Table 1 The assessment system of Natech risk triggered by floods.
From: Natural hazard triggered technological risks in the Yangtze River Economic Belt, China
Target layer | Evaluation index | Indicator description and classification basis | Grading standards | Weights | Score |
|---|---|---|---|---|---|
Risk source indicators (SF) | Hazard degree of risk enterprise | Hazard degree of risk enterprise at different Q levels of districts or counties (%). Classification according to the Eq. (2) | Equation (2) | 1 | 100 |
Hazard factor indicators of flood (HF) | Flood submerged range (F1) | The proportion of each district or county flood inundation in the total inundation (%). Classification according to the part of “Flood submerged range and inundation risk level” | The total inundation frequency of each district or county/4 | 0.3204 | 100 |
Inundation degree (F2) | Superimpose DEM data on submerged area data to classify submerged levels. Based on the statistical results of the sample data is sorted from small to large, grades are set based on the 5, 15, 50, 85 and 95 percentiles of all samples | Level 1 | 0.453 | 90 | |
Level 2 | 75 | ||||
Level 3 | 60 | ||||
Level 4 | 45 | ||||
Level 5 | 30 | ||||
Level 6 | 15 | ||||
Characteristics of significant stations during the flood period (F3) | The over-alarming situation of the highest water level of the flood peak at the main stations (m). Classification based on the statistical analysis results over the years | < 0.5 | 0.1405 | 20 | |
[0.5,1.5) | 40 | ||||
[1.5,2.5) | 60 | ||||
[2.5,3.5) | 80 | ||||
≥ 3.5 | 100 | ||||
Recurrence period (F4) | Recurrence period of significant floods in district or county (year). Classification according to the return period of the historical flood | < 10 | 0.0861 | 25 | |
[10,20) | 50 | ||||
[20,50) | 75 | ||||
≥ 50 | 100 | ||||
Control mechanism level indicators (CF) | Enterprise violation (C1) | The proportion of enterprises with violation records in the administrative area in the total number of enterprises (%). Based on the statistical results of the sample data is sorted from small to large, grades are set based on the 10, 50 and 90 percentiles of all samples | < 2% | 0.4203 | 25 |
[2%, 10.5%) | 50 | ||||
[10.5%, 35%) | 75 | ||||
≥ 35% | 100 | ||||
Proportion of investment in regional environmental management (C2) | The proportion of environmental pollution control investment in GDP of administrative regions from 2010 to 2017 (%). Based on the statistical results of the sample data is sorted from small to large, grades are set based on 10, 50 and 95 percentiles of all samples | < 0.78% | 0.1899 | 100 | |
[0.783%, 1.15%) | 75 | ||||
[1.15%, 1.8%) | 50 | ||||
≥ 1.8% | 25 | ||||
Frequency of regional emergencies (C3) | The proportion of the frequency of emergencies in the administrative region in the total number of regional emergencies from 2009 to 2018 (%). Classification according to statistical results. Based on the statistical results of the sample data is sorted from small to large, grades are set based on the 10, 50 and 90 percentiles of all samples | < 5% | 0.1213 | 25 | |
[5%, 7.5%) | 50 | ||||
[7.5%, 15%) | 75 | ||||
≥ 15% | 100 | ||||
Investment in energy conservation and environmental protection (C4) | The proportion of energy conservation and environmental protection investment in total expenditure (%). Based on the statistical results of the sample data is sorted from small to large, grades are set based on the 10, 55 and 95 percentiles of all samples | < 1.6% | 0.2685 | 100 | |
[1.6%, 2.6%) | 75 | ||||
[2.6%, 4%) | 50 | ||||
≥ 4% | 25 | ||||
Vulnerability indicators (VF) | Population (V1) | The population of districts or counties. Classification according to Eq. (3) | Equation (3) | 0.1737 | 100 |
Sensitive points in hospitals and education (V2) | A number of medical and educational institutions in districts or counties. Classification according to Eq. (4) | Equation (4) | 0.1737 | 100 | |
Real GDP per capita (V3) | Average per capita GDP from 2015 to 2018 (yuan). Based on the statistical results of the sample data is sorted from small to large, grades are set based on the 10, 50 and 90 percentiles of all samples | < 19,000 | 0.4794 | 25 | |
[19000, 39,000) | 50 | ||||
[39000, 105,000) | 75 | ||||
≥ 105,000 | 100 | ||||
Enterprise density (V4) | The proportion of the number of risk enterprises in the area of districts or counties (number/km2). Based on the statistical results of the sample data is sorted from small to large, grades are set based on the 10, 50 and 90 percentiles of all samples | < 0.005 | 0.1011 | 25 | |
[0.005, 0.03) | 50 | ||||
[0.03, 0.2) | 75 | ||||
≥ 0.2 | 100 | ||||
Water system in the flood area (V5) | Grade of target water quality flowing through districts or counties. Classification according to the classification standard of water quality | Grade 1 | 0.0721 | 100 | |
Grade 2 | 80 | ||||
Grade 3 | 60 | ||||
Grade 4 | 40 | ||||
Grade 5 | 20 |
