The Response Of Forest Fires To Climate Change And Its Trend Prediction In Fujian Province

Forest fire is one of the major natural disasters in the world.With the process of climate warming and the frequency of extreme weather increasing,the degree of forest fire damage become more dramatically.Forest fires will not only cause the loss of forest resources,increase carbon emissions and harmful pollutions of the air,but also lead to significant losses of the human life and property security.Therefore,understanding the law of forest fire occurrence and constructing forest fire prevention system are big deal for relevant departments to carry out forest fire prevention.Fujian Province is located in the southeast coastal area of China and across the sea from Taiwan Island,it has very rich forest resources,and the forest coverage rate reaches 66.80% ranked first in the country.At the same time,Fujian Province is also the worst disaster area of forest fire in China.To study the law of climate change and the occurrence of forest fires in Fujian Province and to establish a scientific model to predict the future trend of forest fires can be used to provide some theories for relevant departments to carry out forest fire prevention and control work,and it has important practical significance.Based on the meteorological data of 38 years from 1980 to 2017 and the forest fire data of 28 years from 1990 to 2017 in Fujian Province,and some the statistical analysis software of SPSS,Matlab,Arcgis,etc.,we use the methods of linear regression model,Mann-Kendall mutation test,wavelet analysis,R/S analysis and Pearson Correlation Analysis to analyzes the characteristics and change laws of climatic and forest fire in in the past 38 and 28 years of Fujian,respectively,study the relationship between meteorological factors and forest fire,and establish the relationship model between forest fire change and meteorological factors by multiple regression model and index model.In this paper,the climatic characteristics of Fujian Province are analyzed.The results show that the annual average temperature of Fujian Province has an obvious rising trend and exists a sharp change point in the past 38 years,the annual precipitation of Fujian Province has an increasing trend after 2000,but the trend is not significant,and the annual average precipitation does not have a sharp change point.The first main cycle of annual average temperature change in Fujian is 14 a,the next annual average temperature will have a downward trend,the degree of persistence is weak,the first main cycle of annual precipitation change in Fujian is 27 a,the next annual average precipitation will decrease,the degree of persistence is strong.The sunshine duration fluctuated obviously over the years,and the whole sunshine duration decreased but not significantly,and the next annual average sunshine duration will decrease,the degree of persistence is strong.We analyze the forest fire of Fujian Province in this paper.The results show that Fujian Province is a high incidence area of forest fire.From 1990 to 2017,the total of forest fires occurred in Fujian Province is 9,869,with the average of forest fires occurring annually being more than 352.The main types of forest fires are standard forest fires and relatively large forest fires.The occurrence of forest fires in Fujian Province presents obvious seasonal characteristics,the forest fires were mainly concentrated in spring and winter,and the forest fires are showed obvious spatial difference,mainly concentrated in the northwest of Fujian.The meteorological factors(temperature,precipitation,sunshine hours)were analyzed based on Pearson correlation analysis method and Spearman correlation analysis method,the results show that temperature,precipitation and sunshine hours have significant correlation with the number of forest fires.The mathematical models of forest fire and meteorological factors are established by using exponential model and multiple linear regression model.The results show that the model fits well and passes the significance test.The overall precision of the model is high,but the deviation of individual years is large.