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Based on the data of flood and mainly economic indications data in recent 60a in southern Xinjiang Province, this paper analyzed variations of the flood occurrence, annual aggregate time of occurrence and seasonal in southern Xinjiang and parts of the regions. Analyzed cumulative time of occurrence of inter-annual variation characteristics of the storm flood. Gray relational analysis of the southern counties of sequence correlation and association; with grain and cotton crops were affected and the rate of growth rate and the ratio of representation of grain, cotton, disaster response. The results show that: (1)the floods in southern Xinjiang frequency showing a rising trend, the number of floods in the lower 50-70 years, only three peak, respectively, from 1952 to 1953, 1963 and 1966, from 1980 the number increased significantly after the flood, especially since 1987 the number of abnormal increase in flood occurred, floods were gradually increasing trend. (2) the month of 3 ~ 9 is the main period of flooding in southern of Xinjiang, among them, in July have most times, followed by June, October to February the following year floods have minimum numbers and days, Kashgar have most number of floods in June, July cumulative incidence at the most. (3) The cumulative occurrence time of large and heavy rain floods have significantly increased trend, the cumulative occurrence time short in 1950s-1970s, a peak of 80s is 1982, since 1985, large and heavy rain floods have abnormal increase in the occurrence time. (4) around the southern state of floods and heavy rains flooding the number of cumulative incidence of time showing a rising trend, from the 80’s a significant upward trend. 1950 to 1979 and from 1980 to 2008, the two time periods, Aksu region is the southern most parts of the number of states in the area floods, the annual average of 4.57 times and 1.193 times, but also Bayingolin Mongol Autonomous Prefecture occurred in the cumulative number of days of heavy rain floods the area most, 4.23 days and 12.86 days on average. Flooding around the state the number and timing of storm flood accumulated the highest decadal growth rate is the Bavaria region, growth rates are: 29.79%, 47.75%. (5) The gray correlative degree of southern counties are divided into four areas: one region (0.6-0.7), second region (0.5-0.6), third region (0.4-0.5), forth region (0.3-0.4), the conclude show that: first region and second region mainly distributed in the rainstorm belt of Tianshan mountains, the Tianshan and South veins storm with the more developed agricultural production areas within the river a mountain pass more flood damage large; three areas located in the eastern foot of the Pamirs, Kunlun Mountains and the Tarim Basin, inland areas, most county is not in the rainstorm belt of the Tianshan Mountains, with heavy rain flooding low; four areas distributed in the Kunlun Mountains, the Tarim Basin of inland areas , dry climate, floods very few. (6) Flood and the existence of various economic indicators positive correlation, indicating that flood the land, population, there is a significant economic impact, with the increase in population, expansion of cultivated land, livestock expansion of relations between floods and human activities will be more closely. Rate of affected crops in southern Xinjiang have a positive correlation with the affected area, which, in the early 80’s to 90 in recent 60a to the most affected period, from 1996 to the beginning, hit rate and the affected area decreased significantly but gradually increasing trend. Yield of grain and cotton crops were affected and negative correlation between rate, the higher the hit rate of the year, yields lower, on the contrary, the lower the hit rate of the year, the higher the yield, the impact of flooding on crop acreage positive feedback on the grain, cotton, production. Floods occur most frequently in July, the biggest economic losses, April to August months are the peak of flood economic loss. Economic losses and investment in fixed assets was negative correlation between investments increased year by year, gradually reduce economic losses.
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