Chinese Academy of Meteorological Sciences

Assessment of rainstorm climate risk and rainstorm-induced agricultural disaster risk in east-central China

Huo Zhiguo1, Wen Quanpei1&2, Ma Zhenfeng3,

Xiao Jingjing1, Zhang Lei1

1. Chinese Academy of Meteorological Sciences, Beijing, China 2. Chengdu University of Information Technology, Chengdu, China 3. Climate Center of Sichuan Province, Chengdu, China

EMC/NCEP/NWS/NOAA, Camp Springs, Maryland , USAMay 2012

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CONTENTS

1. Introduction

2. Materials and methods

3. Analysis of rainstorm climatic risk

4. Analysis of relative disaster risk

5.Comparison of rainstorm climatic risk with relative disaster risk

6. Conclusions

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1.1 Background of east-central China

◆ major agricultural region; ◆ abundant precipitation; ◆ dense population; ◆ developed economy; ◆ severe flood damage

1.2 Purpose of this paper ◆Assessment of rainstorm climatic risk

◆Assessment of rainstorm-induced agricultural disaster

risk

1. Introduction

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2. Materials and methods

2.1 Data and data sources●meteorological data

1961-2008 daily precipitation data from 292 meteorological stations in east-central China.

National Meteorological Information Center

●disaster data

1971-2009 annual crop affected area, disaster area and plant area of 17 provinces in east-central China.

Encyclopedia of Meteorological Disasters in China; China Rural Statistical Yearbook 1981-2009; China Meteorological Geographical Divisions Manual

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2.2 Methods

● Selection of rainstorm disaster-inducing factors

◆Selection of rainstorm climatic factors

10 precipitation factors are selected preliminary, which can represent the accumulation and intensity of rainstorm

◆Selection of agricultural disaster factors

percentage of affected area, percentage of disaster area

percentage of affected area = Crop affected area / Plant area percentage of disaster area = Crop disaster area / Plant area

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Factors Name Description of factors

X1Annual rainstorm days Amount of days that daily rainfall exceeds 50mm

within one year

X2

Annual rainstorm accumulation Sum of rainfall of rainstorm within one year

X3

Annual number of rainstorm processes

Amount of one discontinuous rainstorm day and continuous rainstorm days within one year

X4

Annual largest rainfall accumulation

The largest one of rainfall accumulations of rainstorm processes within one year

X5Annual longest duration Day number with the longest duration of rainstorm

process within one year

X6Annual largest daily rainfall The largest daily rainfall within one year

X7Annual heavy rain days The amount of days that daily rainfall is between 100

and 200mm within one year

X8

Annual heavy rain accumulation Sum of rainfall of heavy rain within one year

X9

Annual excessively heavy rainfall days

Amount of days that daily rainfall exceeds 200mm within one year

X10

Annual excessively heavy rainfall accumulation

Sum of rainfall of excessively heavy rainfall within one year

Table1: Selection of rainstorm disaster-inducing factors

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●Constructed and Calculated by using the principal component analysis of the different combination of 10 factors.

Where: BI is the rainstorm climatic index; x is the rainstorm climatic factor; α is coefficient

● Principles of factor combination are as follows: ◆ including the factors representing accumulation of rainfall

in the rainstorm process; ◆ including the factors representing rainstorm intensity in the

rainstorm process; ◆ the rainstorm climatic index should distinguish agricultural

heavy disaster year clearly.

3. Analysis of rainstorm climatic risk

3.1 Construction of rainstorm climatic index

nnXXXXBI 332211

Different combinations of 10 precipitation factors are selected to construct rainstorm climatic index by using the principal component analysis.

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● An optimal combination selected:

annual rainstorm days (X1),

annual rainstorm accumulation (X2),

annual number of rainstorm processes (X3),

and annual largest rainfall accumulation (X4).

●Grade of the rainstorm climate index divided

A higher rainstorm climatic index means more severe rainstorm. Considering the actual rainfall situation, the rainstorm climate index is divided into five grades:

Grade (index between 0 and 0.2), Ⅰ Grade (index between 0.2 and 0.4), Ⅱ Grade (index between 0.4 and 0.6), Ⅲ Grade (index between 0.6 and 0.8), Ⅳ Grade (index ≥ 0.8).Ⅴ

Among the different combinations of 10 precipitation factors

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●Calculation of rainstorm climatic risk probability

Probability of each grade is calculated by using the soft histogram estimation based on information allocation

●Calculation of Rainstorm Climatic Risk Index

Where: Q is the rainstorm climatic risk index,

Ji is the grade of rainstorm climate index,

Pi is the risk probability of the grade,

n is the number of grades (n=5).

1

n

i ii

Q J P

3.2 Calculation of rainstorm climatic risk probability and Risk Index

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3.3 Geographical Distribution of Rainstorm Climatic Risk

a

Figure 1: risk probability of rainstorm climatic index of grade I

The high risk probability areas of grade I are located in Northeast China and North China.

11Figure 2: risk probability of rainstorm climatic index of grade II

The high risk probability areas of grade are located in Ⅱthe Yangtze River basin and eastern coastal areas.

12Figure 3: risk probability of rainstorm climatic index of grade III

13Figure 4: risk probability of rainstorm climatic index of grade IV

14Figure 5: risk probability of rainstorm climatic index of grade V

The probability of grade , , Ⅲ Ⅳ Ⅴdecreases from south to north, with the high probability in southeast coastal areas, the medium probability in the Jianghuai and Xianggan region, and the low probability in most areas of North China.

15Figure 6: distribution of standardization rainstorm climatic risk index

The rainstorm climatic risk decreases from south to north on the whole with relative higher value in Jianghuai region

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4 Analysis of relative disaster risk

4.1 Construction of relative disaster index

●Constructed based on agriculture disaster grades and classification standards for single index

Table 2: Agriculture disaster grades and classification standards for single index

GradePercentage of

affected area (%)Percentage of

disaster area (%)

huge-disaster (40,100) (20,100)

heavy-disaster (4,40) (2,20)

medium-disaster (0.4,4) (0.2,2)

small-disaster (0.04,0.4) (0.02,0.2)

micro-disaster (0.004,0.04) (0.002,0.02)

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● transform of original classification standards

In order to make the same grade of two indexes comparable, the original classification standard is transformed to new one using the transform functions:

Where U(x) is the transformed value, x is the percentage of affected area, y is the percentage of disaster area.

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0.8 1/ 300( 40)

( ) 0.21 (10 / 4)

0

x

U x g x

40< x 100

0.004< x 40

x 0.004

3

0.8 1/ 300(2 40)

( ) 0.21 (10 / 2)

0

y

U y g y

20< y 50

0.002< y 20

y 0.002

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Table 3: The relationship between the individual transformed value and agriculture disaster grade

● Quantitative estimate of relative disaster index

In order to represent the comprehensive agriculture disaster situation, a composite index is constructed based on two indexes by using grey correlation analysis.

huge-disaster

heavy-disaster

medium-disaster

small-disaster

micro-disaster

0.8 ～ 1.0 0.6 ～ 0.8 0.4 ～ 0.6 0.2 ～ 0.4 0 ～ 0.2

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The relevance degree is calculated using the relational coefficients between the reference series and the comparison series. The formula is:

Where is the relevance degree; is the relational coefficient.

0 01

1( )

m

i ij

r jm

0ir

0 ( )i j

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The agriculture disaster grade is classified by the value of relevance degree.

Table 4: The relationship between the relevance degree

and disaster grade

huge-disaster

heavy-disaster

medium-disaster

small-disaster

micro-disaster

0.9 ～ 1.0 0.8 ～ 0.9 0.7 ～ 0.80.6 ～

0.70.5 ～ 0.6

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●Calculation of relative disaster risk probability

Using the normal information diffusion method.

The universe of discourse (U) is divided into 100 dense data points with a step of 0.005. so the calculation result is approximate to continuous probability density function.

4.2 Calculation of relative disaster risk probability and Risk Index

1 2 3 101, , , , 0.50,0.505,0.510, ,1U u u u u

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Figure 7: The relative disaster probability density curves of Anhui, Guangdong, Jiangxi, Henan, Liaoning province a) Anhui ; b)Guangdong ; c) Jiangxi ; d) Henan ; e) Liaoning

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Table 5: The risk probability of each grade of disaster situation in typical provinces

provincehuge-

disasterheavy-disaster

medium-disaster

small-disaster

micro-disaster

Anhui 0.0315 0.1682 0.5757 0.2223 0.0019

Guangdong 0 0.0561 0.7978 0.1452 0.0009

Jiangxi 0.003 0.0993 0.6579 0.2124 0.0273

Henan 0 0.0507 0.5224 0.4062 0.0207

Liaoning 0.0137 0.1023 0.4554 0.3163 0.1124

●The highest and the second highest risk probability of huge disaster is located in Anhui and Liaoning provinces respectively.

●The top 3 risk probability of heavy disaster is located in Anhui,Liaoning and Jiangxi.

●The risk probability of medium disaster is the highest in all typical provinces.

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●Calculation of relative disaster Risk Index

Where Z is the relative disaster risk index,

Ji is the grade of relative situation of agricultural disaster (disaster grade),

Pi is risk probability of the i grade, n is the number of grades,

i=1, 2, 3, 4, 5; n=5.

1

n

i ii

Z J P

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Table 6: The relative disaster index in east-central China

Henan Fujian AnhuiGuan

xiGuangdong

Zhejiang

Hunan HubeiJiang

su

2.65 2.73 3.00 2.68 2.91 2.69 2.96 2.96 2.75

Jiangxi ShanxiShandong

Henan HebeiLiaoning

Jilin Heilongjiang

2.84 2.55 2.64 2.60 2.37 2.59 2.71 2.66

4.3 Distribution of Rainstorm Relative Disaster Index

The higher risk areas are located in Anhui, Hunan, Hubei provinces

The lowest risk area is located in Hebei province

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●Verification by actual disaster situation in typical provinces

Figure 8: The variation of rainstorm climatic index, relative disaster index and the actual disaster situation affected by rainstorm from 1979 to 2008

in Anhui province.

5. Comparison of rainstorm climatic risk with the relative disaster risk

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Figure 9: The rainstorm climatic index, relative disaster index for heavy rain disaster and actual situation affected by rainstorm in typical provinces.

a) Guangdong; b) Jiangxi; c) Henan; d) Liaoning

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● Comparison analysis◆The results show the assessment of disaster grade

coincides with actual disaster situation. ◆In time scale, the rainstorm climatic index matches well with

relative disaster index; the correlation coefficient between the rainstorm climatic index and the agricultural relative disaster index for each of the provinces except Guangdong (0.5) is more than 0.6.

◆The rainstorm climatic index and relative disaster index are high in the south areas and low in North China.

◆The distribution of rainstorm climatic risk and relative disaster risk are not exactly the same, which means the areas with high-value of rainstorm climate risk may not be the areas with the severe disaster. The reasons may be the different ability of disaster prevention and mitigation.

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●Rainstorm climatic index and its risk assessment model are constructed based on annual rainstorm days, annual rainstorm accumulation, annual number of rainstorm processes, annual largest rainfall accumulation, then the maps of rainstorm climatic risk and its geographic distribution in east-central China are compiled.

●The model of relative disaster index based on percentage of crop affected area and disaster area makes risk of the grades of agricultural disaster situation comparable between the regions.

●The high-value areas of rainstorm climatic risk and relative disaster risk are located in the south of east-central China;

●The low-value areas of rainstorm climatic risk and relative disaster risk are located in the North China.

6. Conclusions

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Acknowledgement

This work was funded by National Science & Technology Pillar Program of the Eleventh Five-Year Plan of China (Grant No. 2008BAK50B02)

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Prof. Huo ZhiguoChinese Academy of Meteorological Sciences, Beijing, China 100081Email: huozhigg@cams.cma.gov.cn