1. 1/14
Development of the System for Early
Adaptation to Climate Change in Mongolia
Akihiro OBA1), Wanglin YAN1), Balt SUVDANTSETSEG2),
Masataka WATANABE1), Chuluun TOGTOKH2),
Bolar-Erdane LKHAMSUREN3)
1)Keio
University, Japan
2)National University of Mongolia, Mongolia
3)Kangwon National University, Korea
2. 2/14
Introduction
Met.
Res.
Con.
Livestock Dynamics and Early Adaptation
Extremely Increased Mortality
by Extreme Weather(Zud)
Decision-making from
adaptation options in
each county(Sum)
Early Adaptation
Our Goal
CAP
year
Overgrazing
2010
2000
Economic Liberalization
1990
1980
1970
1960
(Altanbagana and Chuluun, 2010)
10
4,500 thou. heads
4,000
3,500
3,000
2,500
2,000
ex. selling animals
before market
season
Return to Carrying
Capacity and
Stable Grazing
3. 3/14
Introduction
Met.
Res.
Con.
Scientific Data Did Not Put to Practical Use for Zud
Meteorological Data /
Vegetation Data
Statistical Data
LEWS
<http://glews.tamu.edu/Mongolia>
Year Book
National Atlas
Drought Warning Map
Remote Sensing Data
Drought Map
Landsat Data in Mongolia
These information don’t
reach to local people: Gap
GIS Data
http://goo.gl/bdwJy
Unsolved Zud Problem, in 2010
Objective
To show a framework of early adaptation to zud through web based adaptation support
system for herders and mayors
4. 4/14
Intro.
Method
Res.
Con.
Framework: How to Use Scientific Data for Adaptation Practice
Zud
Organizing
Stakeholders
Interview about Current
Action after Zud and
Communication Method
Sort-out of Adaptation
Policy in Each Sum
③System Development
②Field Interview
System Design /
Development of Interface
Evaluation Gap between
Data Needs and Current
Monitoring Data
Early Adaptation
before Zud
Interview about Needs of
Data & Support System
from Herders & Mayors
User Test and
Implementation
④Interview to Central Government
Practice of Adaptation
Policy by Mayors and
Herders
Integrated Database from Existing Databases
Recommended Adaptation Policies with Data
①Database
5. ①Database
5/14
Intro.
Method
Result
Con.
Development of Database and Evaluate Accuracy
Development of Spatial Database
Vegetation, Weather
Statistics
Integrate
GIS
New Database
RS
Exisitng Databases (Data Souces)
Developed Databases (Data Souces)
Evaluation of Database Accuracy
Result of Nonparametric Analysis of Variance (Kruskal-Wallis): No Difference (p < 0.05)
)
1
PostGIS
Analyzed
Colored Area
Existing Zud Index by Authors Data2)
1)Angerer
Zud Index by Developed Database
J, Sean G, Doug T (2009) Technology Transfer Part I: Implementation of the Livestock Early Warning System in Mongolia. Global Livestock CRSP, Research
Brief 09-01-GOBI, Univ. of California-Davis.
2)Chuluun T, Altanbagana M, Tserenchunt B (2011) Land degradation and desertification in Mongolia. Background paper for the Mongolia Human Development Report 2011.
6. 6/10
②Field Interview
Intro.
Met.
Result
Con.
Field Interview to Herders and Mayors
Steppe Zone
Forest Steppe Zone
Gobi Zone
Date: 9/18 – 9/30, 2012
Survey: Interview to Herders, Mayors
Area: 12 Sums, 3 Aimags
(5 landscape zones)
Interview to Herders Interview to Mayors
7. 7
7/14
②Field Interview
Intro.
Met.
Result
Con.
Q. What information do you need for adaptation to zud?(Open Discussion)
2%
Omnogobi 0%
Gobi- Altai
0%
0% Tuv
0%
0%
13% 0%
2%
0%
4%
0%
18%
0%
22%
Nothing in particular
44%
74% 17%
87%
11%
1% Total
1% 6%
6%
Mining points within
or around Sum
News that relates Zud
Rangeland that is warm or has
no snow during winter
15%
6%
3%
Weather Information
Market Price
68%
Information that relates
government
A. Weather Info, Zud Info, Market Price of Each Market, Non-Snowed Area(Herders)
On the top of above, detail information with map(Mayors)
→This information is already provided by government and academic institution.
However, they had not reached to local people. Thus, sending system is needed for them.
8. 8
8/14
②Field Interview
Intro.
Met.
Result
Con.
Q.Who is the first for you to ask for help? Relatives? Neighbors? Or community?
(Gobi-Altai:N=48, Omnogobi: N=18, Tuv:N=8)
6%
Govi- Altai
4%
6%
Omnogobi
0%
5%
Tuv
0%
0%
0%
20%
70%
100
%
89%
5% 3%
78%
Total
14%
Community groups
Family or relatives
No advices
Sum government
→Current communication level among herders becomes not strong.
Adaptation information should be sent to each herder directly.
9. 9/14
②Field Interview
Intro.
Met.
Result
Con.
Q. How will you do in next zud if it can practice early adaptation to zud?
Omnogobi
Tuv
4% Gobi- Altai 11%
9%
7%
0%
11%
22%
0%
28%
25%
6%
54%
37%
25%
44%
4%
6%
4%
0%
Early sales or kills
Total
17%
Move to other
rangeland
Keep or buy pastures
for winter
No idea
26%
40%
Buy livestock animals
7%
Other
A. Early Sales or Kills, Keep Forage, Move to Other Rangeland
→Adaptation policies are listed by based on local knowledge.
13%
10. 10/14
③System Development
Intro.
Met.
Result
Con.
Framework for Adaptation to Zud
Data Flow for Herders and Mayors
Text Based Information
・Recommended Adaptation Policy
by Based on Last Zud Damage
・Market Information
・Non-Snowed Information by
Using Local Location Name
Map Based Information
Attributes
Mobile Phone
Herders
Server in Mobile Company
PostgreSQL
(Database)
PC/Smart
Phone
Sum Mayors
11. 11/14
③System Development
Intro.
Met.
Result
Con.
Developing Interface for Mayors
①Zud Information with Basic
Information of each Sum
③Sum’s Location with GIS Data
②Detail Information
④Visualized Estimation
of Vulnerability
⑤Recommended
Adaptation Plans
Interface: Flash, Map Interface: Google Maps
12. 12/14
③System Development
Developing Interface for Herders
Interface: Email
Weekly Weather Information
Recommended Adaptation Policy
by Based on Last Zud Damage
Market Information
Non-Snowed Information by
Using Local Location Name
13. 13/14
Evaluation by Central Government
• System Evaluation
-Of course quite important. After test, we’d like to consider to
introduce for whole country
• Current method to send information to local herders and mayors
-Local TV and Radio, Traditional Communication Method
• Whole framework for zud as a country scale
-Alert by Central Government, and Emergency Savings for Hazards
• Current responsibility, insurance in zud information
-Nothing
Date: 1/22 – 1/23, 2013
Survey: Interview to Directors of Ministry of Food and
Security, Green Development, Advisor to President
14. 14/14
Intro.
Met.
Result
Conclusion
Conclusion
This study achieved Gaps between preparedness and
awareness in government and herders. We developed
WebGIS based system for zud adaptation to fit these gaps.
○Herders and mayors mainly need any kinds of zud
information, weather information, market information, and
migrate-able area to prevent from zud.
○Mayors and herders exchange their information by using
mobile phone. However, their local communication became
weak nowadays. It needs to send info directly to people.
This study shows a framework for adaptation to zud.
○Framework of the system becomes 2 steps: detail
information with map by based on web system for
mayors, and text based simple info on cell-phone system for
herders.
Next Step
15. Thank you for attention!
Contact
• Mail: perry@sfc.keio.ac.jp
• Adress: Keio University Z203, Yanlab, Endo 5322, Fujisawa, Kanagawa, Japan
• Tel:+81-466-49-2227
• Fax:+81-466-49-2228
Editor's Notes
And I talk about the system architecture for visualizing vulnerability.This system is mainly consist of 3 parts, data storage, data input and mapping interface.GIS data that means vector data and raster data is from some data sources.So these data is managed by server manager, in this case, it’s me.But also users can some location data for example, photo and condition data in the field workby using google maps interface.These data are inputted to PostgreSQL database through CGI,.The data inputted by users are sending to mapping interface through database language in this case XML, and vector and raster data were through mapserver CGI.Users can view these data by overlay, and also can download these data.Almost all data storage system and data input system were already existing our study, so I have to devise data and mapping interface.
And I talk about the system architecture for visualizing vulnerability.This system is mainly consist of 3 parts, data storage, data input and mapping interface.GIS data that means vector data and raster data is from some data sources.So these data is managed by server manager, in this case, it’s me.But also users can some location data for example, photo and condition data in the field workby using google maps interface.These data are inputted to PostgreSQL database through CGI,.The data inputted by users are sending to mapping interface through database language in this case XML, and vector and raster data were through mapserver CGI.Users can view these data by overlay, and also can download these data.Almost all data storage system and data input system were already existing our study, so I have to devise data and mapping interface.
And I talk about the system architecture for visualizing vulnerability.This system is mainly consist of 3 parts, data storage, data input and mapping interface.GIS data that means vector data and raster data is from some data sources.So these data is managed by server manager, in this case, it’s me.But also users can some location data for example, photo and condition data in the field workby using google maps interface.These data are inputted to PostgreSQL database through CGI,.The data inputted by users are sending to mapping interface through database language in this case XML, and vector and raster data were through mapserver CGI.Users can view these data by overlay, and also can download these data.Almost all data storage system and data input system were already existing our study, so I have to devise data and mapping interface.