6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland

1. Global Environmental Risk and its Governance Consilience Mode
PEIJUN, Shi; XIAOBIN, Hu; MING, Wang; TAO, Ye; XU, Yang
State Key Laboratory of Earth Surface Processes and Resource Ecology
Key Laboratory of Environmental Change and Natural Disasters of Ministry of Education
Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs and Ministry of
Education
Beijing Normal University
China
spj@bnu.edu.cn
29-08-2016
International Disaster and Risk Conference Davos 2016,Integrative Risk Management - towards resilient cities
28 August - 1 September 2016 • Davos • Switzerland
Session 06: Governance Challenges and Emerging Risks Room: Schwarzhorn
1:30pm-3:00pm 29 August 2016

2. Global Environmental Risk
Impacts of Climatic Trend, Fluctuation and Climate
Extremeson Rice Yield:
An Agro-meteorological Experimental Station Scale Research on early
paddy rice in Wuling, Changde, Hunan Province, China
Integrated Risk Governance Consilience Mode

3. IPCC AR5 (IPCC, 2014)

4. IPCC AR5 (IPCC, 2014)

5. Rosenzweig et al. PNAS, 2014) 。

6. (Hallegatte et al. Nature climate change. 2013) 。
RCPs

7. (Burke et al. Nature, 2015) 。
(RCP8.5, SSP5)

8. Oki, et. al, 2002, IHE-UNESCO (Based on Statistics from FAO etc., for 2000)
CaribbeanCaribbean
NorthNorth
AmericaAmerica
CentralCentral
AmericaAmerica
 SouthSouth
AmericaAmerica
WestWest
AfricAfric
aa
OceaniaOceania
East &East &
South East AsiaSouth East Asia
SoutSout
hh
AsiaAsia
USSRUSSR
North WestNorth West
AfricaAfrica
WesternWestern
EuropeEurope
MiddlMiddl
ee
EastEast
1~5 5~10 10~15 15~20 20~30 30~50 50<
Importer based, over 5 km3
/y
km3
/y
78.
5
33.
5
46.
2
57.
5
38.
8
36.
4
Economic Globalization: Virtual Water Flows(Cereals only)

9. (John Moore etal.,2012,PNAS)
Frequency of Typhoon in China(1949-2010 ）

10. 气溶胶对云和降水
的长期气候效应
李占清
北京师范大学

11. Temperature Changes in BeijingTemperature Changes in Beijing
Extreme high temperature events
（ daily maximum temperature
>34.5 days℃ ）
1 ～ 7
8 ～ 14
15 ～ 21
22 ～ 28
Air temperature change and extreme high
temperature events frequency of Beijingtemperature( )℃
year
Tendency value ： 0.41 /10a (mean value 12.2 )℃ ℃
Fluctuation value ： -0.05 /10a (mean value 0.45 )℃ ℃
Events frequency value ： 0.5 times/10a (mean value 9.6 times)

12. Extreme precipitation events
（ daily precipitation >50mm days ）
1 ～ 2
3 ～ 4
5 ～ 6
Air temperature change and extreme
precipitation events frequency of Beijing
Precipitation (mm)
year
Tendency value ： -44mm/10a (mean value 590mm)
Fluctuation value ： -26mm/10a (mean value 154mm)
Events frequency value ： -0.3 times/10a (mean value 2 times)
Precipitation Changes in BeijingPrecipitation Changes in Beijing

13. 环境变量
时间
环境变量
时间
环境变量
时间
环境变量
时间
环境变量
时间
环境变量
时间
环境变量
时间
环境变量
时间
环境变量
时间
Climate Change Risks
tendency & Fluctuation

14. This article focus on the essence of climate change,
and presents that the climate change risk (CCR) is
actually the sum total of negative effects of human
sustainable development, which is caused by extreme
events, fluctuation , tendency of climate elements in
particular period and region, in other words, extreme
risk (ER), fluctuation Risk (FR) and tendency Risk
(TR), that is, CCR=ER+FR+TR.
Climate Change Risk

15. 15
Decade Precipitation in ChinaDecade Precipitation in China （（ 1961-20101961-2010 ））

17. 无雨日 连续无雨日 极端降水频次 极端降水强度
Chen et al. Int. J. Climatol.

18. ↓
↓
↓
↑
↑
碳通量
NPP
异养呼吸
火灾损失碳
径流
Liu et al. Environmental Monitoring and Assessment 2014.

19. RCP8.5 和 SSP3 情景下，近期 (2030 ～
2050 年 ) 和远期 (2080 ～ 2100 年 ) 世界人
口热害风险分布图
Dong et al. Climatic Change, 2015.
已取得的相 成果关 —世界人口 害 分布热 风险 图 (0.5°×0.5°)

20.  Sun et al. A statistical downscaling scheme to improve global precipitation forecasting.
Meteorol. Atmos. Phys. 2012.
 Li et al. The return period analysis of natural disasters with statistical modeling of bivariate joint probability
distribution. Risk analysis 2012.
 Zhou et al. Nonstrady state carbon sequestration in forest ecosystems of China estimated by data assimilation. J.
Geophys. Res. 2013.
 Chen et al. Projection and uncertainty analysis of global precipitation-related extremes using CMIP5 models. Int.
J. Climatol. 2014.
 Wu et al. Benchmark wealth capital stock estimations across China's 344 prefectures: 1978 to 2012. China
Economic Review 2014.
 Liu et al. Quantifying the effect of trend, fluctuation, and extreme event of climate change on ecosystem
productivity. Environmental Monitoring and Assessment 2014.
 Tang et al. Extreme summer weather in northern mid-latitudes linked to a vanishing cryosphere. Nature Climate
Change 2014.
 Zhang et al. Runoff sensitivity to global mean temperature change in the CMIP5 Models. Geophysical Research
Letters 2014.
 Bai et al. Realizing China‘ urban dream. Nature 2014.
 Dong et al. New climate and socio-economic scenarios for assessing global human health challenges due to heat
risk. Climatic Change, 2015.
 Yin et al. Risk and contributing factors of ecosystem shifts under climate change in China. Scientific Reports 2016.
 Shi et al. Mapping and ranking global mortality, affected population and GDP loss risks for multiple climatic
hazards. Journal of Geographical Science 2016.
 Shi et al. Mapping Global Mortality and Affected Population Risks for Multiple Natural Hazards. International
Journal of Disaster Risk Science 2016.

21. Global Environmental Risk
Impacts of Climatic Trend, Fluctuation and Climate
Extremeson Rice Yield:
An Agro-meteorological Experimental Station Scale Research on early
paddy rice in Wuling, Changde, Hunan Province, China
Integrated Risk Governance Consilience Mode

22. Observed globally averaged combined land and ocean
Surface temperature anomaly 1985-2012. (Source ： IPCC,
2013)
Observed global mean combined land and ocean
surface temperature anomalies, from 1850 to
2012 from three data sets. Top panel: annual
mean values. Bottom panel: decadal mean values
including the estimate of uncertainty for one
dataset (black). Anomalies are relative to the
mean of 1961−1990.
Impacts of climate change on the yield of paddy
rice in Asia (Source ： CESS, 2010)
Impacts of high temperature event on rice
(Source ： http://www.xn121.com)

23. The research area
Name Wuling
Station ID 57662
Latitude 29°03′N
Longitude 111°41′E
Altitude 35m

24. Items Index/Information Description Sources
Meteorologic
al data
Air temperature, precipitation, solar
radiation (calculated by the
Angstrom –Prescott equation based
on the daily sunshine hours)
Climatological
stations, daily scale,
1981-2012
China Meteorological
Data Website
(http://data.cma.cn/).
Soil data
Bulk density, organic carbon, total
nitrogen, pH value and so
on( Based on data of the office for
the Second National Soil Survey of
China
raster scale (1:1
million),
1995
Harmonized World
Soil Database
(Version 1.2)
Field
agricultural
experimental
data
Rice physiological data,
management
Practices, rice yields and so on
Agro-meteorological
Experimental
station
1981-2012
China Meteorological
Administration
Genetic
coefficients
Thermal time in the basic vegetative
phase of the plant, Grain filling
duration, single grain weight and so
on
Some of
coefficients
Are culculated
based on their
definition
China Meteorological
Administration
The Research database

25. Calibration, validation, and evaluation of Ceres-Rice crop model
Period Rice cultivar Rice cropping system Calibrated years Validated years
1981-1989 Guangluai4 mid maturation 1984 1981, 1983
1990-1999 Zhefu7 mid maturation 1992 1993, 1999
2000-2012 Xiangzaoxian31 mid maturation 2004 2005, 2006, 2007
Information for each selected rice variety
Model performance evaluation
Predicted deviation (PD):
Normalized root mean square error (NRMSE):
:Predicted value
:Observed value
:Observed mean value
:Sample size
:Year code(i=1981, 1982……2012)

26. Criterion of climate extremes
Type Criterion Reference
Daily max
temperature>35℃
Temperature index of high
temperature harm for main
crop (GB/T 21985-2008)
Vegetative phase: Daily min
temperature <12 ;℃
Reproductive phase: Daily
min temperature <20 ;℃
Low temperature disaster of
southern rice, rapeseed and
orange (GB/T 27959-2011)
Daily precipitation >50mm
Classification criterion of
precipitation intensity
(inland part), (China
Meteorological
Administration, 2008)
Spring season: continuous
no rain days>10;
Summer season:
continuous no rain days>5;
Standard of classification
for drought severity
(SL424-2008)
High temperature event
Low temperature event
Heavy rainfall event
Drought event

27. ession of climatic trend
Diagram of climatic trend change for the
temperature of early paddy rice planting stage
in Wuling station, Changde during 1981-2012
Statistics per each
grow stage
Butterworth filter and
trend significance test
Construction of trend
value scenario and mean
value scenario

28. erstanding climatic fluctuation
Diagram of “fluctuation threshold” for the
temperature of early paddy rice planting stage
in Wuling station, Changde during 1981-2012
Statistics per each
grow stage
Butterworth filter and
standard deviation
calculation
Construction scenario
that surpass the
“fluctuation threshold”

29. Model Performance
Coefficients
Definitions
Guangluai4
Zhefu7 Xiangzaoxian31
P1
The growing degree-days during
vegetative phase 334.000 459.700 495.500
P2R
The extent of delay in panicle
initiation 46.340 44.890 68.800
P5
The growing degree-days from
beginning of grain filling to
physiological maturity
362.200 311.800 367.300
P2O
Critical photoperiod at which the
development occurs at a maximum
rate
10.470 12.980 12.410
G1
Potential spikelet number
coefficient 79.870 74.780 69.390
G2 Single grain weight 0.027 0.030 0.021
G3 Tillering coefficient 0.792 0.310 0.814
G4 Temperature tolerance coefficient 1.187 1.018 1.227
coefficients values for each rice variety

30. Model Performance
Year Variety
Flowering
duration
Maturing
duration
Yield
1981 Guangluai4 -3.57% 0.93%
-
3.58%
1983 Guangluai4 11.25% 12.50%
-
3.12%
1984 Guangluai4 -2.44% 2.88% 1.57%
1992 Zhefu7 5.48% 2.97% 2.99%
1993 Zhefu7 5.56% 8.60%
-
5.53%
1999 Zhefu7 -11.90% 0.00%
-
2.43%
2004 Xiangzaoxian31 2.53% 10.00%
-
5.85%
2005 Xiangzaoxian31 2.53% 4.81% 2.40%
2006 Xiangzaoxian31 3.85% 10.10% 0.07%
2007 Xiangzaoxian31 6.41% 11.11%
-
2.44%
dicted deviation results
Simulated yield and Observed
yield of early paddy rice
in Wuling station, Changde during
1981-2012

31. acts of climate extremes
Ratio of reduced yield for each kind of climate extremes

32. pacts of climatic trend
Climatic factors
Ratio of effected
yield
Temperature -4.80%
Precipitation -0.51%
Solar radiation 0.93%Temperature
Precipitation
Solar radiation
Ratio of effected yield of climatic
trend for each kind of climatic factors

33. cts of climatic fluctuation
Climatic
factors
Ratio of reduced yield
Temperature -5.11%
Precipitation -1.06%
Solar radiation -1.08%
Ratio of reduced yield of climatic
fluctuation for each kind of climatic
factors
Temperature Precipitation
Solar radiation

34. Ratio of impacts by climatic trend,
fluctuation and climate extremes on early
paddy rice yield in Wuling station, Changde,
Hunan Province, China
1 Climate change can be divided
into three parts: climatic trend,
climatic fluctuation and climate
extremes. The influence of climatic
trend can be “ trade-off ” .
Moreover, the key point of climatic
fluctuation research is to find
“fluctuation threshold”.
2 Temperature is the most important
climatic factors which will bring
negative impacts on early rice yield.
Moreover, climatic trend is ranked
first which will bring negative
influence on early paddy rice yield
in Wuling station.
1 、 How to improve the simulation accuracy ？
2 、 How to consider the influence of human activities on the rice yield ？

35. Global Environmental Risk
Impacts of Climatic Trend, Fluctuation and Climate
Extremeson Rice Yield:
An Agro-meteorological Experimental Station Scale Research on early
paddy rice in Wuling, Changde, Hunan Province, China
Integrated Risk Governance Consilience Mode

36. Consilience Model for Integrated DS Governance

37. 社会—生态系统风险防范的“凝聚力模型
Consilience model for integrated social-ecosystem risk governance
h
b
构件间无摩擦情况： 极限荷载 ∝ W=bX2h3/6
构件间协同工作情况： 极限荷载 ∝ W=bX(2h)3/6
如果n个构件协同工作，极限荷载增加n2倍。
同放大原理示意协 图
Collaborative amplification
假定，单根无缺陷承载力为100，有缺陷为50，那么，
系统A的极限承载力为50X4=200；
系统B的极限承载力至少100X3=300。
①
②
③
④
系统A 系统B
同分散原理示意协 图
Collaborative diversification
同 束原理示意协 约 图
Collaborative constraint
协同宽容原理示意图
Collaborative tolerance
工程中， 了使 制 索为 钢 绳
足大 形、抗冲 和易成卷满 变 击
扎等需求，多股 以一定捆 钢丝
的 合成 ，规则绞 钢绞线 钢绞线
的力学原理体 了本文所述现
的“ 同 容”协 宽 内涵。
具体表 在：（一）所有现
遵循 一原 行 合，钢丝 统 则进 绞
体 的 容；现对规则 宽 （二）在
容的前提下，整体对规则宽 钢
形成 大 形和冲 荷绞线 对 变 击
更高载 的 容性；（三）宽 钢绞
有 根 所不具 的线拥 单 钢丝 备
良好的工作性能， 大提升其极
包装、 、 用方面的 容运输 应 宽
性。

38. (1) collaborative amplification schematic
工程中，常常通 合 的结构 过组 结构 同性协 设计实现结构
性能的 化。 根的 支梁优 单 简 的抗弯性能与 W=bh
3
/6成正比。
当 根梁之 没有任何 同性（无摩擦） ， 限抗弯性能两 间 协 时 极
与 W=2bh
3
/6成正比；当 根梁之 存在 同性（完全 接）两 间 协 连
， 限抗弯性能与时 极 W=b( 2h)
3
/6成正比。当 n根梁 同 ，协 时
其性能提升为 n
2
倍，不是 的简单 n 倍。
同放大的原理体 在：（一）子系 因协 现 统间 为 同性的协
存在，使得系 整体抵抗能提升， 提升超 了因 子系统 这种 过 为
数目的增加 来的 增量，而是形成了 外的放大效统 带 简单 额
能；（二） 同放大的 需要通 子系 的 同性协 实现 过 统间 协 设计
来完成。
协同放大原理示意图
Collaborative amplification schematic
Emphasized by
cooperative operation
system, making the
system enhanced
resistance to external
shock, and a "1 +1> 2"
effect.
Principal of Consilience Model

39. (2) collaborative diversification schematic
在系统 A中，子系 的缺陷统 （黑色点表示） 来的破坏带
会造成整根 索的断裂绳 ，荷 行重新分配载进 而引 “ 灾害 ”发 链
的传递会使整个系 崩 。统 溃 系统 B中的子系统 同受力，协 有
效分散系 中存在的随机缺陷。假 每个 索在无缺陷 的统 设 绳 时
承 力载 为 100，有缺陷 的承 力时 载 为 50，那么系统 A的 限极
承 力载 为 200，而系统 B的 限承 力在极 载 300至 450之间。
同分散的原理体 在：（一）通 子系 的 同，协 现 过 统间 协
原本存在于系 中地随机 （缺陷）得以降低，从而提升统 风险
整体系 的抵抗能力；（二）子系 中的 在 同后的系统 统 风险 协
中得以分散，系 作 整体分 了子系 中的 ，统 统 为 摊 统 风险 这种
分散的效果取决于系 同性的统协 设计。
协同分散原理示意图
Collaborative diversification
schematic
假定，单根无缺陷承载力为100，有缺陷为50，那么，
系统A的极限承载力为50X4=200；
系统B的极限承载力至少100X3=300。
①
②
③
④
系统A 系统B
Emphasized by cooperative
operation system, making the
system as a whole after a
collaboration, originally faced the
risk of various subsystems in front
of the whole can be effectively
dispersed, so that the overall risk
reduction. The purpose is to make
coordinated distributed systems
minimize overall risk.
cipal of Consilience Model

40. (3) collaborative constraint schematic
由广 胡克定律可知，义 z 方
向的 不 取决于应变 仅 z 方向的应
力，x 和 y 方向的 力同 会在应 样 z
方向 生作用产 。如果在 x 和 y 方
向 行一定 束，将可提升进 约 z 方
向抵抗荷 的能力。在 工程载 结构
中， 一原理广 使用。例如，这 为
混凝土柱体往往在水平面上的设
置箍筋， 水平面内的形 行对 变进
束，从而 大提升了柱体 向约 极 竖
的荷 承 能力。载 载
同 束的原 理体 在：协 约 现
（一）不同 度或 件上的一定纬 构
束会促 系 整体抵抗能力的约 进 统
提升；（二） 束可能会降低局部约
性能或自由度，但在一定范 内围
对整体有利。
协同约束原理示意图
Collaborative constraint schematic
Emphasized by cooperative operation
system, while some subsystems
resource constraints, capital and
behavior, so that the overall ability to
resist risks of system enhancements.
Although the content is often
constrained specific financial, capital,
etc., but the premise is that each
subsystem or constraint actors
awareness and acceptance of the
implementation constraints.
cipal of Consilience Model

41. (4) Collaborative tolerance schematic
工程中， 了使 制 索为 钢 绳
足大 形、抗冲 和易成卷满 变 击
扎等需求，多股 以一定捆 钢丝
的 合成 ，规则绞 钢绞线 钢绞线
的力学原理体 了本文所述现
的“ 同 容”协 宽 内涵。
具体表 在：（一）所有现
遵循 一原 行 合，钢丝 统 则进 绞
体 的 容；现对规则 宽 （二）在
容的前提下，整体对规则宽 钢
形成 大 形和冲 荷绞线 对 变 击
更高载 的 容性；（三）宽 钢绞
有 根 所不具 的线拥 单 钢丝 备
良好的工作性能， 大提升其极
包装、 、 用方面的 容运输 应 宽
性。
协同宽容原理示意图
Collaborative tolerance
schematic
Emphasizes the system through
collaborative operation, the formation
of a unified system of general
consensus, a consensus forming
speed is good or bad? Respond
whether effective? Whether the
possible resources are used wisely?
Determine the risk prevention
measures for the implementation of
specific policies and the efficiency and
effectiveness.
cipal of Consilience Model

42. 相互救助模式下，各类网络模型的系统抗打
击能力
（左：各类网络模型的抗打击能力；右：凝
聚力网络模型提高系统抗打击能力的程度 )
Under the mutual aid mode, various
network model system anti-strike capability
(Left: various network model anti-strike
capability; Right: consilience network model
to improve the degree of anti-strike
capability system)
相互替代模式下，各类网络模型的系统
抗打击能力
（左： 各类网络模型的抗打击能力；右
：凝聚力网络模型提高系统抗打击能力
的程度 )
Under the mutual aid mode, various
network model systemanti-strike
capability (Left: various network model
anti-strike capability; Right: Consilience
network model to improve the degree of
anti-strike capability system)

43. 相互救助模式下，凝聚力优化设计对提
高
系统抗打击能力的影响
（左：受打击后网络结点的总体功能水
平
；右：总体功能水平的相对提升高程度 )
Under the mutual aid mode,
consilience system optimization
design to improve the impact of anti-
strike capability (Left: network node
after being hit by the overall level of
functioning; right: to enhance the
overall function of the relative level of
a high level)
相互替代模式下，凝聚力优化设计对提
高系统抗打击能力的影响（左：受打击
后网络结点的总体功能水平；右：总体
功能水平的相对提升高程度 )
Under the each alternative mode, the
consilience of the system optimization
design to improve the impact of anti-
strike capability (Left: network node
after being hit by the overall level of
functioning; right: to enhance the
overall function of the relative level of a
high level)

44. 社会 - 生态系统综合风险防范的凝聚力模式
Consilience mode of integrated risk governance for social – ecological systems

45. References
Peijun Shi, Wei Xu, Tao Ye, Chunyang He, Ning Li. Developing Disaster Risk Science——Discussion on the
Disaster Reduction Implementation Science. Journal of Natural Disaster Science, 2011,32(2): 79-88.
Peijun Shi, Jiabing Shuai, Wenfang Chen, Lili Lu. Study on Large-Scale Disaster Risk Assessment and Risk
Transfer Models. International Journal of Disaster Risk Science, 2010,1(2): 1-8.
Peijun Shi. On the role of government in integrated disaster risk governance— Based on practices in
China. International Journal of Disaster Risk Science, 3(3)(2012):139-146
Peijun Shi, Ning Li, Qian Ye, Wenjie Dong, Guoyi Han, and Weihua Fang. Research on Integrated Disaster
Risk Governance in the Context of Global Environmental Change. International Journal of Disaster Risk
Science, 2010,1(1): 17-23.
Pjun Shi, Qian Ye, Guoyi Han et al. Living with global climate diversity— suggestions on international
governance for coping with climate change risk.. International Journal of Disaster Risk Science, 3(4)
(2012):177-183.
SHI Peijun, SUN Shao, WANG Ming, LI Ning, WANG Jing’ai, JIN Yunyun, GU Xiaotian & YIN Weixia,
Climate change regionalization in China （ 1961–2010 ） , SCIENCE IN CHINA SERIES D-EARTH
SCIENCES 2014, January 2014 Vol.57 No.1: 1–14 doi: 10.1007/s11430-014-4889-1
SHI Peijun, YANG Xu, FANG Jiayi, WANG Jing’ai, XU Wei, HAN Guoyi ， Mapping and ranking global
mortality, affected population and GDP loss risks for multiple climatic hazards ， Journal of Geographical
Sciences ， July 2016 ， Vol.26, No.7, July 2016
Bai XM, Shi PJ, Liu YS. Society: Realizing China’s urban dream. Nature, 2014,509, 158-160.
Jochen Hinkel, Carlo Jaeger, Robert J. Nicholls, Jason Lowe, Ortwin Renn and Shi Peijun ， Sea-level rise
scenarios and coastal risk management ， NATURE CLIMATE CHANGE ， VOL 5 ， MARCH 2015 ，
188-190

46. 服 于我国 全球 化与务 针对 变
境 的 系、环 风险 关 制定科
学有序的 境 化政应对环 变
策
服 于我国提高 境 化务 环 变 总
体的 估预 水平和能力
服 于解决我国以制度务 设计
核心的 合 境 防为 综 环 风险
御的范式问题
断全球 化 境 的影诊 变 对环 风险
响机理与途径（如何影
响？）
解决渐发 - 突 合 境发综 环 风险
估中评 量化、模 与 估拟 预 的
（影响多少？）；问题
揭示中国 境 在全球 境环 风险 环
水平中的风险 位置， 建构 应
对范式（ 任多大？）责
科学研究 国家需求
科学 、国家需求 迫、国 争激烈，且我国已有 好研究基 ！问题关键 紧 际竞 较 础
（史培 ）总结 军
Thank you!
谢谢谢谢