Study On The Characteristics And Evolution Of Regional Flood Disaster Resilience

The Jiansanjiang Administration has excellent natural conditions and is suitable for agricultural development.It is an indispensable commodity grain production base in China.However,in recent years,with the expansion of urban scale,population growth,intensified climate change,and changes in planting methods,Jiansanjiang Administration has excessively pursued economic development,urban development,and agricultural development,resulting in soil erosion,ecological damage,and increased flood risk.The unbalanced stability of flood disaster resilience should be paid attention to in an environment where global flood disasters intensify.Aiming at the many problems of the development of flood disaster resilience of Jiansanjiang Administration,this paper takes 15 farms under the jurisdiction of Jiansanjiang Administration as an example,through rationally constructing the evaluation index set of resilience to diagnose and calculate the level of flood disaster resilience from 2002 to 2016 Analyze its time difference and space difference.Furthermore,it analyzes the driving factors and driving mechanisms of the resilience of the farms under the administration.Finally,by simulating the future change scenario of the flood disaster resilience of the Administration,it provides theoretical basis and decision support for the sustainable development of regional flood disaster resilience.The main research contents and achievements of this article are as follows:(1)Based on the DPSIR model framework,this paper selects a total of 52 indicators from the natural dimension,social dimension,and economic dimension to form the preliminary selection set of flood disaster resilience evaluation indicators.The class-factor analysis method screens out 19 information overlap indicators,adds two indicators in combination with the rationality analysis of the indicators,and finally obtains 16 indicators to construct a preferred set of evaluation indicators.The comparison with the current popular methods in related fields proves that the preferred model used in this paper has a more comprehensive screening angle,a more efficient screening process and a more reasonable screening result.(2)This paper constructs WOA-RFR model and PSO-RFR model for the diagnosis of flood disaster resilience of Jiansanjiang Administration,and evaluates the resilience of 15 farms under the administration from 2002 to 2016.Combined with Arc GIS spatial data analysis technology to analyze the spatial and temporal variation law of resilience of each farm.The results showed that the initial diagnosis of resilience showed that the average growth rate of resilience of Qianjin Farm,Shengli Farm and Entrepreneurship Farm was slow,reaching only 18%,which was far below the standard level of the Administration 33%;The average index of resilience is relatively low,which is 2.206,2.400,and 2.428,respectively,which has not reached the average of 2.565.The analysis of the spatio-temporal variation of the resilience of each farm shows that the overall resilience of Jiansanjiang Administration has increased steadily over the past 15 years.The average resilience level of farms in the southwest of the Administration is generally high,while the resilience level of farms in the northwest is generally low.(3)The importance ranking of the flood disaster resilience evaluation index of Jiansanjiang Administration was obtained by using the evaluation method of the out-of-bag data of the random forest model.A total of 10 indicators,such as GDP per capita,output value of the tertiary industry,population density,proportion of youth population,GDP growth rate,savings per capita,number of health institutions,income per capita,number of hospital beds,and number of scientific and technical personnel,serve as candidate driving factors,combined with improvements The DEMATEL method takes each farm as an example to calculate the centrality value and cause value of each factor,and obtains the key driving factor,cause factor and result factor of each farm.The results show that GDP per capita is the most critical factor driving changes in the resilience system.Compared with existing studies,the remaining key factors are precipitation,output value of tertiary industry,population density,GDP growth rate,and hospital beds.(4)The scenario analysis method is used to assume four future scenarios,and summarizes the four possible future changes in the resilience of the Jiansanjiang Administration: high-speed development stage,stable development stage,poor development stage,and flood disaster stage.Using WOA-RFR and combined with the predicted values of key driving factors in various scenarios,the change trend of the resilience of the main farms in the future administration can be calculated.The results show that,first of all,the lack of human-induced policy changes in resilience will lead to serious problems of uneven development;second,the resilience of flood disasters on farms in the northwest region is weak and the disaster resistance is poor.In the future,when the large-scale flood disaster in Heilongjiang occurs,the resistance is low,and it should be paid attention to.Combining the general situation of the flood disaster resilience of the farms of the Jiansanjiang Administration,the construction path of the flood disaster resilience of the Jiansanjiang Administration was proposed to provide a basis for decision-making for each farm to maintain healthy and sustainable development.