4.1 Analysis of flash flood hazard indicators
4.1.1 Analysis of hazard Secondary indicators
4.1.1.1 Meteorological condition
According to the investigation and evaluation report of flash flood disaster in all districts and counties of Chongqing Municipality, the results of design storm calculation for each danger zone were collected and organized. After data verification, the number of valid danger zones is 4020. Calculation of indicators as described in section 3.2.
The KMO test value was between 0.7 and 0.9, and the P-value in the Bartlett's test passed the test at the 1% significance level, allowing for factor analysis (Table 8). The gravel plot (Fig. 3) was plotted according to the relationship between the number of factors and the characteristic root, showing that the slope tends to flatten when the number of factors is 5, so the number of factors was chosen to be 5. The component matrix table (Table 9) shows the factor score coefficients (principal component loadings) included in each component, which were used to calculate the component scores. The calculation of the weights of the factor analysis shows (Table 10) that the weight of factor 1 is 26.216%, factor 2 is 24.562%, factor 3 is 23.289%, factor 4 is 20.161%, and factor 5 is 5.773%, where the maximum value of the indicator's weights is for factor 1 (26.216%), and the minimum value is for factor 5 (5.773%).
Table 8 KMO test and Bartlett test
KMO
|
0.719
|
Bartlett Sphericity Test
|
approximate chi-square
|
258272.344
|
df
|
190.000
|
P
|
0.000***
|
Note: ***, **, * represent 1%, 5%, and 10% significance levels, respectively.
Table 9 Ingredient matrix for FA
Index
|
Components
|
Component 1
|
Component 2
|
Component 3
|
Component 4
|
Component 5
|
1%10minYL
|
0.016
|
0.053
|
0.458
|
0.134
|
0.213
|
1%1hYL
|
0.008
|
0.059
|
0.489
|
0.131
|
-0.064
|
1%6hYL
|
0.024
|
0.171
|
0.206
|
0.002
|
0.11
|
1%24hYL
|
0.102
|
0.039
|
0.051
|
0.067
|
0.122
|
2%10minYL
|
0.016
|
0.055
|
0.459
|
0.144
|
0.202
|
2%1hYL
|
0.009
|
0.066
|
0.485
|
0.114
|
-0.144
|
2%6hYL
|
0.017
|
0.173
|
0.156
|
0.207
|
0.056
|
2%24hYL
|
0.104
|
0.031
|
0.069
|
-0.136
|
0.098
|
5%10minYL
|
-0.014
|
0.028
|
0.087
|
0.611
|
0.083
|
5%1hYL
|
-0.005
|
0.059
|
0.171
|
0.514
|
-0.103
|
5%6hYL
|
0.019
|
0.174
|
0.153
|
0.203
|
0.006
|
5%24hYL
|
0.105
|
0.03
|
0.056
|
-0.138
|
0.078
|
10%10minYL
|
-0.014
|
0.021
|
0.088
|
0.586
|
0.18
|
10%1hYL
|
-0.013
|
0.044
|
0.238
|
0.525
|
-0.129
|
10%6hYL
|
0.021
|
0.173
|
0.15
|
0.205
|
-0.032
|
10%24hYL
|
0.105
|
0.028
|
0.042
|
-0.136
|
0.056
|
20%10minYL
|
0.025
|
0.005
|
0.011
|
0.036
|
1.01
|
20%1hYL
|
-0.001
|
0.034
|
0.444
|
0.12
|
-0.078
|
20%6hYL
|
0.031
|
0.167
|
0.187
|
0.002
|
-0.05
|
20%24hYL
|
0.104
|
0.033
|
-0.005
|
0.058
|
0.042
|
20%24hYL
|
0.104
|
0.033
|
-0.005
|
0.058
|
0.042
|
Table 10 Factor weighting results
Index
|
Explanatory rate of variance after rotation (%)
|
Cumulative variance explained after rotation (%)
|
Weights(%)
|
Factor 1
|
24.162
|
24.162
|
26.216
|
Factor 2
|
22.638
|
46.8
|
24.562
|
Factor 3
|
21.464
|
68.264
|
23.289
|
Factor 4
|
18.581
|
86.845
|
20.161
|
Factor 5
|
5.321
|
92.166
|
5.773
|
The factors under each principal component were obtained by multiplying the component matrix table with the design storm values at the five design frequencies and the four standard calendar times, and the factors under each principal component were obtained by using the formula F = (0.242/0.922) × F1 + (0.226/0.922) × F2 + (0.215/0.922) × F3 + (0.186/0.922) × F4 + (0.053/0.922) × F5 to obtain the composite rainfall indicator (Fig. 4(a)).According to section 3.2.1, threshold rainfall was also calculated (Fig. 4(b)).
Meteorological condition was calculated using the weights of the components of the secondary indicators of hazard identified in section 3.3.3 (Fig. 5). Meteorological condition shows that Banan, Beibei, Hechuan, Tongliang, Dazu, Rongchang, Yongchuan and other districts in the main city metropolitan area, Wuxi, Wushan, Kaizhou and other districts in the northeastern region of Chongqing, and Youyang, Shizhu, Xiushan and other districts in the southeastern region of Chongqing, the indicator value is large and the danger is high.
4.1.1.2 Underlay condition
According to section 3.2.1, slope, NDVI, and river network density indicators were also calculated (Fig. 6(a) to Fig. 6(c)). Then, underlay condition were calculated using the weights of the components of the secondary indicators of hazard identified in section 3.3.3 (Fig. 7).The underlay condition shows that the indicators are larger and more dangerous in districts such as Changshou, Jiangbei, and Nanan in the main urban metropolitan area, and Pengshui and Youyang in southeastern Chongqing.
4.1.2 Analysis of hazard primary indicators
Hazard indicators are the result of a combination of meteorological and underlay conditions (Fig. 8). The hazard indicators show that Banan, Beibei, Hechuan, Tongnan, Rongchang, Yongchuan and other districts in the main city metropolitan districts, Wuxi, Kaizhou and other districts in northeastern Chongqing, and Shizhu, Youyang, Xiushan, Pengshui and other districts in southeastern Chongqing have large values of the hazard indicators and are at a high level of hazard.
4.2 Analysis of flash flood disaster vulnerability
4.2.1 Analysis of secondary index of vulnerability
4.2.1.1 Population
According to Section 3.2.2, population density, population density in control areas, and urbanization rate were also calculated (Fig. 9(a) to Fig. 9(c)). The population conditions were then calculated using the weights of the components of the vulnerability secondary indicators identified in Section 3.3.3 (Fig. 10). The population index distribution map shows that the districts and counties with high risk are mainly distributed in Nanan and Jiangbei of the main metropolitan area. The vulnerability of northeast Chongqing and southeast Chongqing counties is relatively low.
4.2.1.2 Economic property
According to section 3.2.2, the share of GDP per capita and the output value of the primary industry is also calculated (Fig. 11(a) to Fig. 11(b)). The economic property conditions are then calculated using the weights of the components of the vulnerability secondary indicators identified in Section 3.3.3 (Fig. 12). The distribution map of economic property indicators shows that the high risk districts are concentrated in Jiangbei, Nanchuan, Changshou and other areas in the main urban areas; The medium risk areas are distributed in the northeast and southeast of Chongqing. The risk of lower districts are the main urban areas, such as Nanan and Shapingba.
4.2.2 Analysis of vulnerability primary indicators
According to the calculation results of the above chapters, among the secondary indexes of vulnerability, the population index is higher than the economic property index, and the specific weight values are shown in Table 7.
The risk distribution map of vulnerability index shows that the vulnerability risk of Nanan, Shapingba, Rongchang and other districts in the main metropolitan area is higher, while the vulnerability risk of northeast Chongqing and southeast Chongqing is lower. This is due to the following reasons: Among the secondary indexes of vulnerability, the population index accounts for 71%, while the control area of the main urban area has a large population density, a high urbanization rate and a developed social economy, and its corresponding flash flood disaster vulnerability is high. The population density of southeast and northeast Chongqing and the population density of prevention and control areas are relatively small, the proportion of output value of primary industry is high, and the level of economic development is relatively low, so the vulnerability of flash flood disaster is low.
4.3 Analysis of disaster resistance index of flash flood disaster
4.3.1 Analysis of second-level index of disaster resistance
4.3.1.1 Monitoring capacity
According to Section 3.2.3, the monitoring site area was calculated (Fig. 14). Since the monitoring of water and rain is only composed of a single element of monitoring station area, the distribution of water and rain monitoring index is the same as that of monitoring station control area index. The monitoring index of water and rain shows that the control area of the main urban area is smaller, the monitoring stations are dense and the disaster forecasting ability is higher than that of northeast and southeast Chongqing. Specific is the main urban area Beibei, Shapingba, Jiangbei, Nanan, Wansheng and other districts.
4.3.1.2 Current flood protection capacity
According to Section 3.2.3, the current flood control capacity is calculated (Fig. 15). Since the second-level index flood control capacity is composed of only the single element of the current flood control capacity, the index distribution of flood control capacity is the same as that of the current flood control capacity. The current flood control capacity index shows that the main urban areas of Jiangbei, Jiulongpo, Qijiang and other districts, Fengjie, Zhongxian, Dianjiang and other districts in northeast Chongqing, the current flood control capacity is higher.
4.3.2 Analysis of first level index of disaster resistance
The disaster resistance index shows that the disaster resistance index of Beibei, Tongnan, Dazhu, Shapingba, Bishan, Jiangbei, Nanan, Wansheng and other districts in the main urban area, and Zhongxian, Liangping, Dianjiang and other districts in northeast Chongqing are relatively high, and the disaster resistance index is relatively high. The disaster resistance index of Wuxi, Yunyang, Chengkou, Wanzhou and other districts in northeast Chongqing, Youyang, Shizhu, Fengdu, Pengshui, Qianjiang and other districts in southeast Chongqing, and Hechuan and other districts in the main urban area are small, and the disaster resistance ability is low.
4.4 Risk degree of flash flood disaster
Based on the risk assessment model and the weights of hazard, vulnerability and resilience indicators. the distribution of flash flood risk value in Chongqing was obtained by raster weighting calculation in ArcGIS (Fig. 17).
The risk value of flash flood disaster in Chongqing is between 0.25 and 0.66. Hechuan, Rongchang, Nanan, Shapingba and other districts in the main urban area, Wuxi, Chengkou and other districts in northeast Chongqing, Youyang, Pengshui and Shizhu and other districts in southeast Chongqing have larger risk values and higher risk of flash flood disaster. Wansheng, Qijiang, Jiangjin, Yongchuan, Yubei, Bishan, Fuling and other districts in the main urban area, Fengjie, Zhongxian, Wanzhou and other districts in northeast Chongqing, and Qianjiang, Wulong and other districts in southeast Chongqing have smaller risk values and lower risk of flash flood disaster.
4.5 Flash flood disaster risk zone division
4.5.1 Risk division
According to the distribution map of flash flood disaster risk, the Iso clustering unsupervised classification tool in ArcGIS is used to grade flash flood disaster risk. In this study, the risk is divided into four levels, corresponding to low, medium, high and extremely high risk areas, and the meaning of the divisions is shown in the Table 11.
Table 11 Flash flood disaster risk classification table
Serial number
|
Grading
|
Disaster implication
|
1
|
Low risk area
|
The possibility of flash floods is extremely low, causing little damage and almost no impact.
|
2
|
Medium risk area
|
The possibility of flash flood disaster is low, and the impact on personnel, farmland and roads is small.
|
3
|
high risk area
|
The possibility of flash flood disaster is high, which has a certain impact on mountain residents, farmland and roads.
|
4
|
Very high risk area
|
The possibility of flash flood disaster is very high, once the flash flood disaster is very likely to cause casualties, farmland inundation, housing and road damage, causing serious property losses.
|
The risk zone diagram is shown in Fig. 18, and the area and proportion of each risk zone are shown in Fig. 19 and Fig. 20.
As shown in the Fig.4.5.1-2, the total area of flash flood disaster risk in Chongqing is 8,234,800 square kilometers, and the area of high risk area is 2,773,800 square kilometer, accounting for the largest proportion (33.68%). The middle risk area was the second, with an area of 2,570,100 square kilometer, accounting for 31.21%; The extremely high risk area covers 1,707,200 square kilometer, accounting for 20.73%; The low-risk area covers 1,183,700 square kilometer, accounting for the smallest proportion (14.37%).
From the perspective of administrative division, the high risk areas are mainly concentrated in Wuxi in northeast Chongqing, Youyang and Shizhu in southeast Chongqing, and the districts of the main city, such as Nanan, Rongchang and Hechuan. High risk areas are mainly distributed in Chengkou, Yunyang, Pengshui, Tongnan, Nanchuan, Changshou and other districts in northeast Chongqing. These spatial and regional differences are mainly caused by the mutual influence of landform, rainfall climate, river network and water system, social economy and disaster resistance.
4.5.2 Risk zoning statistics by district and county
According to the above calculation results of flash flood disaster risk zones in Chongqing, the area and proportion of the four risk zones in each district are classified and counted, as shown in Fig. 21.
It can be seen from the risk map area statistics chart that the extremely high risk areas are Youyang (93%) in southeast Chongqing and Nanan (93%) in the main urban area, followed by Rongchang (82%) in the main urban area. The high risk areas are Shizhu (57%) in southeast Chongqing and Chengkou (56%) in northeast Chongqing.
Northeast Chongqing: the slope is generally in the range of 25°~45°, from the perspective of rainstorm zoning, northeast Chongqing is a typical rainstorm center in Chongqing, and the proportion of primary industry in the region is higher. Among them, Wuxi and other mountainous counties belong to the large undulating mountainous area of the northeast Chongqing curved fold structure with large rainstorm intensity and large proportion of the output value of the primary industry, which is very easy to suffer from flash flood disasters. Wanzhou, Fengjie and other districts are located in the middle and low hilly areas, the density of river network is low, the output value of the primary industry is small, and the degree of flash flood disaster is relatively low.
Southeast Chongqing: the slope is in the range of 0°~25°, from the perspective of economic and social zoning, this region is an important ecological economic zone of the Three Gorges Reservoir area, the river system is more developed, and the proportion of primary industry is relatively high. The counties of Youyang and Pengshui are located in the middle of the northeast fold structure and the mountainous area with large river network density and high proportion of the output value of the primary industry, so they are vulnerable to the risk of flash flood disaster. Qianjiang and Wulong are located in the middle and low hilly areas of parallel ridge valley of the linear fold structure, with low river network density, low proportion of primary industry, and low risk of flash flood disaster.
The main urban area: the slope is mostly lower than 10 degrees. From the perspective of economic and social zoning, it is the region with the highest population density, GDP and urbanization rate in the city. From the perspective of geomorphological zoning, most of this region belongs to flat dam area of soothing folds and hills in West Chongqing. Among them, the population density of the counties in Jiangbei and the Nanan, the population density of the prevention and control areas and the level of economic development are high, which are easy to suffer from flash floods; Tongnan, Nanchuan and other districts and counties have relatively small population density, relatively high proportion of primary industry, and low risk degree of flash flood disaster.