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Spatio-Temporal Characteristics Of Plum Rains And Its Flood Prediction In Northwest Zhejiang Province Based On Monte Carlo

Posted on:2021-01-03Degree:MasterType:Thesis
Country:ChinaCandidate:L DongFull Text:PDF
GTID:2370330626963568Subject:Cartography and Geographic Information System
Abstract/Summary:PDF Full Text Request
In the early summer of each year,Zhejiang Province will experience a period of plum rains.Due to the long duration and concentrated rainfall,it is very easy to produce severe flood disasters,and even cause some natural disasters such as landslides and mudslides,so that threaten people's lives and cause serious economic and property losses.The research area in this article is the northwestern region of Zhejiang Province,most of which belongs to the Qiantang River Basin.The Qiantang River is the largest river in Zhejiang,and also the “Mother River” of Zhejiang Province.There are a large population and abundant natural resources in the river basin.Because of the frequent rainfall in plum rains,the ecology,economy,as well as people's production and life in the region are severely affected.Therefore,it is necessary to understand the variation characteristics of rainfall and flood during plum rains and its future trends,so as to prepare for flood control in advance.This study first selected appropriate flood evaluation index through comparative analysis to evaluate the flood grade in the plum rains period.Then,the distribution patterns of flood indicators of the eight meteorological stations during the 1971?2017 plum rains period were simulated and analyzed by the Monte Carlo simulation method.Thus,their distribution law was obtained.According to the distribution patterns of representative stations,the study further analyzed the probability of different grades flood at each representative station.Next,from the temporal and spatial point of view,this study analyzed the change of rain and waterlogging in the whole region,in order to master its spatial-temporal characteristics.Finally,the rescaled range analysis and stationary time series prediction method were used to predict the future trend of flood indexes and rainfall situation in the plum rains period of this research area.The main results are as follows.First,the index of abnormal precipitation percentage successfully evaluated the flood grade of the plum rains period in the past 47 years.Four different distribution patterns of flood index in the eight stations were found.Lin'an,Hangzhou,Jinhua and Quzhou stations accord with maximum distribution.Chun'an accords with triangular distribution.Shangyu accords with Logistic distribution.Shengzhou and Yiwu accord with normal distribution.Among the representative stations,Quzhou station which is in the southwest region has the highest probability of flood events during the plum rains.The lowest probability appears in Shangyu station in the northeast region.Second,in the plum rains season of the last 47 years,the annual plum rain increased significantly at the level of 0.1,and the annual rainstorm days increased significantly at the level of 0.05.Regarding the change of flood indicators,except that of Jinhua station shows a significant increase(?=0.05),the other stations all show an insignificant upward trend.In terms of space,the west and southwest of the study area are more susceptible to the influence of plum rains.Third,in the future,the flood indicator of Jinhua station will show a significant downward trend,and the other stations will all show an insignificant downward trend.Judging from the changes in the indicators that reached the flood level,results show that this indicator in Lin'an,Yiwu,Chun'an,Quzhou and Shengzhou stations will show an insignificant increase trend.This indicator in Hangzhou and Jinhua stations will show an insignificant downward trend.However,there will be no significant trend in Shangyu.In conclusion,relevant departments should still pay more attention to flood control work in the west,southwest and central regions of the area in the future.
Keywords/Search Tags:Northwest Zhejiang Province, Plum Rain, Flood, Monte Carlo, Distribution Pattern, Temporal and Spatial Characteristic
PDF Full Text Request
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