# Urban Flood Risk Assessment Based on a Combination of Subjective and Objective Multi-Weight Methods
In terms of assessment methods, the existing studies can be broadly classified into the following types: First, a flood scenario simulation is carried out with a hydrological-hydraulic model. For example, [PERSON] et al. used a two-dimensional hydrodynamic model to simulate floods for risk assessment in flood-prone areas [24; 25; 26]. [PERSON] et al. used Infowards ICM to establish a coupled hydrological-hydrodynamic model for flood simulation and risk evaluation of the Baima River area in Fuzhou City, China [27]. [PERSON] et al. carried out a flood disaster risk assessment on Haidian Island with different rainfall intensity combinations based on a PCSWMM model [28]. Second, high-resolution measurement technology is used to collect data and carry out flood disaster risk assessment. For example, [PERSON] et al. used radio frequency technology (RF) for regional flood hazard risk assessment [13]. [PERSON] et al. assessed flood zones and flood risk in Bangladesh based on NOAA AVHRR data using remote sensing technology (RS) and GIS systems [29]. [PERSON] et al. combined unmanned aerial vehicles (UAVs) and structure from motion (SfM) photogrammetry technology to collect and process high-resolution data as needed for flood disaster risk assessment [30]; [PERSON] et al. used miniaturized light and detection ranging (LiDAR) scanners mounted on unmanned aerial vehicles (UAVs) to generate a digital terrain model (DTMs) with ultra-high-altitude resolution and simulate the flooded area through the hydrological screening model (Arc-Malstrom), thus achieving the purpose of flood disaster risk assessment [31]. Thirdly, the indicator system is constructed by using the AHP method, the entropy weighting method, the CRITIC weighting method, etc., for flood risk assessment. For example, [PERSON] et al. used the GIS and AHP methods for flood risk assessment in the Huaihe River Basin and employed the formula of the \"Plus\" model to obtain a comprehensive risk evaluation map of flood disasters [32]. [PERSON] et al. quantitatively analyzed the drainage network of a river, applied AHP in a GIS system, examined the effect of uncertainty in the factor values on the results of the flood hazard evaluation, and produced a corresponding urban flood hazard evaluation map [33]. [PERSON] et al. applied the entropy weight and gray target evaluation model methods to construct a risk evaluation model of heavy rainfall and flooding in southern Shaanxi and combined GIS spatial analysis technology to zone the risk of heavy rainfall and flooding in southern Shaanxi [34]. [PERSON] et al. proposed a multi-criteria decision analysis (MCDA) model for urban flood risk evaluation, using the fuzzy hierarchical analysis method (FAHP), the entropy weighting method (EWM), and a subjective-objective combination of weighting methods to determine the weights, and drew a map of the flood risk distribution in Beijing City [35]. [PERSON] et al. evaluated the flood vulnerability of 76 cities in the Yellow River Basin from 2009 to 2018 using the CRITIC-entropy weighting method and the fuzzy comprehensive evaluation method [36]. [PERSON] et al. assigned weights to various flooding factors through the AHP-entropy weighting method and analyzed and carried out a risk assessment of heavy rainfall and flooding in Guangxi with the help of GIS technology [37]. Fourthly, random forests, neural networks, and other machine learning methods are used to evaluate the risk of flood disasters. For example, [PERSON] et al. considered the return period in spatial modeling using machine learning (ML) models to determine flood hazard areas [38]. [PERSON] et al. used multi-criteria decision-making for coastal flood risk assessment using a machine learning approach [39]; [PERSON] et al. used a random forest model to calculate the contribution rate of each indicator, optimized the indicator system based on the ranking results, and used the XGBoost model to assign weights to the optimized indicator system and assess the flood risk of Yichang City [40].