Research Article

[Retracted] Risk Assessment and Prediction of Rainstorm and Flood Disaster Based on Henan Province, China

Table 2

Indices system of rainstorm and flood disaster loss prediction.

Variable attributesDisaster elementsPrimary indicesSecondary indicesReference source

Characteristic variableHazard factorsRainfall dataProcess accumulated rainfall (J1: mm)Gong et al. [45], Li et al. [46], Huang et al. [47]
Continuous rainfall days (J2: h)
Accumulated rainfall in 12 h (J3: mm)
Accumulated rainfall in 24 h (J4: mm)
Hazard-pregnant environmentNatural environmentDigital elevation model (DEM) (Z1: m)Wang and Deng [48], Hu et al. [49]
Relief amplitude (Z2: m)
Vegetation coverage (Z3: %)
Density of the river network (Z4: m2/m2)
Hazard-bearing bodySocial economic dataDensity of population (S1: thousand people/km2)Gong et al. [50], Pan et al. [51], and Li et al. [46]
GDP of per person (S2: people/ten thousand yuan)
Proportion of garden green space area (S3: %)
Proportion of house area (S4: %)
Disaster resilienceDisaster resilience and constructionGDP of every city (K1: ten million yuan)Zhang et al. [52] and Xu et al. [53]
GDP of per square kilometer (K2: ten million yuan/km2)
Length of urban drainage pipeline (K3: ten thousand km)

Target variableRainstorm and flood disaster lossDisaster loss situationNumber of rainstorm and flood disasters (Y1: time)Zhang et al. [54] and Wang et al. [55]
Direct economic loss (Y2: hundred million yuan)