been used to estimate this intensity from the conventional seismic magnitude (e.g., Mjma), which is the only parameter regarding earthquake size issued by EEW. The magnitude determined from displacement records, however, is not an adequate parameter to describe the seismic intensity, which is a result of short-period accelerations. In this paper, we introduce a new parameter, seismic intensity magnitude (MI), which is defined directly from observed seismic intensity (I). The definition of MI is as follows,
 MI = I/2 + log(r) + αt_s + b−c
where α=π/ln(10)f_s/Q_s. r, t_s, f_s and Q_s are the hypocentral distance, travel time of S wave, predominant frequency of S wave and Q value for S wave, b is a constant and c is a site correction term, respectively. Once MI has been determined, we can easily obtain seismic intensity at any site from MI and the hypocentral distance. In order to confirm its effectiveness, we determined MI for 127 earthquakes observed by Hi-net, and estimated the seismic intensity at 11242 sites. We compared observed seismic intensity with estimated one at each site and found the averaged estimation error of seismic intensity by MI is 0.438 (rms), which is 22% smaller than the error by the conventional method using Mj.
Next, we developed a method to calculate MI from P wave (MIp) for EEW systems and showed that averaged estimation error by MIp is 0.466 (rms), which is still 17% smaller than the conventional method using all the phases of seismic waves. We also found that MIp can estimate seismic intensity more rapidly than the conventional method for the earthquakes larger than 7. These results indicate that MI and/or MIp is a very effective parameter for rapid estimation of seismic intensity in EEW systems.

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Breakwaters which defend ports from high waves are mainly constructed with box caissons in Japan. Caisson breakwaters made of reinforced concrete are often damaged by wave forces during a long period after the construction. The inner sand of the damaged caissons flows out. As a result, growth of the cavities in the caissons is accelerated. In order to detect the existence of the cavities, we first observe the condition of the breakwater surface and measure the elevation or the shape of the caissons. Next, we bore the breakwater from its surface and insert a waterproof camera into the holes to observe the cavities. This method takes much time and cost.
GPR (ground penetrating radar) is commonly applied to detect cavities in the underground or concrete constructions. However, the investigation depth of conventional impulse GPR system is shallow and they can detect the cavities only up to about 1m depth behind the concrete structures.
We have developed a diagnosis system which was equipped with a FM-CW (frequency modulation coutinuous wave) GPR, for investigating the existence and thickness of cavities inside caissons from the breakwater surface in a non-destructive manner. Furthermore we designed an automatic diagnosis program so that any engineer, regardless of the experience on GPR surveys, could operate the program and evaluate cavities in caissons immediately at the field site.
This automatic diagnosis program needs electrical properties (relative dielectric permittivity and electrical conductivity) of the concrete crown of the caissons. We measured electrical properties of concrete core samples at the same frequency range of the FM-CW GPR system.
Parameters needed for the automatic diagnosis program were decided by a numerical modeling of the electromagnetic wave propagation in breakwaters, to which the electrical property values obtained by the core sample measurements were applied. Diagnosis results are simply visualized and are stored in a built-in PC by the automatic diagnosis program.
In this paper, we introduce technical features of the diagnosis system and demonstrate exploration results at Niigata-higashi port and Kanazawa port.

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CO₂ sequestration into a deep aquifer is considered one of the most effective methods to solve Global warming problem. In order to realize the geological sequestration of CO₂, we have to develop the method estimating optimum aquifer for CO₂ sequestration and the technique monitoring the behavior of injected CO₂. In this study, for increasing the accuracy of the monitoring survey using electrical and electromagnetic methods, we tried to monitor the behavior of gas, liquid and supercritical CO₂ injected into a sandstone specimen saturated with brine water by measuring resistivity time variations. We made an experimental equipment which can reproduce the high pressure environments same as the underground conditions. A cylindrical sample of Berea sandstone (5cm in diameter and 12cm in length) was used in this experiment. CO₂ of gas, liquid, and supercritical phases was flooded through the sandstone specimen at three different flow rates. We could monitor the movement of CO₂ in the sand stone by the resistivity change and the resistivities increased up to 2 to 3 times. The resistivity changes were monitored for whole period from initial injection time to high saturated time. We estimated the CO₂ replacement ratio using Archie's equation. The CO₂ replacement ratios estimated from resistivity data are nearly equal to those calculated from actual outflow volumes. These results show the high reliability of electrical survey to monitor CO₂ saturation. Additionally, the replacement ratio of liquid and supercritical CO₂ are higher than that of gas CO₂.

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