open house 2007 institute of industrial science...
TRANSCRIPT
Flood Today, and the Water Scarcity
on the Day After Tomorrow
Open House 2007 Institute of Industrial Science
University of Tokyo
Oki and Kanae Laboratory (Hydrology and Water Resources Engineering)
Theme3 New Observations
Oki & Kanae Lab, IIS, Univ of Tokyo
Author: Shinta SETO, Hyungjun KIM 2007
Integrated water resources model uLessons by flood disaster in 2006 uA pilot water management system
Virtual Water Trade Flood in Japan
Flood Today, and the Water Scarcity on the Day After Tomorrow
Welcome to Oki and Kanae Laboratory ! Oki and Kanae Laboratory is always seeking for better scientific
understanding of water cycle and water resources and trying to deliver it to the society. By using various tools of natural and social sciences, we are struggling with many problems on different scales from global to micro. Our laboratory consists of 31 members led by Prof. Taikan Oki and Associate Prof. Shinjiro Kanae.
Flood in Thailand
uHeat island increases torrential rainfall ? uFlood risk mapping all over Japan
nNatural and anthropogenic water cycle nOptimization of crop calendar
nJapan relies on foreign water resources nWhen you eat meat, water table decreases.
What is Hydrology?
Isotope
In a word, Hydrology is a study of terrestrial water cycle. To estimate the flux and storage amount of water is an essential problem and also an ultimate goal of hydrology. Left figure shows our latest estimate of it (Oki and Kanae, 2006, Science). It represents not only natural water cycle components such as precipitation but anthropogenic water cycle components such as irrigation water intake from river. Human impact on water cycle has been getting heavier, and it became a hot topic of hydrology.
Realtime simulations uWeather forecast to flood forecast uMonitoring rainfall from the space
Impact of climate change n4 billion people will be under water stress nHeavy snowfall and global warming
lThe fifth world best high precision H2O measurement. l“Isotope flux” can separate evaporation & transpiration.
Field observations lObservation network covering various climate and land cover types.
In Japan, river levee and dams have been well established up to today. However, only such hard measures never fully secure our life. In the world, a large number of people live along rivers without levee. Hydrologists should consider soft measures such as early flood warning system.
Theme 1 Flood Theme 2 Water Scarcity Overview of Open House 2007
Theme4 Experience Hydrology Measurement of soil temperature
A miniature of global water cycle Let’s circulate global water cycle by yourself. (for children)
You can try to make an observation tool to measure soil temperature
Thank you for your interest.
Feel free to ask questions !
According to the 4 th report of IPCC, by the end of this century, global average air temperature will increase by 6.4 degrees at most. How will global warming affect the water resources? To give more reliable answer to this question, we are developing an evaluation tool of water demand/supply.
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prediction
validation analysis
Relating Observation and Simulation
observation observation
phenomena phenomena understanding understanding
model model expression
1km 10m 100km Global
year
century
5cm
Temporal
Temporal
Spatial and temporal scale
day
hour
Portable measurem
ent
Flux Tower
Spatial Spatial
OkiKanae Lab. : Hydrology & Measurement Oki & Kanae Lab, IIS, Univ of Tokyo
Hydrology and Hydrological Cycle
How to Measurement the Hydrological Factors?
3.Evapotranspiration
Precipitation is very important hydrological factor incoming water on land surface.
Eddy covariance system at the tower measures evapotranspiration transferred by turbulence.
2. Precipitation 4. Soil moisture 5. Soil water depth
TDR installs in the soil and detects soil water content by difference electronic conductance.
#TDR(Time Domain
Reflectometry) This sensor put into the water and converts water pressure into water depth. We apply at paddy to monitor irrigation water.
Micro Rain Radar
Rain Rain Gauge Gauge
EC system
Cloud Image by Meteorological Satellites
1. Satellite
Monitoring the Terrestrial Ecosystem
LAI Albedo
Experiment Design Which
instrument useful?
Data Application How to use?
Author: Satoshi WATANABE, Jaeil CHO 2007
Through contributing a review article to SCIENCE Journal in 2006, our laboratory has represented the hydrological prospect about the water resource that is necessary for all creatures including human beings in the past, the present and the future in terms of global water circulation. It shows our interpretations about, such as, renewable freshwater resources assessed, virtual water trade, water use change in the future and impacts of climate change.
Hydrology is the science which deals with the water as a circulating resource on the earth, such as rain/snow fall, river flow, evapotranspiration, erosion and accumulation, water quality, and systems of water resources and their interactions. Furthermore, global water problems became one of the most important international tasks since United Nations Millennium Declaration in September of 2000. Considering the current situation, hydrology is in charge of not only ensuring adequate supplies of water to ecosystem and human society but also protecting societies from natural hazard. In this point of view, hydrology is the science delivering earth system science to society.
Green Water (=Invisible water flow)
Blue Water (=Visible water flow)
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Hydro-meteorological forecasting systems at the Oki/Kanae Lab. Oki & Kanae Lab., IIS, Univ. of Tokyo
The development of hydro-meteorological forecasting and warning systems is a high priority in many countries. An accurate and early warning system can help to minimize disaster damages.
At the Oki & Kanae Lab, several hydro-meteorological early warning systems are under developing on global scale, regional scale, and local scale.
Some results are now real-time available at the website: http://hydro.iis.u-tokyo.ac.jp/LIVE/ for the three systems: Today’s Earth, Today’s Japan and Today’s Indochina.
Today’s Indochina
Today’s Earth Outputs: - Global land surface hydro/energy balance
- river discharge Spatial Resolution: 1 degree (~100 km) Time: - Run every 12 hours
- Give predictions for coming 84 hours (lead time is about 3 days)
Today’s Japan Outputs: similar to Today’s Earth
Spatial Resolution: 0.1 degree (~10 km)
Time: - Run every 6 hours - Give predictions for coming 15 hours (lead time is about 10 hours)
Outputs: - Land surface hydro-energy flux - Coming soon: river discharge, river velocity, river depth, etc.
Spatial Resolution: - 72 km for the mother domain - 24 km for the inner domain
Time: - Run every 6 hours - Give predictions for coming 72 hours (lead time is about 67 hours)
Mother domain
Inner domain
JMA-GSM Japan Meteorological Agency –
Global Spectral Model
Iso-MATSIRO Isotope- Minimal Advanced
Treatments of Surface Interaction and RunOff
TRIP Total Runoff Integrating Pathways
JMA-MSM JMA – MesoScale Model
Iso-MATSIRO
TRIP
MM5-NOAH Fifth Generation Pennsylvania State
Uni/National Center for Atmospheric Research Mesoscale Model – Ncep
Oregon state uni. Air force Hydrologic Research Lab
ATRIP Advanced TRIP
NCEP-GFS National Centers for Environmental
Prediction – Global Forecast System
Author: Thanh NGO-DUC, Kei Yoshimura 2007 4
Introduction and Study Areas
Early Flood Warning System in Japan and Thailand Oki & Kanae Lab, IIS, Univ of Tokyo
Observation and Data Report System
Ping River Basin Thailand
River Length:740 km
Catchment Area:36,018 km 2
*Tributary of Chao Phraya River(162,800 km 2 )flowing to Gulf of Thailand
Study Area
* Chiang Mai one of the major cities along the river
*Damaged from flood in 2005
Ping river basin with observation stations
Kariyata and Ikarashi River Basins (Niigata)
Kariyata River
River Length:53.5 km
Catchment Area:239.8 km 2
Ikarashi River
River Length:53.5 km
Catchment Area:239.8 km 2
Study Area
*Arasawa in Niigata Prefecture in between Kariyata and Ikarashi rivers
*Damaged from flood in 2004
Shinano river basin
Flood Prediction and Legal System for flood warning
Location
Measured Data and
organization responsible
Measurement Method
Frequency of Measurement (Normal)
Frequency of Report (Normal)
Frequency of Measuremen t (Flood)
Frequency of Report (Flood)
Transmis sion Method
Chiang Mai
Rainfall (RID) Manual 1 time/day (7 a.m.)
1 time/day (7 a.m.)
1 time/day (7 a.m.)
1 time/day (7 a.m.)
Cell Phone
Water Level (RID)
AAutomatic BManual
AContinuous B 5 times/day (Every 3 hours after 6 a.m.)
A1 time day B1 time/day (Both 6 a.m.)
AAll Times BHourly
AHourly BHourly
Cell Phone
Niigata
Rainfall (JMA) Automatic Every 10 min.
Every 10 min.
Every 10 min.
Every 10 min.
Telemetry
Water Level (Niigata Prefectural Office)
Automatic Every 10 min.
Every 10 min.
Every 10 min.
Every 10 min.
Telemetry
RID: Royal Irrigation Department, Thailand; JMA: Japan Meteorological Agency
Chiang Mai *Flood prediction and warning by RID and Department of Public Disaster Prevention and Relief, Ministry of Interior. * Based on water level correlation method
Niigata *Models are not used for flood prediction. First, JMA forecasts the weather and gives flood warning based on rainfall prediction Second, Municipality issues the warning judging on whether the resident should evacuate or not.
Flood Mitigation Measures
It can be broadly classified into two categories
Hard measures representing structural methods
Soft measures representing nonstructural methods
Discussion and Conclusions
Niigata Flood, 2004 * Flooding was due to rainfall and subsequent breakdown of the dike in the river * Inundation starts at areas near the breakdown of dike * The duration between critical rainfall and inundation is very short than Chiang Mai. 0.0
1.0
2.0
3.0
4.0
5.0
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0
P67 W.L. (T6 hrs.)m
P1 W
.L.(T
hrs
.) m
0
1
2
3
4
5
6
10/0
7/20
04
11/0
7/20
04
12/0
7/20
04
13/0
7/20
04
14/0
7/20
04
m 0
10
20
30
40
50
60
70
mm/hour
Hourly Rainfall
W.L. at Arasawa Flood Alert (Rainfall)
F lood Alert (W.L.)
Critical Situation
0
20
40
60
80
100
120
140
160
180 0
1
2
3
4
5
6
7
8/12/2005
8/13/2005
8/14/2005
8/15/2005
8/16/2005
mm/day m
Daily Rainfall
W.L. at P67
W.L. at P1
Flood Alert (Rainfall)
Flood Alert (W.L.)
Critical Situation
* The liberal collaboration between concerned authorities and proper dissemination of information is quite effective in Thailand.
*The delay in Niigata was due to the absence of quantitative concrete criteria. Niigata city has developed a system in internet that provides real time information on rainfall, water level and dam.
*Flood warning is always efficient if the lead time of prediction is high so as sufficient evacuation time can be provided to residents.
*A realtime flood forecasting based on real time observation can be used even in big river basins like Chiang Mai.
Authors: KOIRALA Sujan, ARAI Yuko 2007
Observation and Data Report System
Measurement System of Ping River Basin Some pictures of measurement station in Ping river basin
Predicted Inundation Areas in Chiang Mai
Inundation Areas in Niigata
Figure: Chiang Mai Floods (Ping River)
Niigata Floods (Ikarashi River)
Water Level correlation between P1 and P67 stations in Ping River
Chiang Mai Flood, 2005 * Flooding due to heavy overnight rainfall *Inundation occurs gradually from area with low elevation to areas with high elevation *There is 6 hours difference between the exceedance of critical level and inundation.
Oki & Kanae Lab carried out a research on issues and characteristics of early flood warning system (EFWS) in Japan and Thailand and proposed improvements on them.
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Oki & Kanae Lab, IIS, Univ of Tokyo
Author: Naota HANASAKI, Dai YAMAZAKI 2007
IIS/NIES Global Integrated Water Resources Model What about subannual variation?
Global warming
Population growth
Economic growth
Change in water resources
Increase in water demand
Background
• Most of earlier global water resources assessments did not deal with subannual variation in water resources and use explicitly. •However, an extreme seasonality in both water resources and water use exists in some parts of the world. •Moreover, global warming is projected to alter future temperature, precipitation and snowmelt patterns, and consequently, influence not only the amount but also the timing of water resource availability and use. Annual. water withdrawal
Annual. water resources
Water resources assessment
Index=
Oki and Kanae, 2006
•Gridbased model •6 submodels
Soi lT emp Soi lMoist
Qs
Qsb
Evap SubSnow
Snowf
Qg
Qle Qh
SWE
Rainf
Qsm
SWnet LWnet
W W max 0.75W max
E
E pot
W
Q sb 1.5
=1.5 W . W ma x
Land surface model 1
Global river model 2
Environmental flow requirement model 3 Stress
TS: Temperature Stress WS: Water Stress
Photosynthesis
Cropping period
Daily Temp. Base Temp.
Cum
ulative Tem
p.
Necessary Temp.
DOY
Daily
Temp. Cumulative Temp.
Cropping period
18 Crop type s
•Withdrawal model 6
Crop model 4
Reservoir operation model 5
demand
Inflow Storage capacity
452 reservoirs Integrated Model
Method
Integrated Water Resources Assessment
1°×1° spatial resolution Daily temporal resolution
Meteorological Input GCM MIROC 3.2 Scenario SRES A1B Period 20012050,
3hourly Resolution 1.125°×1.125°
Land Use, Socioeconomic data • Population, GDP (SRES A1B scenario) • Industrial water demand, Domestic water demand and Irrigated area was estimated using a simple regression model • Crop type, crop calendar was estimated using an agricultural model
The Earth Simulator (Yokohama, Japan)
Population under a waterstressed condition
Estimated Water demand
Stress increase in 2050 Stress decrease in 2050
Results Two indices for assessment
Withdrawal to water resources ratio Cumulative daily withdrawal to demand ratio
Domestic
Industrial
Agricultural
2000 2025 2050
Withdraw
al [km 3 /yr]
6000
5000
4000
3000
2000
1000
0
Shiklomanov, 2000
0
50
100
150
200
250
1 2 3 4 5 6 7 8 9 10 11 12
水資源量 水需要量
0 20 40 60 80
100 120 140 160
1 2 3 4 5 6 7 8 9 10 11 12
水資源量 水需要量
[mo] [mo]
Ann. withdrawal Ann. resources
Σdaily withdrawal Σdaily demand
CWD=1.0 CWD<1.0
・Conventional Index -Withdrawal to water resources ratio (WWR):
・New Index -Cumulative daily withdrawal to demand ratio (CWD):
Basin A Basin B resources demand
resources demand
WWR is a useful index, but it can not indicate the water stress caused by a gap in the subannual distribution of water
resources and water use. Therefore, a new index CWD was devised.
Change in index (between 2010 and 2050)
A global water resources assessment under climate change
High stress in both 2010 and 2050
Low/No stress in both 2010 and 2050 Medium stress in both 2010 and 2050
In the future, How much water will be available? How much water stress does we have?
It is estimated that… Along with global warming, water resource distribution will be change Population growth and economic growth may increase water demand
Stress is increase in Asian monsoon and Sun Saharan Africa, where seasonal deviation of precipitation is large.
Population [10 6
]
10000
8000
6000
4000
2000
0
2000 2025 2050
High stress
Medium stress
Low stress
Ratio of highstressed population
Population with waterstress will increase.
River Discharge
Irrigation water demand Irrigation water supply Environmental flow requirement
Reservoir Release/Storage Evaporation/Soil moisture
Output
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Virtual Water Virtual Water ~ ~Invisible movement of water resource Invisible movement of water resource~ ~ Oki & Kanae Lab, IIS, Univ of Tokyo Water resource per person in the Middle East is very few. However, their life is Water resource per person in the Middle East is very few. However, their life is established. established. Why? Why?
Prof. Tony Allan (Univ. of London)
They depend for most food on import. Therefore, it is not necessary to use water required in order to produce food. It is like having sold oil and buying water resources.
So to speak, import of food is import of Virtual Water Virtual Water.
Advent of concept as Virtual Water Virtual Water
Virtual Water and, life of Japanese Virtual Water and, life of Japanese Import of Virtual Water Import of Virtual Water to Japan (Virtually required water) to Japan (Virtually required water)
4.6
40.6
10.5
1.3
1.8 1.0
2.4
Others:1.4
Total import amount: 64.3 billion m 3 /yr (Yield per unit in Japan given by table of demand and supply of food in 2000)
(Trade volume given by trade statistics of ministry of finance)
Japan Jordan
3300m 3 /p/yr 150m 3 /p/yr
Population:127 million
Total amount:400km 3 /yr
Population:7 million
Total amount:1km 3 /yr
RFWR (Renewable Fresh Water Resources) / person
Let’s compare water resource between Japan and Jordan・・・
1 22
10.5 10.5 tubs tubs
11.2 11.2 tubs tubs
2.9 2.9 tubs tubs
4.2 4.2 tubs tubs
0.7 0.7 tubs tubs
SanukiUdon
Kake Udon ¥ 290
341kcal
120L
Hamburger
Teriyakiburger Frenchfried R
¥ 430
911kcal
530L
2 Hamburgers Frenchfries S
¥ 268
745kcal
2020L
Medium size ¥ 280
710kcal
1890L
Soba
Tsukimi Soba ¥ 300
377kcal
750L
How many bath tubs ? How many bath tubs ?
Beef bowl
Water consumption of fast food Water consumption of fast food
Hamburger
1.1
28.9
11.9
1.6
1.5
0.6
3.3
Others:1.1
Total import amount: 53.3 billion m 3 /yr (Yield per unit in Japan given by table of demand and supply of food in 2000)
(Trade volume given by trade statistics of ministry of finance)
Maize
Soybean
Wheat
Rice
Barley
Beef
Pork
Chicken
Virtual Water balance in 2000(m Virtual Water balance in 2000(m 3 3 /p/yr) /p/yr)
The exporting country of virtual water inclines The exporting country of virtual water inclines toward some countries, such as U.S. Canada toward some countries, such as U.S. Canada
Australia. Australia.
Export Import
Virtual Water trade in 2000 Virtual Water trade in 2000 (only main grain) (only main grain)
Caribbean Caribbean
North North America America
Central Central America America
South South America America
West West Africa Africa
Oceania Oceania
East & East & South East South East Asia Asia South South
Asia Asia
USSR USSR
North West North West Africa Africa
Western Western Europe Europe
Middle Middle East East
1~5 5~10 10~15 15~20 20~30 30~50 50< Km 3 /yr
78.5
33.5
46.2
57.5 38.8
36.4
Exporting countries base, shown only over 5 km 3 /yr
By following grain trade statistics in By following grain trade statistics in detail, movement of VW in the world is revealed. detail, movement of VW in the world is revealed.
(based on statistical data of FAO and so on in 2000)
Virtual Virtual Water Water i in n the world the world
Traditional assessment of water resources Traditional assessment of water resources
RFWR per capita in 2000
Estimation from water resources statistics and so on in the world
10 10 3 3 m m 3 3 /p/yr /p/yr
Estimation from water resources statistics and so on in the world
Extreme stress (~1) High stress (1~2) Moderate stress (2~5)
10 10 3 3 m m 3 3 /p/yr /p/yr No stress (5~10) Rich water (10~)
Assessment of water resources in the world Assessment of water resources in the world considered in Virtual Water considered in Virtual Water RFWR per capita in 2000
Poor water resources is Poor water resources is covered by import of grains. covered by import of grains.
VW VW adjusted water self adjusted water self sufficiency ratio sufficiency ratio
Really required water: amount of water resources used in exporting countries (producing country) Virtually required water: amount of water resources needed if importing countries (consumer country) will produce same amount of production in own country.
Especially, a great deal of water is used for production of meat.
Above two charts reflect the trend of trade movement after 2000. (ex., Changes due to suspension of beef import from U.S. because of BSE)
Definition of Virtual Water (Oki & Definition of Virtual Water (Oki & Kanae Kanae Lab.) Lab.)
(100 million m 3 /yr)
Amount of import
Water selfsufficiency ratio is given by
domestic quantity of water intake + green water for agriculture
domestic water intake + green water for agriculture + imported VW – exported VW
Reference: AQUASTAT P.H.Gleick, Ed., Water in Crisis(Oxford Univ. Press, 1993)
Water self Water self sufficiency ratio(WR): Top 10, Major countries, Worst 10 sufficiency ratio(WR): Top 10, Major countries, Worst 10
Green water for agriculture = Rain amount x agriculture area x α
α : factor. Rate of evapotranspiration in rainfall, where rate is 7/11 based on estimation of Gleick (1993).
Only grain & animal product
Only grain & animal product
Extreme stress (~1) High stress (1~2) Moderate stress (2~5)
No stress (5~10) Rich water (10~)
2000
4 4 years later years later ・・・ ・・・ What kind of water ? What kind of water ?
It seems that Japan has abundant water resources. But, a great amount of food import means that Japan imports a great deal of Virtual Water. Water resources in the world is also important for Japan.
2004
0.93
18.9 1.0
0.43 1.5
Others: 0.45
6.1 Total: 29.5 billion m 3 /yr
Grain & animal product, 2004
Really required water is smaller than Virtually required water, because Really required water is estimated by producer base.
0.001
1.1
0.12
0.055
0.067
Others:0.017
Total:1.5 billion m 3 /yr 0.13
Irrigation water (river + reservoir + fossil water)
Canada:Almost green water Import of VW in each origin
Green water is very large.
Import of Virtual Water Import of Virtual Water to Japan to Japan (Really required water) (Really required water)
Wheat 53 Beef 51 Pork 4.6 Chicken 12
Barley 4.9 Maize 106 Rice 8.3 Soybean 57
Green water River Reservoir Fossil water
Author: Toshiyuki INUZUKA, Yadu POKHREL, Masashi KIGUCHI, Dai YAMAZAKI 2007
2004 Unit: billion m3/yr
about 5 % about 5 %
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
Kazakhstan
Ireland
Australia
Argentin
a Denmark
Urugu
ay
Canada
Paragu
ay
France
Thailand
U.S.A.
India
Brazil
Germany
China
Japan
Korea
Israel
Malta
Cyprus
Algeria
Kuw
ait
Jordan
U.A.E.
Cape Verde
Djib
outi
Sing
apore
0.8
no data
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Profile of Oki and Kanae Laboratory Oki & Kanae Lab., IIS, Univ. of Tokyo
Address 1538505 Be607, IIS, 461, Komaba, Meguroku, Tokyo, JAPAN Phone : 0354526382 Fax : 0354526383 Email : [email protected]tokyo.ac.jp Web Page:http://hydro.iis.utokyo.ac.jp/
Professors
Professor Taikan OKI Research Topics ・Global Water Resources Assessment Considering Anthropogenic Activities ・Analysis of global water cycle by using stable isotope measurement and remote sensing ・Integrated River and Water Resources Management in Japan, Asia, and the world
CV 1987.3 Bachelor of Engineering (University of Tokyo) 1989.3 Master of Engineering (University of Tokyo) 1989.9 Research Associate (IIS, University of Tokyo) 1995.5 Assistant Professor (IIS, University of Tokyo) 1995.10 JSPS Oversea Researcher (NASA/GSFC) 1997.10 Associate Professor(IIS, University of Tokyo) 2002.4 Associate Professor(Research Institute of Humanity and Nature, also at IIS, University of Tokyo) 2003.12 Associate Professor(IIS, University of Tokyo) 2006.11 Professor(IIS, University of Tokyo)
Ph.D. Thesis 水文・水資源予測のための大気水循環過程に関する研究 (1993.9)
Research Topics ・LandAtmosphere Interaction and Global Water Cycle Model
・Future Perspective of Water Cycle and Society in Monsoon Asia
・Climate Change and its Impact on Flood and Drought
CV 1994.3 Bachelor of Engineering (University of Tokyo) 1996.3 Master of Engineering (University of Tokyo) 1999.3 Doctor of Engineering (University of Tokyo) 1999.4 JSPS PostDoctoral Research Fellow 1999.5 Research Associate (IIS, University of Tokyo) 2003.3 Assistant Professor (IIS, University of Tokyo) 2003.11 Associate Professor (IIS, University of Tokyo) 2003.12 Associate Professor (Research Institute of Humanity and Nature, also at IIS, University of Tokyo) 2007.4 Associate Professor (IIS, University of Tokyo)
Ph.D. Thesis Land surface hydrological processes and the variations of water resources in regional climate systems (1999.3)
(Publication and Award lists can be found in our web page)
Other Members
(Staff)
Assistant Professor
Kei YOSHIMURA Technical Associate
Masahiro KOIKE
8
Associate Professor Shinjiro KANAE
Secretaries 2
Research Fellow 10
(Students)
Doctor Course 4
Master Course 10
Undergraduate 1
(As of May 2007) Access