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Huo Zhiguo 1 , Wen Quanpei 1&2 , Ma Zhenfeng 3 , Xiao Jingjing 1 , Zhang Lei 1

Assessment of rainstorm climate risk and rainstorm-induced agricultural disaster risk in east-central China. Huo Zhiguo 1 , Wen Quanpei 1&2 , Ma Zhenfeng 3 , Xiao Jingjing 1 , Zhang Lei 1 1. Chinese Academy of Meteorological Sciences, Beijing, China

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Huo Zhiguo 1 , Wen Quanpei 1&2 , Ma Zhenfeng 3 , Xiao Jingjing 1 , Zhang Lei 1

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  1. 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 , USA May 2012

  2. 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

  3. 1. Introduction 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

  4. 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

  5. 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

  6. Table1: Selection of rainstorm disaster-inducing factors

  7. 3. Analysis of rainstorm climatic risk 3.1 Construction of rainstorm climatic index ●Constructed and Calculated by using the principal component analysis of the different combination of 10 factors. Where: BIis the rainstorm climatic index; x is the rainstorm climatic factor; αis 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. Different combinations of 10 precipitation factors are selected to construct rainstorm climatic index by using the principal component analysis.

  8. ●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: GradeⅠ (index between 0 and 0.2), GradeⅡ (index between 0.2 and 0.4), Grade Ⅲ (index between 0.4 and 0.6), Grade Ⅳ (index between 0.6 and 0.8), GradeⅤ (index ≥ 0.8). Among the different combinations of 10 precipitation factors

  9. 3.2 Calculation of rainstorm climatic risk probability and Risk Index ●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: Qis the rainstorm climatic risk index, Jiis the grade of rainstorm climate index, Piis the risk probability of the grade, nis the number of grades (n=5).

  10. 3.3 Geographical Distribution of Rainstorm Climatic Risk a The high risk probability areas of grade I are located in Northeast China and North China. Figure 1: risk probability of rainstorm climatic index of grade I

  11. The high risk probability areas of gradeⅡ are located in the Yangtze River basin and eastern coastal areas. Figure 2:risk probability of rainstorm climatic index of grade II

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

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

  14. The probability of grade Ⅲ, Ⅳ, Ⅴ decreases 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. Figure 5:risk probability of rainstorm climatic index of grade V

  15. The rainstorm climatic risk decreases from south to north on the whole with relative higher value in Jianghuai region Figure 6:distribution of standardization rainstorm climatic risk index

  16. 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

  17. ● 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.

  18. 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.

  19. 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.

  20. The agriculture disaster grade is classified by the value of relevance degree. Table 4: The relationship between the relevance degree and disaster grade

  21. 4.2 Calculation of relative disaster risk probability and Risk Index ●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.

  22. 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

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

  24. ●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.

  25. 4.3 Distribution of Rainstorm Relative Disaster Index Table 6: The relative disaster index in east-central China The higher risk areas are located in Anhui, Hunan, Hubei provinces The lowest risk area is located in Hebei province

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

  27. 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

  28. ● Comparisonanalysis ◆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.

  29. 6. Conclusions ●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.

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

  31. Thank you for your attention! Prof. Huo Zhiguo Chinese Academy of Meteorological Sciences, Beijing, China 100081 Email: huozhigg@cams.cma.gov.cn

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