Evaluation of Emergency Response Capacity of Urban Pluvial Flooding Public Service Based on Scenario Simulation

Abstract

The evaluation of emergency response capability under different pluvial flooding scenarios is an essential approach to improve the emergency response capability of flood disasters. A new evaluation method of emergency response capacity of urban public services is proposed based on urban pluvial flooding scenario simulation. Firstly, inundation area and depth under different pluvial flooding scenarios are simulated based on the SCS-CN model. Following that, space densities of all indicators include inundation area and depth, road network and the emergency public service institutions. Then, the indicator weight is determined by the combined weighting method of entropy weight and coefficient of variation. Finally, the emergency response capacity index (of each pixel) is calculated based on the graph stacking method. Taking Erqi District, Zhengzhou City as an example, the emergency response capacity of public service under different urban flooding scenarios is evaluated. The results show that the spatial distribution difference of public service emergency response capacity in Erqi District, Zhengzhou City is obvious, and with the increase of the precipitation return period, the high value area of public service emergency response capability decreases gradually and the low value area increases gradually. This method takes into account the specific urban flooding scenario and the layout of public service institutions and road networks that have strong practicability. the results of the evaluation can provide a reference for the construction of urban flood emergency response capacity and provide support for emergency decision-making.

Keywords: GIS; accessibility; capacity evaluation; emergency response; scenario simulation; urban pluvial flooding.

Figure 3

Land Use Types in Erqi District of Zhengzhou City.

Figure 4

Simulation map of inundation area and depth under different pluvial flooding scenarios in the Erqi District: (a) the 50-year pluvial flooding scenario; (b) the 100-year pluvial flooding scenario; (c) the 500-year pluvial flooding scenario.

Figure 6

Distribution map of emergency response capacity of medical institutions with different r pluvial flooding scenarios: (a) the 50-year pluvial flooding scenario; (b) the 100-year pluvial flooding scenario; (c) the 500-year pluvial flooding scenario.

Figure 7

Distribution of emergency response capability of firefighting institutions under different pluvial flooding scenarios: (a) the 50-year pluvial flooding scenario; (b) the 100-year pluvial flooding scenario; (c) the 500-year pluvial flooding scenario.

Figure 8

Distribution of emergency response capacity of public security organs under different pluvial flooding scenarios: (a) the 50-year pluvial flooding scenario; (b) the 100-year pluvial flooding scenario; (c) the 500-year pluvial flooding scenario.

Figure 9

Distribution map of comprehensive emergency response capacity of public service under different pluvial flooding scenarios: (a) 50-year pluvial flooding scenario; (b) 100-year pluvial flooding scenario; (c) 500-year pluvial flooding scenario.

Figure 1

Location of the study area.

Figure 2

Schematic of study area: (a) Digital elevation model (DEM); (b) the location of Public Service Organization and Road types.

Figure 5

Spatial distribution of emergency response capability evaluation indicators of public service institutions: (a) road density; (b) comprehensive density of public service institutions; (c) hospital density; (d) fire station density; (e) police station density; (f) inundation depth under 50-year pluvial flooding scenario; (g) inundation depth under 100-year pluvial flooding scenario; (h) inundation depth under 500-year pluvial flooding scenario; (i) inundation area under the 50-year pluvial flooding scenario; (j) inundation area under the 100-year pluvial flooding scenario; (k) inundation area under the 500-year pluvial flooding scenario.