There are five purposes in this research. To know the function of the member disaster prevention specialist, how to relate to measurement data from rain station, can the result data from member disaster prevention specialist used for evacuation basis, to know the relationship between rain station and the member, can complement each other, in area they can’t reach or no station or member, and the last purpose is to know the typhoon path and rainfall spatial distribution. The research conducted in South Hualien, Hualien County Taiwan, and only focused on typhoon occurred in 2016-2017. Methodologies to use are Thiessen method to divide the rain station in South Hualien into 17 polygon, which 1 polygon represent 1 rain station and nearest member, and then compare the data of cumulative rainfall, is have the correlation with the rain station and member even though they are in different polygon. Collect cumulative rainfall data from the Central Weather Burau and member disaster prevention specialist, study Taiwan map from government to know the condition of the South Hualien and location of the member and rain station in South Hualien. This study use UTM is TWD 97 as location. Starts from analyzing data, researcher focused to measure the typhoon in 2016-2017. There is nine typhoon event and one Torrential Heavy raining hit Taiwan. but researcher focused on six events which is Typhoon Meranti, Magi, Aere, Nesat, Haitang, Hato and one Torrential Heavy rain on 11th September 2017. The data shows in each rain station and member have different accumulation rainfall even though they are in one area, so researcher analyzed by looking on three important factors, which is typhoon trail, elevation and member measurement. The results there is some of member have the data higher than rainfall, look from the three factor such as location, environmental factor and typhoon trail the data from the member can be used for the basis of early warning system in that area or maybe the neighbor area, analysis include the potential rainfall distribution, landslides risk area and 24 hours message suggestion. It can help the community to know the high risk-area and make the right decision.

LIST OF CONTENTS
ACKNOWLEDGEMENT: i
ABSTRACT: iii
LIST OF CONTENTS: v
LIST OF PICTURES: ix
LIST OF GRAPHS: xi
LIST OF TABLES: xvii
LIST OF APPENDIX: xix
CHAPTER I INTRODUCTION: 1
A. Background: 1
B. Research Objectives: 4
CHAPTER II LITERARY REVIEW: 5
A. Weather: 5
B. Typhoon: 5
C. Typhoon Effect on Taiwan: 7
D. Typhoon Size on Taiwan: 9
E. Typhoon Tracks on Taiwan: 10
F. Accumulated Rainfall Characteristic: 12
G. Threshold on Taiwan: 13
H. Disaster Management in Taiwan: 14
CHAPTER III METHODOLOGY: 19
A. Study Site: 19
B. Data Collection: 22
C. Data Analysis: 29
CHAPTER IV RESULTS AND DISCUSSION: 31
A. Result: 31
1. Typhoon History in 2016-2017: 31
a. Typhoon Meranti: 31
b. Typhoon Magi: 32
c. Typhoon Aere: 34
d. Typhoon Nesat: 35
e. Typhoon Hato: 37
f. Heavy rain 11th Oct 2017: 40
2. Satellite Images and Map Analysis:s 42
a. S1 (81T890): 43
b. S2 (01T800): 45
c. S4 (C0Z061): 47
d. S6 (01T230): 49
e. S8 (O1T820): 51
f. S9 (81T900): 53
g. S10 (01T220): 55
h. S12 (01T810): 56
i. S13 (81T910): 58
j. S14 (01T720): 60
k. S15 (C0Z020): 62
l. S17 (C1S850): 63
3. Discussion: 65
CHAPTER V CONCLUSION: 73
REFERENCES: 75
APENDIX: 79

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