Monday, July 13, 2015
Sunday, January 20, 2013
Everest and the Toenail
One Day The Earth Will Drop Kathmandu – Earthquake Risk in Nepal
The Last Ten Seconds: https://www.youtube.com/watch?v=n-FMpNBfna8

Thursday, January 5, 2012
Intensity of Nepal-Sikkim 6.8 Earthquake
Tuesday, February 15, 2011
VALIDATION OF SPATIAL AUTOCORRELATION (SPAC) METHOD WITH L-SHAPE ARRAY IN JYOSO CITY,JAPAN
Prithvi Lal SHRESTHA*
ABSTRACT
This study is aimed to validate the efficiency of an L-shape array for SPAC method using microtremor in estimating the shear wave velocity (Vs) structure. The experiment for validation was conducted in the Toyota Community Baseball Ground, Jyoso City, Ibaraki Prefecture, Japan in March 2009 with an equilateral triangle array with side length of 40m and in June 2010 with an equilateral triangle array with side length of 50m, together with an L-shape array of the similar size. Multichannel Analysis of Surface Waves (MASW) was also performed simultaneously in June 2010. In the same lot PS-logging data are available from nearby IBRH10 station of the KIK-NET (NIED, Japan) that shows soft sediment of about 20m thick with Vs of 110 m/s in the geological column of the site. The comparison of the determined phase velocity and that calculated from PS logging data shows close matching of two sets of curves separately. One is between PS logging and the triangle array (40m) and the other is between the triangle array (50m) and the L-shape array (50m). Former two are of the almost same place whereas other two arrays are deployed about 200m away from the other set. Some discrepancy between two sets is shown. This seems due to lateral variation of underground velocity structure which is consistent with the result of MASW.
Based on the results of analysis we can say that an L-shape array can be applied to estimate shear wave velocity for shallow depth so it can be layout in urban areas to determine phase velocity information from microtremor. Therefore it may be feasible to apply it in the Kathmandu valley, Nepal that is based upon the soft soil with high possibility of liquefaction or earthquake hazard. Keywords: SPAC, PS logging data, Equilateral Triangle array, L-shape array. *National Seismological Centre, Department of Mines & Geology, Kathmandu, Nepal.
1. INTRODUCTION
Nepal Himalaya lies in the active seismic belt. Seismicity in the Himalaya is the consequence of under-thrusting of the Indian plate towards the north lying Tibetan plate. Nepal has suffered earthquake disasters through its history due to its high seismicity and highly vulnerable construction practices, therefore one of the most earthquake disaster prone countries in the world.
1.1. Purpose of my study:
Since we are expecting a great earthquake disaster in near future in our country Nepal, seismic hazard assessment is required. Estimation of the amplification factor of the ground, i.e., microzonation on the basis of the shallow Vs structure is a basic step of seismic hazard assessment. The microtremor array measurement will be applied in Nepal in future, because this SPAC method seems to be reliable, easy to,comparatively affordable and do not cause any environmental problems, thus suitable as a tool for seismic microzonation and earthquake disaster mitigation. Conventional circular or equilateral triangle arrays, however, are sometimes difficult to deploy in crowded urban areas where only L-shape or linear arrays layout can suit to road pattern. The purpose of this study is to understand the effectiveness, limitations and advantages of L-shape array for the SPAC method by applying and verifying the applicability and accuracy by comparison with standard equilateral triangle array in Jyoso city, Ibaraki, Japan.
2. METHODOLOGY
2.1. SPAC method:
This is a successful method to determine the phase velocity information from surface waves contained in microtremor (e.g., Aki 1957; Okada 2003). The SPAC coefficient for distance r between two stations at the angular frequency ω provides the information about the phase velocity of the propagating waves in the array. This is obtained by the azimuthal average of coherency between microtremor records observed at two stations.
2.2. Procedure of analysis:
Triangle and L-shape arrays are set up to get the microtremor data. First SPAC coefficient is obtained
after filtering and resampling and then screening is done. Second, the dispersion curve
of Rayleigh wave is determined and finally velocity structure model is estimated by the heuristic search method using the very fast simulated annealing method (VFSA) combined with the downhill simplex method (DHSM)(VFSA-DHSM, Yokoi 2005).
3. DATA ACQUISITION
3.1. Observation site:
The experiment was conducted in the Toyota Community Baseball Ground, Jyoso City, Ibaraki Prefecture, Japan in March 2009 and June 2010.
IBRH10 of KIK-NET (NIED, Japan) is located at the south-east corner of the same lot where PS-logging data are available. MASW (Hayashi and Suzuki 2004) was also conducted this year. Soft sediment as thick as about 20 m with velocity of S-wave (Vs) 110 m/s is observed in the geological column at IBRH10. There are a national road R294 about 300 m west and a prefectural road 24 about 100 m south and both of them have heavy traffic all day long.
The baseball ground itself, however, was almost quiet during the measurement (Yokoi and Hayashi 2009).
3.2. Array deployment and instruments:
Equilateral triangle array with side length of 40m with 7 sensors was deployed in March 2009 nearby IBRH10 whereas 50 m of equilateral triangle with 10 sensors and L-shape array with 11 sensors were deployed in June 2010 about 200m away from IBRH10. All sensors are vertical component. MASW with total length of 105m was conducted in the same place.
4. ANALYSIS AND RESULTS
4.1. Preprocessing:
Multiplexing and re-sampling are done applying digital anti-aliasing filter (Saito 1978). The screening is conducted next with two steps. The data are divided into time blocks with 512 samples. The consecutive time blocks are overlapped each other by 50% of their duration.
First step: If peak is greater than “ajudge” times of RMS amplitude then this time block is not used in analysis. This is a countermeasure against impulsive noise due to traffic, i.e. vehicles passing near by sensors.
Second step: If RMS amplitude in a time block deviates more than another given constant “a_sgm” times the standard deviation from the average, this time block is not used in analysis, where the average and the standard deviation are calculated over the all time blocks that survived in the above mentioned screening step 1. This is a countermeasure against outliers. In this study ajudge=4 and a_sgm=2 are used for the screening of the obtained data.
4.2. SPAC coefficient calculation:
Re-sampled and screened time block files are used to calculate SPAC coefficient that is an azimuthal average of the coherency between microtremor records at two stations. The initial frequency range of analysis is set from 0.1Hz to 10Hz. Band width of Parzen window for smoothing power and cross spectra is set at 0.5Hz.
4.3. Determination of dispersion curve:
The dispersion curve of Rayleigh wave i.e., the phase velocity depending upon the frequency is determined from SPAC coefficient. First, SPAC coefficient ρ(ωr) is converted to the value of kr by applying the following fifth order polynomial equation that approximates the inverse function of J0(kr). The first maximum of c(ω) from the low frequency side is recognized as a lower limit of the available frequency range for the respective inter-station distance. The maximum from this lower limit to the highest one is recognized as the high frequency limit of the available frequency range. Then these values again are averaged and converted to c(ω) = rω/(kr). The weight coefficient used at averaging is the reciprocal of the variance of SPAC coefficients at the respective inter-station distance and the frequency.
4.4. Estimation of velocity structure by Heuristic search:
A heuristic search method is conducted to obtain the optimum underground structure by fitting the theoretical phase velocity of Rayleigh wave to the observed dispersion curve. Five layer models are introduced with its search range. The used method is the downhill simplex method (DHSM, e.g., Press et al. 2002) combined with the very fast simulated annealing (VFSA, Ingber 1989). Hereafter, the combined methods is called the DHSM-VFSA. The optimum, namely, the fastest schedule for the inversion of underground velocity structure from the dispersion curve of Rayleigh waves is used with the parameters t0=1.0, a=0.6, and c=1.3 as given by Yokoi (2005).
5. DISCUSSION
5.1. Comparison of dispersion curves:
Fig shows a comparison of phase velocity over frequency between 40m triangle, 50m triangle and 50m L-shape arrays with the curve of PS logging data.This shows close matching of two sets of curves separately, one is between PS logging and 40m triangle and the other is 50m triangle and L-shape. PS logging and 40m triangle array are from the same place where other two arrays are also from the same place but about 200m away from the other set. A discrepancy is seen between these two sets. This seems to be due to lateral variation of underground structure as MASW result implies.
5.2. Comparison of velocity structure:
Figure shows the comparison of Vs
structure models determined by the data of the three arrays with the PS logging data. Vp is fixed to 1500m/s for the 1st to 4th layer and 1956m/s for the underlying half space.
Density is calculated from Vp then fixed to 1.9g/cm3 and 2.13g/cm3 respectively(Ludwig et al. 1970). As seismometer’s natural frequency is 2.0Hz, the lower limit of the frequency range for analysis is set at
2.0Hz and the upper one at 5.0Hz by considering on the S/N of microtremor. The value of misfit is as small as 3.0, 4.0 and 4.2 m/s for the triangular array (40m), triangular array (50m) and L-shape array respectively. From Figure it is clear that for the 20m depth Vs of all arrays are similar to the logging datai.e., around 110m/s to 150m/s that implies soft soil. Vs structures of the triangular array (50m) and L-shape array coincide to each other whereas 40m triangle shows a clear deviation from them and lower Vs than PS logging data. This shows that the lateral variation of underground velocity structure implied by MASW is detected also using SPAC method.
6. CONCLUSION
In this study I have conducted the analysis of the data of microtremor array observation held in the Toyota Community Baseball Ground, Jyoso city, Ibaraki prefecture, Japan for shallow depth using L-shape and equilateral triangle array with the SPAC method for Rayleigh wave in comparison with PS logging data and MASW. The dispersion curve and Vs Structures determined by the data of L-shape array coincide well to those of equilateral triangular array (50m). These deviate together from Vs structure of PS logging data and the dispersion curve calculated from PS logging data respectively. This discrepancy, however, is due to lateral variation of Vs structure as the result of the triangular array (40m) shows and that of MASW implies. Based on the results of analysis I conclude that L-shape array can be applied to estimate Vs structure for shallow depth so it can be layout in urban areas to determine phase velocity information from surface wave in microtremor.
ACKNOWLEDGEMENT
I would like to express my sincere gratitude to Dr. Koichi Hayashi, OYO Corporation for his help during the field work.
REFERENCES
Aki, K., 1957, Bulletin of Earthquake Research Institute, 35, 415-457.
Hayashi, K., and Suzuki, H., 2004, Exploration Geophysics, 35, 7-13.
Ingber, L., 1989, Mathematical and Computer Modeling, 12, 967-973.
Ludwig, W. J. et al., 1972, The Sea, Vol. 4, Wiley-Interscience, New York, 53-84
Okada, H., 2003, The Microtremor Survey Method. Society of exploration geophysicists.
Press, W. H., et al., 2002, Numerical recipes. Cambridge University Press.
Saito, M., 1978, BUTURI- TANSA, 31, 112-135 (in Japanese with English abstract).
Shiraishi, H., et al., 2006, Geophys. Res Let, Vol. 33, L18307.
Yamanaka, H., 2004, Proc. of 13th World Conference on Earthquake Engineering, Paper 1161.
Yokoi, T., 2005, Programme and Abstract, Seismological Society of Japan Fall Meeting, B049.
Yokoi, T., and Hayashi, K., 2009, Proc. of 9th Int. WS on Seismic Microzoning and Risk Reduction, Cuernavaca, Mexico.
Friday, February 12, 2010
We observed two phases in this visit which are described below,
(ii) Aim of visit: To observe the aftermath memories of the Great Kanto Earthquake and Air Raid by US during 1923 and World War II respectively, and to learn some thing for preparing to cope with the affects caused by disaster in the future.
(iii) Targets: It was touching moment to see the tragic effects of the Great Kanto Earthquake and Air Raid during WWII (Fig. 1 & 2). As a picture speaks out, the result was so horrible that anyone could get speechless. We observe the design of planned town to lessen the disaster affects (Fig.3). We observed Memorial Hall (praying place) designed by a famous architect Dr. Chuta ITO (received the Order of Culture in 1943) and constructed by the Metropolitan Government of Tokyo in the memories of those victims. This design is a sort of mixture of Buddhist temple, church and Castle. We, also observed the near by Yasuda park where we felt little ease by the Nature.
(iv) Name of the lecturers: Dr. YOKOI Toshiaki, Ms. OMUKA Hiromi
(v) Description: Observing these memories, I think people should be given education in awareness and preparedness for the disaster calamities. Planning, design and construction are other vital things. Of course you can’t do anything with Air strikes. The design of planned city was the good model. In my country’s case earthquake awareness and preparedness program and conducting building code would be the best solution to reduce Human casualties.
2.(i) Survival Walk Practice (2nd half day): From Yokoami-Cho Park to Asakusa temple along the National Route # 6 after crossing Kuramae Ryogoku-Bashi bridge over Shumida-Gawa river. It is about six km long.
(ii) Aim of visit: To observe and be familiar with the various supporting symbolic stickers of different symbols like danger objects, water available, supporting station, signal etc., along the supporting road[2].
(iii) Targets: After crossing the Ryogoku-Bashi bridge I saw a big ware house for disaster prevention on the right hand side (Fig. 4). I also saw stickers corresponding to the danger (Fig. 5) and supporting label (Fig. 6) a shop with fire cracker and chemicals, gas station, vending machine without anchor and an advertisement boards (Fig. 8). Some old houses and tilted house were also seen.
(v) Description: It is amazing to see the idea of Supporting Road toward the reduction of Natural Calamities with various information. It is very useful for safe evacuation when the big one hit. As my country being high risk in Earthquake Hazard I can try to communicate and implement this method to some extent. Other thing I like is the gaps between two buildings and pipelines going through it (Fig. 7). May be it is to reduce fire risk from one house to another.
Finally, I would like to thank Yokoi-San and Omuka-San for their valuable guidance about this trip and of course Saito-San for being as a guardian in the whole trip.
Fig.1 aftermath photo inside museum
Fig.2 remaining outside museum
Fig.3 design of planned city
Fig.4 symbol for danger
Fig.5 supporting label
Fig.7 advertisement boards
[1] It occurred in 1923 with magnitude 7.9 and depth 20-30 km.
[2] There are 16 main roads as a supporting road.
Wednesday, July 29, 2009
Thursday, July 10, 2008
Earthquake Season in the Himalayan Front
Earthquake Season in the Himalayan Front
SAN FRANCISCO, Calif.--Scientists have long searched for what triggers earthquakes, even suggesting that tides or weather play a role. Recent research spearheaded by Jean-Philippe Avouac, professor of geology and director of the Tectonics Observatory at the California Institute of Technology, shows that in the Himalayan mountains, at least, there is indeed an earthquake season. It's winter.
For decades, geologists studying earthquakes in the Himalayan range of Nepal had noted that there were far more quakes in the winter than in the summer, but it was difficult to assign a cause. "The seasonal variation in seismicity had been noticed years ago," says Avouac. Now, over a decade of data from GPS receivers and satellite measurements of land-water storage make it possible to connect the monsoon season with the frequency of earthquakes along the Himalaya front. The analysis also provides key insight into the timescale of earthquake nucleation in the region.
Avouac will present the results of the study on December 12 at the annual meeting of the American Geophysical Union (AGU) in San Francisco. They are also available online through the journal Earth and Planetary Science Letters, and will appear in print early next year.
The world's tallest mountain range, the Himalaya continues to rise as plate tectonic activity drives India into Eurasia. The compression from this collision results in intense seismic activity along the front of the range. Stress builds continually along faults in the region, until it is released through earthquakes.
Avouac and two collaborators from France and Nepal--Laurent Bollinger and Sudhir Rajaure--began their earthquake seasonality investigation by analyzing a catalog of around 10,000 earthquakes in the Himalaya. They saw that, at all magnitudes above this detection limit, there were twice as many earthquakes during the winter months--December through February--as during the summer. That is, in winter there are up to 150 earthquakes of magnitude three per month, and in summer, around 75. For magnitude four, the winter average is 16 per month, while in summer the rate falls to eight per month. They ran the numbers through a statistical calculation and ruled out the possibility that the seasonal signal was due merely to chance.
"The signal in the seismicity is real; there is no discussion," Avouac says. "We see this seasonal cycle," he adds. "We didn't know where it came from but it is really strong. We're looking at something that is changing on a yearly basis-the timescale over which stress changes in this region is one year."
Earlier studies suggested that seasonal variations in atmospheric pressure set off earthquakes, and this had been proposed for seasonal seismicity following the 1992 Landers, California, quake.
The scientists turned to satellite measurements of water levels in the region. Using altimetry data from TOPEX/Poseidon, a satellite launched in 1992 by NASA and the French space agency CNES (Centre National d'Etudes Spatiales), they evaluated the water level in major rivers of the Ganges basin to within a few tens of centimeters. They found that the water level over the whole basin begins its four-meter rise at the onset of the monsoon season in mid-May, reaching a maximum in September, followed by a slow decrease until the next monsoon season.
They combined river level measurements with data from NASA's GRACE--Gravity Recovery and Climate Experiment--mission, which studies, among other things, groundwater storage on landmasses. The data revealed a strong signal of seasonal variation of water in the basin. Paired with the altimetry data, these measurements paint a complete picture of the hydrologic cycle in the region.
In the Himalaya, monsoon rains swell the rivers of the Ganges basin, increasing the pressure bearing down on the region. As the rains stop, the river water soaks through the ground and the built-up load eases outward, toward the front of the range. This outward redistribution of stress after the rains end leads to horizontal compression in the mountain range later in the year, triggering the wintertime earthquakes.
The final piece connecting winter earthquake frequency to season, and lending insight into the process by which earthquakes nucleate, lay in GPS data. Installation of GPS instruments across the Himalayan front began in 1994, and now they provide a decade's worth of measurements showing land movement across the region. Instead of looking at vertical motions, which are widely believed to be sensitive to weather and the same forces that cause tides on Earth, the scientists concentrated on horizontal displacements. The lengthy records, analyzed by Pierre Bettinelli during his graduate work at Caltech, show that horizontal motion is continuous in the range front. Stress constantly builds in the region. But just as water levels near their lowest in the adjacent Ganges basin and earthquakes begin their doubletime, horizontal motion reaches its maximum speed.
"We had been staring at [the seasonal signal] for years, and then the satellite data came in and we deployed the GPS network and suddenly it became crystal clear," says Avouac. "It's like something you dream of."
While many scientists have suggested that changing water levels can influence the earthquake cycle, a definitive mechanism had yet to be pinpointed. "There are two main avenues by which people have tried to understand the physics of earthquakes: Earth tides and aftershocks," says Avouac. With the water level data, he could show that the rate at which stress builds along the rangefront, rather than the absolute level of stress, triggers earthquakes.
Although Earth tides induce stress levels similar to what builds up during seasonal water storage, they only vary over a 12-hour period. The Himalayan signal shows that it is more likely that earthquakes are triggered after stress builds for weeks to months, which matches the timescale of seasonal stress variation in that region.
About other earthquake-prone regions Avouac says, "seasonal variation has been reported in other places, but I don't know any other place where it is so strong or where the cause of the signal is so obvious."
Other authors on the paper are Pierre Bettinelli, Mireille Flouzat, and Laurent Bollinger of the Commissariat a l'Énergie Atomique, France; Guillaume Ramillien of the Laboratoire d'Etudes en Géophysique et Océanographie Spatiales, France; and Sudhir Rajaure and Som Sapkota of the National Seismological Centre in Nepal.
Avouac will present details of the group's findings at AGU on Wednesday, December 12, at 2 p.m., Moscone West room 3018, in session T33F: Earthquake geology, active tectonics, and mountain building in south and east Asia.
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Contact: Elisabeth Nadin (626) 395-3631 enadin@caltech.edu
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